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SILPAKORN UNIVERSITY Science and Technology Journal SUSTJ

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Silpakorn University Science and Technology Journal

Contents

Volume 6 Number 2 (July - December) 2012

Research Articles

Effect of the Emulsifier Polymers and the Concentration of Drug

on the Viscosity and Antifungal Activity of Clotrimazole Cream……………...........................…………...........……......

Thawatchai Phaechamud, Suchalinee Juntawong, Juree Charoenteeraboon and

Gaysorn Chansiri

Numerical Computation of pH and Buffer Capacity in Complex Mixtures

of Acids, Bases and Ampholytes……............................………….....……............................………….....……............................…………..........

PM10 Levels and Hotspots in Western Thailand in Agro-Residue Burning Season..........…………............

Constant Current Stress……............................………….....……............................………….....……............................…………..............................

Prakash Chidambaram and Ramakrishnan Govindan

Acknowledgement to Referees 2011 - 2012........................………….....……................................................………….....……............

Margareta Pecovska-Gjorgjevich, JulijanaVelevska and Elena Atanassova

Influence of Blend Ratio on Thermal Properties of Bamboo/Cotton Blended Woven Fabrics.......

Aungsiri Tipayarom

Behavior of Ta2O5-Si Capacitors with Different Gate Electrode under

Wibul Wongpoowarak, Damrongsak Faroongsarng, Nimit Worakul and Prapaporn Boonme

The Editorial Board

Silpakorn University Science and Technology Journal (SUSTJ) is now available on the following databases: Chemical Abstract Service (CAS) SciFinder Scholar (CAPLUS) International Information System for the Agricultural Sciences and Technology (AGRIS) (FAO) AGRICultural Online Access (AGRICOLA) Food Science and Technology Abstracts (FSTA) The National Science Digital Library (NSDL) CAB Abstract Directory of Open Access Journals (DOAJ) Google Scholar Thai Journal Citation Index Centre (TCI Centre)

Research Article Effect of the Emulsifier Polymers and the Concentration of Drug on the Viscosity and Antifungal Activity of Clotrimazole Cream Thawatchai Phaechamud1*, Suchalinee Juntawong2, Juree Charoenteeraboon3 and Gaysorn Chansiri1 Department of Pharmaceutical Technology, Faculty of Pharmacy, Silpakorn University, Nakhon Pathom, Thailand 2 Department of Pharmacy, Damnoensaduak Hospital, Damnoensaduak, Rachburi, Thailand 3 Department of Biopharmacy, Faculty of Pharmacy, Silpakorn University, Nakhon Pathom, Thailand * Corresponding author. E-mail address: thawatchaienator@gmail.com 1

Received September 30, 2011; Accepted April 22, 2012

Abstract The preparation of emulsions without heating is an ideal production process for the heat-sensitive ingredients and energy saving. This study investigated the utilization feasibility of emulsifying polymers in cream base prepared without heating for clotrimazole. A stable and acceptable cream base readily for mixing with clotrimazole was prepared at room temperature using isopropyl isostearate as an oil phase, emulsifying polymer as an emulsifier, concentrated paraben as a preservative, polyethylene glycol 400 as a solubilizer and distilled water as a water phase at a ratio of 15:3:1:5:75, respectively. Clotrimazole creams comprising emulsifying polymer were evaluated for their viscosity and pH. The evaluations were also performed on the drug release using Franz diffusion cells and the inhibition of Candida albicans using agar diffusion method compared with a commercial product. The drug loading and the viscosity of cream influenced the drug release and the antifungal activity of this developed clotrimazole cream. The types of emulsifying polymer also affected the drug release but not the antifungal activity. The drug release and antifungal activity of this clotrimazole cream were not significantly different from Canesten速 cream. There was a possibility to prepare clotrimazole cream without heating using the emulsifying polymer. Key Words: Cream; Clotrimazole; Emulsifying Polymer Introduction Emulsifying polymer is a polymer based on hydro-swelling droplets polymer technology which is classified as a gelling and thickening agent (Anchisi, 2001). Oil, acrylate-acrylamide polymer, water and surfactant are the main components of this emulsifying polymer. This pre-neutralized polymer contains non-ionic surfactant catching around it and

Silpakorn U Science & Tech J 6 (2) : 9-19, 2012

being dispersed in oil phase. By adding water, it is inverted and the polymer network expands instantly. Thereafter, the polymer forms a macromolecular network around each droplet of dispersed oil. Emulsifying polymer could be employed to create the gel-emulsions without heating and high energy supply based on principle of low energy emulsification. The advantage of the product prepared with this

Silpakorn U Science & Tech J Vol.6(2), 2012

Effect of the Emulsifier Polymers and the Concentration of Drug

polymer is its good stability because of cold processing, which is an ideal production process for the heat-sensitive ingredients. Additionally, it composes with a non-ionic emulsifying agent in formulation therefore it has been suggested as a non-irritant alternative to skin. While the conventional emulsion sometimes exhibited disadvantages for its instability, skin irritation from composition in formulation and time consuming for production. Emulsifying polymer has been widely used in many cosmetics. A component comprising a mixture of polyacrylamide, C13-14 isoparaffin and laureth-7 (Sepigel 305®) has been reported to be used for creams containing vegetable extracts from Salvia officinalis, Centella asiatica and Calendula spp. (Anchisi, 2001) and vitamins E and A (Thais et al., 2006). Emulsifying polymer is designed for all skin and hair care preparations, formulated as gels (Anna et al., 2006), cream gels (Anchisi, 2001), shampoo and after-sun product (Claude & Daniele, 1995). Type and amount of these emulsifying polymers or solvent and order of mixing notably affected viscosity of cream base as previous reported by our research group (Juntawong et al., 2009). However, there was no scientific publication on the research of using emulsifying polymers in pharmaceuticals. Superficial fungal infections caused by dermatophytes, yeasts and nondermatophyte molds are among the most common skin diseases affecting in both healthy and immunocompromised persons (Cohn, 1992; Gupta et al., 2006). Typically, the topical antifungal treatments often have a broad spectrum of action on dermatophytes and yeast. Clotrimazole [1-[(2-chlorophenyl) diphenyl methyl]-1-H-imidazole] is a lipophilic drug with an antimycotic action that is used both locally and systemically (Ahmed & Gibaly, 1998). It is an odorless, white to pale yellow, crystalline powder. It is practically insoluble in water, but freely soluble in alcohol and soluble in polyethylene glycol 400. It is active against dermatophytes, yeasts, dimorphic

fungi, and bacteria (Borgers, 1980; Shadomy, 1971). Its antimycotic effect is due to the inhibition of ergosterol synthesis and the promotion of the fungal plasma membrane leakage (Burgess and Bodey, 1972; Ritter et al., 1982). Several dosage forms of this drug were prepared and used in topical (Souto et al., 2004), oral (Pandey et al., 2005), esophagal (Janet et al, 1986) and vaginal candidiasis (Abdel-Moety, 2002). Clotrimazole has been reported to use as an active compound in solid lipid nanoparticle (Souto et al., 2004), complex with cyclodextrin (Ahmed et al., 1998), liposome (Zeljka et al., 2005), and mucoadhesive gel (Chang et al., 2002). Clotrimazole cream has been used in the management of skin mycoses. However, clotrimazole has not yet been reported to be used as active compound in cream prepared from emulsifying polymer. The aim of this work was to investigate the effect of the emulsifier polymers and the concentration of drug on the viscosity and antifungal activity of clotrimazole cream prepared without heating. The commercial 1% w/w clotrimazole cream (Canesten® cream) was used for comparison. Materials and Methods Materials Clotrimazole (ctz) (batch no. 20001304, Lambrochem, Italy) and Canesten® cream (batch no. 6B23, Bayer Thai Co., Ltd., Bangkok, Thailand) were used as received. Sepiplus 265® (Se 265) (Ammonium acrylate/Acrylamide copolymer & Polyisobutene & Polysorbate 20) (batch no. T44031), Sepigel 305® (Sg 305)(Polyacrylamide + C13-14 Isoparaffin + Laureth-7) (batch no. T52135), Sepiplus 400® (Se 400)(Polyacrylate & Polyisobutene & Polysorbate 20) (batch no. T43131), Simulgel EG® (Si EG)(Sodium acrylate / Sodium acryloyidimethyl taurate + Isododecane + Polysorbate 80) (batch no. T51411), Simulgel NSÒ (Si NS) (Hydroxyethylacrylate / Sodium acryloyidimethyl taurate copolymer & squalane & Polysorbate 60) (batch no. 32631) were purchased 10

T. Phaechamud et al.

Silpakorn U Science & Tech J Vol.6(2), 2012

from Seppic, Paris, France. Isopropyl isostearate (Prisorine 2021®) (batch no. 1129023, Uniqema, U.K.), methyl hydroxyl benzoate (MP) (batch no. A16/18), propyl hydroxyl benzoate (PP) (batch no.000130), polyethylene glycol 400 (PEG 400) (batch no.P077241) and propylene glycol were supplied by P.C. Drug Center Co., Ltd., Thailand. Cellulose acetate membrane with a pore size of 0.45 mm (Whatman®, Brentford, English), and methanol (HPLC grade) (batch no. 0605570, VWR International, EC) were used as received. Potassium hydrogen orthophosphate (batch no. AF501340), sodium hydrogen orthophosphate (batch no. AF405300) and citric acid (batch no. AF411021) were purchased from Ajax chemicals, Australia. Syringe filter 13 mm disposable filter device and nylon filter with a pore size of 0.45 mm (Lot no.L231 Whatman®, Brentford, English) were used as received. Sabouraud dextrose agar (batch no. 6166081), sabouraud dextrose broth (SDB) (batch no. 6345690), tryptic soy agar (TSA) (batch no. 7341698) and tryptic soy broth (batch no. 1121004) were purchased from Becton, Dickinson and company, France. Methods Preparation of ctz cream The component of cream base is shown in Table 1. An oil phase (phase A: isopropyl isostearate (Prisorine® 2021)) and an aqueous phase (phase B: water and emulsifying polymer) were weighed into separate container. Five emulsifying polymers

were used in this study as following: Sepiplus 265® (Se 265), Sepigel 305® (Sg 305), Sepiplus 400® (Se 400), Simulgel EG® (Si EG), Simulgel NS® (Si NS). Phase A was gradually added to phase B (A to B) at room temperature with glass stirrer to form the emulsion. Finally, the remaining ingredients of phase C (concentrated paraben solution containing 1:10 PP:MP in propylene glycol) and/or drug were added to the bulk. The emulsion was mixed until it was homogenous. The ctz dissolved in PEG (at amount of 5% w/w of formula) was gradually mixed with the cream base. The effect of type of emulsifying polymers and drug loading were investigated. To investigate effect of drug loading on physical properties, drug release and antifungal activity, the selected cream base loaded with 0.125-3 % w/w ctz was prepared and evaluated. Study of physical properties The physical appearance of prepared creams was visually observed. The viscosity of formula was measured using brookfield helipath viscometer (Model: DV-I, Brookfield Engineering Laboratories, INC., USA) at room temperature with constant shear rate for 5 min. The pH of formula was measured using a pH meter (Professional Meter PP-15 Sartorius, Goettingen, Germany). All measurements were performed at room temperature in triplicate for each sample. The physical stability of prepared creams was also tested after 6 cycles temperature cycling. For one cycle, all formulations were kept at 4° C for 24 h in the refrigerator and then at 40°C for 24 h in the hot air oven (FED 720, Scientific promotion, Bangkok, Thailand). Viscosity alteration and phase separation were used to indicate the physical stability. The criteria of selection included a good appearance with a homogeneous, smooth, white creamy texture without the phase separation or without the high viscosity change after temperature cycling.

Table 1 Composition of the cream base

Composition Emulsifying polymer Isopropyl isostearate Paraben concentrated solution PEG 400 Water

% w/w 3 15 1 5 q.s.

Silpakorn U Science & Tech J Vol.6(2), 2012

Effect of the Emulsifier Polymers and the Concentration of Drug

Drug release study A. In vitro release study The Franz® diffusion cells were used for the drug release study comprising the donor compartment with 2.1 cm diameter orifice and the receptor phase was stirred by a constantly spinning magnetic bar at 100 rpm. Since ctz was slightly soluble in water, a mixture of 0.1 M citratephosphate buffer pH 5.5: ethanol at a ratio of 1:1 at 37 ± 0.5°C was used as receptor solution. The receptor compartment was filled with 15 mL of receptor solution. The membrane used in this study was cellulose acetate membrane with a pore size of 0.45 mm. One gram of cream was added into the donor compartment. Cellulose acetate membrane was previously soaked with the receptor solution for 30 min to obtain the equilibrium with this medium. Then it was placed between the donor and receptor compartments. At appropriate time intervals (1, 2, 3, 4, 6, 8, 12 and 24 h), 1 mL of receptor solution was withdrawn. The amount of drug released was measured using HPLC. The volume of sample solution removed was replaced with an equal volume of fresh receptor solution. The extract amounts of ctz released at each time interval were calculated using a calibration curve. All of the experiments were performed triplicate, and the mean release rate ± S.D. was calculated. The release rate through membrane was calculated by plotting the cumulative amount of drug per area against the square root of time. The slope of linear portion of the curve and the X-intercept values were determined by linear regression analysis. B. Determination of ctz Chromatographic separation was carried out at ambient temperature on a LiChrospher® 100 (125, 4 mm) C18, 5 mm. The compounds were separated with a mobile phase consisting of a mixture of methanol: dibasic potassium phosphate buffer pH 6.5 (3:2). The pH of the binary solvent mixture was finally adjusted to 4.0 with o-phosphoric acid. The mobile phase was filtered through 0.45 mm

membrane filter and degassed for approximately 15 min in the sonicator bath prior to use. The flow rate was 1 mL/min. An injection volume was 20 mL, and eluted analyses for ctz were traced by UV-detection at 254 nm. The ctz cream containing 10 mg of ctz was extracted with mobile phase about 50 mL by warming at 50°C using water bath and occasionally shaking until it was completely dissolved and was then removed from the bath, shaken vigorously for 5 min. Afterward, the extractive was cooled in an ice bath for 15 min, and filtered through filter paper into a 100 mL volumetric flask. The volume was finally adjusted to 100 ml with the mobile phase. The acceptable percentage of recovery from the true value was within 90 to 110 %. Antifungal activity test Antifungal activity against Candida albicans (C. albicans) ATCC 17110 of prepared creams was determined using agar cup diffusion method. An isolated colony of C. albicans from sabouraud dextrose agar (SDA) was inoculated into sabouraud dextrose broth (SDB) and incubated at 37°C for 24 h. An amount of culture was obtained by comparing the culture turbidity to standard 0.5 M MacFarland (Lorian, 1991). The adjusted culture was spread over the SDA by a sterile cotton swab. Sterilized cylinder cups were placed carefully on the surface of the swabbed agar. The ctz cream was filled into a cylinder cup. Each plate was placed with cylinders containing the cream with varying concentrations of ctz (0.125, 0.25, 0.5, 1 and 3 %) in selected cream base incubated at 37 °C for 72 h. The 1% ctz in PEG 400 was also tested as a control group since this drug dissolves completely in this solvent. For studying the effect of cream base, the various types of emulsifying polymers with 1% ctz were also used since the commercial cream contains 1%w/w of ctz. The cylinders were then removed and antifungal activity was measured as the diameter (mm) of clear zone. The tests were carried in triplicate and the mean inhibition zone ± S.D. were calculated.

