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Leveraging Scatterometry to Enhance STI Etch Process Development Matthew Sendelbach and Andres Munoz, IBM Microelectronics Pedro Herrera, KLA-Tencor Corporation
Scatterometer profiles on line/space arrays are often compared to XSEM images to determine how well they match. However, these comparisons lack precision because they are typically qualitative. This problem can be circumvented by comparing multiple measurements of critical dimension (CD), sidewall angle, and height/depth from XSEM images to scatterometry measurements previously collected from the same locations. A series of etched shallow trench isolation (STI) wafers subjected to a range of etch processes was used in this study. The end result indicates that increased sampling of scatterometry can be used to improve etch process development.
Introduction
Etch process development requires more than just CD measurements. Full profile information showing CD, sidewall angle (SWA), depth, and film thickness is needed. Cross-section SEM (XSEM) is usually used to provide this information because of the detailed images they provide. But XSEM metrology is slow and only provides the profile at a very localized spot. Each wafer is typically sampled using XSEM in only a couple of places, often center and edge. Depending on the XSEM lab workload and the priority of the work, results can take anywhere from several hours for urgent work to several days for normal priority work. Process decisions are then made using this very limited information. Furthermore, XSEM metrology is costly and destructive, so wafers cannot be reused for further process development downstream. Scatterometry has the potential to be an alternative to XSEM metrology because it can also provide full profile information. Although it cannot provide as many subtle details as XSEM metrology, it collects information over a much larger area—tens
of micron in diameter per measurement. This is preferable because it provides greater sampling. In addition, scatterometry can measure at a rate of only a few seconds per measurement. This enables the measurement of every field on the wafer in only a few minutes. Lastly, scatterometry measurements are relatively inexpensive and non-destructive, so the wafers can be reused. But how accurate are scatterometry’s measurements of CD, SWA, and depth? They need to be at least as accurate as XSEM measurements. And how should scatterometry measurements be compared to XSEM measurements in order to determine this? Scatterometry can provide measurements using either library-based or regression-based models. But is one of these more accurate than the other? Or do they provide the same result? This article addresses these questions using a specific case study. Wafer samples and their measurement
Wafer Samples
STI refers both to the series of processes used to form electrically isolating structures in the wafer substrate and to the isolating structures themselves. The nine 300-mm wafers used in this study were part of development work in which various etch processes were evaluated. After etch, the wafers were processed until the Spring 2006
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film stack consisted of nitride over a thin oxide over etched silicon. One of these processes was a nitride pullback step that reduced the bottom CD of the nitride relative to the top CD of the silicon. This is a typical film stack for STI wafers measured at final inspect (FI). Two scatterometry gratings consisting of lines and spaces were identified for measurement: one with a nested pitch (265 nm) and one with a semi-isolated pitch (840 nm). Although the semi-isolated pitch grating does not have truly isolated lines, for the rest of this article it will be referred to more simply as the isolated pitch grating. Every chip on each wafer was measured using librarybased scatterometry. In most cases, spectra were saved so that regression-based results could later be generated offline. Next, the wafers were submitted for XSEM analysis. For the nested grating, 16 chips across all of the wafers were cleaved for XSEM analysis. For the isolated grating, a total of 12 chips were cleaved. Four of the 16 nested gratings did not have scatterometry spectra collected from them; thus, for these four gratings, library and XSEM measurements, but not regression measurements, were made. Figure 1 shows a typical XSEM image of the nested grating. Overlaying this image is the scatterometrygenerated profile corresponding to the grating for that chip. Six parameters were chosen for the comparisons
Chromium decoration Nit BCD
Nitride
Si Height Si SWA
Silicon
Total Height
Si TCD
Oxide
Si BCD
300 nm Figure 1: Typical XSEM image of a nested grating with overlay (left structure) of library-based scatterometry profile for the same grating. Right structure shows the six parameters measured from XSEM images.
