International Symposium for Testing and Failure Analysis最新文献

{"title":"A BERT-Based Report Classification for Semiconductor Failure Analysis","authors":"Corinna Grabner, Anna Safont-Andreu, C. Burmer, Konstantin Schekotihin","doi":"10.31399/asm.cp.istfa2022p0028","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2022p0028","url":null,"abstract":"Failure Analysis (FA) is a complex activity that requires careful and complete documentation of all findings and conclusions to preserve knowledge acquired by engineers in this process. Modern FA systems store this data in text or image formats and organize it in databases, file shares, wikis, or other human-readable forms. Given a large volume of generated FA data, navigating it or searching for particular information is hard since machines cannot process the stored knowledge automatically and require much interaction with experts. In this paper, we investigate applications of modern Natural Language Processing (NLP) approaches to the classification of FA texts with respect to electrical and/or physical failures they describe. In particular, we study the efficiency of pretrained Language Models (LM) in the semiconductors domain for text classification with deep neural networks. Evaluation results of LMs show that their vocabulary is not suitable for FA applications, and the best classification accuracy of appr. 60% and 70% for physical and electrical failures, respectively, can only be reached with fine-tuning techniques.","PeriodicalId":417175,"journal":{"name":"International Symposium for Testing and Failure Analysis","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133384353","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}

{"title":"Transmission Electron Imaging AND Diffraction in the SEM—What, Why, and How To Do This in Your Microscope","authors":"Jason Holm","doi":"10.31399/asm.cp.istfa2022tpj1","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2022tpj1","url":null,"abstract":"\u0000 This presentation covers the theory and practice of scanning transmission electron microscopy in a scanning electron microscope or STEM-in-SEM. It provides a detailed overview of the measurement physics, the equipment required, the importance of collection angle control, and contrast interpretation. It explains how and why different detectors are used and how they are calibrated. It addresses the issue of beam damage and explains how to quantify and deal with it. It also covers advanced concepts, including 4D STEM-in-SEM, nanoscale strain and temperature mapping, and the use of programmable STEM detectors for imaging and diffraction, and provides examples demonstrating the capabilities of the various measurement setups.","PeriodicalId":417175,"journal":{"name":"International Symposium for Testing and Failure Analysis","volume":"337 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122330590","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}

{"title":"Failure Analysis Methodology Comparison to Define Potential Root Cause on Lifted Copper Ball Bond","authors":"Ong Pei Hoon, T. S. Yee, Lo Chea Wee","doi":"10.31399/asm.cp.istfa2022p0392","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2022p0392","url":null,"abstract":"\u0000 Copper (Cu) material was extensively studied in the past years and widely implemented in high volume wire bonding process as a replacement of Gold (Au) material during semiconductor device fabrication. No doubt, Cu wire provide low cost alternative to gold with higher thermal and electrical conductivity, but it does pose some drawback especially after reliability stress. One of the most common problem was ball lifted after component gone through several reliability stress tests. In this paper, several FA analytical techniques and procedures will be discussed in detail to demonstrate the use of these techniques in ball lifting investigation.","PeriodicalId":417175,"journal":{"name":"International Symposium for Testing and Failure Analysis","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114265002","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}

{"title":"Newly Designed, Faster, and More Sensitive Scanning Capacitance Microscope for Failure Analysis","authors":"Haigang Zhang, M. Kocuń, B. Ohler, R. Proksch","doi":"10.31399/asm.cp.istfa2022p0434","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2022p0434","url":null,"abstract":"\u0000 A new scanning capacitance microscope, with an optimized, modern RF circuitry is described. The new design results in improved ease of use and sensitivity. We will discuss the design details and show application examples on semiconductor devices and ferroelectric materials.","PeriodicalId":417175,"journal":{"name":"International Symposium for Testing and Failure Analysis","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131455118","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}

