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Data feed-forward for improved optical CD and film metrology L. Mihardja*, M. Di, Q. Zhao, Z. Tan, J. C. Robinson, H. Chouaib KLA-Tencor Corporation; One Technology Drive, Milpitas, CA 95035, U.S.A. ABSTRACT Advanced integrated circuit (IC) manufacturing requires high quality metrology for process disposition and control in order to achieve high yields. As the industry advances in high volume manufacturing of 3x and 2x nm nodes with the associated advanced materials and complex structures, understanding and reducing film and critical dimension (CD) measurement uncertainty is more critical than ever. Optical film metrology is used for measurement of critical film parameters such as n & k, thickness and composition, while optical CD metrology is used for measurement of CD, sidewall angle (SWA), height, and other structure-related parameters. Both optical film and CD metrologies utilize advanced structure modeling that includes fitting parameters of the device stack for multiple layers simultaneously.

These methods have been proven and established in both R&D and high volume manufacturing scenarios. As film stacks and structures become more complex and design tolerances shrink, however, additional parameters need to be included in the modeling, in some cases leading to reduced parameter precision and unwanted parameter correlation. In this paper we discuss a new methodology, Data Feed Forward, that utilizes multiple metrology steps, and the feed forward of the derived parameters to next metrology steps, for improved measurement sensitivity and quality. In addition, we discuss Data Feed Forward requirements for fab-wide implementation.

Keywords: Scatterometry, Optical Metrology, Feed Forward, Measurement Uncertainty, Parameter Correlation

1. INTRODUCTION The advancement of semiconductor processes continuously brings new and exciting challenges for metrology technologies to measure, characterize, and monitor the critical process steps. With the shrinking physical size, process tolerance, and more complex and sophisticated materials and shapes, the need for accurate and precise metrology has become more critical than ever.

Optical CD and film metrology is widely adopted in high volume manufacturing for design nodes at 90 nm and below.

The need for higher precision, accuracy and more robust performance has become more and more critical. Optical metrology continues to be the preferred metrology solution because of its advantageous characteristics: (1) It provides a fast time to result compared to X-SEM, Transmission Electron Microscope (TEM) or AFM measurement; (2) It is nondestructive; and, (3) It is precise and has a small total measurement uncertainty (TMU)1,2,3.

In order to push the envelope on performance, novel and highly flexible measurement methods must be developed to complement the hardware and optical improvements, while not sacrificing the key advantages of optical metrology stated above.

In this paper, we first explore a measurement method called Data Feed Forward (DFF), briefly comparing it to another method called Multi Target Measurement (MTM). Secondly, we review several case studies that demonstrated the benefits of the DFF approach. Lastly, we conclude with a recommendation for future DFF development to extend its complementary benefits to enhance optical metrology solutions.

1.1 Optical metrology challenges and data feed forward approach The increasing complexity of advanced node materials and shapes is intensified by the shrinking process tolerance, resulting in many challenges for optical metrology.

*lanny.mihardja@kla-tencor.com; phone 1 408 875-3000; fax 1 408 875-4144; kla-tencor.com Metrology, Inspection, and Process Control for Microlithography XXVI, edited by Alexander Starikov, Proc. of SPIE Vol. 8324, 83241H 路 漏 2012 SPIE 路 CCC code: 0277-786X/12/$18 路 doi: 10.1117/12.916405

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These challenges are: (1) Complex 2D and 3D models that require a high number of floated parameters; (2) Strong parameter correlation; (3) Longer time to results due to long calculation time and multiple iterations required; and, (4) Measurement imprecision, inaccuracy, and unrepeatability. All these challenges are interconnected and intercompounding, where the presence of one would likely raise the severity of the others. For example, the more complex the 3D models that require a higher number of floated parameters, the higher the likelihood that two or more of those parameters have strong correlation with each other, and the longer the calculation time will take.

The concept of Data Feed Forward (DFF) is to optimize the unique sensitivity of different measurement steps, thus breaking parameter correlation, and improving measurement accuracy, precision, and stability. Of the top four challenges of optical metrology noted above, DFF will not directly improve all of them; however, it may indirectly improve them. Table 1 below lists how a DFF solution could affect the optical metrology challenges.

Table 1. Optical metrology challenges and how the DFF solution affects these challenges.

Top optical metrology challenges

Could DFF directly improve?

Complex 2D and 3D model that requires high number of floated parameters Strong parameter correlation

Yes

Long time to results due to long calculation time and multiple iterations Imprecision, inaccuracy, and unrepeatability

No. (It may improve indirectly) Yes

Yes

1.2 DFF and other optical metrology methods DFF is a capability to feed a measurement result from one process step forward to the next process step on the same wafer. The next process step does not need to be the immediate next and could be a few steps forward. In some cases, the feed forward may be on the same process step where a measurement result done on a target is fed forward to a measurement done on a different target of the same wafer. This method is also commonly known as feed sideways. In DFF, the measurement results could include film thickness, CD parameters, optical dispersion values (n & k), or other critical parameters. Figure 1 depicts the flow of the DFF method.