T. Phaechamud et al.

Silpakorn U Science & Tech J Vol.6(2), 2012

Data evaluation A significance of the differences between the viscosity, the drug release rate constant and the inhibition zone (where p < 0.05) of the prepared cream and Canesten® cream was analyzed using ANOVA and pair t-test from SPSS for window version 11.0. Each data point represents an average of three determinations.

ctz cream prepared using different drug loading was ctz 0.125 % cream > ctz 0.25 % cream > ctz 0.5% cream > ctz 1 % cream > ctz 3 % cream (Figure 2). The viscosity of creams was not significantly different as the drug concentration was increased. It was probably due to the low drug content and the limit of drug solubility at high drug loading therefore the dispersed drug slightly influenced the cream viscosity. The viscosity of the formulation was varied depending on the types of emulsifying polymer. The pH of all prepared creams was in the range of 6.30 ± 0.08 to 7.40 ± 0.04 (Tables 2 and 3) which was not different from the acceptable cream base (Mehling, 2007). The viscosity of all cream bases after 6 cycles of temperature cycling was not significantly different (p > 0.05) from freshly prepared cream base. All cream bases before and after 6 cycles of temperature cycling presented a good appearance with homogeneous texture and smoothness and there was no phase separation or color change. The translucent characteristic of the above formula could be ranked in the following descending order: ctz 1% (Si EG), ctz 1% (Si NS), ctz 1% (Sg 305) > ctz 1% (Se 400) and ctz 1% (Se 265). The viscosity value of all creams after 6 cycles of temperature cycling was not significantly different (p>0.05) from freshly ctz cream.

Results and Discussion Physical properties of drug-loaded creams The most stable and elegant cream base included isopropyl isostearate as an oil phase, emulsifying polymers, PEG 400 (5%w/w) as a solubilizer, paraben concentrated solution as a preservative and distilled water as a water phase at a ratio of 15:3:5:1:75. PEG 400 at the amount of 5 % (w/w) was selected as a solvent to dissolve the drug because ctz can dissolve in PEG 400 (AHFs Drug information, 2005). The viscosities of the prepared ctz creams were in the range of 176,889 ± 4,682 to 260,889 ± 5,048 cps (Figure 1). The viscosity of 1 %ctz cream prepared using different emulsifying polymers could be ranked in the following descending order: ctz 1% (Si 265) > ctz 1% (Se 400) > ctz 1% (Si EG) > ctz 1% (Sg 305) > ctz 1% (Si NS). The rank order for the viscosity of 300,000

before

250,000

200,000

viscosity (cps)

250,000

300,000

after

150,000

after

200,000 150,000

100,000

50,000

50,000 0

0 Se 265

Se 400

Si EG

Sg 305

Se 265

Si NS

Se 400

Si EG

Sg 305

Si NS

Type of emulsifying polymer

(B)

Figure 1 The viscosity of ctz cream prepared using different emulsifying polymers both before and after temperature cycling (n=3)

Figure 2 The viscosity of ctz cream containing different concentration of ctz before and after temperature cycling (n=3) 13

Silpakorn U Science & Tech J Vol.6(2), 2012

Effect of the Emulsifier Polymers and the Concentration of Drug

Table 2 pH Value of 1 % ctz creams prepared with different emulsifying polymers (n=3)

cumulative release (ug/cm )

1400

Types of emulsifying polymer

pH ± S.D. Freshly prepared

After temperature cycling

Se 265

7.40 ± 0.04

7.32 ± 0.07

Se 400

7.34 ± 0.15

7.32 ± 0.12

Si EG

6.39 ± 0.14

6.36 ± 0.10

Sg 305

6.44 ± 0.09

6.44 ± 0.07

Si NS

6.35 ± 0.25

6.30 ± 0.08

After temperature cycling

0.125 %

7.33 ± 0.02

7.32 ± 0.02

0.25 %

7.35 ± 0.10

7.34 ± 0.08

0.5 %

7.34 ± 0.10

7.36 ± 0.05

7.33 ± 0.03

7.36 ± 0.03

7.32 ± 0.08

7.30 ± 0.04

Si EG

1000

Sg 305

800

Se 265

600 400 200

2 3 4 1/2 square root of time (h )

Figure 3 Release profiles of ctz cream prepared using different emulsifying polymers (n=3) the drug release from cream base. The variation in amount and types of acrylate polymer, oil, and the surfactant incorporation in the emulsifying polymers could probably influence the viscosity of the prepared dosage forms. Generally, the greater the viscosity of the formulation, the lower the release of drug (Chowdary and Kumar, 1994; Tehrani and Mehramizi, 2000; Salamon et al., 1979; Lindner and Lippold, 1995; Kim and Fassihi, 1997; Reynolds et al., 1998). The viscosity of cream base prepared using the different emulsifying polymers was ranked as followed: Se 265 > Se 400 > Si EG > Se 305 > Si NS. The release rate of ctz cream with emulsifier as Se 265, Se 400, Si EG, Se 305 or Si NS was 176.38, 182.27, 285.34, 353.69, or 365.63 mg/cm2/ h1/2, respectively. Therefore, the higher viscosity of the emulsion system retarded the drug release. The utilization of emulsifying polymer led to the formation of a dense polymer matrix structure, resulting in smaller pores and a more tortuous structure. Thereafter, the diffusion of incorporated drug through the network was difficult. The lag times of drug release from creams containing different types of emulsifying polymers showed no significant difference (p>0.05).

pH ± S.D. Freshly prepared

Si NS

Table 3 pH Value of creams prepared with Se 265 containing different amount of ctz (n=3) ctz (%w/w)

Se 400

1200

Drug release from creams Effect of emulsifying polymer types on drug release The release of ctz from cream bases containing different emulsifying polymers is shown in Figure 3. The rank order of release of ctz cream prepared by using different emulsifying polymers was Si NS > Se 305 > Si EG > Se 400 > Se 265. The effect of different emulsifying polymers among Se 265, Se 400, Si NS, Si EG, Si 305 on the release rate was significantly different (p<0.05) (Table 4). The types of emulsifying polymer affected

T. Phaechamud et al.

Silpakorn U Science & Tech J Vol.6(2), 2012

Table 4 Estimate parameters from cure fitting with Higuchi’s equation of drug release from different cream bases and different drug concentration (n=3) Formula

Correlation Coefficient (r2)

Release rate (ug/cm2/h1/2)

lag time (h)

Mean+S.D.

Canesten® cream

0.9951

177.56+4.21

0.67+0.06

1 % ctz (Se 265)

0.9945

176.38+2.27

0.80+0.05

1 % ctz (Se 400)

0.9940

182.27+2.80

0.71+0.03

1 % ctz (Si EG)

0.9993

285.34+4.25

0.78+0.04

1 % ctz (Si NS)

0.9971

365.63+4.61

0.81+0.05

1 % ctz (Sg 305)

0.9985

353.69+5.06

0.89+0.04

0.125% ctz cream*

0.9976

46.25+1.63

0.32+0.07

0.25% ctz cream*

0.9974

65.13+2.04

0.27+0.03

0.5% ctz cream*

0.9971

166.39+0.96

0.72+0.03

1% ctz cream *

0.9944

174.66+1.04

0.68+0.10

3% ctz cream*

0.9946

185.01+1.93

0.56+0.07

cream base containing 3% Se 265 as an emulsifier, 15 % isopropyl isostearate as an oil, 1% paraben conc. solution, 5% PEG400 and distilled water.

Effect of drug loading on drug release By comparison at the same concentration, Se 265 provided cream which showed the highest viscous and stable therefore this emulsifying polymer was selected to prepare the cream base loaded with different amount of ctz. The drug release was increased depending on drug concentration in the cream (Figure 4). The release rate was enhanced as a drug concentration was increased. The release rate of cream containing different drug loading was significantly different (p<0.05). The similar result was also reported by Yan-Fei et al. (2007). Increased release rate with an increment of a loading dose might be due to an increase in thermodynamic activity of the drug, which is related to its concentration in the cream base (Vlachou et al, 1992).

In vitro drug release studies of creams containing ctz demonstrated a prolonged release characteristic following Higuchi’s model (Higuchi, 1962) with a correlation coefficient ranging from 0.9940 to 0.9993 (Table 4), which signified an excellent model fit. This finding indicated that the rate-controlling stage in the release process was the diffusion of the dissolved drug through the polymeric network of the external medium. Thus, the drug release increased linearly along the increasing concentration until it reached the same limiting value which was the value of the saturated solution. However, the in vitro release results obtained under artificial stirring conditions and buffer medium might not directly mimic the in vivo situation. The in vitro release results, however,

700

ctz 0.125 %

600

ctz 0.25 %

Effect of the Emulsifier Polymers and the Concentration of Drug

800 700

ctz 0.5 %

500

cumulative release (ug/cm )

Silpakorn U Science & Tech J Vol.6(2), 2012

ctz 1 %

400

ctz 3 %

300 200 100 0 0

2 3 4 square root of time (h 1/2)

600 ctz cream 500

canesten cream

400 300 200 100

Figure 4 Release profiles of ctz creams prepared with Se 265 containing different amount of drug (n=3)

0 0

2 3 4 square root of time (h 1/2)

Figure 5 Release profiles of ctz from developed clotrimazole cream prepared with Se 265 and Canesten® cream (n=3)

provided information of the release rate of ctz from cream base. Only about 40 % of drug content was released from Franz diffusion cell at 24 hour, the rest might be hold by emulsifying polymer or absorbed on membrane (Shantha and Harding, 2003).

shown in Table 5. The cream bases did not exhibit the inhibition of C. albicans growth (data not shown). Antifungal activities of all 1 % ctz creams prepared using different emulsifying polymers were insignificantly different (p<0.05). However, they were significantly different (p<0.05) from 1 % ctz solution prepared in PEG 400. This result was not corresponding to the in vitro drug release. Therefore the antifungal activity depended on the drug concentration whereas the type of emulsifying polymer did not play important role on this activity.

Comparison of drug release from Canesten®cream and prepared ctz cream The release of ctz from Canesten® cream and selected ctz cream was investigated. The release pattern of ctz from prepared cream (1% ctz cream prepared using 3% Sepiplus 265® as an emulsifier, 1% paraben concentrated solution and 15 % isopropyl isostearate as an oil) resembled that of commercial ctz cream (Canesten® cream) as shown in Figure 5. The release rate (Table 4) of Canesten® cream and ctz cream was insignificantly different (p>0.05). Therefore, the release of drug from prepared cream was similar to a commercial ctz cream (Canesten® cream). The lag time of drug release from prepared cream and Canesten® cream showed no significant difference (p>0.05).

Table 5 Inhibition diameter (mm) of 1% ctz cream containing different emulsifying polymers (n=3)

Antifungal activity test Effect of emulsifying polymer types on antifungal activity The antifungal activity of ctz creams prepared using different emulsifying polymers is

Type of emulsifying polymer

Inhibition diameter ± S.D. (mm)

Si NS

16.4 ± 0.5

Sg 305

16.0 ± 0.5

Si EG

16.1 ± 0.9

Se 265

15.2 ± 0.8

Se 400

15.3 ± 0.7

1 % ctz solution

32.0 ±1.0

1 % ctz solution prepared in PEG 400

T. Phaechamud et al.

Silpakorn U Science & Tech J Vol.6(2), 2012

Effect of drug loading on antifungal activity The antifungal activity of cream containing different amount of ctz against C. albicans is shown in Table 6. Increasing the amount of ctz from 0.1250.50 % tended to enhance the antifungal activity of ctz cream. Due to the limit of ctz solubility in this cream base the drug loading higher than 0.5% did not apparently increased the antifungal activity. The inhibition clear zone of creams containing 0.53% ctz was significantly wider (p<0.05) from those containing 0.125-0.25% ctz. The greater the drug content, the wider the inhibition zone. In comparison between the different concentrations of ctz cream and 1% ctz solution, the cream 0.5-3 % ctz showed the significantly lower antifungal activity than the solution. Antifungal activity of Canesten® cream and ctz cream The antifungal activity of ctz cream prepared using 1 % w/w ctz, 3% w/w Sepiplus 265®, 1% paraben concentrated solution and 15% w/w isopropyl isostearate is shown in Table 7. The inhibition zone of ctz cream was not significantly different (p>0.05) from Canesten® cream which was corresponded to their in vitro release results.

It was suggested that the antifungal activity against C. albicans of the Canesten® cream and prepared cream was not different. Table 7 Inhibition zone diameter (mm) of ctz cream and Canesten® cream (n=3)

Inhibition diameter ± S.D. (mm)

0.00%

0.0 ± 0.0

0.125 %

10.9 ± 0.7

0.25 %

11.7 ± 0.3

0.5 %

16.4 ± 0.2

16.5 ± 0.5

17.2 ± 0.3

1 % ctz solution*

32.0 ±1.0

Inhibition diameter ± S.D. (mm)

Canesten® cream

15.1 ± 0.4

1% ctz cream

14.9 ± 0.2

Conclusion The ctz cream could be prepared without heating using the emulsifying polymer. The most stable and elegant cream base included isopropyl isostearate as an oil, ammonium acrylate/acrylamide copolymer & polyisobutene & polysorbate 20 (Se 265) as an emulsifier, paraben concentrate as a preservative, PEG 400 (5%w/w) as a solubilizer and distilled water as a water phase at a ratio of 15:3:1:5:75. The formulation was shown to have a highly effective antifungal activity. From this investigation, the emulsifying polymer could be considered as choice materials in preparation of cream base for ctz.

Table 6 Inhibition diameter (mm) of ctz creams containing different amount of ctz (n=3) Clotrimazole

Type of cream

Acknowledgements This research work was kindly supported by the Faculty of Pharmacy, Silpakorn University. We appreciate Assist. Prof. Dr. Nontima Vardhanabhuti and Dr. Parichat Chomto for their invaluable comments. References Abdel-Moety, E. M., Khattab, F. I., Kelani, K. M., and AbouAl-Alamein, A. M. (2002) Chromatographic determination of clotrimazole, ketoconazole and fluconazole in pharmaceutical formulations. Il Farmaco 57: 931-938.