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between scatterometry and XSEM measurements: the nitride bottom CD (Nitride BCD), the silicon top CD (Si TCD), the silicon bottom CD (Si BCD), the silicon sidewall angle (Si SWA), the silicon height/depth (Si Ht), and the total structure height (Total Ht). Three of these (Si TCD, Si SWA, and Si Ht) are critical etch parameters. The other three were measured not only because they can be useful to an integration engineer in understanding what is occurring in other areas of the STI module, but also because the authors wanted to evaluate the success of scatterometry in providing the “full picture.�
Scatterometry Measurements
Developing a scatterometry model involves using the film stack information (thickness and dispersion of each film) and the grating information (pitch, height, and profile characteristics) to create a theoretical model of the measured structure. Existing film dispersion files were used to measure the film thicknesses on the STI wafers and verify that the dispersion files provided a good match to the measured STI stack. Initially, coarse scatterometry models were generated for the dense and isolated targets; these models were centered on the nominal CD, HT, and SWA for the silicon and the measured thicknesses of the oxide and nitride. Measurements taken with these models were used to determine the correct parameter values and ranges, and determine the sensitivity to and correlation of the expected profile features (e.g., the nitride height, nitride SWA, nitride pullback, silicon profile, any top-rounding or bottomrounding of the overall profile, etc.). Results of this analysis showed models with four degrees of freedom (DOF) provided good measurement performance. The final models varied the CD, height, and SWA of the silicon and the height of the nitride. The SWA of the nitride, the thickness of the oxide, the nitride pullback, and the profile rounding were fixed at their measured average values. Using fewer DOF simplifies the comparison to the XSEM results and allows for a faster regeneration or expansion of the models if one needs to measure a different pitch or account for a large change in the etch process. The parameters that were varied were used to perform both library and regression measurements. For library measurements, the theoretical spectra are generated before the measurement by varying each model parameter through its range at a fixed step. A theoretical spectrum is generated for each combination of parameter values, and the collection of these spectra is referred to as a library. Each measured spectrum is compared to the
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library, and the library location that gives the best fit is used to determine the answer (the parameter values that best describe the measured spectra). In a regression measurement, new theoretical spectra are created during the measurement as the measurement algorithm works toward the best answer. Each method has its advantages. Library measurements are typically faster since the measurement consists of matching the measured spectra to the library (with some interpolation). Regression measurements are more flexible since the parameter ranges are not fixed and one can add or remove DOF to the measurement as necessary.
XSEM Measurements
Each selected 50 x 50 Âľm scatterometry target was cleaved once for XSEM analysis. Care was taken to ensure that selected chips were properly identified so that the XSEM results could be compared to the correct scatterometry measurements. In general, multiple lines and spaces were imaged and measured along each cleave in order to capture some amount of across-grating variation. In addition, the cleaved chips were selected from both the center and edge regions of the wafers in order to maximize the chances of capturing a larger range of values for each parameter. The XSEM samples were coated with chromium, cleaved, and then subjected to a 12-second plasma etch. The plasma etch served as a decoration; that is, it highlighted the materials relative to each other. The chromium preserved the outer profile during the plasma etch and made it easier to collect the measurements by improving the edge delineation. Improved edge delineation made measurements easier to collect consistently. In order to maintain consistency, the edge of a feature was defined as the inner-most section of the interface between chromium and silicon or nitride. The measurements were performed manually using specialized software. The type of system that was used, the Hitachi 5200, is among the best XSEM systems available. Multiple systems were used for this work, which was done at a world-class IBM lab. The Feature calibration of the systems in both the x and y directions is monitored monthly Nitride BCD and ensured to within five percent of a NIST-traceable standard. Si TCD To determine Nitride BCD and Si TCD, the thin oxide layer between the silicon and nitride was used as a point of reference; the top of the oxide layer was used to measure the Nitride BCD, while the
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bottom section was used to measure Si TCD. The Si BCD was measured at the level in the profile where the trench depth was uniform, but not necessarily the deepest. The Si Ht was measured by extending a line from the Si TCD to the point where the trench depth was uniform and deepest. Similarly, the Total Ht of the profile was determined by extending the line used to measure the Si Ht to the top nitride / chromium interface. The Si SWA was measured by using as a reference the Si TCD and Si BCD lines. XSEM drift is a phenomenon that makes lines appear to tilt more than they really do. When measuring STI profiles, the SWA measurement of one side of the profile will be larger, while the measurement of the other profile will be smaller. In order to cancel this effect, all silicon sidewall angles were measured in pairs; that is, both sides of the profile were measured. The pitch was measured when at least two complete profiles were viewed in a XSEM image. It was used to calibrate the CD and height measurements, which is necessary for critical measurements because the scale is only controlled to within five percent of a standard. SWA measurements were not calibrated. The calibration was done by first calculating the calibration factor, which is the ratio of the nominal pitch (265 or 840 nm for this work) to the measured pitch. Uncalibrated XSEM measurements of CD and height were multiplied by the calibration factor in order to obtain calibrated XSEM measurements:
(1)
Table 1 summarizes the average number of XSEM measurements per pitch per feature collected for this study. A total of 669 XSEM measurements, including pitch, Avg. Number of XSEM Meas/Grating/Chip Nested Pitch - 16 chips
Iso Pitch - 12 chips
3.8
3.0
3.5
3.0
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3.0
Si SWA
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3.1
2.5
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Table 1: Average number of XSEM measurements per grating per chip for each of the six measured parameters.