{"title":"Defect Localization and Analysis of Compound Semiconductors using ECCI, CBED, and STEM-in-SEM for an All-In-Situ Workflow Using a FIB/SEM Microscope","authors":"Adam Stokes, Libor Strakoš, T. Landin","doi":"10.31399/asm.cp.istfa2022p0211","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2022p0211","url":null,"abstract":"\u0000 Complex failure analysis often requires the use of multiple characterization instruments. For example, a defect or failure may be localized using one tool, whereas the subsequent marking, precision targeting, and high-resolution analysis may require completely different instruments. As a result, the analysis workflows require sample and operator coordination between instruments and engineers, which leads to lower throughput and success rates. This paper describes a complete in-situ workflow for comprehensive failure analysis processes on a compound semiconductor using a state-of-the-art FIB/SEM system, incorporating electron channeling contrast imaging (ECCI) and a STEM-in-SEM detector used in unison with an insertable detector positioned underneath the sample to capture transmitted electron condensed beam electron diffraction (CBED) micrographs.","PeriodicalId":417175,"journal":{"name":"International Symposium for Testing and Failure Analysis","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131136671","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}

{"title":"Zero Channel Bias Determination of Device Turn-On and the Seebeck Effect in Nanoprobing","authors":"Gregory M. Johnson, H. Stegmann, A. Rummel","doi":"10.31399/asm.cp.istfa2022p0262","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2022p0262","url":null,"abstract":"\u0000 In prior work, it was demonstrated that information about device turn-on can be obtained in a nanoprobing setup which involves no applied bias across the channel. This was performed on nFET logic devices in 7 nm technology and attributed to the Seebeck effect, or heating from the SEM beam. In this work, the experiments are continued to both nFET and pFET devices and on both 22 nm and 5 nm devices. Further discussion about the opportunities and evidence for Seebeck effect in nanoprobing are discussed.","PeriodicalId":417175,"journal":{"name":"International Symposium for Testing and Failure Analysis","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121587642","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}

{"title":"Machine Learning Based Data and Signal Analysis Methods for Application in Failure Analysis (2022 Update)","authors":"M. Kögel, S. Brand, F. Altmann","doi":"10.31399/asm.cp.istfa2022tps1","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2022tps1","url":null,"abstract":"\u0000 This presentation is an introduction to machine learning techniques and their application in semiconductor failure analysis. The presentation compares and contrasts supervised, unsupervised, and reinforcement learning methods, particularly for neural networks, and lays out the steps of a typical machine learning workflow, including the assessment of data quality. It also presents case studies in which machine learning is used to detect and classify circuit board defects and analyze scanning acoustic microscopy (SAM) data for blind source separation.","PeriodicalId":417175,"journal":{"name":"International Symposium for Testing and Failure Analysis","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115884969","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}

{"title":"Precession Electron Diffraction (PED) Strain Characterization in Stacked Nanosheet FET Structure","authors":"J. Li, S. Mochizuki, E. Stuckert, L. Tierney, K. Toole, R. Conte, N. Loubet","doi":"10.31399/asm.cp.istfa2022p0074","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2022p0074","url":null,"abstract":"\u0000 Non-planar semiconductor devices, such as vertical fin-based field-effect transistor (FinFET) devices have been developed that include multiple vertical fins serving as conducting channel regions to enable larger effective conduction width in a small layout area. However, as circuits are scaled to smaller dimensions, it has become increasingly difficult to improve the performance of FinFET devices. Stacked nanosheet FETs have been developed to further enable larger effective conduction width in a given small layout area while enabling gate length scaling. Nanosheet (NS) FET devices have attracted attention as a candidate to replace FinFET technology at the 5 nm technology node and beyond due to their excellent electrostatics and short channel control. The use of silicon-germanium for the channel material has been explored as a major technology element for FinFET CMOS technology, and the performance benefits of Si-Ge channel over silicon channel have been demonstrated. Compared with conventional FinFET, stacked gate-all-around (GAA) NS CMOS shows higher electron mobility for nFET but lower hole mobility for pFET due to its unique device architecture and carrier transport direction. To improve pFET performance, SiGe NS is proposed as the pFET channel material. However, introducing and maintaining strain in the SiGe GAA NS channel is challenging but important for improving carrier transport. It is critical to understand the strain distribution in the advanced 3D nanosheet FET structures. This paper describes the use of advanced transmission electron microscopy (TEM) techniques to investigate the strain distribution in strained SiGe channel NS pFET through Si channel trimming and selective Si1-xGex epitaxial growth. A stacked GAA NS pFET was fabricated from compressively strained Si1-xGex channel with good crystallinity and high uniaxial compressive stress of ~1 GPa. From lattice deformation maps with a nanometer spatial resolution obtained by TEM techniques, the authors demonstrate that nano-beam precession electron diffraction techniques can be used to investigate the local strain distribution of the stacked GAA NS pFET devices with high precision, and thus help to optimize the integration process and strain engineering for pFET device performance enhancement for the next generation of CMOS logic in GAA NS technology.","PeriodicalId":417175,"journal":{"name":"International Symposium for Testing and Failure Analysis","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129461593","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}