1 % ctz solution prepared in PEG 400

Silpakorn U Science & Tech J Vol.6(2), 2012

Effect of the Emulsifier Polymers and the Concentration of Drug

AHFs Drug information part 5, (2005) American Society of Health-System Pharmacists, Bethesda, USA., pp. 3366-3371. Ahmed, M. O. and El-Gibaly, I. (1998) Effect of cyclodextrins on the physicochemical properties and antimycotic activity of clotrimazole. International Journal of Pharmaceutics 171: 111-121. Anchisi, C., Maccioni, A. M., Sinico, C., and Valenti, D. (2001) Stability studies of new cosmetic formulations with vegetable extracts as functional agents. Il Farmoco 56: 427-431. Anna, R. B., Maria, C. B., Giovanni, M., and Franco, F. V. (2006) Development and stability of semisolid preparations based on a supercritical CO2 Arnica extract. Journal of Pharmaceutical and Biomedical Analysis 41: 449-454. Burgess, M. A. and Bodey, G. P. (1972) Clotrimazole : in vitro and clinical pharmacological studies. Antimicrobial Agents and Chemotherapy 2: 423-426. Chang, J. Y., Oh, Y., Kong, H. S., Kim, E. J., Jangd, D. D., Namd, K. T., and Kima, C. (2002) Prolonged antifungal effects of clotrimazole containing mucoadhesive thermosensitive gels on vaginitis. Journal of Controlled Release 82: 39-50. Chowdary, K. and Kumar, P. A. (1994) Formulation and evaluation of topical drug delivery systems of ciprofloxacin. Indian Journal of Pharmaceutical Sciences 58(2): 47-50. Claude, D. and Daniele, C. (1995) Use in cosmetics or in topical application of an aqueous dispersion based on organopolysiloxanes and on a cross-linked acrylamide/neutralized 2-acrylamido-2-methylpropanesulfonic acid copolymer. U.S. Patent No. 5470551. Cohn, M. S. (1992) Superficial fungal infections. Topical and oral treatment of common types. Postgraduate Medicine 91: 239-244, 249-252.

Gupta, A. and Tu, L. (2006) Dermatophytes: diagnosis and treatment. Journal of the American Academy of Dermatology 54: 1050-1055. Higuchi, W. I. (1962) Analysis of data on the medicament release from ointments. Journal of Pharmaceutical Sciences 51: 802-804. Janet, C., Kevin, M., Laura, F., Rita, B., and Edward, J. B. (1986) Clotrimazole treatment for prevention of oral candidiasis in patients with acute leukemia undergoing chemotherapy : Results of a double-blind study. The American Journal of Medicine 81(5): 771-774. Juntawong, S., Charoenteeraboon, J., Chansiri, G., and Phaechamud, G. (2009) Utilization feasibility of emulsifying polymers in cream base. Thai Pharmaceutical and Health Science Journal 4(4): 456-462. Kim, H. and Fassihi, R. (1997). Application of binary polymer systems in drug release rate modulation. 2. Influence of formulation variables and hydrodynamic conditions on release kinetics. Journal of Pharmaceutical Sciences 86: 323-328. Lindner, W. D. and Lippold, B. C. (1995) Drug release from hydrocolloid embeddings with high or low susceptibility to hydrodynamic stress. Pharmaeutical Research 12: 17811785. Lorian, V. (1991) Antibiotics in Laboratory Medicine. Williams and Wilkins, Baltimore, pp. 12-13. Mehling, A., Kleber, M., and Henson, H. (2007) Comparative studies on the ocular and dermal irritation potential of surfactants. Food and Chemical Toxicology 45(5): 747-758. Pandey, R., Ahmad, Z., Sharma, S., and Khuller, G. K. (2005) Nano-encapsulation of azole antifungals: Potential applications to improve oral drug delivery. International Journal of Pharmaceutics 301(1-2): 268-276. 18

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Reynolds, T. D., Gehrke, S. H., Hussain, A. S., and Shenouda, L. S. (1998) Polymer erosion and drug release characterization of hydroxypropylmethylcellulose matrices. Journal of Pharmaceutical Sciences 87: 1115-1123. Ritter, W., Patzschke, K., Krause, U., and Stettendorf, S. (1982) Pharmacokinetic fundamentals of vaginal treatment with clotrimazole. Chemotherapy 28: 37-42. Salomon, J., Doelker, E., and Buri, P. (1979) Importance de la technologie formulation mecharnism liberation potassium content matrices hydrophiles. Influence of viscosity of percentage of gel. Acta Pharmaceutica Helvetiae 54: 82-85. Shadomy, S. (1971) In vitro antifungal activity of clotrimazole. Infection and Immunity 4(2): 143-148. Shantha, K. L. and Harding, D. K. (2003) Synthesis, characterisation and evaluation of poly [lactose acrylate-N-vinyl-2-pyrrolidinone] hydrogels for drug delivery. European Polymer Journal 39: 63-68. Souto, E. B., Wissing, S. A., Barbosa, C. M., and Muller, R. H. (2004) Development of a controlled release formulation based on SLN and NLC for topical clotrimazole delivery. International Journal of Pharmaceutics

278: 71-77. Tehrani, M. R. and Mehramizi, A. (2000) In vitro release studies of piroxicam from oil in water creams and hydroalcoholic gel topical formulations. Drug Development Industrial Pharmacy 26(4): 409-414. Thais, G. and Mirela, D. 2006. Stability of cosmetic formulations containing esters of Vitamins E and A: Chemical and physical aspects. International Journal of Pharmaceutics 327: 12-16. Vlachou, M. D., Rekkas, D. M., Dallas, P. P., and Choulis, N. H. (1992) Development and in vitro evaluation of griseofulvin gels using Franz diffusion cells. International Journal of Pharmaceutics 82(1-2): 47-52. Yan-Fei, L., Ke-Long, H., Dong-Ming, P., Ping, D., and Gui-Yin, L. (2007) Preparation and characterization of glutaraldehyde cross-linked O-carboxymethylchitosan microspheres for controlled delivery of pazufloxacin mesilate. International Journal of Biological Macromolecules 41(1): 87-93. Zeljka, P., Natasa, S. B., and Ivan, A. (2005) Characterisation and in vitro evaluation of bioadhesive liposome gels for local therapy of vaginitis. International Journal of Pharmaceutics 301: 140-148.

Research Article Numerical Computation of pH and Buffer Capacity in Complex Mixtures of Acids, Bases and Ampholytes Wibul Wongpoowarak, Damrongsak Faroongsarng, Nimit Worakul and Prapaporn Boonme* Department of Pharmaceutical Technology, Faculty of Pharmaceutical Sciences, Prince of Songkla University, Hat-Yai, Songkhla, Thailand Corresponding author. E-mail address: prapaporn.b@psu.ac.th

Received September 14, 2011; Accepted May 5, 2012 Abstract

This study was aimed to simplify the pH calculation for complex mixtures of acids, bases and

ampholytes; the theoretical concept on pH calculation was renovated. A new algorithm was proposed to state that buffer capacity (b) could be simultaneously achieved with pH. To validate the method, the buffer systems of Na2HPO4/NaH2PO4 and Na2HPO4/citric acid were employed. Acid and base titration was done on the buffer systems using HCl and NaOH, respectively. It was demonstrated that only the charge balance equation (CBE) was necessary and sufficient to successfully compute b. To achieve the desirable accuracy, the pH interval used in such algorithm should be 10-4 for general calculation; between 10-4 and 10-2 for 8 significant-digits calculation; between 2 x 10-10 and 4 x 10-4 for 16 significant-digits calculation. Visual Basic Source Code written in Microsoft AccessTM for demonstrating computation of pH and b of pure water was also illustrated. Key Words: pH; Buffer capacity; Computational prediction; Algorithm Introduction

This assumption-dependent algebraic method is

Prediction of pH and buffer capacity (b) of

inconvenient to predict pH of a multi-component

multi-component solutions has been very useful in

solution. Butler (1964) described a unified concept

several applications. For pharmaceutical field, it

to calculate pH of a solution by writing and solving

can be used in the design of dosage forms (York,

two equations from three possible equations, i.e.,

2002), in analytical process (Heyrman and Henry,

proton balance equation (PBE), mass balance

nd), in prediction of oral drug absorption (Obata et

equation (MBE) and charge balance equation

al., 2005) and in food preservation (Coiffard et al.,

(CBE). The variables appeared in these equations

1997; Chung et al., 2010; Garcia-Gonzalez et al.,

relate to each other by dissociation constant of

2010).

solutes in a solvent. If these relationships could be

A method in pH and b calculation is algebraic

solved and as long as no constraints were involved,

method under specific assumptions for each system.

pH prediction of a solution containing various acids,

Silpakorn U Science & Tech J 6 (2) : 20-29, 2012

P. Boonme et al.

Silpakorn U Science & Tech J Vol.6(2), 2012

bases and/or ampholytes would be possible. If in the

the CBE (Cutler, 1986). The difference of both sides

situation with constraints, other parameters should

calculated from the negative-charge side minus the

be mutually considered. Nevertheless, solving

positive-charge side in CBE, designated as D, is then

simultaneous equations would be ending up with

introduced as an indicator for the validity of CBE.

high-degree nonlinear-multivariate polynomial

The CBE is valid when the value of D is zero and

equations. Since the root of the equation must be

that pH would be the unique possible value of such

solved with numerical method, it may not be suitable

a system. Moreover, with pH increases, negative

for database purpose due to the complexities in the

charge increases whereas positive charge decreases.

calculation process.

The value of D should be a monotonous function

of pH. This monotonous property is specifically

The database could be constructed on the

basis that we could numerically and symbolically

solvable by binary search method (Cutler, 1986).

split substance dissolved into all related species.

By varying pH, the pKa, pKw and mass balance

terms of equivalent unit, the negative and positive

relationship could be solved for all species at that

species are referred to basic and acidic compounds,

particular pH. By using the approach suggested by

respectively. Therefore, D is the base in excess (i.e.,

Cutler (1986), pH was guessed in binary search

equivalent to adding bases into a system). The slope

style to check for validity of charge balance

of the plot between the pH and the corresponding

equation. When the valid pH was found (no charge

D (where pH exhibits the actual value, i.e., at D =

balance anomaly), buffer capacity is also know

0) is the change of bases in terms of equivalent unit

simultaneously according to our algorithm.

per liter versus the change in pH from its initial

The aim of the article was to demonstrate

equilibrium condition. Thus, b will be the slope of

that not only b could be directly derived from CBE

the D vs pH plot by definition, since b is defined as

with slight modification of Cutler’s concept but also

the ratio of change of bases in equivalent unit per

simultaneously obtained with pH in the prediction

liter divided by the change in pH. By finding the

process.

actual pH according to Cutler’s concept, the b of

Since the charge balance is always defined in

that system could also be obtained simultaneously Review of the computation of pH and β

from the slope of D-pH plot at that specific pH.

Theoretical aspects of CBE

In multi-component mixtures, it was assumed

excess that corresponds to the changing of pH, the

that there was no interference between different

reverse was also expected to be true, i.e., the base

species via chemical reactions. At any specified pH,

in excess caused the pH to change. It implied that

all species conforming to that pH could be able to

the whole isovolumetric titration profile of any fixed

compute from the definition of weak acid dissociation

system could be constructed within the single-point

constants (Ka’s), dissociation constant of water

pH calculation process.

Since D could be interpreted as the base in

Species calculation

solved from MBE, CBE and dissociation constants

At any given pH, all related species could

(Butler, 1964). According to an electroneutrality

be computed from algebraic expressions (Sinko,

rule, the valid pH would be where the positive-

2010). For a complex mixture of acids, bases and

charge side equaled to the negative-charge side in

ampholytes, the expressions may be complicated.

(Kw) and MBE. In the other words, the pH could be

Silpakorn U Science & Tech J Vol.6(2), 2012

Numerical Computation of pH and Buffer Capacity

It is of importance to have an insight into the

where b and C are buffer capacity and the total

calculation process for triprotic acid with the

concentration of that buffer species, respectively. In

simplest algebraic expression that is more suitable

the case of overlapping pKa near the pH of interest,

to implement into software. The species calculation

buffer capacity contribution from all overlapping

is arranged into 2 steps.

pKa had to be summed up together, i.e., insertion

of summation sign for the last terms is a more

In the first step, an arbitrary unit could be used

in the process, e.g., H3A = 1 unit. The next species

appropriate form for such case.

will be the previous species multiply with 10

pH-pKa

Theoretically, the contribution of pH on the

For the particular example, all species involved

b of the system is determined according to Eq. 7,

would be as illustrated in Eq. 1-3, where H3A is

i.e., ignoring the last term in the Eq. 6.

a representative of an acid with three hydrogen

b = ln( 10)([ H3O + ] + [OH− ])}

atoms which can be dissociated to H2A-, HA2-, and A3- (Sinko, 2010). −

H 2 A = H 3A × 10

pH − pK a1

3−

2−

A = HA × 10

b would be 4.6 x 10-7 at pH 7 (see Appendix for

(Eq. 2)

pH − pK a 3

demonstrating code to compute this value by using the principle outlined in the above section).

(Eq. 3)

At physiological pH, suitable for pharmaceutical

The overall sum of all HA-related species (T)

preparation where pH is not in too acidic or basic

can be calculated using Eq. 4. −

T = H 3A + H 2 A + HA

2−

region, only the third term in the Eq. 6 can be

3−

expanded by using the definition of pH and pKa to

(Eq. 4)

yield Eq. 8.

In the second step, correction with the actual

C(10 − pH − pK a ) b = ln( 10) (10 − 2pH + 2 × 10 − pH − pK a + 10 − 2pK a ) (Eq. 8)

unit was done. Let M be the total concentration of all HA-related species, T unit = M molar

(Eq. 5)

By multiplying with M/T, all species in molar

program, at an assigned pH, species calculation

(10pK a − pH + 2 + 10pH − pK a )

multicomponents or polyelectrolytes, using only

the basic definition of the acidity constants involved. Classical β calculation

In the case of weak acids or weak bases in

(without pH effect), Eq. 9 can be rewritten as Eq. 10. b = ln( 10)(

C[H3O ]K a

Rearranging the terms in the parenthesis

simplified form of Van Slyke’s equation for b

showed in Eq. 6 is utilized (Sinko, 2010):

([ H3O + ] + K a ) 2

(Eq. 9)

as well as substituting the term 10|pH-pKa| by X, a

aqueous solution, the exact Van Slyke’s equation

b = ln( 10)

is straightforward even in a solution containing

Simplifying the Eq.8 by factoring with

(10-pH-pKa), the Eq. 9 is gotten.

unit could be obtained. In computational software

b = ln( 10){[ H3O + ] + [OH− ] +

The Eq. 7 is pH effect, which could be totally

neglected at physiological pH. The minimum

(Eq. 1)

HA 2 − = H 2 A − ×10pH − pK a 2

(Eq. 7)

1 2+X+ X

}(Eq. 6)

)

(Eq.10)

P. Boonme et al.

Silpakorn U Science & Tech J Vol.6(2), 2012

In a mixture of various buffering components,

meter (Model 20, Denver Instrument Company,

the total b could be computed from its partial

USA). Titration was performed at 25°C in three

contribution for each dissociation constant. In

replicates. The concentration of acid (negative

addition, the b correction due to the pH effect (Eq.

value) or base (positive value) added were plotted

7), together with the ionic strength correction, may

against corresponding pH. The b was calculated

be used to achieve more accurate value.