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were collected. This large number of reference measurements helps to indicate the magnitude and thoroughness of this study. Data analysis
Total Measurement Uncertainty (TMU) Analysis
In order to properly compare the different metrology results, Total Measurement Uncertainty (TMU) analysis1 was used to quantify the measurement error of each system. TMU analysis compares a measurement system that is being tested (also called the Tool under Test, or TuT) to a Reference Measurement System (RMS). The RMS is assumed to have no systematic error; its random error, called the Reference Measurement System Uncertainty (RMSU), can be estimated using techniques first detailed by Sendelbach et al.2 The RMSU has four components: one associated with the short-term precision of the RMS, one associated with the long-term precision, one with the use of multiple reference tools comprising the RMS, and one with the across-grating or acrosssample variation. The uncertainty associated with the last component is not directly caused by the RMS, but must be attributed to the RMS so as to make sure that the TMU is only a measure of the uncertainty attributable to the TuT. TMU analysis results in several parameters that are used extensively in this work. The primary parameter, TMU, is a 3s quantity and, when plotting measurements from the TuT and the RMS against each other, is a measure of how much the scatter around a best-fit line is caused by the TuT. TMU has dimensions, it takes into account (removes) the measurement error of the RMS, and it is a combined measure of both the precision and accuracy of the TuT. As a matter of convention, the TuT data are plotted on the x-axis, and the RMS data are plotted on the y-axis. Because TMU is an estimate of measurement error, upper and lower limits for this estimate can be computed. In this work, these limits are labeled “TMU UL” and “TMU LL,” and are calculated using 90 percent confidence limits, as described by Sendelbach et al.3 TMU percent is another parameter, and is defined as: (2)
where y is the mean of the RMS measurements in the TMU analysis. TMU % can be thought of as an indicator 4
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of relative quality of measurement, while TMU is more an indicator of absolute quality of measurement. TMU % is especially useful when comparing TMU results of different parameters, such as CD or depth. For example, consider two TMU analyses: one of 50 nm gate CDs, and the other of 500 nm via depths. A TMU result of 5 nm for each case would suggest equivalent performance for each system. However, most metrologists would consider a 5 nm TMU for a gate CD measurement to be inadequate, while a 5 nm TMU for a via measurement may be considered excellent. TMU % quantifies this effect, as seen by the 10 percent result for the gate analysis and the 1 percent result for the via analysis. The slope of the best-fit line is another output parameter of TMU analysis; because it is also an estimated quantity, it has a 3s standard deviation associated with it. Slopes close to unity are preferred, since they indicate that the TuT has a similar sensitivity as the RMS to changes in the parameter being measured. The average offset, which is the difference in the means of the RMS and TuT measurements, and the number of data pairs, which is the number of samples measured by each system, are also displayed frequently in this work. Finally, a parameter called the minimum range, or “Min Range,” is shown. This quantity is the smaller of two numbers: the range of the RMS measurements and the range of the TuT measurements. It has often been found to be useful when compared to the TMU. Experience has shown that the minimum range generally needs to be at least two to four times greater than the TMU in order for the TMU to be meaningful. As the TMU approaches the minimum range, the plot comparing the TuT data to the RMS data becomes more scattered and less linear. This usually means that the samples being measured do not span a large enough range in order to properly determine the TMU.
