Scatterometer-based scanner fingerprinting technique(ScatterLith) and its applications in image field and ACLV analysis

Wang, Chang‐An; Zhang, Gary; DeMoor, Stephen J.; Boehm, Mark A.; Littau, Michael E.; Raymond, Christopher J.

doi:10.1117/12.485434

Cited by 4 publications

(7 citation statements)

References 1 publication

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“…Figure 2b compares typical model results with empirical data, as generated with and in-house lens fingerprinting technique [10], for two reference pitches at three lens positions. The agreement is quite good, especially considering the relative simplicity of the model.…”

Section: Methodsmentioning

confidence: 98%

Monte-Carlo-based analysis of local CD variation and application to establish realistic process and tool error budgets

Blatchford

Fruga

2004

SPIE Proceedings

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Local' critical dimension (CD) variations, defined in this paper as those that impact transistor gate lengths within a localized 2.5 mm X 2.5 mm area of a semiconductor device, are of most critical interest to circuit performance, as these errors determine critical path delays. However, these errors are difficult to quantify in the fab and historically have been neglected by the lithography community. We combine an empirically anchored response surface model with a Monte Carlo engine to examine in detail the variation in local CD error across a typical lens field and as a function of various process parameters. This methodology allows for the correct statistical treatment of systematic and random errors, and enables the separation of in-die and die-to-die CD variations (as the former impact yield much more than the latter). We demonstrate that local CD variation defines the space of allowable process errors to a much greater extent than acrosschip linewidth variation (ACLV) or die-to-die variation, and we use the output of the model to establish control limits for tool parameters for a candidate 90-nm-node alternating phase-shift gate process.

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Section: Methodsmentioning

confidence: 98%

Monte-Carlo-based analysis of local CD variation and application to establish realistic process and tool error budgets

Blatchford

Fruga

2004

SPIE Proceedings

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“…After ScatterLith reduces ACLV to ASLV, the majority of low order CD error contributors are excluded [12]. The remainder is higher order lens aberration and illuminator variation.…”

Section: A New Methodology To Characterize Aclvmentioning

confidence: 99%

“…In this study we demonstrate how much ACLV is attributed to imaging field variation by using Scatterlith step-by-step imaging field correction procedure [12]. In figure 5.1, best focus and ACLV are mapped across 13X5 exposure field locations.…”

Section: Imaging Field Characterizationmentioning

confidence: 99%

“…Scatterlith is a new scanner lens imaging field and ACLV characterization technique recently developed at Texas Instruments [12]. A full field micro-stepping test reticle is designed to perform this lens test.…”

Section: Scatterometer Based Scanner Lens Fingerpringting Technique (mentioning

confidence: 99%

“…In this paper we present a detailed characterization of ACLV performance of the latest ASML TWINSCAN AT1200B 193 scanner using Texas Instruments proprietary scatterometer based lens fingerprinting technique (ScatterLith) [12]. The scanner is equipped with on-aboard lens aberration measurement system ILIAS [11] and in-situ illuminator source profile measurement system.…”

Section: Introductionmentioning

confidence: 99%

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Characterization of ACLV for advanced technology nodes using scatterometer-based lens fingerprinting technique

et al. 2004

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Gate CD control is crucial to transistor fabrication for advanced technology nodes at and beyond 65 nm. ACLV (across chip linewidth variation) has been identified as a major contributor to overall CD budget for low k 1 lithography. In this paper, we present a detailed characterization of ACLV performance on the latest ASML scanner using Texas Instruments proprietary scatterometer based lens fingerprinting technique (ScatterLith). We are able to decompose a complex ACLV signature including patterns placed in both vertical and horizontal directions and trace the CD errors back to various scanner components such as lens aberrations, illumination source shape, dynamic image field, and scan synchronization. Lithography simulation plays an important role in bringing together the wafer and tool metrology for direct correlation and providing a quantitative understanding of pattern sensitivity to lens and illuminator errors for a particular process setup. A new ACLV characterization methodology is enabled by combining wafer metrology ScattereLith, scanner metrology and lithography simulation. Implementation of this methodology improves tool-to-tool matching and control on ACLV and V-H bias across multiple scanners to meet tight yield and speed requirements for advanced chip manufacturing.

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Comparison of solutions to the scatterometry inverse problem

Raymond

Littau

Chuprin³

et al. 2004

Metrology, Inspection, and Process Control for Microlithography XVIII

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Scatterometry is a novel optical metrology that has received considerable attention in the silicon industry in the past few years. Based on the analysis of light scattered from a periodic sample, scatterometry technology can be thought of as consisting of two parts known as the forward problem and the inverse problem. In the forward problem, a scatterometer "signature" is measured. The signature is simply the measured optical response of the scattering features to some incident illumination, like laser light. In the inverse problem, the signature is analyzed in order to determine the parameters (such as linewidth, thickness, profile, etc) of the scattering features. Typically a rigorous electrodynamic model is used in the solution to the inverse problem, but due to the complexity of the model there is no direct analytic solution. Instead, a variety of numerical methods to solve the inverse problem have been proposed and utilized.The earliest widely used method of solution to the inverse problem involved the generation of a "library" of scatter signatures corresponding to discrete parameter combinations of the structure being measured. Once the library was generated, it was then searched in order to determine the best match to the measured signature. The parameters of the best match were then reported as the parameters of the measured signature. As the technology matured, other methods such as model optimization techniques also emerged. In fact, a variety of alternate techniques have been explored and reported, but a general study comparing the results (and hence the strengths and weaknesses) of the various techniques has yet to be performed.In this research, we shall report results from using several different solutions to the inverse problem on two applications (patterned resist and etched poly). The solution methods shall include the classic library search method as well as three common optimization methods. The results will show that each technique has strengths and weaknesses. For example, the library search methods are generally the most robust but also the most time consuming, and the optimization methods, while fast, are prone to reporting a local but not global minima.

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Scatterometer-based scanner fingerprinting technique(ScatterLith) and its applications in image field and ACLV analysis

Cited by 4 publications

References 1 publication

Monte-Carlo-based analysis of local CD variation and application to establish realistic process and tool error budgets

Monte-Carlo-based analysis of local CD variation and application to establish realistic process and tool error budgets

Characterization of ACLV for advanced technology nodes using scatterometer-based lens fingerprinting technique

Comparison of solutions to the scatterometry inverse problem

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