Dr. Aron J. Cepler Profile

Dr. Aron J. Cepler

Application Scientist at Nova Measuring Instruments Inc

SPIE Involvement:

Author

Publications (27)

Proceedings Article | 27 April 2023 Presentation + Paper

TSV stress evolution mapping using in-line Raman spectroscopy

Stefan Schoeche, Daniel Schmidt, Marjorie Cheng, Aron Cepler, Abraham Arceo de la Pena, Jennifer Oakley

Proceedings Volume 12496, 124960D (2023) https://doi.org/10.1117/12.2658458

KEYWORDS: Annealing, Raman spectroscopy, Semiconducting wafers, Silicon, Metals, Copper, Oxides, Chemical mechanical planarization, Reactive ion etching, Phonons

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SPIE Journal Paper | 21 February 2023 Open Access

Spectral interferometry for fully integrated device metrology

Daniel Schmidt, Manasa Medikonda, Michael Rizzolo, Claire Silvestre, Julien Frougier, Andrew Greene, Mary Breton, Aron Cepler, Jacob Ofek, Itzik Kaplan, Roy Koret, Igor Turovets

JM3, Vol. 22, Issue 03, 031203, (February 2023) https://doi.org/10.1117/12.10.1117/1.JMM.22.3.031203

KEYWORDS: Metrology, Interferometry, Data modeling, Tunable filters, Semiconducting wafers, Scatterometry, Optical filters, Machine learning, Education and training, Dielectrics

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Proceedings Article | 8 June 2022 Presentation + Paper

Scatterometry-based methodologies for characterization of MRAM technology

M. Medikonda, D. Schmidt, M. Rizzolo, M. Breton, A. Dutta, H. Wu, E. Evarts, A. Cepler, R. Koret, I. Turovets, D. Edelstein

Proceedings Volume PC12053, PC120530J (2022) https://doi.org/10.1117/12.2614137

KEYWORDS: Metrology, Resistance, Critical dimension metrology, Chemical mechanical planarization, Logic, Data modeling, Instrument modeling, Scatterometry, Semiconducting wafers, Machine learning

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Proceedings Article | 26 May 2022 Presentation + Paper

Vertical travelling scatterometry for metrology on fully integrated devices

D. Schmidt, M. Medikonda, M. Rizzolo, C. Silvestre, J. Frougier, A. Greene, M. Breton, A. Cepler, J. Ofek, I. Kaplan, R. Koret, I. Turovets

Proceedings Volume 12053, 120530S (2022) https://doi.org/10.1117/12.2614077

KEYWORDS: Metrology, Semiconducting wafers, Scatterometry, Optical filters, Dielectrics, Data modeling, Back end of line, Front end of line, Chemical mechanical planarization, Transmission electron microscopy

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SPIE Journal Paper | 27 January 2022 Open Access

In-line Raman spectroscopy for gate-all-around nanosheet device manufacturing

Daniel Schmidt, Curtis Durfee, Juntao Li, Nicolas Loubet, Aron Cepler, Lior Neeman, Noga Meir, Jacob Ofek, Yonatan Oren, Daniel Fishman

JM3, Vol. 21, Issue 02, 021203, (January 2022) https://doi.org/10.1117/12.10.1117/1.JMM.21.2.021203

KEYWORDS: Silicon, Germanium, Raman spectroscopy, Optical lithography, Manufacturing, Semiconducting wafers, Polarization, Metrology, Raman scattering, Phonons

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Proceedings Article | 5 March 2021 Presentation + Paper

OCD enhanced: implementation and validation of spectral interferometry for nanosheet inner spacer indentation

D. Schmidt, C. Durfee, S. Pancharatnam, M. Medikonda, A. Greene, J. Frougier, A. Cepler, G. Belkin, D. Shafir, R. Koret, R. Shtainman, I. Turovets, S. Wolfling

Proceedings Volume 11611, 116111U (2021) https://doi.org/10.1117/12.2582364

KEYWORDS: Interferometry, Silicon, Metrology, Scatterometry, Reflectometry, Transmission electron microscopy, Semiconductor manufacturing, Reflectivity, Polarization control