“Average” versus “Single” XSEM Measurements
Previously, the difference between calibrated and uncalibrated XSEM measurements was explained. In this section, another distinction must be made: the difference between “average” and “single” XSEM measurements. As its name implies, the average XSEM measurements for a given parameter are the arithmetic average of the multiple XSEM measurements collected for that parameter from a specific grating. For the CD and height parameters, the averages could be of either the individual calibrated or the individual uncalibrated XSEM measurements. Averaging multiple measurements provides a better estimate than individual measurements of the “true” value across the grating.
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Because the average XSEM measurements are commonly used as the RMS in this study, properly estimating the RMS uncertainty (RMSU) is important. Since multiple measurements per grating are collected for each parameter, the RMSU is calculated using case #1 from the work of Sendelbach et al.2 This is done by first computing for each parameter the variance of the individual measurements from each grating. The average of these variances is calculated, and this average is divided by the average number of measurements per grating (for this study, the average number of measurements per grating is shown in Table 1). Finally, the resulting quantity is converted to a 3s value by taking its square root and then multiplying by three.
the TMU resulting from the comparison of the single XSEM results to the average XSEM results. The same procedure was also applied to the slope and average offset parameters. For the average offset, it is important that a simple averaging of the different offsets is not used because of the cancellation effect that offsets of different signs have. This cancellation effect makes the combined average offset appear closer to zero than it should. In summary, compared to using only one set of individual XSEM results, this averaging technique better represents what would be expected if individual random XSEM measurements are compared to average XSEM measurements.
Single XSEM measurements mimic the approach commonly used in development to gather information from a XSEM image. This approach involves making only one measurement per parameter per grating. To determine the measurement quality that this approach provides, comparisons between single XSEM measurements and the average XSEM measurements were needed. Here, the average XSEM measurements act as the RMS. But since each parameter has several measurements per grating, determining which individual measurements should be compared to the average measurements must be resolved. The solution to this problem has already been used by Sendelbach et al.3 For each parameter, multiple measurements per grating are collected. The number of measurements per grating varies from one chip to the next. The minimum number of measurements per grating must be identified, because this determines the number of TMU analyses that must be completed. For each TMU analysis, one randomly selected measurement from each grating is paired with the average XSEM measurement for that grating. This pairing is done for each chip in the TMU analysis. Individual measurements already selected are not used again in the other TMU analyses. Each TMU analysis generates a set of results, such as TMU, slope, and average offset, which reveal how well that set of individual measurements compares to the average measurements.
Results
Each set of results is then combined to form a single set of results that is the final representation of how well the single measurements compare to the average of the measurements. To determine the final TMU, each of the individual TMUs from the different analyses are first converted to variances (TMU is a 3s quantity) and then averaged. The average of the variances is then converted back to a 3s quantity. This final quantity is reported as
Comparison of Calibrated and Uncalibrated XSEM Data
Before fully evaluating the quality of the scatterometry results compared to the XSEM data, it is interesting to determine the effect that the calibration of the XSEM data has on the comparison. As explained previously, all raw XSEM measurements except the silicon SWA were calibrated using the XSEM scale and the measured pitch in each image. Figure 2 shows that for the silicon height measurement on the isolated pitch, using the calibrated XSEM values (represented by open triangles when paired with the scatterometry data) changes the appearance of the scatter plot noticeably but not significantly compared to the use of the uncalibrated XSEM values (solid diamonds when paired with the scatterometry data). Note that the best-fit line does not shift significantly. The other parameters give similar results.
Lib. vs Avg XSEM (Cal & Uncal) Si Ht - Isolated Pitch 510
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XSEM XSEM
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Figure 2: Example of the extent that calibration alters the best-fit line and the data pairs (noticeably, but not significantly).
