Pub Date : 2023-11-12DOI: 10.31399/asm.cp.istfa2023p0432
Susan Li, John Frame, Edita Madriaga-Berry, Jose Hulog, Ming Zhang, Masako Terada, Allen Gu, David Taraci
Abstract In this work we present a new defect localization capability on Wafer Level Chip Scale Packages (WLCSP) with small-scale Cu pillars using advanced 3D X-ray microscopy (XRM). In comparison to conventional microcomputed tomography (Micro-CT or microCT) flat-panel technology, the synchrotron-based optically enhanced 3D X-ray microscopy can detect very small defects with submicron resolutions. Two case studies on actual failures (one from the assembly process and one from reliability testing) will be discussed to demonstrate this powerful defect localization technique. Using the tool has helped speed up the failure analysis (FA) process by locating the defects non-destructively in a matter of hours instead of days or weeks as needed with destructive physical failure analysis.
{"title":"Detecting Wafer Level Cu Pillar Defects Using Advanced 3D X-ray Microscopy (XRM) with Submicron Resolution","authors":"Susan Li, John Frame, Edita Madriaga-Berry, Jose Hulog, Ming Zhang, Masako Terada, Allen Gu, David Taraci","doi":"10.31399/asm.cp.istfa2023p0432","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2023p0432","url":null,"abstract":"Abstract In this work we present a new defect localization capability on Wafer Level Chip Scale Packages (WLCSP) with small-scale Cu pillars using advanced 3D X-ray microscopy (XRM). In comparison to conventional microcomputed tomography (Micro-CT or microCT) flat-panel technology, the synchrotron-based optically enhanced 3D X-ray microscopy can detect very small defects with submicron resolutions. Two case studies on actual failures (one from the assembly process and one from reliability testing) will be discussed to demonstrate this powerful defect localization technique. Using the tool has helped speed up the failure analysis (FA) process by locating the defects non-destructively in a matter of hours instead of days or weeks as needed with destructive physical failure analysis.","PeriodicalId":20443,"journal":{"name":"Proceedings","volume":"97 18","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136353180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-12DOI: 10.31399/asm.cp.istfa2023p0448
Mario Wolf, Bugra Birki, Peter Hoffrogge, Peter Czurratis, Chaitanya Bakre, Mario Pacheco, Deepak Goyal
Abstract This paper investigates the enhanced inspection of High Bandwidth Memory (HBM) stacks using Scanning Acoustic Microscopy (SAM). As the multi-layer structure is quite complex, sophisticated signal processing methods are employed. To improve detection capabilities and inspection time, the Synthetic Aperture Focusing Technique (SAFT) is utilized. In contrast to previous trials applying SAFT on SAM data, this contribution introduces Near Field SAFT. Reconstruction is also performed for layers between the transducer and its focus, in the near field of the transducer. This approach allows for measurements with common working distances, providing higher frequencies and improved resolution. Systematic evaluations are conducted on various measurement setups and transducers with different center frequencies and focal lengths in order to determine the most optimal measurement setup.
{"title":"Near-Field Synthetic Aperture Focusing Technique to Enhance the Inspection Capability of Multi-Layer HBM Stacks in Scanning Acoustic Microscopy","authors":"Mario Wolf, Bugra Birki, Peter Hoffrogge, Peter Czurratis, Chaitanya Bakre, Mario Pacheco, Deepak Goyal","doi":"10.31399/asm.cp.istfa2023p0448","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2023p0448","url":null,"abstract":"Abstract This paper investigates the enhanced inspection of High Bandwidth Memory (HBM) stacks using Scanning Acoustic Microscopy (SAM). As the multi-layer structure is quite complex, sophisticated signal processing methods are employed. To improve detection capabilities and inspection time, the Synthetic Aperture Focusing Technique (SAFT) is utilized. In contrast to previous trials applying SAFT on SAM data, this contribution introduces Near Field SAFT. Reconstruction is also performed for layers between the transducer and its focus, in the near field of the transducer. This approach allows for measurements with common working distances, providing higher frequencies and improved resolution. Systematic evaluations are conducted on various measurement setups and transducers with different center frequencies and focal lengths in order to determine the most optimal measurement setup.","PeriodicalId":20443,"journal":{"name":"Proceedings","volume":"97 17","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136353181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-12DOI: 10.31399/asm.cp.istfa2023p0420
Branden Long, Yang Su, Yunfei Wang, Christopher Morgan, Md Faisal Kabir, Ramya Padmanaban, Weston Hearne, Tad Daniel
Abstract We have identified a method for nanoprobing CMOS circuits at MHz frequencies using the same hardware already used for single transistor pulsing applications. In this paper we show example responses and failure isolation examples for both sequential and combinational logic cells and discuss the test setup and sample prep that were used to successfully collect the responses.