from the slope of a linear regression when small

amount of acid or base added. These results were Materials and Methods

compared to the calculated pH and b values used the

Materials

binary search method with optimizing computation

Sodium dihydrogen phosphate monohydrate

accuracy. Determination of pH and β of solution

(NaH2PO4.H2O), hydrochloric acid (HCl) and sodium

hydroxide (NaOH) were obtained from Merck,

containing X ml of 0.2 M Na2HPO4 and (100-X

Germany. Di-sodium hydrogen orthophosphate

ml) of 0.1 M citric acid

(Na2HPO4) were obtained from BDH Laboratory

Supplied, UK. Citric acid (C6H8O7) was obtained

fractions of 0.2 M Na2HPO4 and 0.1 M citric acid

from Vidhyasom Co., Ltd., Thailand. Distilled water

were prepared and determined pH values at 25°C

was used throughout the experiment. All chemicals

using the pH meter. The b was determined by the

were pharmaceutical grade and used without further

identical method as previously mentioned. The

modification.

experimental values were plotted with the simulated

Determination of pH and β of solution

values and the values taken from the reference

containing 0.002 M Na2HPO4 and 0.001 M

(Dean, 1999) to demonstrate the applicability of

NaH2PO4

the proposed method in prediction of the pH and b

of a complicated mixture, in which the simultaneous

This experiment was done by the titration of

Buffer solutions with different volume

equations may not be easily solved.

buffer solution with acid or base. The acidic or basic buffer solutions were prepared by adding a stock solution of HCl or NaOH previously standardized

Results and Discussion

following the method specified in USP24 (2000)

into buffer solution to get a final concentration of

accuracy

0.02 gram-equivalent/liter. The concentrations of

Na2HPO4 and NaH2PO4 in the solutions were similar

as multivariate equations could be transformed to

to those of original buffer, i.e., 0.002 M Na2HPO4

a univariate equation. However, solving univariate

and 0.001 M NaH2PO4. During titration of these

problem by numerical method is not always flexible

solutions into an original buffer, the concentration

for software implementation, some method may also

of HCl or NaOH gradually changed whereas the

posses a limitation, for instance, Newton-Raphson

sum of Na2HPO4 and NaH2PO4 concentrations was

method may encounter numerical instability in a

kept constant. The titrant was added by micropipette

very low slope region (Mathews, 1987). Since low

and stirred with magnetic stirrer (Model MR 3000D,

slope would occur in the case of very low b system,

Heidolph, Germany). The sample was allowed

Newton-Raphson method would not be a preferable

to equilibrate before each pH recording by a pH

choice. The binary search method was selected since

Calculation for β: optimizing computation As stated by Culter (1986), MBE and CBE

Silpakorn U Science & Tech J Vol.6(2), 2012

Numerical Computation of pH and Buffer Capacity

its stable with monotonous function and always

error as a trade-off. In the binary search, the interval

rapidly converged to 8 significant-digits precision

for each of iteration could be reduced by half. When

within 30 iterations.

the search interval was near an optimal value, one

Since the slope is a derivative of a function,

would achieve the highest calculation accuracy. To

approximation of slope requires infinitely small

determine its effect on the accuracy of b calculation,

value of pH interval. However, too small value of

the computer simulation was performed using

this pH interval may lead to numerical rounding

protocol shown in Algorithm 1.

Algorithm 1 Simulation protocol for finding optimal pH interval to be used in b computation process. Vary acid concentration within 1 and 10-15 range. Vary pH interval within 1 and 10-11 range. Calculate pH of the system using such pH interval Calculate b by this method using such pH interval Calculate b by exact Van Slyke’s equation Calculate prediction error Record the best pH interval at each acid concentration Summarize the optimal pH interval that is applicable to most cases of acid concentrations. Note: Criteria to determine the best pH interval is to minimize MaxError or RMSE

MaxError = Maimum ( bThisMethod − b VanSlyke ) RMSE = (∑ bThisMethod − b VanSlyke ) 2 / N Optimal pH interval is the pH interval that cause the calculation error to be smaller than the acceptable limit: MaxError < Multiplier x best case MaxError and RMSE < Multiplier x best case RMSE MaxError is the worst-case prediction error, while RMSE is the general prediction error in statistical sense. The multiplier of 10 is used in nearly all conditions, except when the optimal pH interval range is too narrow for practical purpose or shift away from the usual range applicable to other situations that we will use the multiplier of 100 instead.

In addition, the optimal pH intervals for

determining the b resulting from each protocol are shown in Algorithm 2.

P. Boonme et al.

Silpakorn U Science & Tech J Vol.6(2), 2012

Algorithm 2 Optimizing results using the protocol according to Algorithm 1. 1. Strong monoprotic acid at various concentrations between 1 and 10-15 Single precision computation mode Conclusion: By using the multiplier of 10 (see Algorithm 1), the optimal pH range is very narrow and may limit its usefulness; therefore multiplier as 100 is used to obtain a more applicable range. It was found that the optimal pH interval should be between 3 x 10-5 and 5 x 10-2. Double precision computation mode Conclusion: The optimal pH interval should be between 2 x 10-10 and 4 x 10-4. 2. Weak monoprotic acid at various concentration between 1 and 10-15 Single precision computation mode Conclusion: The optimal pH interval should be between 1 x 10-4 and 1 x 10-2. Double precision computation mode Conclusion: The optimal pH interval should be between 2 x 10-10 and 4 x 10-4. Conclusion: The universal optimal pH interval is 1 x 10-4. This should be applicable for both single and double precision calculation. In the case of calculation with specific significant digit, this optimal value should be changed.

We found that pH interval between 10 -4

pH and β of a solution containing 0.002 M

and 10 was suitable for single precision mode (8

Na2HPO4 and 0.001 M NaH2PO4

significant digits), and that between 2 x 10-10 and

Approximating the pH of this system using Henderson-Hasselbalch equation, by assuming the pH close to pKa2 due to the fact that [HPO42-] and [H2PO4-] are the dominant species, provides pH at 7.51 (= pKa2 + log 0.002/0.001). The b of this system computed from Van Slyke's equation with correction from pH effect was 0.00153. A group of equations containing those of dissociation constants, MBE, and CBE was specified according to Algorithm 4. By varying pH and computing all related species, a plot of pH against D in Figure 1 could be illustrated. It was found that exact solving for the root of equation (pH at which D = 0) provided a pH of 7.38±0.02, with slope at that point equaled to 0.00151±0.00004 (i.e., the b of the system). These values were comparable with those obtained from Van Slyke's equation.

-2

4 x 10-4 for double precision mode (16 significant digits). The value of 10-4 was set since it could be used satisfactorily for both single and double precision calculation in various situations. The computed b is accurate for at least 3 decimal places. If the selected pH interval was higher than this optimal value, the accuracy may be deteriorated, whereas, smaller value would lead to rounding error instability. In addition, the method allowed computing b simultaneously with the pH value. Algorithm 3 summarized a pseudo-code for program implementation.

Silpakorn U Science & Tech J Vol.6(2), 2012

Numerical Computation of pH and Buffer Capacity

Algorithm 3 The pseudo-code of buffer computation for program implementation. Set Maximum pH and compute CBE inequality at Maximum pH (usually 14 or higher). Set Minimum pH and compute CBE inequality at Minimum pH (usually 0 or lower). Set Converge = False Do Set Middle pH to (Maximum pH + Minimum pH)/2 Compute CBE inequality at Middle pH If CBE inequality at Middle pH is positive then Set Maximum pH to Middle pH (and update its CBE inequality) Else Set Minimum pH to Middle pH (and update its CBE inequality) End if If Maximum pH - Minimum pH > 0.0001 (the optimal pH interval) then Set b to (CBE inequality at Maximum pH - CBE at Minimum pH) divided by (Maximum pH - Minimum pH) Else Set Converge = TRUE End if Loop until Converge Report Middle pH and the corresponding b Algorithm 4 Equations dealing with dissociation constants as well as MBE and CBE of 0.002 M Na2HPO4 /

0.001 M NaH2PO4 buffer.

Constant definition: K w = [H 3O + ][OH − ]

K a1 = [H 3O + ][ H 2 PO 4 − ] /[ H 3PO 4 ] = 10 −2.12 K a 2 = [H 3O + ][ HPO 4 2 − ] /[ H 2 PO 4 − ] = 10 −7.21

K a 3 = [H 3O + ][ PO 43− ] /[ HPO 4 2 − ] = 10 −12 .67 Mass balance: [H 3PO 4 ] + [H 2 PO 4 − ] + [HPO 4 2 − ] + [PO 43− ] = 0.003

[ Na + ] = 0.005 Charge balance: [H 3O + ] + [ Na + ] = [OH− ] + [H 2 PO 4 − ] + 2[HPO 4 2 − ] + 3[PO 43− ] From charge balance, D (the deviation from the electroneutrality rule) is described as the negative charge side of CBE minus the positive-charge side of CBE.

D = ([ OH − ] + [H 2 PO 4 − ] + 2[HPO 4 2 − ] + 3[PO 43− ]) − ([ H 3O + ] + [ Na + ])

P. Boonme et al.

Silpakorn U Science & Tech J Vol.6(2), 2012

Volume fraction of Na2HPO4

Figure 1 Plot of pH against D of 0.002 M

Figure 2 Plot between volume of 0.2 M Na2HPO4

Na2HPO4/0.001 M NaH2PO4 buffer from

against pH and b of Na 2HPO 4/citric

computer simulation using conditions in

acid buffer: circular symbol referred to

Algorithm 4: circular symbol referred

experimental values (blank: 100b, filled:

to experimental values and solid lines

pH), square symbol referred to pH values

referred to calculated values

taken from the reference (Dean, 1999), and solid lines referred to calculated

values

pH and β of a solution containing x mL of

0.2 M Na2HPO4 plus (100-x) mL of 0.1 M Citric

satisfactorily applicable. The pH and b of a solution

acid A set of pH’s and b’s of a solution containing

containing mixtures of polyprotic acids that were

various volume fraction of 0.2 M Na2HPO4 and that

generally regarded as difficult and very tedious to

calculate could be easily accessible by this method.

of 0.1 M citric acid was computed using the previous manner. Figure 2 illustrates the plot of volume

Conclusions

fraction of 0.2 M Na2HPO4 against pH and 100b for the ease of viewing.

In addition to the computation, Robinson-

applicable to predict pH of a buffer without any

Guggenheim-Bates correction for pH due to ionic

difficulty for a multicomponent system. However,

strength (Mathews, 1987) was utilized. It was

when precipitation or chemical change occurs,

observed that the experimental data of the calculated

the usefulness of this concept is limited due to the

pH and b were comparable to those of the available

effects of the mass balance. The precipitation or

pH data previously published (Dean, 1999). It was

chemical change will be the constraint of solving

clearly demonstrated that the overall concept was

mass balance equation. The binary search method

The concept of Butler and Cutler would be

Silpakorn U Science & Tech J Vol.6(2), 2012

Numerical Computation of pH and Buffer Capacity

Dean, J. A. (1999) Langeâ&#x20AC;&#x2122;s Handbook of Chemistry,

would become useless in such case. Multivariable search methods should be used instead, which is

15th ed., McGraw-Hill, New York.

outside the scope of this paper.

Garcia-Gonzalez, L., Teichert, H., Geeraerd, A. H.,

In this article, the charge balance equation

Elst, K., Van Ginneken, L., and Van Impe,

contained necessary and sufficient information

J. F., Vogel, R. F., Devlieghere, F. (2010)

to compute b was proposed. With proper

Mathematical modelling and in situ

implementation, the accuracy of computation was

determination of pH in complex aqueous

ascertained. From the simplicity of these concepts, it

solutions during high-pressure carbon dioxide

was possible to create a database that could compute

treatment. The Journal of Supercritical Fluids

various solution properties relating to pH. When

55: 77-85.

systematically combined with pKa prediction by

Heyrman, A. N. and Henry, R. A. (nd), Importance

group contribution methods, it is possible to make

of controlling mobile phase pH in reversed

a priori prediction of various solution properties

phase HPLC. [Online URL: www. hplcsupply.

that is necessary for separation in combinatorial

com/pdf/App_9.pdf.] accessed on January

chemistry. The database could be customized to be

14, 2011. Mathews, J. M. (1987) Numerical Methods for

used in experimental research such as customizing

Computer Science, Engineering, and

buffer with desirable properties.

Mathematics, pp.64-65. Prentice-Hall, References

London.

Butler, J. N. (1964) Ionic Equilibrium: A

Obata, K., Sugano, K., Saitoh, R., Higashida, A.,

Mathematical Approach, Addison-Wesley,

Nabuchi Y., Machida, M., and Aso, Y. (2005),

Massachusetts, pp.61-68.

Prediction of oral drug absorption in humans

Chung, C. C., Chen, H. H., and Ting, C. H. (2010)

by theoretical passive absorption model.

Grey prediction fuzzy control for pH

International Journal of Pharmaceutics

processes in the food industry. Journal of

293: 183-192. Sinko, P. J. (2010) Martinâ&#x20AC;&#x2122;s Physical Pharmacy

Food Engineering 96: 575-582. Coiffard, C. A., Coiffard, L. J., and De Roeck-

and Pharmaceutical Sciences, 6th ed., pp.

Holtzhauer, Y. M. (1997) Influence of pH

163-181. Lippincott Williams & Wilkins,

on thermodegradation of thaumatin in

Philadelphia.

aqueous solution. Food Research

USP24 (2000) The United States Pharmacopeia

International 30: 707-710.

24, pp.2231-2232. The United States

Cutler, D. (1986) Calculation of pH for complex

Pharmacopeial Convention, Maryland.

mixtures of acids, bases and ampholytes.

York, P. (2002) The design of dosage forms, In

Journal of Pharmacy and Pharmacology

Pharmaceutics: The Science of Dosage

38: 499-501.

Form Design (Aulton, M.E., ed.), 2nd ed., pp.1-12. Churchill Livingstone, London.

P. Boonme et al.

Silpakorn U Science & Tech J Vol.6(2), 2012

Appendix

If Delta > 0 Then

Demonstration of computing pH and β of water

maxph = pH

Constant definition: K w = [ H 3O + ][OH − ]

MaxpHDelta = Delta

Mass balance: [H 3O ] = 10

Else

− pH

minph = pH MinpHDelta = Delta

[OH− ] = K w /[ H 3O + ]

End If If maxph - minph > 0.00001 Then

Charge balance: [H O + ] = [OH− ] 3

‘Remark: optimal pH interval is 0.00001 for double precision mode

From charge balance, D (the deviation from the

Beta = (MaxpHDelta - MinpHDelta) /

electroneutrality rule) is described as the negative

(maxph - minph)

charge side of CBE minus the positive-charge side

Else

of CBE.

Converge = True

D = ([OH− ] − [H 3O + ])

Exit Do

The following code was written in the Microsoft

End If

AccessTM. Please be noted that log ( ) function is

Loop Until Converge

natural logarithm.