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Proceedings Article | 25 February 2021 Presentation + Paper

In-line Raman spectroscopy for stacked nanosheet device manufacturing

D. Schmidt, C. Durfee, J. Li, N. Loubet, A. Cepler, L. Neeman, N. Meir, J. Ofek, Y. Oren, D. Fishman

Proceedings Volume 11611, 116111T (2021) https://doi.org/10.1117/12.2582181

KEYWORDS: Raman spectroscopy, Manufacturing, Metrology, Optical lithography, X-ray diffraction, Silicon, Nondestructive evaluation, Germanium, Diffraction, Transistors

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Proceedings Article | 4 May 2020 Presentation + Paper

Measuring local CD uniformity in EUV vias with scatterometry and machine learning

Dexin Kong, Daniel Schmidt, Jennifer Church, Chi-Chun Liu, Mary Breton, Cody Murray, Eric Miller, Luciana Meli, John Sporre, Nelson Felix, Ishtiaq Ahsan, Aron Cepler, Marjorie Cheng, Roy Koret, Igor Turovets

Proceedings Volume 11325, 113251I (2020) https://doi.org/10.1117/12.2551498

KEYWORDS: Scatterometry, Machine learning, Semiconducting wafers, Critical dimension metrology, Etching, Photoresist materials, Lithography, Metrology, Scatter measurement, Data modeling

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Proceedings Article | 2 July 2019 Presentation + Paper

Machine learning and hybrid metrology using scatterometry and LE-XRF to detect voids in copper lines

Dexin Kong, Koichi Motoyama, Abraham Arceo de la peña, Huai Huang, Brock Mendoza, Mary Breton, Gangadhara Raja Muthinti, Hosadurga Shobha, Liying Jiang, Juntao Li, James Demarest, John Gaudiello, Gauri Karve, Aron Cepler, Matthew Sendelbach, Susan Emans, Paul Isbester, Kavita Shah, Shay Wolfing, Avron Ger

Proceedings Volume 10959, 109590A (2019) https://doi.org/10.1117/12.2515257

KEYWORDS: Metrology, Machine learning, Scatterometry, Copper

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Proceedings Article | 5 September 2018 Presentation + Paper

In-line characterization of non-selective SiGe nodule defects with scatterometry enabled by machine learning

Dexin Kong, Robin Chao, Mary Breton, Chi-chun Liu, Gangadhara Raja Muthinti, Soon-cheon Seo, Nicolas Loubet, Pietro Montanini, John Gaudiello, Veeraraghavan Basker, Aron Cepler, Susan Ng-Emans, Matthew Sendelbach, Itzik Kaplan, Gilad Barak, Daniel Schmidt, Julien Frougier

Proceedings Volume 10585, 1058510 (2018) https://doi.org/10.1117/12.2297377

KEYWORDS: Scatterometry, Semiconducting wafers, Scanning electron microscopy, Machine learning, Metrology, Data modeling, Scatter measurement, Mathematical modeling, Transmission electron microscopy, Field effect transistors