{"title":"Black Mushroom Formation on Aluminum Bond Pad","authors":"Yong Guo, Brian Smith, Yanan Guo, J. Hurst, C. Penley, Hanfei Lu, Sergei Drizlikh","doi":"10.31399/asm.cp.istfa2022p0306","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2022p0306","url":null,"abstract":"\u0000 By using fluorocarbon gases for aluminum (Al) pad open plasma etch, the pad inevitably has a thin surface remnant layer of Al-oxyfluoride (AlOF) by-product. This layer is chemically stable and does not directly cause issues in chip testing or wire bonding. This is true until open Al pads were exposed to a humid environment causing pad corrosion over time. The F-assisted corrosion created so-called black mushroom (BM) defects on the Al pads according to the defects appearance, resulting in the non-stick pads for wire bonding. Experimental tests were carried out to induce the Al pad corrosion via placing random fab-out wafers in a cassette pod hosting about 90% RH over a period up to a week. Optical imaging revealed BMs nucleated, primarily at Al grain boundaries. BMs were found all to be composed of O, F, and Al. In the cross section, BMs were shown to have separations of F-rich region next to Al and O-rich region towards the surface. In addition, BMs were composed of small crystallites and were porous. The former indicates an ionic bonding involving in O, F, and Al. The latter indicates the corrosion generated gaseous byproduct. A moisture (H2O) involved cyclic chemical reaction incorporating these analyses has been formulated. Factors to prevent BM formation were discussed.","PeriodicalId":417175,"journal":{"name":"International Symposium for Testing and Failure Analysis","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129675532","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}

{"title":"Fault Isolation and Physical Failure Analysis of IC-Embedded OLED Display Device’s Failure","authors":"Hoseok Song, Heejeong Seo, Ki-Jong Lee, Yong H. Lee","doi":"10.31399/asm.cp.istfa2022p0078","DOIUrl":"https://doi.org/10.31399/asm.cp.istfa2022p0078","url":null,"abstract":"\u0000 In the failure analysis (FA) of an organic light emitting diode (OLED) display device, fault isolation and physical failure analysis (PFA) were used to identify the root cause of display failure. It is challenging to conduct the FA of a display device, as it consists of display panel, a circuit board and components like semiconductor chips and this integration makes the failure complicated and difficult to analyze and understand. In the case of the display failure studied in this paper, the first work of fault isolation did not clearly identify the origin of the malfunction and its PFA didn’t show any specific defects. To precisely identify the defect location before destructive analysis, the fault isolation technique of OBIRCH was applied to the display device and subsequent PFA successfully identified a crack defect causing the display failure. This finding was given as feedback to the wafer fab and processing parameters were adjusted to prevent generation of the defect in the OLED display device.","PeriodicalId":417175,"journal":{"name":"International Symposium for Testing and Failure Analysis","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127943616","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}