{"title":"Nanoprobing for Logical Cell Operational Tests","authors":"Branden Long, Yang Su, Yunfei Wang, Christopher Morgan, Md Faisal Kabir, Ramya Padmanaban, Weston Hearne, Tad Daniel","doi":"10.31399/asm.cp.istfa2023p0420","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2023p0420","url":null,"abstract":"Abstract We have identified a method for nanoprobing CMOS circuits at MHz frequencies using the same hardware already used for single transistor pulsing applications. In this paper we show example responses and failure isolation examples for both sequential and combinational logic cells and discuss the test setup and sample prep that were used to successfully collect the responses.","PeriodicalId":20443,"journal":{"name":"Proceedings","volume":"98 21","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136353332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-12DOI: 10.31399/asm.cp.istfa2023p0393
Jay Anderson, Michael K. F. Lo, Eoghan P. Dillon, Mustafa Kansiz
Abstract Failure analysis of small contamination at the surface and sub-surface interface represents a major set of common microelectronics and semiconductor issues. The application of O-PTIR spectroscopy analyses provides flexibility to sample preparation and improves sensitivity to very small levels of contamination even below <1 micron in layers or particles on or just below the surface. The detection of this contamination can be limited if only bright field imaging is used to contrast the region of interest (ROI) and the surrounding structure. Adding fluorescence microscopy is an additional imaging technique that adds another layer of chemical specificity and provides locations of unseen ROI’s for additional IR and Raman spectral analysis.
{"title":"Expanding Failure Analysis Using Fluorescence Combined with IR and Raman","authors":"Jay Anderson, Michael K. F. Lo, Eoghan P. Dillon, Mustafa Kansiz","doi":"10.31399/asm.cp.istfa2023p0393","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2023p0393","url":null,"abstract":"Abstract Failure analysis of small contamination at the surface and sub-surface interface represents a major set of common microelectronics and semiconductor issues. The application of O-PTIR spectroscopy analyses provides flexibility to sample preparation and improves sensitivity to very small levels of contamination even below &lt;1 micron in layers or particles on or just below the surface. The detection of this contamination can be limited if only bright field imaging is used to contrast the region of interest (ROI) and the surrounding structure. Adding fluorescence microscopy is an additional imaging technique that adds another layer of chemical specificity and provides locations of unseen ROI’s for additional IR and Raman spectral analysis.","PeriodicalId":20443,"journal":{"name":"Proceedings","volume":"98 18","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136353335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-12DOI: 10.31399/asm.cp.istfa2023p0085
Joana Mae De Jesus, Mark Anthony Acedillo
Abstract Failure localization is one of the vital processes in the field of failure analysis. However, as newer fabrication processes emerge and demand for smaller transistors keeps on increasing, the complexity of failure analysis fault isolation involving micro-probing also increases along with the challenges on fault isolation equipment such as limited magnification and susceptibility to vibrations. In this paper, the capability of Focused Ion Beam (FIB) to perform circuit edit was utilized along with Avalon CAD navigation to pinpoint the location of the defects without the need of micro-probing while doing fault isolation. Results showed that through this technique, physical defect locations were successfully identified in three different case studies.
{"title":"Failure Localization Technique for Metal and Transistor Defects Through Avalon CAD Navigation and Focused Ion Beam Circuit Edit","authors":"Joana Mae De Jesus, Mark Anthony Acedillo","doi":"10.31399/asm.cp.istfa2023p0085","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2023p0085","url":null,"abstract":"Abstract Failure localization is one of the vital processes in the field of failure analysis. However, as newer fabrication processes emerge and demand for smaller transistors keeps on increasing, the complexity of failure analysis fault isolation involving micro-probing also increases along with the challenges on fault isolation equipment such as limited magnification and susceptibility to vibrations. In this paper, the capability of Focused Ion Beam (FIB) to perform circuit edit was utilized along with Avalon CAD navigation to pinpoint the location of the defects without the need of micro-probing while doing fault isolation. Results showed that through this technique, physical defect locations were successfully identified in three different case studies.","PeriodicalId":20443,"journal":{"name":"Proceedings","volume":"98 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136353346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-12DOI: 10.31399/asm.cp.istfa2023p0160
Alexander Maggiacomo, Rabindra Pahari, Torsten Schaefer, Gregory Billus, Suresh Shekar, Satish Kodali, Felix Beaudoin, Aaron Sinnott
Abstract Physical Failure Analysis (PFA) is essential for SRAM yield learning, especially in new technologies or FAB transfers. For this to be successful, physical coordinates for tested bitcell failures must be accurately calculated and verified. The timeline for this process can vary dramatically based on the extent and complexity of any issues. This paper details the successful use of fault localization on isolated, voltage sensitive failures to achieve confidence in verification of physical location prior to PFA.