Debug.Print “pH =”; pH

Option compare database

Debug.Print “b (our method):"; Beta

DefDbl A-Z

Debug.Print "b (Van Slyke):"; Log(10) * (H +

Sub Main()

OH)

minph = 0

End Sub

maxph = 14

By typing main and press [Enter] key (in the Debug

Kw = 1e-14

window), the following result would be shown in

the Debug Window.

pH = (maxph + minph) / 2

pH = 6.99999332427979

H = 1 / 10 ^ pH

b (our method): 4.6051701867266E-07

OH = Kw / H

b (Van Slyke): 4.60517018653215E-07

Delta = OH - H

Research Article PM10 Levels and Hotspots in Western Thailand in Agro-Residue Burning Season Aungsiri Tipayarom Department of Environmental Science, Faculty of Science, Silpakorn University, Nakhon Pathom, Thailand Corresponding author. E-mail address: aungsiri@gmail.com Received November 5, 2011; Accepted May 28, 2012 Abstract Open burning of agro-residues normally generates a large amount of pollutants which may result in potential impacts on the ambient air quality and public health. A study of a correlation between PM10 levels in ambient air and hotspot counts in Western Thailand was conducted to investigate whether the air quality of Nakhon Pathom Province was influenced by the emission from agro-residue burning. Two high Volume Samplers for PM10 sampling were installed in Silpakorn University to obtain the representative PM10 levels in Nakhon Pathom province. The number of hotspots, as the fingerprints of open burnings, was provided by the NASAâ&#x20AC;&#x2122;s Earth Observatory website. The hotspot counting was divided into 2 parts; (i) 5-year backward counting in the province to investigate the burning season, and (ii) counting in Nakhon Pathom province and upwind-adjacent provinces including Kanchanaburi, Ratchaburi, Pathumthani, Pranakorn Sriayudhaya and Suphanburi in a burning season. Wind directions to the sampling locations were obtained from a HYSPLIT Model. Average PM10 levels found in this study was 88Âą34 mg/m3, which does not exceed Thailand Air Quality Standard of 120mg/m3. The positive correlation between PM10 levels and hotspot counts was found at R2=+0.81. This study indicated that air quality in Nakhon Pathom Province was affected by emissions from agro-residue burning. Key Words: Agro-residues; Burning Season; Hotspots; PM10 Introduction Burning biomass, including living and dead vegetation, may take place intentionally (e.g. burning of vegetation for land clearing), or by natural causes. It is estimated that humans are responsible for about 90% of biomass burning with only a small percentage of natural fires contributing to the total amount of vegetation burnt (Baldini et al., 2004; NASA, 2004a). Emission from biomass burning is one of the environmental and health hazards. Humans

Silpakorn U Science & Tech J 6 (2) : 30-36, 2012

are exposed to a large quantity of carcinogenic compounds from open burning smoke. Pollution from biomass burning emerges frequently in our daily lives, in both indoor and outdoor environment. To reduce the exposure in North America, many communities have regulations to manage domestic burning in fireplaces and wood-burning stoves to control atmospheric pollution (Andreae, 1991). For the outdoor air, biomass burning also causes multiple effects. For examples, airports like SantarĂŠm, which

A. Tipayarom

Silpakorn U Science & Tech J Vol.6(2), 2012

Materials and Methods Determination of PM10 Sampling site Silpakorn University was selected as a sampling site because it was located moderately far (3 km) from Nakhon Pathom downtown. Moreover, the traffic in the university was considered light. Consequently, PM10 from vehicle travelling in the university did not interfere with the PM10 samples. The sampling equipment was situated on the decks of the two 3-storey buildings in the university. Sampling and analysis methods Glass fiber filters (GFF) (pore size 37 mm, 20x25 cm) were used for PM10 collection. A Five-digit balance was used to measure the particulate matter weight on the sample filters for mass analysis. The filters were prepared by keeping them in a desiccator for at least 24 hours. Filters were then pre-weighted and stored in airtight plastic bags. After sampling, filters were taken back to the lab and desiccated for at least 24 hours before post-weighing by a five-digit balance. Field blank was taken into account for PM mass. Proper flow calibration of the High Volume Sampler (1.13 m3/min) was done for the correct fractionation of the particles below 10 mm. The sampling period was from February 1, 2010 to March 30, 2010. The air samples were collected every 3 days in order to cover both weekdays and weekends in a dry season, which was the harvesting and burning season. During this period, many fires were set intentionally for land clearing and agro-residue removal for the upcoming growing season. Air was continuously drawn through the filters for 24 hours with desired flow from 8:00 a.m. to 8:00 a.m. on the next day. Temperature and pressure were determined. The total number of samples in this study was 20. The levels of PM10 in air samples were defined as

is in the middle of the Amazon Basin, have to be closed frequently during the burning season because of poor visibility resulting from the smoke from fires located hundreds to thousands of kilometers away from the airports. Another example was Indonesian forest fire in 1997, which caused episodic high air pollution in Kalimantan and Sumatra (Lawrence et al., 2001). Agro-residue burning is one of the major types of intentional burning of biomass. Normally, biomass burning plays an important role in agriculture and economy (Andreae, 1991). Burning of agricultural wastes, e.g. straw and stubble from grain crops or sugar-cane fields after harvesting is a very noticeable source of air pollution in many tropical regions. Emissions from the combustion of biomass produce a large amount of particles and gaseous pollutants, which cause respiratory problems when they are inhaled (Mitra et al., 2002; NASA, 2004b). There is a significant contribution of biomass burning to the fine particulate matters (PM) pollution in the Bangkok Metropolitan Region (BMR). Source apportionment of fine and coarse fractions of PM in BMR reveals that biomass burning contributes around 30% of fine PM mass in the region (Yootong, 2003; Kim Oanh, 2006). In Nakhon Pathom province, paddy rice is one of the major crops. Most of the crop residues are disposed of by burning. The amount of agricultural waste burnt is high each year because no regulations exist. Air pollution from biomass burning is largely overlooked. Finding the influence of agro-residue burning emission to air quality of the province is a challenge. The goal of this study is to overcome this challenge to the extent possible. Therefore, the correlation of PM10 levels and the satellite data was employed along with the trajectory modeling, which presented possible directions of the emission transport, to describe the impacts on the air quality in Western Thailand.

Silpakorn U Science & Tech J Vol.6(2), 2012

PM10 Levels and Hotspots in Western Thailand

Quality assurance and quality control (QA/ QC) Sampling: High Volume Samplers were calibrated for desired flow rate before every sampling. All sample filters were kept in air-tight plastic bags to avoid contamination during the transportation. Field blanks, which were conditioned and unsampled filters, were used to determine whether similar contamination occurred during samplings by exposing to ambient air without pumping. Analysis: Filter samples were kept in the desiccators for at least 24 hours before weighing. Three replicated measurements usually agreed within less than 0.01% of filter weight. Determination of hotspots During PM10 sampling period, the hotspots in Nakhon Pathom and the nearby provinces were extracted daily from the NASAâ&#x20AC;&#x2122;s Earth Observatory website. The fires (hotspots) detected are updated daily on website (http://firefly.geog.umd.edu/ firemap/). Figure 1 shows an example of hotspots in Thailand in March 2011. This study received the fire information (hotspots) for (i) five years backward (2005-2009) and (ii) PM 10 sampling days. Tipayarom and Kim Oanh (2007) revealed that PM10 levels emitted from biomass burning showed a good correlation with hotspot counts. In this study a HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) Model was used to determine wind direction to Silpakorn University (sampling site) on the days of PM10 sampling and to identify in which provinces hotspots should be counted on each day. Figure 2 illustrates an example of wind direction to the sampling site. In this case, the number of hotspots in Nakhon Pathom and Suphanburi (located in the north of Nakhon Pathom) provinces was counted and recorded.

u Pranakorn Sriayudhaya v Nontaburi w Bangkok x Samutsakon Figure 1 Example of hotspots

Suphanburi

Nakhon Pathom

Figure 2 Example of wind direction obtained from HYSPLIT model

Data analysis Two data sets obtained from PM10 samplings and hotspot countings were compared to ascertain an effect of open agro-burning in Nakhon Pathom and the nearby provinces on air quality of Nakhon Pathom Province. Correlation (R2) was defined.

A. Tipayarom

Silpakorn U Science & Tech J Vol.6(2), 2012

Results and Discussions PM10 levels In Nakhon Pathom, levels of PM10 were 88±34 mg/m3. The results showed that the levels on certain days exceeded Thailand Air Quality Standard which is 120 mg/m3. The results are illustrated in Figure 3. Comparing to Klinmalee (2008)’s study in Pathumthani Province (rice-growing province) in 2006, it was reported that PM10 levels in ambient air were only 47±10 mg/m3. The PM10 levels in

Pathumthani were lower than in Nakhon Pathom for the reason that roughly 30-40% of rice-growing farmers in Pathumthani dispose their wastes by plowing instead of burning. Five-year backward counting of hotspots The results from hotspot counting in 2005 - 2009 indicated that farmers typically burn their agricultural wastes during February to March each year as shown in Figure 4. Hence, the number of hotspots and PM10 levels were determined through

Figure 3 PM10 levels in Nakhon Pathom from 2 sampling points

Figure 4 Five-year backward hotspot counts in Nakhon Pathom Province

Silpakorn U Science & Tech J Vol.6(2), 2012

PM10 Levels and Hotspots in Western Thailand

(R2 = +0.81). Scatter plots of correlation are shown in Figure 6. However, there were some uncertainties related to hotspot counts such as cloudiness and the short duration of rice paddy burning. MODIS satellite images were available for only two times per day in Thailand. However, the positive correlation revealed that air quality in Nakhon Pathom province had been impacted by agro-residue burning. Tipayarom and Kim Oanh (2007) studied the correlation between PM10 levels and hotspot counts in Pathumthani province during burning period. The results showed that hotspot counts varied in the same way as PM10 levels (R2 = +0.77) corresponding to this study.

that period. This finding corresponded to Klinmalee (2008)â&#x20AC;&#x2122;s study that rice-growing farmers burnt their rice straw after harvesting especially in dry season (January - April). Tipayarom (2004) studied emission from open rice-straw burning in Thailand and also showed high hotspot counts during November April. Study of Phuong (2006) regarding to impact of rice straw burning on ozone air quality in BMR also revealed the higher monthly hotspot counts in a dry season (December - April) and lower counts in a wet season (May - November). Thus, there was a large amount of smoke emitted and dispersed during that period. Similar information about burning period was also obtained from Nakhon Pathom Agricultural Extension Office (2010). Therefore, the period selected for this study was February 2010 - March 2011. Correlation between PM 10 levels and hotspot counts Since PM 10 was emitted from biomass combustion, the daily hotspot counts in the studied areas were plotted against PM10 levels. The results are demonstrated in Figure 5. The relationship between PM10 and hotspot counts was statically significant

Conclusion The integrated method in this study is unique and the study demonstrates that it can be used to primarily indentify the possible source of PM10 in ambient air. Reasonable correlation between MODIS hotspot counting and ground monitoring data of PM10 at Silpakorn University station suggests that open burning of agro-residue in Nakhon Pathom Province may affect air quality in the area.

Figure 5 PM10 levels and hotspot counts

A. Tipayarom

Silpakorn U Science & Tech J Vol.6(2), 2012

Figure 6 Correlation between PM10 levels and hotspot counts Acknowledgements The author would like to thank The Faculty of Science, Silpakorn University for the financial support as well as Prof. Dr. Fred Finley and Assistant Prof. Dr. Boonjeera Chiravate for editing.

No. EV-08-4. Lawrence, K. C. C., Avelino, A. F., and John, M. L. (2001) Investigating the Haze Transport from 1997 Biomass Burning in Southeast Asia: Its Impact Upon Singapore: Asia. Atmospheric Environment 35(15): 2723-2734. Mitra, A. P., Morawska, L., Sharma, C., and Zhang, J. (2002) Chapter Two: Methodologies for Characterization of Combustion Sources and for Quantification of Their Emissions. Chemosphere 49(9): 903-922. Nakhon Pathom Agricultural Extension Office. (2010) Statistical Data of Agricultural Growing in Nakhon Pathom Province in 2010, Department of Strategy and Information, Nakhon Pathom. National Aeronautics and Space Administration. (2004a) Biomass Burning. [Online URL: http://earthobservatory.nasa.gov/ Library/ BiomassBurning] accessed on July 22, 2004. National Aeronautics and Space Administration. (2004b) Biomass Burning: A Hot Issue in Global Change. [Online URL:http://asdwww.larc.nasa.gov/biomass_burn/Factsheet. pdf.] accessed on August 4, 2004. Phuong, N. L. (2006) Modeling Impact of Open Rice-Straw Burning Emission on Ozone Air

References Andreae, M. O. (1991) In Biomass Burning: Its History, Use, and Distribution and Its Impact on Environmental Quality and Global Climate (Levine, J. S., ed.), MIT Press, Cambridge. Baldini, G., Campadelli, P., and Fradegrada, M. (2002) Biomass burning monitoring by scene analysis. In Proceedings of Visualization, Imaging, and Image Processing, Calgary. Kim Oanh, N. T., Upadhyay, N., Zhuang, Y. H., Hao, Z. P., Murthy, D. V. S., Lestari, P., Villarin, J. T., Chengchua, K., Co, H. X., Dung, N. T., and Lindgren, E. S. (2006) Particulate air pollution in six Asian cities: spatial and temporal distributions, and associated sources. Atmospheric Environment 40(18): 3367-3380. Klinmalee, A. (2008) The development of assessment procedure for exposure to open rice straw burning emission : a case study of school children in Thailand. AIT Dissertation,

Silpakorn U Science & Tech J Vol.6(2), 2012

PM10 Levels and Hotspots in Western Thailand

Quality in the Bangkok Metropolitan Region. AIT Thesis, No. EV-06-21. Smith, K. R. (1987) Biofuels, Air Pollution, and Health: A Global Review, Plenum Press, New York. The Fire Information for Resource Management System. (2011). Hotspot Count. [Online URL: http://firefly.geog.umd.edu/firemap/] accessed on March 31, 2011. Tipayarom, D. (2004) Source Characterization for Air Pollution Emission from Open RiceStraw Burning in Thailand. AIT Thesis, No. EV-04-5.

Tipayarom, D. and Kim Oanh, N. T. (2007) Effects from Open Rice Straw Burning Emission on Air Quality in the Bangkok Metropolitan Region. Science Asia 33: 339-345. United State Environmental Protection Agency. (1999) Determination of Polycyclic Aromatic Hydrocarbons (PAHs) in Ambient Air Using Gas Chromatography/Mass Spectrometry (GC/MS). Compendium Method TO-13A. Yootong, S. (2003) Receptor Modeling for Source Apportionment of Fine and Coarse Fractions of Particulate Matters in Bangkok Metropolitan Region During Rainy Season. AIT Thesis, No. EV-03-31.