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As device scaling continues, controlling defect densities on the wafer becomes essential for high volume manufacturing (HVM). One type of defect, the non-selective SiGe nodule, becomes more difficult to control during SiGe epitaxy (EPI) growth for p-type field effect transistor (pFET) source and drain. The process window for SiGe EPI growth with low nodule density becomes extremely tight due to the shrinking of contact poly pitch (CPP). Any tiny process shift or incoming structure shift could introduce a high density of nodules, which could affect device performance and yield. The current defect inspection method has a low throughput, so a fast and quantitative characterization technique is preferred for measuring and monitoring this type of defect. Scatterometry is a fast and non-destructive in-line metrology technique. In this work, novel methods were developed to accurately and comprehensively measure the SiGe nodules with scatterometry information. Top-down critical dimension scanning electron microscopy (CD-SEM) images were collected and analyzed on the same location as scatterometry measurement for calibration. Machine learning (ML) algorithms are used to analyze the correlation between the raw spectra and defect density and area fraction. The analysis showed that the defect density and area fractions can be measured separately by correlating intensity variations. In addition to the defect density and area fraction, we also investigate a novel method – model-based scatterometry hybridized with machine learning capabilities – to quantify the average height of the defects along the sidewall of the gate. Hybridizing the machine learning method with the model-based one could also eliminate the possibility of misinterpreting the defect as some structural parameters. Furthermore, cross-sectional TEM and SEM measurement are used to calibrate the model-based scatterometry results. In this work, the correlation between the SiGe nodule defects and the structural parameters of the device is also studied. The preliminary result shows that there is strong correlation between the defect density and spacer thickness. Correlations between the defect density and the structural parameters provides useful information for process engineers to optimize the EPI growth process. With the advances in the scatterometry-based defect measurement metrology, we demonstrate such fast, quantitative, and comprehensive measurement of SiGe nodule defects can be used to improve the throughput and yield.

Proceedings Article | 19 March 2018 Presentation

Novel hybrid metrology for process integration of gate all around (GAA) devices (Conference Presentation)

Gangadhara Muthinti, Nicolas Loubet, Robinhsinkuo Chao, Abraham Arceo De La Pena, Dexin Kong, Juntao Li, Brock Mendoza, Veeraraghavan Basker, Tenko Yamashita, John Gaudiello, Matthew Sendelbach, Aron Cepler, Susan Ng-Emans, Gilad Barak, Wei Ti Lee

Proceedings Volume 10585, 105850Z (2018) https://doi.org/10.1117/12.2297500

KEYWORDS: Metrology, Gallium arsenide, Etching, Silicon, Measurement devices, Geometrical optics, X-ray fluorescence spectroscopy, Semiconductors, Nanolithography

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Proceedings Article | 12 April 2017 Presentation + Paper

Electrical test prediction using hybrid metrology and machine learning

Mary Breton, Robin Chao, Gangadhara Raja Muthinti, Abraham de la Peña, Jacques Simon, Aron Cepler, Matthew Sendelbach, John Gaudiello, Susan Emans, Michael Shifrin, Yoav Etzioni, Ronen Urenski, Wei Ti Lee

Proceedings Volume 10145, 1014504 (2017) https://doi.org/10.1117/12.2261091

KEYWORDS: Copper, Metrology, Resistance, Machine learning, Metals, Back end of line, Semiconducting wafers, Scatterometry, X-rays, Process control

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Electrical test measurement in the back-end of line (BEOL) is crucial for wafer and die sorting as well as comparing intended process splits. Any in-line, nondestructive technique in the process flow to accurately predict these measurements can significantly improve mean-time-to-detect (MTTD) of defects and improve cycle times for yield and process learning. Measuring after BEOL metallization is commonly done for process control and learning, particularly with scatterometry (also called OCD (Optical Critical Dimension)), which can solve for multiple profile parameters such as metal line height or sidewall angle and does so within patterned regions. This gives scatterometry an advantage over inline microscopy-based techniques, which provide top-down information, since such techniques can be insensitive to sidewall variations hidden under the metal fill of the trench. But when faced with correlation to electrical test measurements that are specific to the BEOL processing, both techniques face the additional challenge of sampling. Microscopy-based techniques are sampling-limited by their small probe size, while scatterometry is traditionally limited (for microprocessors) to scribe targets that mimic device ground rules but are not necessarily designed to be electrically testable. A solution to this sampling challenge lies in a fast reference-based machine learning capability that allows for OCD measurement directly of the electrically-testable structures, even when they are not OCD-compatible. By incorporating such direct OCD measurements, correlation to, and therefore prediction of, resistance of BEOL electrical test structures is significantly improved. Improvements in prediction capability for multiple types of in-die electrically-testable device structures is demonstrated. To further improve the quality of the prediction of the electrical resistance measurements, hybrid metrology using the OCD measurements as well as X-ray metrology (XRF) is used. Hybrid metrology is the practice of combining information from multiple sources in order to enable or improve the measurement of one or more critical parameters. Here, the XRF measurements are used to detect subtle changes in barrier layer composition and thickness that can have second-order effects on the electrical resistance of the test structures. By accounting for such effects with the aid of the X-ray-based measurements, further improvement in the OCD correlation to electrical test measurements is achieved. Using both types of solution incorporation of fast reference-based machine learning on nonOCD-compatible test structures, and hybrid metrology combining OCD with XRF technology improvement in BEOL cycle time learning could be accomplished through improved prediction capability.