Figure 1. DFF method schematic.

There are known benefits and limitations of the DFF method for optical metrology. The known benefits are: (1) It enables layer ‘separation’ to reduce the number of floated parameters in a complex model; (2) It breaks parameter correlation and improves measurement accuracy; and, (3) It improves measurement precision and stability. The known limitations are: (1) It is limited only for process steps that do not change the physical or chemical properties of the previous layer, for example the DFF method would not be useful for any amorphous Si or poly going through higher temperature, or for any metals on Si or poly; and, (2) It is typically limited to single tool utilization; and, (3) Depending

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on how metrology measurements are implemented in the fab, the DFF method may add time to process flow due to measurement of the additional process steps.

Another known method that many commonly compare to DFF is Multi Target Measurement (MTM). In MTM, a multiple target measurement is done in a single process step, for example, a simultaneous measurement of a dense line grating target and an isolated (iso) line grating target on the same wafer. The basis of MTM is to utilize the unique sensitivity of different measurement targets at different wavelengths to break strong parameter correlation, thus improving measurement accuracy.

Both DFF and MTM are highly flexible and robust measurement methods targeted to optimize measurement sensitivity and break strong parameter correlation. Today, the initial decision to select either DFF or MTM mostly rely on a priori knowledge of the wafer and process. However, there are a few pointers that could be used to determine which method to use.

DFF is suitable for measuring parameters of interest that remain stable between process steps and are not significantly affected by processing. An example is the overall dielectric layer thickness that remains stable between pre- and postetch. DFF measurement is not affected by a process loading effect on different targets on the same wafer. On the other hand, MTM method floats all parameters of interest and not limited to only parameters that are stable between process steps. However, it may be affected by process loading effect on different targets on the same wafer and this may reduce the overall measurement sensitivity. In addition to these considerations, other factors such as the measurement time and the material availability may influence the decision on whether to use DFF or MTM.

2. CASE STUDIES AND RESULTS 2.1 Single tool DFF case studies In this section we will explore a variety of DFF case studies. All but one case are single tool use cases. In all cases, the DFF measurement method improved the final measurement quality as compared to the non-DFF method.

2.2 Examples and results Example 1: BEOL dielectric layer recess depth In this example, the critical parameter of interest is the recess depth of dielectric layer #3 as shown in Figure 2 below.

Background and problem statement: The original measurement approach without DFF was able to accurately measure the parameter of interest only within a limited range of thicknesses differences between layer #3, #4, and #5. When a larger thickness difference between these three layers was introduced, the measurement model reported an incorrect recess depth as verified by TEM. The root cause of the measurement inaccuracy was strong parameter correlation between layer #3 to #5. Layer #3 and #5 are dielectric layers and difficult to separate accurately within the measurement as they share very similar optical properties and layer #4 is a very thin contrast layer.

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Figure 2. BEOL original measurement model with strong parameter correlation that causes measurement inaccuracy.

Solution and result: The approach taken to solve this problem was to separate the layer measurement in order to break parameter correlation as shown in Figure 3. Layer #3 and #4 thicknesses were first measured and the result was then fed forward to solve for layer #5 thickness and the critical parameter of interest, layer #3 recess depth. The approach proved effective after TEM verification showed high TEM correlation for wide range of thickness differences between layers #3, #4, and #5. In further analysis, it was also verified that the measurement accuracy for each layer thickness was overall improved using the DFF method. Layer #3 and #5 thickness correlations to their process targets were higher in the DFF method than those of the original model without DFF as listed in Table 2.

Figure 3. BEOL dielectric layer recess depth measurement model using DFF successfully broke parameter correlation and resulted in high measurement accuracy.

Table 2. Further analysis of layer #3 and #5 correlation to the process targets showed improved measurement accuracy with DFF approach.

2

Analysis R original model Layer #3 thickness correlation to process targets 0.36 Layer #5 thickness correlation to process targets 0.73

2

R with DFF 1 0.98

Example 2: Trench depth and middle CD In this example, the critical parameters of interest are the trench depth and middle CD (MCD) as shown in Figure 4 below.

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Background and problem statement: In the original measurement approach, the trench depth measurement achieved high precision and accuracy, whereas the trench MCD had low precision. After model analysis, it was found that the trench MCD was highly correlated to dielectric layer #2 thickness, therefore leading to MCD measurement error.

Figure 4. Trench depth (TD) and MCD original model has strong parameter correlation causing measurement imprecision.

Solution and result: The approach taken to solve this problem was to separate the measurement before and after the trench etch step.

Dielectric layer #1 and #2 thicknesses were first measured then fed forward to solve for the trench depth and MCD after etch. The result achieved by the DFF method met the production monitoring requirement for the trench depth and MCD, as well as maintained the measurement performance for other parameters of interest.