{"title":"Logical to Physical SRAM Bitmap Verification with Fault Localization","authors":"Alexander Maggiacomo, Rabindra Pahari, Torsten Schaefer, Gregory Billus, Suresh Shekar, Satish Kodali, Felix Beaudoin, Aaron Sinnott","doi":"10.31399/asm.cp.istfa2023p0160","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2023p0160","url":null,"abstract":"Abstract Physical Failure Analysis (PFA) is essential for SRAM yield learning, especially in new technologies or FAB transfers. For this to be successful, physical coordinates for tested bitcell failures must be accurately calculated and verified. The timeline for this process can vary dramatically based on the extent and complexity of any issues. This paper details the successful use of fault localization on isolated, voltage sensitive failures to achieve confidence in verification of physical location prior to PFA.","PeriodicalId":20443,"journal":{"name":"Proceedings","volume":"99 19","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136353483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract It has been a challenge to perform failure analysis for miniaturization of process node technology in high-speed transceiver. Failure analysis plays an important role in root cause analysis to enable R&D, product quality & reliabily improvement. This paper demonstrated an effective FA approach on a real case with ADPLL functional failure within a high-Speed transceiver in complex sub-nano FPGA. This successful case is achieved by incorporating Analog Probe (APROBE), Infrared Emission Microscopy (IREM), extensive layout study, delayering, Nanoprobing and Scanning Electron Microscopy (SEM) for defect localization.
{"title":"Effective Fault Localization Approach for High Speed Transceiver Failure: From Non-destructive to Destructive","authors":"Kuan Lai Khei, Liew Chiun Ning, Goh Lay Lay, Wu Jia Jun, Sailesh Suthar","doi":"10.31399/asm.cp.istfa2023p0190","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2023p0190","url":null,"abstract":"Abstract It has been a challenge to perform failure analysis for miniaturization of process node technology in high-speed transceiver. Failure analysis plays an important role in root cause analysis to enable R&D, product quality & reliabily improvement. This paper demonstrated an effective FA approach on a real case with ADPLL functional failure within a high-Speed transceiver in complex sub-nano FPGA. This successful case is achieved by incorporating Analog Probe (APROBE), Infrared Emission Microscopy (IREM), extensive layout study, delayering, Nanoprobing and Scanning Electron Microscopy (SEM) for defect localization.","PeriodicalId":20443,"journal":{"name":"Proceedings","volume":"99 18","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136353484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-12DOI: 10.31399/asm.cp.istfa2023p0370
Melissa Mullen, Mark McClendon, Adam Stokes, Xiaoting Gu, Pete Carleson
Abstract Continued advancements in the architecture of 3D packaging have increased the challenges in fault isolation and failure analysis (FA), often requiring complex correlative workflows and multiple inference-based methods before targeted root cause analysis (RCA) can be performed. Furthermore, 3D package components such as through-silicon-vias (TSVs) and micro-bumps require sub-surface structural characterization and metrology to aid in process monitoring and development throughout fabrication and integration. Package road-mapping has also called for increased die stacking with decreased pitch, TSV size, and die thickness, and thus requires increased accuracy and precision of various stateof- the-art analytical techniques in the near future. Physical failure analysis (PFA), process monitoring, and process development will therefore depend on reliable, high-resolution data directly measured at the region of interest (ROI) to meet the complexity and scaling challenges. This paper explores the successful application of plasma-FIB (PFIB)/SEM techniques in 2D and 3D regimes and introduces diagonal serial sectioning at package scales as a novel approach for PFA and metrology. Both 2D and 3D analysis will be demonstrated in a high bandwidth memory (HBM) package case-study which can be applied more broadly in 3D packaging.