Proceedings Article | 31 March 2017 Paper

Materials characterization for process integration of multi-channel gate all around (GAA) devices

Gangadhara Raja Muthinti, Nicolas Loubet, Robin Chao, Abraham de la Peña, Juntao Li, Michael Guillorn, Tenko Yamashita, Sivananda Kanakasabapathy, John Gaudiello, Aron Cepler, Matthew Sendelbach, Susan Emans, Shay Wolfling, Avron Ger, Daniel Kandel, Roy Koret, Wei Ti Lee, Peter Gin, Kevin Matney, Matthew Wormington

Proceedings Volume 10145, 101451U (2017) https://doi.org/10.1117/12.2261377

KEYWORDS: Germanium, Silicon, Diffractive optical elements, Gallium arsenide, Semiconducting wafers, Etching, Solids, X-ray diffraction, X-ray fluorescence spectroscopy, Materials processing

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Proceedings Article | 28 March 2017 Presentation + Paper

Complex metrology on 3D structures using multi-channel OCD

Taher Kagalwala, Sridhar Mahendrakar, Alok Vaid, Paul Isbester, Aron Cepler, Charles Kang, Naren Yellai, Matthew Sendelbach, Mihael Ko, Ovadia Ilgayev, Yinon Katz, Lilach Tamam, Ilya Osherov

Proceedings Volume 10145, 101451C (2017) https://doi.org/10.1117/12.2261419

KEYWORDS: 3D metrology, Metrology, Thin films, Process control, Scatterometry, Thin film devices, Semiconducting wafers, Photomasks, Chemical species, Dielectrics, Transmission electron microscopy, Diffractive optical elements, Solids, Channel projecting optics, Etching

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SPIE Journal Paper | 25 October 2016

Measuring self-aligned quadruple patterning pitch walking with scatterometry-based metrology utilizing virtual reference

Taher Kagalwala, Alok Vaid, Sridhar Mahendrakar, Michael Lenahan, Fang Fang, Paul Isbester, Michael Shifrin, Yoav Etzioni, Aron Cepler, Naren Yellai, Prasad Dasari, Cornel Bozdog

JM3, Vol. 15, Issue 04, 044004, (October 2016) https://doi.org/10.1117/12.10.1117/1.JMM.15.4.044004

KEYWORDS: Semiconducting wafers, Metrology, Optical lithography, Scatterometry, Critical dimension metrology, Finite element methods, Scatter measurement, Diffractive optical elements, Transmission electron microscopy, Reactive ion etching

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Proceedings Article | 30 March 2016 Paper

Advanced in-line metrology strategy for self-aligned quadruple patterning

Robin Chao, Mary Breton, Benoit L'herron, Brock Mendoza, Raja Muthinti, Florence Nelson, Abraham De La Pena, Fee li Le, Eric Miller, Stuart Sieg, James Demarest, Peter Gin, Matthew Wormington, Aron Cepler, Cornel Bozdog, Matthew Sendelbach, Shay Wolfling, Tom Cardinal, Sivananda Kanakasabapathy, John Gaudiello, Nelson Felix

Proceedings Volume 9778, 977813 (2016) https://doi.org/10.1117/12.2220601

KEYWORDS: Critical dimension metrology, Metrology, Transmission electron microscopy, Optical lithography, Semiconducting wafers, Etching, Process control, Scatterometry, Reactive ion etching, Diffractive optical elements