Figure 5. Trench depth (TD) and MCD measurement model using DFF successfully broke parameter correlation and resulted in high measurement precision for all parameters of interest.

Example 3: High-k thickness and optical dispersion (n, k) Background and problem statement: In the original measurement approach, the precision and repeatability performance of high-k thickness and refractive index were poor, as shown in Figure 6. Precision is the 3-sigma calculation of 30 measurement repeats in a single wafer load cycle, whereas repeatability is a 3-sigma calculation of 10 wafer load cycles. Further analysis of the data showed high correlation between high-k thickness, high-k optical dispersion, and the underlayer SiO2 thickness.

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Figure 6. This stack measurement has strong parameter correlation between the current (high-k) and underlayer (SiO2) causing poor measurement results.

Solution and result: The approach taken to improve the high-k measurements is to first measure the SiO2 thickness and feed it forward to the next measurement to solve for high-k thickness and dispersion n, k. The result of the feed forward method much improved both the precision and repeatability of high-k film measurement.

Figure 7. The measurement model using DFF successfully broke parameter correlation and improved high-k measurements.

Example 4: High-k gauge repeatability and reproducibility (gauge R&R) Background and problem statement: In the original approach, a set of four design of experiment (DOE) wafers with varying high-k thicknesses were measured and the measurement results showed poor gauge repeatability and reproducibility (gauge R&R) performance.

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Figure 8. High-k DOE wafer measurements showed poor gauge R&R for varying high-k thicknesses.

Solution and result: The DFF method was used to first measure the SiO2 and SiN layer thicknesses which were then fed forward to solve for the high-k thickness. The result was much improved gauge R&R for all four DOE wafers.

Figure 9. The measurement model using DFF improved gauge R&R measurements for all DOE wafers.

Example 5: SiON gauge repeatability and reproducibility (gauge R&R) Background and problem statement: This case presented another marginal gauge R&R performance for SiON thickness measurement. The stack being measured consisted of SiN and SiON with an anisotropic layer in between them denoted by UZ. UZ is a modeled stack in which the optical dispersion in Z direction is different from that of in X and Y directions. The optical dispersion in X and Y directions are uniformly the same.

Figure 10. This stack showed poor gauge R&R measurement.

Solution and result: The DFF method was used to first measure the SiN and anisotropic layer thicknesses which were then fed forward to

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solve for SiON thickness. In this study, we also added a separate second measurement on another optical metrology tool of the same type. The intent was to compare the performance difference between single tool and multi tool DFF. In addition to the improved gauge R&R with the DFF approach, the result also showed comparable performance between single tool (tool #1 fed forward to tool #2) and multi tool (tool #1 fed forward to tool #2) feed forward methods for this example.

Figure 11. The measurement with DFF on both single tool and multi tool scenarios improved gauge R&R comparably.

3. DISCUSSION Single tool DFF is proven to be an effective and robust measurement method to improve the final measurement quality.

As explored in the last example, single tool DFF could potentially be extended to multi tool use cases where it will enable implementation and adoption in a fab wide environment. There are currently rather limited use cases of multi tool or inter tool DFF in a fab wide environment due to many reasons, from logistical to technical. A few known limitations had been discussed in the earlier section of this paper. A couple other common reasons are longer device cycle time due to the additional metrology steps needed and the unknown impact of tool fleet performance to the total measurement error. We would like to explore the last issue a bit further in this section. In the multi tool use case, the tool-to-tool matching allowance increases the overall measurement uncertainty as shown in the equation below (Figure 12). The impact of this variable into the total measurement uncertainty varies based on the applications and use cases. In some use cases it may be insignificant, whereas in others it may be significant enough to invalidate the final measurement. In order to implement multi tool DFF in a fab wide environment, the impact and propagation of the tool-to-tool matching allowance needs to be understood and addressed accordingly.

Figure 12. DFF total measurement uncertainty (FFU) of single and multi tool use cases.

4. CONCLUSION

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Data Feed Forward is one of the available methods to address the current challenges in optical metrology and improve the overall measurement quality for advanced semiconductor manufacturing applications. It effectively optimizes measurement sensitivity from the different measurement steps, thus breaking parameter correlation, improving accuracy, precision, and stability. While the benefits and limitations of the single tool DFF method are widely understood from existing use cases, the extension to multi tool use cases is still limited today. One of the reasons is insufficient experience and methodology to quantify and address the error propagation of the tool fleet matching allowance. Once the solution to this challenge is resolved, DFF could be successfully implemented in a fab-wide environment.

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[2] M.K. Lee et al, “Applications of AFM in semiconductor R&D and manufacturing at 45nm technology node and beyond”, Proc. of SPIE Vol. 7272, (2009).

[3] M. Sendelbach et al, “Comparison of scatterometry, atomic force microscope, dual beam system, and XSEM to measure etched via depths”, Proc. of SPIE Vol. 5752, p.272-287, (2005)

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