{"title":"2D and 3D Metrology and Failure Analysis for High Bandwidth Memory Package by Xe and Ar Plasma-FIB","authors":"Melissa Mullen, Mark McClendon, Adam Stokes, Xiaoting Gu, Pete Carleson","doi":"10.31399/asm.cp.istfa2023p0370","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2023p0370","url":null,"abstract":"Abstract Continued advancements in the architecture of 3D packaging have increased the challenges in fault isolation and failure analysis (FA), often requiring complex correlative workflows and multiple inference-based methods before targeted root cause analysis (RCA) can be performed. Furthermore, 3D package components such as through-silicon-vias (TSVs) and micro-bumps require sub-surface structural characterization and metrology to aid in process monitoring and development throughout fabrication and integration. Package road-mapping has also called for increased die stacking with decreased pitch, TSV size, and die thickness, and thus requires increased accuracy and precision of various stateof- the-art analytical techniques in the near future. Physical failure analysis (PFA), process monitoring, and process development will therefore depend on reliable, high-resolution data directly measured at the region of interest (ROI) to meet the complexity and scaling challenges. This paper explores the successful application of plasma-FIB (PFIB)/SEM techniques in 2D and 3D regimes and introduces diagonal serial sectioning at package scales as a novel approach for PFA and metrology. Both 2D and 3D analysis will be demonstrated in a high bandwidth memory (HBM) package case-study which can be applied more broadly in 3D packaging.","PeriodicalId":20443,"journal":{"name":"Proceedings","volume":"99 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136353493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-12DOI: 10.31399/asm.cp.istfa2023p0007
Sebastian Brand, Michael Kögel, Christian Grosse, Frank Altmann, Christian Hollerith, Pascal Gounet
Abstract Non-destructive inspection and analysis techniques are crucial for quality assessment and defect analysis in various industries. They enable for screening and monitoring of parts and products without alteration or impact, facilitating the exploration of material interactions and defect formation. With increasing complexity in microelectronic technologies, high reliability, robustness and thus, successful failure analysis is essential. Machine learning (ML) approaches have been developed and evaluated for the analysis of acoustic echo signals and time-resolved thermal responses for assessing their ability for defect detection. In the present paper different ML architectures were evaluated, including 1D and 2D convolutional neural networks (CNNs) after transforming time-domain data into the spectra-land wavelet domains. Results showed that 2D CNN with wavelet domain representation performed best, however at the expense of additional computational effort. Furthermore, ML-based analysis was explored for lock-in thermography to detect and locate defects in the axial dimension based on thermal emissions. While promising, further research is needed to fully realize its potential.
{"title":"Advances in High-Resolution Non-Destructive Defect Localization Based on Machine Learning Enhanced Signal Processing","authors":"Sebastian Brand, Michael Kögel, Christian Grosse, Frank Altmann, Christian Hollerith, Pascal Gounet","doi":"10.31399/asm.cp.istfa2023p0007","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2023p0007","url":null,"abstract":"Abstract Non-destructive inspection and analysis techniques are crucial for quality assessment and defect analysis in various industries. They enable for screening and monitoring of parts and products without alteration or impact, facilitating the exploration of material interactions and defect formation. With increasing complexity in microelectronic technologies, high reliability, robustness and thus, successful failure analysis is essential. Machine learning (ML) approaches have been developed and evaluated for the analysis of acoustic echo signals and time-resolved thermal responses for assessing their ability for defect detection. In the present paper different ML architectures were evaluated, including 1D and 2D convolutional neural networks (CNNs) after transforming time-domain data into the spectra-land wavelet domains. Results showed that 2D CNN with wavelet domain representation performed best, however at the expense of additional computational effort. Furthermore, ML-based analysis was explored for lock-in thermography to detect and locate defects in the axial dimension based on thermal emissions. While promising, further research is needed to fully realize its potential.","PeriodicalId":20443,"journal":{"name":"Proceedings","volume":"99 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136353498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-12DOI: 10.31399/asm.cp.istfa2023p0279
Dong-yeob Kim, Su-yeon Kim, Woo-jun Kwon, Min-kook Kim, Christopher H. Kang
Abstract In this paper, we propose a method to get more accurate metrology data using the tilt-axis on a transmission electron microscope (TEM) to compensate for microscopic tilt-axis changes that occur during focused ion beam (FIB) sample preparation processing. This method was developed using V-NAND plan-view samples which require channel hole measurements for each layer to support process monitoring. To test this method, we obtained the same image by progressively tilting the alpha and beta axes one degree in the positive and negative direction using a V-NAND planar sample. The strongest contrast edge was found by contrast profile analysis of each edge of the V-NAND channel using automated software. Through this method, we were able to optimize the sample position and automate the process to capture high quality images to accurately measure V-NAND channel holes. The details are discussed in this paper.
{"title":"Proposal of Tilt-Axis Adjustment in V-NAND Plan-View without Si Substrate Using Automated Metrology of Transmission Electron Microscope","authors":"Dong-yeob Kim, Su-yeon Kim, Woo-jun Kwon, Min-kook Kim, Christopher H. Kang","doi":"10.31399/asm.cp.istfa2023p0279","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2023p0279","url":null,"abstract":"Abstract In this paper, we propose a method to get more accurate metrology data using the tilt-axis on a transmission electron microscope (TEM) to compensate for microscopic tilt-axis changes that occur during focused ion beam (FIB) sample preparation processing. This method was developed using V-NAND plan-view samples which require channel hole measurements for each layer to support process monitoring. To test this method, we obtained the same image by progressively tilting the alpha and beta axes one degree in the positive and negative direction using a V-NAND planar sample. The strongest contrast edge was found by contrast profile analysis of each edge of the V-NAND channel using automated software. Through this method, we were able to optimize the sample position and automate the process to capture high quality images to accurately measure V-NAND channel holes. The details are discussed in this paper.","PeriodicalId":20443,"journal":{"name":"Proceedings","volume":"100 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136352351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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