Research Article Behavior of Ta2O5-Si Capacitors with Different Gate Electrode under Constant Current Stress Margareta Pecovska-Gjorgjevich1*, JulijanaVelevska1 and Elena Atanassova2 Institute of Physics, Faculty of Natural Sciences and Mathematics, St. Cyril and Methodius University, Skopje, R Macedonia 2 Bulgarian Academy of Sciences, Sofia, Bulgaria * Corresponding author: e-mail address: pecovska@pmf.ukim.mk

Received February 11, 2012; Accepted June 7, 2012 Abstract

The electrical characteristics of MOS capacitors with Ta2O5 as oxide and with different gate electrodes

(Al, Au, W, TiN) are investigated using high frequency capacitance-voltage (C-V) and current–voltage (I-V) measurements. The influence of deposition techniques of gate electrode (reactive sputtering and evaporation) and the type of electrode material (different work functions) are observed. Charged trapping properties were studied by measuring the gate voltage shift due to trapped charge generation in order to investigate the response to constant current stress (CCS) under various current/time conditions at room temperature. The results showed that the presence of pre-existing electron traps leads the changes of time dependent voltage during gate injected CCS in the initial stage, followed by the slow positive charge build-up, same for all the structures and characteristic for this oxide. Gate-induced defects due to ther rate of reaction of gate electrode with the oxide are responsible for different behavior of the structures with different gate electrodes, observed in the initial stage of CCS. The Au-gated devices appear to be the most susceptible to the constant current stress degradation. They also have highest values of capacitance and lowest leakage currents. Key Words: Gate electrode; Dielectric properties; Oxides; Constant current stress Introduction

gate thickness needed to decrease to maintain

For few decades, the semiconductor industry

adequate capacitance across it, but below 2 nm, the

used silicon dioxide as its gate insulator. SiO2, with

gate oxide becomes so thin that direct tunneling

a dielectric constant of 4.2, is well investigated, its

currents through it rapidly increase and make this

electrical characteristics are known and it is highly

oxide unsuitable for further use in microelectronics

compatible with the transistor’s underlying silicon

industry.

metal layer. The rapid shrinking of transistor feature

sizes has resulted in shrinking semiconductor size,

poly silicon gates and silicon oxide with metal

according to Moore’s law. The SiO 2 transistor

gates and alternative high-k gate dielectrics. These

Silpakorn U Science & Tech J 6 (2) : 37-48, 2012

Logical solution of this problem is to replace

Silpakorn U Science & Tech J Vol.6(2), 2012

Behavior of Ta2O5-Si Capacitors with Different Gate Electrode

materials have the same value of capacitance at

dielectric constants k > 104 have been achieved by

greater physical thickness, thus avoiding tunneling

doping high-k perovskites materials (Nalwa, 1999).

effect. But, several points are to be fulfilled.

Such ceramics have a face-centered-cubic crystal

High dielectric constant, low leakage current,

structure and no net polarization of charge above

low dielectric loss, high breakdown voltage,

their Curie point. Below this temperature, the ions

good interface and thermal stability sufficient to

shift to create a permanent dipole in the material and

resist the high temperature CMOS manufacturing

exhibit a very high dielectric constant. But, there

processing are required. Necessity of new gate

is some indication that the dielectric constant of

dielectric materials with higher dielectric constant

perovskites decreases for thin films with thicknesses

k, (in the interval 10-100) such as Ta2O5, TiO2,

<1nm, where the crystal structures responsible for

Y2O3, HfO2, Er2O3 Al2O3, CeO2, ZrO2, La2O3 and

the high-k values are no longer present in thin

Nb2O5 as a replacement for currently dominant

films (Kingon, 2000). This lack of scalability will

SiO2 appeared (Brown, 2004). These materials

restrict the application of perovskites to devices with

can be deposited with several methods compatible

thicker dielectric films. This lack of scalability may

with existing industrial production including

mean that perovskites do not have an advantage

chemical vapor deposition (CVD), and its variations

over other high-k materials for memory and logic

like metalorganic chemical vapor deposition

applications. Problems may also arise due to the

(MOCVD), anodization, DC sputtering, reactive

low Curie temperature of some of these perovskite

magnetron sputtering, atomic layer deposition

materials. The lower Curie temperature will make

(ALD) etc. (Groner and George, 2003).Their

these materials unsuitable for devices with high

characteristics are intensively studied now days in

operating temperatures.

order to integrate in future generations of integrated

circuits (Atanassova and Paskaleva, 2007).

materials for gate electrodes. Few parameters are

Other materials with even higher value

to be observed in finding the most appropriate

of dielectric constant are perovskite materials.

candidate for this role. Very important characteristics

They have tendency to have very large dielectric

of these materials are their work function, resistivity

constants due to their ferroelectric behavior at

and compatibility with the existing semiconductor

temperatures below the Curie point (Wilk, 2001;

processes (Jiang and Chen, 2004). Some of those

Groner and George, 2003). Barium titanate (BaTiO3)

materials that reach the demands for gate application

based ceramics with the perovskite structure can

in MOS systems are Al, Au, W, TiN, W/TiN (Lee

exhibit relative dielectric constant as high as 15000

et al, 2001; Gilmer et al., 2000), WN, and TaN ( Lee

(Swartz, 1990), depending on the grain size and

et al, 2000).

crystal structure. Other perovskite material with

high dielectric constant is SrTiO3 (Vehkamaki,

dielectric. This material showed itself as a potential

2001). Higher dielectric constant k ~ 103-104 is

replacement for SiO2 because of its ability for

obtained with mixing these two materials to form

deposition by conventional methods with equipment

BaxSr1-xTiO3 (BST) (Kingon, 2000). BST has been

already available in process line, high capacitance

used in bulk capacitors and is being investigated

per unit area and low leakage current density. (ITRS)

for DRAM capacitor applications. Even higher

With these characteristics, tantalum pentoxide

Silicon gates are also replacing with new

In this article we investigated Ta2O5 as a gate

M. Pecovska-Gjorgjevich et al.

Silpakorn U Science & Tech J Vol.6(2), 2012

appeared appropriate for applications in high-density

Thicknesses of the films measured by ellipsometry

dynamic-random-access memories (DRAMs). Its

with laser light of l = 632.8 nm are ~17 nm. MOS

dielectric and electric behavior with Al as gate

structures were formed with evaporation of Au or

electrode were already subjects of investigation

Al layer as a gate; and by reactive sputtering of

(Atanassova et al., 2002; Pecovska-Gjorgjevich

W or TiN (gas pressure 3 Pa, rf power density 3

et al., 2003; Novkovski et al., 1999). The conduction

W/cm2). The sample preparation and its structure

mechanism in Ta2O5 in low voltage range within

investigations can be found elsewhere (Atanassova

the devices that work nowadays and the gate oxide

and Spassov, 1999; Atanassova et al., 2002;

reliability is studied extensively. The results from

Atanassova and Spassov, 2000). The gate areas

our earlier works (Pecovska-Gjorgjevich et al,

were 1.96·10-3cm2 for Au and 2.5·10-3cm2 for Al, W

2004; Pecovska-Gjorgjevich et al., 2005) showed

and TiN. Because of its thermodynamic activity Si

that Schottky emission (electrode limited emission)

substrate reacts with Ta2O5 which results in reducing

was dominant conduction mechanism for low fields

the oxide film and forming an interfacial layer of

and Pool-Frenkel mechanism, normal or modified

SiO2 (or SiOx, or SiTaO layer). This interface layer

(bulk limited with high concentration of defects),

induces defects that increase leakage currents and

appeared at medium fields.

lead to higher interface state density and lower

In order to define the most appropriate gate

breakdown strength (Lai et al., 2002). Interfacial

material for its improved performance, structural and

layers can severely decrease the capacitance of a

dielectrics properties and degradation of gate/Ta2O5/

high-k film. The equivalent SiO2 thickness of the

Si capacitors with different material gate electrodes

MOS structure is increased and the capacitance of

under constant voltage stress were investigated

Ta2O5 is calculated from the structure formed of

earlier, (Spassov et al., 2006; Atanassova et al.,

two serial capacitors (first the layer of SiO2 and the

2008; Novkovski and Atanassova, 2005). Changing

second the layer of Ta2O5).

the gate material, i.e. the work function between

the metal gate and the poly-Si substrate, we observed

substrate and the Ta2O5 dielectric is formed in our

the difference in the leakage currents and the

structures (Atanassova et al., 2002; Atanassova and

possible improvement of the MOS structures.

Spassov, 1999; Atanassova et al., 1995; Dimitrova

In our work we investigated the electrical

et al., 2001) which generates a lot of traps and puts

characteristics (C-V and I-V) of the structures

this material appropriate for memory application.

from the aspect of different gate electrodes. We

It is well known that memory capacitors require

submitted these structures to constant current stress

extremely low leakage currents (<10-8A/cm2) at

and discussed their behavior. The materials used for

low electric field and high capacitance density, for

the gate electrode were Al, Au, W and TiN.

charge storage, but the interface quality is not as

Thin interlayer of SiO2 ~3 nm between Si

critical to capacitor performance (Wilk et al., 2001). Materials and Methods

In order to decrease the negative charge density

Tantalum pentoxide thin films were deposited

in the structures (to repair oxygen vacancies and

on p-type Si substrates (15-17Wcm) by reactive

various structural non-perfections present in the

sputtering of Ta-target in an Ar/O2 mixture (O2

as-deposited films) and obtain better thermal

content Nc=10%, substrate temperature Ts = 493K).

stability, all films are submitted to a H 2 post

Silpakorn U Science & Tech J Vol.6(2), 2012

Behavior of Ta2O5-Si Capacitors with Different Gate Electrode

metallization annealing at 450°C for one hour.

Typical I-V curves for both gate polarities

were made with HP 4140B picoammeter with voltage step of 0.1 V and rate of 0.1 V/s with a delay time of 2.5 s before recording the current. The negative bias (electron injection is from the gate electrode) refers to Si-substrate in accumulation and the positive bias (electron injection from the substrate) to Si-substrate in inversion.

In order to investigate the electric/defect

characteristics of the structures, high frequency

Figure 1 Leakage current density for rf sputtered

capacitance-voltage (C-V) measurements were

carried out by HP LCR meter at 1MHz with a step

Ta2O5 films with different gate electrodes

of 10 mV.

Time dependence of the gate voltage was

the leakage current and the conduction is limited by

investigated performing constant current stress

electron injection into SiO2 from the Si (Nishioka

measurements with low-high current gate injection

et al., 1987). The results giving leakage current

using HP 3458A multimeter. The stressing was

density bellow 10-7 A/cm2 at ±1V for all structures

biased negatively, with current injection from the

are similar with the literature (Liu et al., 2011).

gate, i.e. p-Si substrate in accumulation.

observed in Schottky emission term (SE electrode

All measurements were performed at room

temperature.

The leakage currents of the structures were

limited conduction) given with ln J vs

(E ) 1

Results and Discussion

dependence, Pool-Frenkel term (PF bulk limited

conduction), defined with ln 

( ) and

1 J 2  vs E E

Typical I-V characteristics for all structures

for gate positive and negative biased are shown in

Fowler-Nordheim tunneling effect, described as

Figure 1. Leakage current density for all samples

 J  1 ln  2  vs   . E  E

is bellow 10-7 A/cm2 untill 1.7-2.9 MV/cm (3-5V) for negative bias and 0.9-1.7 MV/cm (1.5-3V) for positive bias. The gate current depends on the

barrier height and on the position of the potential

Schotky emission dominates for low fields (till

maximum in the dielectric near the injection contact.

1.5 MV/cm for Al-gate, 2.35 MV/cm for W-gate

The characteristics are sensitive to the internal field

to 2.8 MV/cm for Au and TiN-gate) and goes to

and the space charge in the oxide which, in turn,

Pool-Frenkel for medium fields. For positive bias,

affects the barrier height and the position of the

fast increase of the current is observed over 2-3 V

potential maximum near the interface (NANDI

(1.2-1.75 MV/cm) which is due to the breakdown

et al., 2003). Higher leakage currents under positive

of the ultrathin SiO2 at the interface with Si. The

In accumulation regime, (negative bias)

bias come from the presence of the SiO2 interface

conduction mechanism for this region is combination

layer between Si substrate and Ta2O5 which defines

of Fowler-Nordheim tunneling (FN) through SiO2

M. Pecovska-Gjorgjevich et al.

Silpakorn U Science & Tech J Vol.6(2), 2012

and PF through Ta 2O 5 (Pecovska-Gjorgjevich

although his work function is lower than tungsten’s

et al., 2004).

or TiN. The explanation could be in the reaction

Figure 2 shows high frequency C-V

of Al with Ta2O5 and high generation of traps

characteristics of structures with different gate

at the interface of gate and the oxide (Atanassova

electrodes at 1MHz. The measured value of

et al., 2008). The relative dielectric constant of the

accumulation capacity was 5.5 mF/cm for Au,

structures including the interfacial SiO2 layer was

5.14 mF/cm2 for Al, 4.56 mF/cm2 for W and 5.02 mF/

estimated to 10.8, 9.9, 8.6 and 9.7 respectively.

cm for TiN as a gate. The difference in capacitance

values for different MOS structures come from

films and it was taken to be the highest value of the

different work functions of gate electrode and the

voltage during the stress. The characteristic time-

concentration of defects on the interface between the

dependent voltage curve for Ta2O5 does not show

gate and the oxide, generated during the deposition

catastrophic breakdown like the one for SiO2, but

process. In order to discuss their influence on the

so called soft breakdown. The initial stage of time

capacitance value and leakage currents, the work

dependence of the gate voltage shows increase of the

functions of the gate materials were used from

external field connected to negative charge trapping

the literature, Au (F = 5.1eV), Al (F = 4.26eV),

referring to the presence of pre-existing electron

W (F = 4.55eV) and TiN (F = 4.95eV) (Wyon,

traps in the oxide. After the maximum of the voltage

2002). Larger work function of Au results in higher

is reached, these oxide films exhibit an additional

values of capacitance and lower leakage currents

slow decrease for a long time afterwards, which is

confirming good contact between Au and oxide

happening because of the slow degradation of the

without high concentration of interface defects. The

SiO2 interfacial layer. In this stage the slow positive

lowest value of capacitance for W is connected to

charge build-up takes place and negative charge

lowest value of its work function. Al on the other

is releasing (Roderick, 1980). Similar curves are

hand have higher values of capacitance, similar

obtained for Au, Al and W gate electrode. TiN gate

to TiN gate structures and higher leakage current

MOS structures show different behavior depending

Breakdown field EBD was measured for all

on injected current. 6

is estimated around 3.25 MV/cm, ~6 MV/cm for

Capacitance (10-6F/cm2)

Breakdown field for tungsten gate structures

gold electrode, and over 6 MV/cm is measured for

aluminum gate MOS structures. Higher injected

currents through the oxide initiate higher values of

TiN

breakdown voltage.

Figure 3 shows time-dependent curve of

voltage during constant current stress (CCS) with

0 -4

-3

-2

-1

current density J = - 0.02 A/cm2, - 0.2 A/cm2 and

- 4 A/cm2 for Au gate MOS structures. Observing

Gate Voltage (V)

the initial part of curves, we can see that the value

Figure 2 High-frequency C-V curves for rf

sputtered oxides with different gate

electrodes

of the injected current does not affect the behavior of the structure. The initial voltage is approximately

Silpakorn U Science & Tech J Vol.6(2), 2012

Behavior of Ta2O5-Si Capacitors with Different Gate Electrode

same for all injected currents (2.5-2.8V), suggesting

investigated structures. Small hysteresis effect in

the low concentration of defects in the interlayer

Au gate structures (0.1V) suggests small density

Au-Ta2O5. Maximum value is reached for very

of slow border states. The biggest shift is observed

short time, i.e. for very small amount of charge

for Al gate structures, 0.8V, while W gate and TiN

injected (1C/cm for 0.02A/cm ), followed by slow

gate structure exhibit similar values 0.45V and 0.4V

degradation during further injection of constant

respectively.

current. Higher current density initiates higher

electric field across the structure (faster generation

obtained from the experimental dependence 1/C2

of interface positive charges appears), probably

vs Vg curve as intercept with the Vg axis. The result

because of the presence of hydrogen in the interface

of VFB for Au gate MOS structures is given in

because of post metallization annealing in H2.