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Self-Aligned Quadruple Patterning (SAQP) is a promising technique extending the 193-nm lithography to manufacture structures that are 20nm half pitch or smaller. This process adopts multiple sidewall spacer image transfers to split a rather relaxed design into a quarter of its original pitch. Due to the number of multiple process steps required for the pitch splitting in SAQP, the process error propagates through each deposition and etch, and accumulates at the final step into structure variations, such as pitch walk and poor critical dimension uniformity (CDU). They can further affect the downstream processes and lower the yield. The impact of this error propagation becomes significant for advanced technology nodes when the process specifications of device design CD requirements are at nanometer scale. Therefore, semiconductor manufacturing demands strict in-line process control to ensure a high process yield and improved performance, which must rely on precise measurements to enable corrective actions and quick decision making for process development. This work aims to provide a comprehensive metrology solution for SAQP.

During SAQP process development, the challenges in conventional in-line metrology techniques start to surface. For instance, critical-dimension scanning electron microscopy (CDSEM) is commonly the first choice for CD and pitch variation control. However, it is found that the high aspect ratio at mandrel level processes and the trench variations after etch prevent the tool from extracting the true bottom edges of the structure in order to report the position shift. On the other hand, while the complex shape and variations can be captured with scatterometry, or optical CD (OCD), the asymmetric features, such as pitch walk, show low sensitivity with strong correlations in scatterometry. X-ray diffraction (XRD) is known to provide useful direct measurements of the pitch walk in crystalline arrays, yet the data analysis is influenced by the incoming geometry and must be used carefully.

A successful implementation of SAQP process control for yield improvement requires the metrology issues to be addressed. By optimizing the measurement parameters and beam configurations, CDSEM measurements distinguish each of the spaces corresponding to the upstream mandrel processes and report their CDs separately to feed back to the process team for the next development cycle. We also utilize the unique capability in scatterometry to measure the structure details in-line and implement a “predictive” process control, which shows a good correlation between the “predictive” measurement and the cross-sections from our design of experiments (DOE). The ability to measure the pitch walk in scatterometry was also demonstrated. This work also explored the frontier of in-line XRD capability by enabling an automatic RSM fitting on tool to output pitch walk values. With these advances in metrology development, we are able to demonstrate the impacts of in-line monitoring in the SAQP process, to shorten the patterning development learning cycle to improve the yield.

Proceedings Article | 29 March 2016 Paper

Advanced in-line optical metrology of sub-10nm structures for gate all around devices (GAA)

Raja Muthinti, Nicolas Loubet, Robin Chao, John Ott, Michael Guillorn, Nelson Felix, John Gaudiello, Parker Lund, Aron Cepler, Matthew Sendelbach, Oded Cohen, Shay Wolfling, Cornel Bozdog, Mark Klare

Proceedings Volume 9778, 977810 (2016) https://doi.org/10.1117/12.2220379

KEYWORDS: Nanowires, Silicon, Germanium, Metrology, Gallium arsenide, Optical lithography, Scatterometry, Metals, Semiconducting wafers, Multilayers

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Proceedings Article | 24 March 2016 Paper

Scatterometry-based metrology for SAQP pitch walking using virtual reference

Taher Kagalwala, Alok Vaid, Sridhar Mahendrakar, Michael Lenahan, Fang Fang, Paul Isbester, Michael Shifrin, Yoav Etzioni, Aron Cepler, Naren Yellai, Prasad Dasari, Cornel Bozdog

Proceedings Volume 9778, 97781W (2016) https://doi.org/10.1117/12.2228329

KEYWORDS: Transmission electron microscopy, Metrology, Optical lithography, Scatterometry, Reactive ion etching, Etching, Semiconducting wafers, Diffractive optical elements, Critical dimension metrology, Scatter measurement

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Proceedings Article | 19 March 2015 Paper

Scatterometry-based defect detection for DSA in-line process control

Robin Chao, Chi-Chun Liu, Cornel Bozdog, Aron Cepler, Matthew Sendelbach, Oded Cohen, Shay Wolfling, Todd Bailey, Nelson Felix