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Figure 3 quantifies the effect of using calibrated XSEM measurements for the isolated pitch. Here, the TMU is plotted, with upper and lower estimates, for the library-based scatterometry measurements when compared to both the calibrated and uncalibrated average XSEM measurements. The silicon SWA is not shown because it does not get calibrated. In most cases, there is a slight improvement when comparing the scatterometry data to the calibrated XSEM data. This is expected: the calibrated results are believed to be a better Reference Measurement System. When an RMS has inaccuracies that are unaccounted for in its measurement, TMU analysis inadvertently assigns this extra error to the tool under test, so the calculated TMU increases. This modest improvement in TMU validates the use of the calibration procedure. Furthermore, the slopes and average offsets for the isolated measurements did not change significantly. The nested measurements had similar results.
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Figure 3: Library-based scatterometry measurements versus both calibrated and uncalibrated average XSEM measurements. In most cases, using calibrated XSEM data improves the correlation between scatterometry and XSEM measurements.
Avg XSEM (nm)
Avg XSEM (nm)
indicating that the scatterometry measurements are successfully tracking the XSEM measurements. The TMU is good, but has large uncertainty due to the Library versus Average XSEM small number of data pairs. The average offset for this Although both library-based and regression-based parameter (as well as the other CD and height paramscatterometry results for both the dense and isolated eters, as will be seen below) is equal to or under 6 nm, targets were compared to the XSEM data, only the which is quite good. This is important because in etch library-based dense target plots are shown in this development it is not always sufficient to know that section, in the interest of brevity. The isolated target the measurement correlates to changes in a parameter. results are discussed when there is a marked difference The offset must be small because some parameters, between dense and isolated results. A summary of the such as the final etched CD for critical layers, must regression-based results will be presented in the next strictly adhere to an absolute specification dictated by section. All of the results are comparisons of the library the design manual or process requirements. A large data to the calibrated average XSEM data. Figure 4 offset would require the scatterometry measurements shows the results for the Nitride BCD dense measureto be adjusted so that adherence to the design or ment. For this measurement there is a clear correlation, process requirements could be properly evaluated. This adjustment Lib. vs Avg XSEM (Cal) Lib. vs Avg XSEM (Cal) Si TCD - Nested Pitch Nitride BCD - Nested Pitch is inconvenient, easily forgotten by 140 120 the user, and therefore undesirable. Perhaps the most interesting Nitride 130 110 BCD result is that the nested best-fit 120 100 line slope is more than three sigmas 110 from unity, while for the isolated 90 pitch the slope is very close to unity 100 80 (1.03 slope for isolated). The reason 90 70 for this difference is unknown. 70
TMU 5.8 Slope 0.69
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TMU % 6.5 3Ďƒ Slope 0.28
90 100 110 Scatterometer (nm) TMU UL 9.7 Avg Offset 5.1
TMU LL 1.2 Min Range 23.1
RMSU 5.7 Data Pairs 16
Figure 4: TMU analysis for nitride BCD (nested pitch).
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TMU % 4.1 3Ďƒ Slope 0.26
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TMU LL 0.0 Min Range 28.8
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RMSU 5.2 Data Pairs 16
Figure 5: TMU analysis for silicon TCD (nested pitch).
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The silicon TCD results displayed in Figure 5 are impressive. Good correlation (TMU) and slope are seen across a large range of values.
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Lib. vs Avg XSEM (Cal) Si BCD - Nested Pitch
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Figure 6: TMU analysis for silicon BCD (nested pitch).
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TMU % 0.6 3σ Slope 0.51
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TMU LL 0.0 Min Range 2.6
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RMSU 0.88 Data Pairs 16
Figure 7: TMU analysis for silicon SWA (nested pitch).