Figure 5. This gives us information about the value

The stability of the dielectric was observed by

of the work function Fms, (VFB = Fms = Fm - Fs),

sweeping the voltage from inversion to accumulation

as well as the doping concentration NA (Di Maria

and back in interval (5V to -5V and back to 5V).

et al., 1993; Sze, 2001). The obtained flat band

Hysteresis in C-V curves is usually connected to

voltage VFB for Ta 2O 5-SiO 2-Si structures with

charge trapping in the states near the interface with

different gates were: 0.1V for Au gate, 0.4V for

Si. Figure 4 shows negative hysteresis behavior

structures with W as a gate, -0.2V for Al gate,

of the C-V足 curve, which indicates the presence of

and 0.2V for TiN gate. The results from Figure 4

interfacial traps in the oxide defect states, when

and Figure 5 indicate the acceptors as generated

the structure is under stress. The sign of these

traps. The number of the slow trapping states, NA

interfacial traps appears to be positive which is

is estimated using the equation NA= CDVfb/(eS),

obtained from the negative voltage shift in the high

(Lai et al., 2002) where C is the capacitance of the

frequency C-V characteristics, due to the presence

oxide, DVfb is the hysteresis loop of the flat band

of slow states at Si/SiO2 interface (Dimitrova

voltage, e is the electron charge and S is the capacitor

et al., 2001). The negative shift is observed for all

area. The extracted values of NA for structures

The flat band voltage VFB can be directly

1,2

1,0

0,8

C/Cacc

Voltage(V)

6 J = - 0.02 A/cm2 J = - 0.2A/cm2 J = - 4 A/cm2

4 2 0

100

150

200

0,6 0,4 0,2

Au gate, dTa2O5=17.4nm 0

Au gate, C-V shift

250

0,0

300

-4

-2

Voltage(V)

Time(s)

Figure 4 The hysteresis effect in MOS structures

Figure 3 Voltage vs time during CCS for Au-Ta2O5

SiO2-Si structures with three different

with Au gate electrode. First curve gives

injected currents from the gate

changes from inversion to accumulation, the second opposite direction.

M. Pecovska-Gjorgjevich et al.

Silpakorn U Science & Tech J Vol.6(2), 2012

1/C2 (1/F 2)1012

190

140

N A ~ reciprocal of slope

40 W Au

-10 -1

Voltage (V)

Figure 5 1/C2 vs Vg for Au and W-gate MOS

Figure 6 Long term V-t curves for Al gate oxides

structure

for three different injected currents

with Au, Al, W and TiN gate were 1.6x1011cm2,

lots of defects in the interfacial layer between Al and

3,3x10 cm , 1.33x10 cm

Ta2O5. The initial dropping of the voltage before

and 7.8x10 cm 11

increasing due to existence of the positive charge

respectively. Since the Ta2O5 layers of all four MOS

traps in the structures characteristic for thicker films

structures were deposited with the same process,

not submitted to H2 post metallization annealing

the difference in their electrical properties comes

(Novkovski et al., 1999; Pecovska-Gjorgjevich

from the interaction between the gate material and

et al., 2004) is not observed in our thin films.

Ta2O5 and the generation of interfacial positive traps.

The charge trapping behavior of the samples

Seems that Al gate structures present more positive

with Au and Al gate, observed by continuously

charges which may be attributed to the deposition

monitoring of the change in gate voltage (DVg

method of evaporation, while structures with Au as

= Vg -Vg0, Vg0 is the initial value of the voltage

a gate have lowest value of these traps, suggesting

on the structure), required to maintain a constant

good compatibility between Au and Ta2O5.

current of different values under gate injection is

The evolution of the V-t curves during constant

shown in Figure 7 for Au and Figure 8 for Al gate.

current stress for Al-gate MOS structures for three

The difference in those two types of structures is

current densities injected from the gate, – 0.02 A/

obvious; while Au-gate structures have higher DVg

cm , – 0.2 A/cm and – 4 A/cm is given in Figure

with higher injected currents, the Al-gate structures

6. The initial behavior of these structures is different

show opposite behavior, the higher injected current,

from what we observed for Au-gate capacitors.

the lower voltage change. This confirms the absence

The initial voltage for injected current of –0.02 A/

of defects in the first structure and their proportional

cm is 2.35 V, 6.56 V for -0.2 A/cm and 9.58 V

creating with increasing the injected current.

for -4 A/cm injected current density. The higher

The initial fast increase of the voltage for Al

injected current initiates the higher initial voltage

gate MOS structures, more pronounced for lower

suggesting the presence of native positive traps and

stressing currents is due to the filling of native

Silpakorn U Science & Tech J Vol.6(2), 2012

Behavior of Ta2O5-Si Capacitors with Different Gate Electrode

characteristic behavior for Ta2O5 structures.

Oxide structures with W gate electrode show

Au gate, dTa205 = 17.4nm

no difference in the curve depending on low and

DVg ∆Vg (V)(V)

high currents injected. They have very similar

behavior like Au-gate structures. The negative

C-V shift and sharp voltage rate in short time (30s) with low injected charge (6C/cm2 for 0.2A/cm2),

4 J = - 0.02A/cm2

confirms the existence of imperfections at Si/SiO2

J = - 0.2A/cm2 J = - 4 A/cm2

interface. A presence of high concentration of

0 0

Time (s)

traps at the W-oxide interface (radiation defects

generated during the sputtering of W) (Atanassova

Figure 7 ∆Vg vs time in the initial moments of

et al., 2008) is the reason for high initial voltage for

stress for Au gate electrode capacitors and

all structures and all injected currents. The space

different injected currents

affects the gate voltage (Nandi et al., 2003). The

initial change in gate voltage (DVg) during first 50s,

Al gate. d Ta2O5 = 17nm

(V) ∆DV Vgg (V)

charge in the oxide affects the barrier height which

under gate injection for W is shown in Figure 9. The

slow degradation without catastrophic breakdown

in the late stage is similar with the other films and

is refer as soft breakdown.

MOS structures with d =17 nm and with TiN

J = - 0.02A/cm 2 J = - 0.2A/cm 2 J = - 4A/cm 2

electrode on the top represented bad voltage/time

characteristics during stress period with very low

current injected (0.001 A/cm2), suggesting that the 0

reactive sputtering is maybe not suitable method

Time (s)

for obtaining capacitors with this gate material, or

Figure 8 ∆Vg vs time in the initial moments of

they can be used for very low injected currents.

stress for Al gate electrode capacitors and

Instead, the films with thickness of 34 nm and

different injected currents.

TiN as gate material are submitted to CCS with different current density, Figure 10. Low injected

traps and high rate of generation of new traps, with

current initiates very low change of the voltage,

enough time for slow positive traps to be created,

i.e. low concentration of pre-traps exist in the

unlike very low increasing rate of the voltage for

structures (which is confirmed with low leakage

higher injecting currents. The increasing of the

currents results), but the second stage of catching

voltage-time curve happens in the initial 50-100 s.

positive charge is more pronounced till 50s. The

Afterward we observe very slow degradation of the

higher injected currents lead to massive catch of

film, i.e. impact ionization of neutral traps leading to

electrons in the initial stage, suggesting that the rate

release of the electrons or positive charge built -up.

of creation of negative charge traps during injection

This is mutual for all investigated structures and is

from the gate is high.

M. Pecovska-Gjorgjevich et al.

Silpakorn U Science & Tech J Vol.6(2), 2012

deposition process of the gate, lowest for Au and

highest for Al.

∆ Vg (V) (V) DVg

J = - 0.2 A/cm 2 J = - 2 A/cm 2

The structures are also submitted to constant

current stress with various current densities. The evolution of the obtained curves shows fast increase

in the beginning (due to the filling of native traps and a high rate of generation of new traps) followed

by a slow evolution, mainly caused by the reduction

of generation rate due to trapping. The time-

W gate, dTa2O5 = 16.7nm

dependent voltage curves reveal difference

0 0

Time(s)

between various gate oxides in the initial stage. The presence of the pre-existing traps in the interface

Figure 9 ∆Vg vs time for structures with W as a gate

gate electrode-oxide is responsible for the trapping

electrode in the initial moments of stress

kinetics common for all structures, but with differences in the initial behavior.

Different initial voltage over the structure

observed for different injected currents densities

of Al gate MOS capacitors implies for lower rate Voltage (V)

of creating new traps during stress with higher J= J= J= J=

9 8 7

-0.4A/cm 2 -0.8A/cm 2 -2.4A/cm 2 -4A/cm 2

currents. This effect is not observed for Au and W gate structures, where we see similar behavior of the structures under different CCS. Increasing the voltage through the structure with increasing the

TiN gate, dTa2O5=34nm

injected constant current is observed for Au-gate

6 0

Time (s)

100

structures. Lower initial voltage for Au structures

150

show lower concentration of traps generated during

Figure 10 Voltage vs time during constant current

deposition process than Al-gate structures connected

stress for TiN gate with thicker Ta2O5

to the reaction between Al and the oxide. The change of the voltage during different CCS is almost the

layer.

same for W-gate structures, indicating that the defect Conclusion

concentration in the oxide and interface oxide-gate

Electrical characteristics of MOS structures

generated during deposition process is much higher

of Ta2O5–SiO2–Si with different gate electrodes

than concentration of the charge traps generated

(Al, Au, W, TiN) are investigated. The results show

during CCS.

high capacitance density and low leakage currents

The second stage of voltage-time curves is

(below 10 A/cm for ±1V) for Au-gate structures

characterized with positive charge build-up and new

which put them in the group of materials for possible

bulk traps generation for all films, expressing with

application in DRAM industry. C-V shift confirms

slow degradation. This behavior is relatively same

presence of traps in the structures generated during

for all the films.

-7

Silpakorn U Science & Tech J Vol.6(2), 2012

Behavior of Ta2O5-Si Capacitors with Different Gate Electrode

TiN-gate MOS structures with thinner oxide

annealing effects on the properties of thermal

layer degrade very fast, so we observed thicker

Ta2O5 on Si. Microelectronics Journal 30:

(34nm) films which pronounced different behavior

265-274.

in the initial stage.

Atanassova, E., Dimitrova, T., and Koprinarova,

From all the structures investigated we can

J. (1995) AES and XPS study of thin RF-

distinguish the one with Au gate. This structure

sputtered Ta 2O5 layers. Applied Surface

has low leakage current density and from the

Science 84: 193-202.

high breakdown conditions, as well as from

Atanassova, E., Paskaleva, A., and Novkovski,

the high values of the accumulation capacity, it

N. (2008) Effects of the metal gate on the

reaches the required demands for its application in

stress-indusced traps in Ta2O5/SiO2 stacks.

microelectronic industry. The CCS measurements

Microelectronics Reliability 48: 514-525.

show these structures as reliable in long term. As

Atanassova, E., Stojadinovic, N., Paskaleva, A.,

we know, gold is an excellent conductor, so it is

Spassov, D., Vracar, L., and Georgieva,

not surprise to see that it has the lowest current

M. (2008) Constant voltage stress induced

density and high accumulation capacity (Nandi

current in Ta2O5 stacks and its dependence

et al., 2003; Atanassova et al., 2008). This material

on a gate electrode. Semiconductor Science

could be considered as promising candidate for such

Technologies 23: 075017.

structures in future MOS technology.

Brown, G. A. (2004) Scaling CMOS Materials & devices. Materials Today 7(1): 20-25.

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Research Article Influence of Blend Ratio on Thermal Properties of Bamboo/ Cotton Blended Woven Fabrics Prakash Chidambaram1* and Ramakrishnan Govindan2 Department of Fashion Technology, Sona College of Technology, Salem, India Department of Fashion Technology, Kumaraguru College of Technology, Coimbatore, India * Corresponding author. E-mail address: dearcprakash@rediffmail.com 1

Received March 28, 2012; Accepted June 11, 2012 Abstract Thermal comfort characteristics of plain woven fabrics made out of 30s Nec cotton in warp and 30s Nec 100% bamboo, bamboo/cotton blended yarns in weft have been studied. The fabric characteristics such as air permeability, wicking, thermal resistance, relative water permeability related to comfort characteristics are discussed. The experimental results show that 30s Nec cotton in warp and 30s Nec bamboo in weft plain woven fabric exhibits higher air permeability when compared to other samples, 30s Nec cotton in warp and 30s Nec bamboo in weft plain woven fabric shows very low thermal resistance and higher wicking rate than other samples. Relative water permeability value of 30s Nec cotton in warp and 30s Nec bamboo in weft fabric is higher and that of 30s Nec cotton both in warp and weft fabrics are lower when compared to other samples. Key Words: Thermal properties; Air-permeability; Water-vapour permeability; Thermal resistance; Wickability Introduction Life standard is nowadays getting higher. The demands of people in all areas are increasing, as well as the requirements regarding new textile materials with new or improved properties which are important for the required higher comfort or industrial use. Comfort, which defined as states in which there are no driving impulses to correct the environment by the behaviour (Li, 2001). Clothing comfort is closely related to thermal comfort (Watkins et al., 1981; Pac et al., 2001). The body produces lots of heat energy and the body temperature increases. To reduce the high temperature, the body perspires a lot in liquid and vapour form. While this perspiration

Silpakorn U Science & Tech J 6 (2) : 49-55, 2012

is transmitted to atmosphere, the body temperature reduces and then the body feels cool. So the garments should allow the perspiration to pass through, otherwise it will result in discomfort. Bamboo is an important forest biomass resource. Bamboo textiles have many fantastic properties when used as textile materials such as high tenacity, excellent thermal conductivity, resistant to bacteria, and high water and perspiration adsorption. Yarns of bamboo fibre provide the desirable properties of high absorbency, antimicrobial and soft feel in textiles and made ups. Currently, regenerated bamboo fibres are used in apparels including undergarments, sports textiles, t-shirts and socks. They are also suitable for