Proceedings Volume 9424, 942419 (2015) https://doi.org/10.1117/12.2087093

KEYWORDS: Defect detection, Scatterometry, Semiconducting wafers, Scanning electron microscopy, Process control, Inspection, Metrology, Optical lithography, Image analysis, Directed self assembly

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Proceedings Article | 2 April 2014 Paper

Novel metrology methods for fast 3D characterization of directed self-assembly (DSA) patterns for high volume manufacturing

Chandra Sarma, Benjamin Bunday, Aron Cepler, Ted Dziura, JiHoon Kim, Guanyang Lin, Jian Yin

Proceedings Volume 9050, 90500O (2014) https://doi.org/10.1117/12.2046785

KEYWORDS: Semiconducting wafers, Scatterometry, Metrology, Polymethylmethacrylate, Bridges, Data modeling, Critical dimension metrology, Picosecond phenomena, Line edge roughness, Directed self assembly

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Proceedings Article | 2 April 2014 Paper

CD-SEM metrology for sub-10nm width features

Benjamin Bunday, Aron Cepler, Aaron Cordes, Abraham Arceo

Proceedings Volume 9050, 90500T (2014) https://doi.org/10.1117/12.2047099

KEYWORDS: Metrology, Scanning electron microscopy, Silicon, Image resolution, Edge detection, Detection and tracking algorithms, Lawrencium, 3D metrology, Optical simulations, Critical dimension metrology

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Proceedings Article | 10 April 2013 Paper

In-line E-beam wafer metrology and defect inspection: the end of an era for image-based critical dimensional metrology? New life for defect inspection

Eric Solecky, Oliver Patterson, Andrew Stamper, Erin McLellan, Ralf Buengener, Alok Vaid, Carsten Hartig, Benjamin Bunday, Abraham Arceo, Aron Cepler

Proceedings Volume 8681, 86810D (2013) https://doi.org/10.1117/12.2010007

KEYWORDS: Metrology, Defect inspection, Inspection, Ion beams, Semiconducting wafers, Scanning electron microscopy, Manufacturing, Dimensional metrology, 3D metrology, Critical dimension metrology

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Metrology measurement and defect inspection steps in routes are more pervasive than many people realize and the number continues to grow. Digging deeper, it turns out that E-beam metrology and defect inspection tools typically occupy the most overall steps and therefore are extremely critical tools for semiconductor development and manufacturing. The Critical Dimension Scanning Electron Microscope (CDSEM) is an E-beam tool responsible for image-based structural metrology measurements while the E-beam review (EBR) and E-beam inspection (EBI) tools are responsible for defect inspection. The CDSEM faces significant future challenges in a world where device architectures are changing (as with the FinFET device), increasing the need for more structural measurement parameters such as sidewall angle, height and undercut, than the CDSEM can deliver. These applications are now migrating to scattering-based tools, also referred to as model- or computational-based structural metrology techniques. We explore the history of the CDSEM, the key fundamental limits (primarily resolution) of the CDSEM preventing it from capturing these applications and assess if an image-based structural metrology tool is still needed given the niche that scattering tools are filling. The answer is yes. Next we discuss whether the CDSEM will eventually meet those needs or if other alternative solutions are needed. Lastly, we discuss an industry survey on which image-based technique holds the most promise to solve these challenges. Regarding defect inspection, resolution is also a concern for the applications that need to detect extremely small defects which current optical-based Brightfield tools cannot address. While resolution is a primary concern in structural metrology, current EBI and EBR tools possess the resolution needed for defect inspection and have extendibility through at least the next advanced technology node. We also explore the niche E-beam is filling in defect inspection, evaluate the idea that a better synergistic solution exists today between the CDSEM and the EBI tools and propose a future E-beam landscape where E-beam tool variety in future fabs is significantly reduced to enhance productivity.