This is an important parameter because design manual final CD requirements at the STI level are usually applied to it, instead of the bottom CD. The silicon BCD comparison, shown in Figure 6, also indicates a clear correlation to the XSEM data. The silicon height and total height had varying degrees of correlation. The TMUs are generally larger (10.6 – 18.0 nm) than those for the CD plots; however, this can be expected because the heights are considerably greater than the CDs. The TMU % values for the heights are in line with those of the CDs, so the relative quality of measurement is similar. Figure 7 shows a good correlation for the nested silicon SWA. The average offset is very low (0.2°), as is the TMU % (0.6 percent). Despite having a similar TMU, TMU %, and average offset, the isolated silicon SWA results shown in Figure 8 appear to be considerably poorer than the nested results. The larger apparent scatter of the data pairs and the negative slope are clues to the poorer correlation. But the large apparent scatter is due to the small range of the data: the minimum range is only 1.4° for the isolated plot, while it is 2.6° for the nested plot. Because of this small minimum range compared to the TMU (0.59°), the correlation for the isolated SWA is inconclusive. With a large enough range of data, the apparent scatter would likely appear less, and the upper limit of the TMU could be determined better. But when the minimum range is not much larger than the TMU, the upper limit of the TMU cannot be bounded. Although several of the slopes from Figures 4-8 do not appear to be close to unity, in all but one of these cases
TMU 0.59 Slope -0.48
81 82 Scatterometer (nm) TMU % 0.7 3σ Slope 0.71
TMU UL 1.3 Avg Offset 0.4
TMU LL 0.0 Min Range 1.4
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RMSU 0.84 Data Pairs 12
Figure 8: TMU analysis for silicon SWA (isolated pitch).
the slope is within 3s of unity. The small number of data pairs makes it difficult to determine the slope with a small uncertainty. Note also that for all of these correlations, the RMSU is either larger than or within a factor of two of the TMU. Thus, the error of the XSEM measurement, combined with the across-grating variation, is significant relative to the error in the scatterometry measurement.
Library and Regression versus Average XSEM
One of the goals of this study is to examine whether regression-based library measurements are better, equal to, or worse than library-based scatterometry measurements. In order to do this, both types of measurements must be compared to an RMS. Once again, the RMS is chosen to be calibrated average XSEM measurements. Since regression results on the nested gratings were only available for 12 out of the 16 chips measured using the library and XSEM methods, only these 12 chips were used for this analysis. For the isolated gratings, all 12 chips are included in the analysis because all of them were measured using all three techniques. Figure 9 summarizes the TMUs for both the library and regression dense measurements compared to the XSEM measurements. The TMUs are very similar and the uncertainty bars have significant overlap for all of the parameters. The Mandel slopes resulting from the TMU analyses are also similar and the 3s error bars have significant overlap. Both methods also provide similar average offsets. For CD and height parameters, the difference in the offsets between the methods is always about 7 nm or less. The silicon SWA offsets are within a couple tenths of a degree of each other. The isolated results showed a similar agreement between Spring 2006
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Figure 9: TMU summary for library and regression measurements versus
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Figure 10: TMU summary for library versus regression measurements.
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Figure 10 shows the TMU between the library and regression methods for both pitches and all parameters. The TMUs are very good, but what is especially encouraging is that the lower limit in every case is 0 nm or 0째. This means that with more data collection the
Library and Single XSEM (Cal) vs. Avg XSEM (Cal) TMU - Nested Pitch
Single XSEM
The next comparison again involves both library-based and regression-based scatterometry measurements. In the last section, these were compared to XSEM measurements in order to show that both methods are equivalent in measurement quality. Another related, but separate, question is whether library and regression measurements agree well with each other. If they agreed perfectly with each other, the TMU and average offset between them would be zero, and the slope would be unity. But perfect agreement is not, and should not be, expected because these methods use different computational techniques to calculate the results. For the TMU analyses in this section, again only 12 nested and 12 isolated measurements could be compared. Since it is unclear which system should be the RMS, the TMU analyses were iterated until the RMSU equaled the TMU. In this way, an equal amount of error was assigned to each system. There is no across-grating variation in the comparison because measurements were collected from each wafer only once. The spectra collected were then analyzed using both techniques.
Library
Library versus Regression
TMU for each parameter has the potential to approach zero. The TMU % results are also impressive: all of the percentages are less than three. The height and SWA results are better than the CD results on a relative scale, but this is questionable for the isolated SWA result because of the small minimum range in the isolated measurements. For the slope results, in all cases the 3s uncertainty limits either cross or nearly cross unity. The uncertainty limits for the isolated silicon SWA are large because the minimum range is so small. For the average offset results, all of the CD and height offsets have a magnitude less than 7 nm, and most have a magnitude less than 4 nm. The SWA offsets have magnitudes of about 0.5째 or less. In summary, the library-based and regression-based techniques agree very well with each other.
