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Non-destructive thickness characterisation of 3D multilayer semiconductor devices using optical spectral measurements and machine learning

作     者:Hyunsoo Kwak Sungyoon Ryu Suil Cho Junmo Kim Yusin Yang Jungwon Kim 

作者机构:Department of Mechanical EngineeringKorea Advanced Institute of Science and Technology(KAIST)Daejeon 34141South Korea Memory Metrology&Inspection Technology TeamMemory Manufacturing Technology CenterSamsung Electronics Co.Ltd.Gyeonggi-do 18448South Korea School of Electrical EngineeringKorea Advanced Institute of Science and Technology(KAIST)Daejeon 34141South Korea 

出 版 物:《Light(Advanced Manufacturing)》 (光(先进制造)(英文))

年 卷 期:2021年第2卷第1期

页      面:1-11页

学科分类:08[工学] 0812[工学-计算机科学与技术(可授工学、理学学位)] 

基  金:supported by the Industry–Academia Cooperation Program of Samsung Electronics Co. Ltd 

主  题:NAND multilayer character 

摘      要:Three-dimensional(3D)semiconductor devices can address the limitations of traditional two-dimensional(2D)devices by expanding the integration space in the vertical direction.A 3D NOT-AND(NAND)flash memory device is presently the most commercially successful 3D semiconductor *** vertically stacks more than 100 semiconductor material layers to provide more storage capacity and better energy efficiency than 2D NAND flash memory *** the manufacturing of 3D NAND,accurate characterisation of layer-by-layer thickness is critical to prevent the production of defective devices due to non-uniformly deposited *** date,electron microscopes have been used in production facilities to characterise multilayer semiconductor devices by imaging cross-sections of ***,this approach is not suitable for total inspection because of the wafer-cutting ***,we propose a non-destructive method for thickness characterisation of multilayer semiconductor devices using optical spectral measurements and machine ***200-layer oxide/nitride multilayer stacks,we show that each layer thickness can be non-destructively determined with an average of approximately 1.6Åroot-mean-square *** also develop outlier detection models that can correctly classify normal and outlier *** is an important step towards the total inspection of ultra-high-density 3D NAND flash memory *** is expected to have a significant impact on the manufacturing of various multilayer and 3D devices.

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