Proceedings Article | 10 April 2013 Paper

Gaps analysis for CD metrology beyond the 22nm node

Benjamin Bunday, Thomas Germer, Victor Vartanian, Aaron Cordes, Aron Cepler, Charles Settens

Proceedings Volume 8681, 86813B (2013) https://doi.org/10.1117/12.2012472

KEYWORDS: Critical dimension metrology, Metrology, Scanning helium ion microscopy, 3D metrology, Silicon, Image resolution, Etching, Scanning electron microscopy, Oxides

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Proceedings Article | 10 April 2013 Paper

Photoresist shrinkage effects in 16 nm node extreme ultraviolet (EUV) photoresist targets

Benjamin Bunday, Cecilia Montgomery, Warren Montgomery, Aron Cepler

Proceedings Volume 8681, 86810J (2013) https://doi.org/10.1117/12.2012470

KEYWORDS: Photoresist materials, Extreme ultraviolet lithography, Data modeling, Metrology, Scanning electron microscopy, Semiconducting wafers, Extreme ultraviolet, Lithography, Electron beams, Systems modeling

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Photoresist shrinkage (i.e., line slimming) is an important systematic uncertainty source in critical dimension-scanning electron microscope (CD-SEM) metrology of lithographic features [1] [2] [3] [4] [5]. It influences both the precision and the accuracy of CD-SEM measurements, while locally damaging the sample. Minimization or elimination of shrinkage is desirable, yet elusive. This error source will be a factor in CD-SEM metrology on polymer materials in EUV lithography. Recent work has demonstrated improved understanding of the trends in the shrinkage response depending on electron beam and target parameters in static measurements [2] [3] [4] [5] [6]. Some research has highlighted a second mode of shrinkage that is apparent over time and progresses as a function of time between consecutive measurements, a form of “dynamic shrinkage” that appears to be activated by electron beam, in which the activated feature perpetually and logarithmically shrinks [7] [8]. Another work has demonstrated that as pitches continue to get smaller with resulting reductions in spaces between lines, charging may emerge as an additional, competing, unpredictable error source for CD-SEM metrology on dense photoresist features, an issue that is predicted to become more common as these spaces become more confined [9]. In this work, we explore the static shrinkage behaviors of various EUV photoresists into the 16 nm half-pitch node, with samples generated using the advanced EUV lithography capable of generating such tight pitches [10]. Dynamic shrinkage behavior was explored on these materials last year [15]. The static shrinkage behaviors will be validated to show compliance with the SEMATECH shrinkage model [5] [6] on small EUV resist features. Using the results of the model fits, a simulation study will predict the shrinkage trends at future nodes. Further studies will confirm whether or not charging phenomena are observable, and the beginning of a charging simulation study will be discussed.

Proceedings Article | 14 May 2012 Paper

Improving the performance of the critical dimension-scanning electron microscope with the contrast transfer function

Aron Cepler, Bradley Thiel

Proceedings Volume 8378, 83780T (2012) https://doi.org/10.1117/12.919293

KEYWORDS: Contrast transfer function, Spatial frequencies, Scanning electron microscopy, Microscopes, Imaging systems, Electron microscopes, Fourier transforms, Lithography, Semiconducting wafers, Spatial resolution

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Proceedings Article | 5 April 2012 Paper

Scanning electron microscopy imaging of ultra-high aspect ratio hole features

Aron Cepler, Benjamin Bunday, Bradley Thiel, John Villarrubia

Proceedings Volume 8324, 83241N (2012) https://doi.org/10.1117/12.916552

KEYWORDS: Particles, Electrons, Signal detection, Scanning electron microscopy, Silicon, Copper, Selenium, Metrology, Interference (communication), Oxides

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Proceedings Article | 23 March 2012 Paper

Effect of radiation on the defectivity and stability of Ru-capped MoSi multilayer blanks

Abbas Rastegar, Göksel Durkaya, Aron Cepler, Matt House, Steve Novak

Proceedings Volume 8322, 832211 (2012) https://doi.org/10.1117/12.916631

KEYWORDS: Ruthenium, Silicon, Extreme ultraviolet, Extreme ultraviolet lithography, Reflectivity, Photomasks, Oxides, Radiation effects, Scanning probe microscopy, Oxidation

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