TMU (nm or deg)
library and regression measurements. Thus, within the level of certainty that this study can determine, both regression-based and library-based techniques provide an equivalent quality of measurement.
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Figure 11: TMU summary for library and single XSEM measurements versus average XSEM measurements (nested pitch).
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Figure 12: Average offset summary for library and single XSEM measurements versus average XSEM measurements.
Library and Single XSEM versus Average XSEM
The final comparison is probably the most significant. Here, the question of whether library-based scatterometry results are better than single XSEM results is addressed. The single XSEM results used here are calibrated; how they are calculated was described earlier. The calibrated average XSEM measurements are chosen as the RMS. All 16 chips are used for the nested results, while the isolated results consist of 12 chips. Figure 11 shows the TMU results for the nested pitch. Within the bounds of the confidence limits, the TMUs are roughly equivalent in most cases. For the slopes, the overlap of the 3s uncertainty bars is significant for all parameters. Finally, the average offset results are shown in Figure 12. In most cases, the magnitude of the offset for the CD and height parameters is less than 3 nm, while the magnitude of the SWA offsets is always less than 0.5°. Thus, both methods provide small average offsets. Although the single XSEM results performed slightly better than the scatterometry results, two factors must be considered. First, the single XSEM results were calibrated. In development, XSEM measurements are frequently not calibrated. So by comparing the scatterometry measurements to calibrated single XSEM measurements, the “benefit of the doubt” was given to the XSEM measurements. Although not shown here, the use of uncalibrated XSEM measurements narrows the already small gap between the scatterometry and single XSEM measurements. Second, the average
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XSEM results consisted of only a few XSEM measurements per parameter, as shown in Table 1. In each case these individual measurements were all collected from a very small region of the grating. A preferred, but much more difficult, sampling would include many more individual measurements collected more uniformly across the grating in order to better take into account across-grating variation. If this were done, it is believed that the scatterometry results would have much better matched the average XSEM results because of scatterometry’s averaging ability. Furthermore, this improved sampling would likely have worsened the single XSEM results. Therefore, because the results between the two methods were already so close, the authors believe that an even more meticulous study would show that scatterometry can provide superior measurement capability compared to single XSEM measurements. Scatterometry and etch process development
Because scatterometry can provide measurements of multiple profile parameters quickly, the possibility of easily generating full wafer contour maps of these parameters becomes possible. This capability is a powerful aid to etch process development. In order to maximize the likelihood of providing a robust, uniform process that meets the required specifications, an etch engineer must know how a given process affects Figure 13: Full wafer contour map several parameters across of non-uniform silicon height detected the entire wafer. after STI etch using scatterometry.
Figure 14: Full wafer contour map of non-uniform silicon TCD detected after STI etch using scatterometry.
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In order to show the power of this capability, two examples are provided. The first, shown in Figure 13, involves the measurement of the silicon height at final inspection (FI) after STI etch. The non-uniform height occurred at the silicon etch step, and could indicate either an etch equipment problem or a non-optimized etch process. The range across the wafer
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is over 15 nm. This pattern could not reasonably be caught by either XSEM or AFM measurements because of their slower sampling speeds.
were inconclusive because the comparison was limited by a small range of data; a larger range is required to properly estimate the correlation.
The second example involves the measurement of the silicon top CD at final inspection after STI etch, and includes an interesting lithography/etch interaction. Limited XSEM measurements detected a center-to-edge variation of the silicon top CD caused by the silicon etch step. Because the CD-SEM data was being used to monitor only the bottom CD, the XSEM measurements were the sole data used to decide upon a corrective action. The corrective action, called a “litho edge comp,” was to compensate for the center-to-edge difference by exposing the edge chips differently than the center chips at the lithography step. But because the litho edge comp was based on limited XSEM data, it was not tuned correctly. This was not detected until the full wafer scatterometry measurement of the silicon top CD (Figure 14) was made. The scatterometer detected that the litho edge comp overcompensated for the etch variation by about 7 nm. So, not only can full-wafer scatterometry measurements detect subtle across-wafer etch variations, they can also detect non-uniformities caused by previous process steps.