Silpakorn U Science & Tech J Vol.6(2), 2012

Influence of Blend ratio on Thermal properties of Bamboo

hygienic products and sanitary materials such as sanitary napkins, absorbing pads, masks, bandages and surgical gowns (Saravanan et al., 2007; Prakash et al., 2011). Blending of different fibres is a very common practice in the spinning industries. Blending different types of fibres is a widely practiced means of enhancing the performance and the aesthetic qualities of a fabric. Bamboo blended with cotton is usually 50/50 combinations (Abhijit Majumdar et al., 2010). Okubo et al. (2005) studied the mechanical properties of bamboo fibres and concluded that the strength of bamboo fibres was equivalent to that of glass fibres. Grineviciute et al. (2007) revealed that hand properties of bamboo fibre better than cotton fabrics. Gun et al. (2008) reported that fabrics made from 50/50 bamboo/ cotton yarns had a similar appearance as compared with those made from 50/50 viscose/cotton and 50/50 modal/cotton. They concluded that the weight, thickness and air permeability was independent of the fibre type. Kawahito (2008) indicated that cotton fabrics had a higher tenacity, greater thickness under a heavier load, faster water absorption and better drying properties than bamboo fabrics. Filiz Sekerden (2011) studied that the effect of the yarn and weave types on the physical and mechanical properties of the bamboo blended fabrics were examined. He found that the weave type affected the physical and mechanical properties of the fabric more than the fibre mix and type in the weft yarn. Many researchers have conducted studies to evaluate and analyse the thermal comfort of woven fabrics (Senthilkumar et al., 2010; Tyagi

et al., 2011). The work was aimed to investigate the influence of the bamboo content and compare the thermal comfort parameters of woven fabrics made from 100% cotton yarn, 100% bamboo and bamboo/cotton blended yarns. In this study testing air, moisture and thermal transfer properties such as air permeability, relative vapour permeability, thermal resistance and wickability of plain weave fabrics and studying their comfort characteristics. Materials and Methods In this study, 100% bamboo, 70/30 bamboo/ cotton, 50/50 bamboo/cotton, 30/70 bamboo/cotton and 100% cotton yarns were procured from pallava spinning mills (p) ltd, India. It was ensured that all of the yarns produced had the same mean linear density of 30s Nec. The properties of fibre and yarns were given in Table 1 and 2. In this study, plain woven fabrics were chosen and these fabrics were washed thoroughly with hot and cold water, and given scouring treatment using appropriate recipe. The geometrical properties of woven fabrics are given in Table 3. The test parameters related to thermal and moisture related comfort characteristics are given in Table 4. Weaving process was performed using unsized warp, bamboo fibre was inserted only in the weft system. Table 1 Properties of the fibres

Fibre properties

Bamboo

Cotton

Fibre length, mm

27.27

Fibre fineness, dtex

1.52

1.70

Tenacity, cN/tex

19.87

33.33

Elongation at break, %

21.11

6.1

P. Chidambaram and R. Govindan

Silpakorn U Science & Tech J Vol.6(2), 2012

Table 2 Characteristics of bamboo-cotton yarns 100 %

70:30 % Cotton/

50:50 % Cotton/

30:70 % Cotton/

100%

Cotton

Bamboo

0.198

0.185

0.177

0.166

0.150

937

912.3

1075

869.6

802

Tenacity RKM

10.67

10.32

7.26

7.34

11.00

Tenacity CV %

28.93

21.85

28.53

31.23

21.08

Elongation at break %

3.22

3.79

3.40

3.72

6.77

Elongation at cv%

30.11

15.23

22.01

38.35

31.97

Thin place/km (-50%)

4540

2036

1096

1433

550

Thin place CV%

3.89

11.28

18.81

55.93

25.92

Thick place/km (+50%)

3725

2628

1464

2102

1027

Thick place CV%

2.36

7.39

11.59

35.62

4.71

Neps/km

3942

2862

1713

2083

1358

Neps CV%

2.56

8.57

19.21

20.09

9.66

Single yarn strength(g)

210.1

203.2

143

144.7

216.7

Blend ratio Yarn Diameter mm Twist/meter

Testing The following tests were carried out for the woven fabrics such as fabric mass, fabric thickness, air permeability, relative water permeability, thermal conductivity and thermal resistance. The standard test procedure BS 2471, 1974 was followed for determining the fabric mass of woven fabrics in this study. Shirley thickness gauge was used for the measurement of fabric thickness as per ASTM D1777. The wicking properties were measured by

the technique of vertical wicking test as per TAPCC standard. The Lees disc method was used to measure fabric thickness and thermal resistance; water vapour permeability was measured on a Permetest instrument working on simulated skin principle as recommended in ISO 11092; fabric air permeability was measured according to the TS 391 EN ISO 9237 using Tester FX3300. All the fabric samples are conditioned at standard atmospheric condition 65% ±2% RH and 27ºC±2ºC.

Table 3 Geometrical property of woven fabrics

Sample

Warp yarn

Fabric Weft yarn

Thickness

Ends/inch Picks/inch

Warp

Weft

Fabric

cover

factor

(K1)

(K2)

(Kc)

100% Bamboo

0.26

14.61

11.69

20.89

70:30 Bamboo: Cotton

0.28

14.61

12.05

20.72

50:50 Bamboo: Cotton

0.33

14.61

12.59

20.63

30:70 Bamboo: Cotton

0.36

14.61

12.78

20.37

100% Cotton

0.46

14.61

13.15

20.19

100% cotton

Silpakorn U Science & Tech J Vol.6(2), 2012

Influence of Blend ratio on Thermal properties of Bamboo

Table 4 Thermal transfer properties of plain woven fabrics Fabric

Air

wicking

permeability,

height, (cms)

(cm3/cm2/sec)

48.32

14.4

117

71.89

45.11

12.1

106

208.66

80.55

43.22

10.4

214.89

89.35

41.17

9.2

97.9

239.98

97.81

40.04

8.1

Fabric mass,

Thermal resistance,

Relative water

(g/m2)

(mkm2/w x 10 -3)

permeability (%)

197.32

60.38

204.78

Sample

Results and Discussion Air permeability The air permeability results of the fabrics are shown in Figure 1. The results indicate that air permeability is higher in the sample A, and when the bamboo fibre content drops below 50%, the fibre proportion is not so effective in air permeability. This can be explained in terms of the enhanced rate of air flow as a consequence of the reduced bulk of bamboo-majority yarns. Higher air permeability

value of Sample A compared with samples B, C, D and E could be because of lower fabric cover factor values. G端n et al. (2008) compared fabrics produced from mixes of 50/50 bamboo/cotton, 50/50 viscose/cotton and 50/50 modal/cotton, and reported that air permeability is independent of fibre type. When Figure 1 is examined, it is observed that air permeability decreases when the proportion of bamboo in the mix decreases.

Figure 1 Influence of bamboo/cotton blend ratio on air permeability

P. Chidambaram and R. Govindan

Silpakorn U Science & Tech J Vol.6(2), 2012

Thermal resistance

Figure 2 Influence of bamboo/cotton blend ratio on thermal resistance to all other samples. This may be due to higher air permeability. An increase in the cotton content in the fibre-mix improves the thermal resistance. The increased cotton content traps the air, making the structure more thermally resistant. Figure 2 also shows that sample E fabrics have significantly higher thermal insulation values than other samples.

The thermal resistance of Sample E fabric exhibits higher value when compared to all other samples. This is due to the higher fabric thickness and higher fabric cover factor. From the results, it is observed that higher thermal resistance values are noticed in the case of thicker fabric. Sample A exhibits lower thermal resistance when compared

Wicking

Figure 3 Influence of bamboo/cotton blend ratio on wickability

Silpakorn U Science & Tech J Vol.6(2), 2012

Influence of Blend ratio on Thermal properties of Bamboo

Figure 3 shows the results of wickability test. The wicking property of a fabric mainly depends on characteristics of fibre and structure of component yarns and fabric. The experimental results show that Sample A has higher wicking rate when compared to all other samples. Wicking can only occur when fibre assemblies with capillary spaces between them are wetted by a liquid. Sample D exhibits wicking height up to 14.4mm due to better capillary rise and the yarn has soft and smooth feel. As stated, the higher hydrophilicity together with macro channels presented in the bamboo cellulose account for the enhanced wickability of bamboo-majority fabrics

(Erdumlu et al., 2008). Water vapour permeability Figure 4 illustrates the values of water vapour permeability with respect to blend ratio of bamboo. The water vapour permeability is highly dependent on the macro-porous structure of the constituent fibres. The water vapour permeability is considerably higher for the sample A fabrics compared with those for the other samples. Higher moisture regain together with the macro channels presented in bamboo fibre represents no hindrance to moisture transfer in hydrophilic systems (Erdumlu et al., 2008).

Figure 4 Influence of bamboo/cotton blend ratio on water vapour permeability Conclusion The thermal comfort parameters of woven fabrics made from 100% cotton yarn, 100% bamboo and bamboo/cotton blended yarns have been analyzed. The fabric comfort characteristics such as air permeability, wicking, water absorption and thermal resistance have been studied. The fabrics produced with higher bamboo content, in general, are substantially more air and water permeable, more absorbent, have lower thermal resistance and yield higher wickability than the equivalent fabrics produced with cotton fabrics.

Acknowledgements The authors would like to express their sincere thanks to M. Agalya, T. Mathura, V. Saranya and R. Subathrakala for their assistance in the experimental part, to the management of Sona College of Technology for permission to use the laboratory facilities and lastly to the Textile Research Centre, TIFAC-CORE in Textile Technology and Machinery, of Kumaraguru College of Technology, Coimbatore, India for test all the samples in their advanced manufacturing laboratory.

P. Chidambaram and R. Govindan

Silpakorn U Science & Tech J Vol.6(2), 2012

References Erdumlu, N. and Ozipek, B. (2008) Investigation of regenerated bamboo fibre and yarn characteristics. Fibres & Textiles in Eastern Europe. 16: 43-47. Grinevičiūtė, D., Kazakevičiūtė, G., Gutauskas, M., Rimkutė, R., and Abraitienė, A. (2007) Influence of bamboo fibre on fabric hand. Proceedings of 7th Baltic Polymer Symposium. 176-80. Gun, A. D., Unal, C., and Unal, B. T. (2008) Dimensional and physical properties of plain knitted fabrics made from 50/50 bamboo/ cotton blended yarns. Fibres and Polymers. 9: 588-592. Kawahito, M. (2008) A comparative study of bamboo shijara fabric and cotton shijara fabric. Sen-I-Gakkaishi. 64: 108-112. Li, Y. (2001) The Science of clothing comfort. Textile Progress, Taylor & Francis, Manchester. Majumdar, A., Mukhopadhyay, S., and Yadav, R. (2010) Thermal properties of knitted fabrics made from cotton and regenerated bamboo cellulosic fibres. International Journal of Thermal Science. 40: 2042-2048. Okubo, K., Fujıı, T., and Yamamoto, Y. (2005) Development of bamboo-based polymer composites and their mechanical properties. Composite Part A-Application system. 35: 377- 383.

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Acknowledgement to Referees 2011 - 2012 Between 2011 and 2012 (4 issues), there were 24 articles submitted to SUSTJ. 20 Manuscripts were accepted for publication, 2 were rejected, and 2 manuscripts the Editorial Board did not receive a revised version from the authors. The members of the Editorial Advisory Board and the Editorial Board wish to express their grateful appreciation to the reviewers named below for their competent and critical evaluation of submitted articles between 2011 and 2012. Anchalee Tassanakajon Department of Biochemistry, Faculty of Science, Chulalongkorn University, Thailand. Apirat Laobuthee Department of Materials Engineering, Faculty of Engineering, Kasetsart University, Thailand. Benchawan Wiwatanapataphee Centre of Excellence in Mathematics (CEM), Thailand. Ching-Hua Ting Department of Mechanical and Energy Engineering, National Chiayi University, Taiwan. Doungjai Thirathumthavorn Department of Food Technology, Faculty of Engineering and Industrial Technology, Silpakorn University, Thailand. Ho Soon Min Department of Chemistry, Faculty of Science, Universiti Putra Malaysia, Malaysia. Jantip Suesat Department of Textile Science, Faculty of Agro-Industry, Kasetsart University, Thailand. Kaewta Limhang Faculty of Animal Science and Agricultural Technology, Silpakorn University, Thailand. Kamolchanok Panishkan Department of Statistics, Faculty of Science, Silpakorn University, Thailand. Ladda Wongpayapkul Department of Pharmaceutical Science, Faculty of Pharmacy, Chiang Mai University, Thailand. Mitr Pathipvanich Department of Food and Pharmaceutical Chemistry, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Thailand. Nihal Yatawara Department of Mathematics and Statistics, Curtin University of Technology, Australia. Niti Yongvanich Department of Materials Science and Engineering, Faculty of Engineering and Industrial Technology, Silpakorn University, Thailand. Nittiya Pabhapote School of Science and Technology, University of the Thai Chamber of Commerce, Thailand.

Silpakorn U Science & Tech J 6 (2) : 56-58, 2012

Noppamas Soonthornchareonnon Department of Pharmacognosy, Faculty of Pharmacy, Mahidol University, Thailand. Norziah Mohd Hani School of Industrial Technology, Universiti Sains Malaysia, Malaysia. Patanee Udomkavanich Department of Mathematics, Faculty of Science, Chulalongkorn University, Thailand. Patcharaporn Neammanee Graduate School of Applied Statistics, National Institute of Development Administration (NIDA), Thailand. Pawapol Kongchum Faculty of Animal Science and Agricultural Technology, Silpakorn University, Thailand. Pojanie Khummongkol Division of Materials Technology, School of Energy, Environment and Materials, King Mongkutâ&#x20AC;&#x2122;s University of Technology Thonburi, Thailand. Pongchanun Luangpaiboon Department of Industrial Engineering, Faculty of Engineering, Thammasat University, Thailand. Prasong Siriwongwilaichat Department of Food Technology, Faculty of Engineering and Industrial Technology, Silpakorn University, Thailand. Pupong Pongcharoen Department of Industrial Engineering, Faculty of Engineering, Naresuan University, Thailand. Ramidha Srihera Department of Mathematics and Statistics,Faculty Science and Technology, Thammasat University, Thailand. Rangrong Yoksan Department of Packaging and Material Technology, Faculty of Agro-Industry, Kasetsart University, Thailand. Sarawut Phupaichitkun Department of Materials Science and Engineering, Faculty of Engineering and Industrial Technology, Silpakorn University, Thailand. Suda Tragantalerngsak Department of Statistics, Faculty of Science, Silpakorn University, Thailand. Suwayd Ningsanond Institue of Agricultural Technology, Suranaree University of Technology, Nakhon Ratchasima, Thailand. Thitikom Puapansawat Department of Mathematics, Faculty of Science, Mahidol University, Thailand. Toshihiko Toida Department of Analytical Chemistry, School of Pharmaceutical Sciences, Chiba University, Japan.

Turenjai Dooljindachabaporn Department of Environmental Science, Faculty of Science, Khon Kaen University, Thailand. Varaporn Junyaprasert Department of Pharmacy, Faculty of Pharmacy, Mahidol University, Thailand. Vipawan Laoarun Department of Statistics, Faculty of Science, Silpakorn University, Thailand. Vorrada Loryuenyong Department of Materials Science and Engineering, Faculty of Engineering and Industrial Technology, Silpakorn University, Thailand. Walailak Atthirawong Department of Statistics, King Mongkutâ&#x20AC;&#x2122;s Institute of Technology Ladkrabang, Thailand. Wirawan Chinviriyasit Mathematics Department, King Mongkutâ&#x20AC;&#x2122;s University of Technology Thonburi, Thailand. Worachart Sirawaraporn Department of Biochemistry, Faculty of Science, Mahidol University, Thailand. Yudi Pranoto Department of Food and Agricultural Product Technology, Faculty of Agricultural Technology, Gadjah Mada University, Indonesia.