Regression-based scatterometry measurements were also evaluated in this study. These measurements were shown to correlate to XSEM data just as well as librarybased measurements. They were also shown to agree well with library-based measurements when directly compared to them. The final comparison investigated in this study compared both scatterometry measurements and individual XSEM measurements, which is the current standard in etch process development, to the averages of multiple XSEM measurements in order to determine whether a single scatterometry measurement can measure as well as a single XSEM measurement. Although the single XSEM measurements performed slightly better on some parameters and equivalent to scatterometry on others, the experiment was heavily biased in favor of the XSEM measurements. This bias could have been reduced if many more XSEM measurements over more regions of each grating were used to generate average grating values. Doing this would be difficult, but would likely show that scatterometry measurements are significantly better than a single XSEM measurement.
Conclusions
A large number of XSEM measurements were made on several etched wafers at the STI level and compared to scatterometry measurements previously collected at the same locations. The XSEM measurements were calibrated by using the known structure pitch in the images; calibrated measurements were found to modestly improve the scatterometry-to-XSEM correlation compared to uncalibrated measurements. Library-based scatterometry measurements were compared to XSEM measurements for several parameters, including CD, height, and sidewall angle, that together provide significant profile information about the structure. Multiple XSEM measurements from each grating for each parameter were averaged in order to better represent the “true” average XSEM value for each parameter and grating. TMU analysis was used to properly quantify the comparisons. Results show that the library-based measurements correlated well to the XSEM measurements for each parameter except for the silicon sidewall angle of the isolated pitch grating. Here, the results
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Yield Management Solutions
Based on this study, it is evident that scatterometry can accurately measure multiple profile parameters from an etched line/space structure. With the proper experiments, these promising findings should be reproducible on other structures, such as gates and vias, and at other process steps, such as after lithography. Although scatterometry is being widely implemented in manufacturing, its potential for supporting process development remains largely untapped. It should be noted that scatterometry should not fully replace XSEM metrology for process development because XSEM images should still be used as a final check for subtle profile characteristics. But scatterometry can replace much of the existing XSEM work. This will not only enable a more complete evaluation of the performance of a process, but also improve process development cycle times. With the advent of 300 mm wafers, detecting across-wafer variations becomes critical and can be done easiest for multiple parameters through the use of scatterometry. If a process is developed using sparse metrology sampling, it is less likely to be robust and more likely to limit manufacturing yield.
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Acknowledgements
The authors would like to thank Dave Dobuzinsky and John Faltermeier of IBM for their willingness to use scatterometry to support STI etch process development, and their support in obtaining the resources to make this experiment happen. We also thank Jesus Rivas of KLA-Tencor for his assistance with data collection. References 1. M. Sendelbach and C. Archie, “Scatterometry measurement precision and accuracy below 70 nm,” Metrology, Inspection, and Process Control for Microlithography XVII, Daniel J. Herr, Editor, Proceedings of SPIE, Vol. 5038, pp. 224-238, 2003. 2. M. Sendelbach, W. Natzle, C. Archie, B. Banke, D. Prager, D. Engelhard, J. Ferns, A. Yamashita, M. Funk, F. Higuchi, and M. Tomoyasu, “Feedforward of mask open measurements on an integrated scatterometer to improve gate linewidth control,” Metrology, Inspection, and Process Control for Microlithography XVIII, Richard M. Silver, Editor, Proceedings of SPIE, Vol. 5375, pp. 686-702, 2004. 3. M. Sendelbach, C. Archie, B. Banke, J. Mayer, H. Nii, P. Herrera, and M. Hankinson, “Correlating scatterometry to CD-SEM and electrical gate measurements at the 90 nm node using TMU analysis,” Metrology, Inspection, and Process Control for Microlithography XVIII, Richard M. Silver, Editor, Proceedings of SPIE, Vol. 5375, pp. 550-563, 2004.
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