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

查看全文 作　　者：Hyunsoo [1]Kwak;Sungyoon [2]Ryu;Suil [2]Cho;Junmo [3]Kim;Yusin [2]Yang;Jungwon [1]Kim

机构地区：[1]Department of Mechanical Engineering,Korea Advanced Institute of Science and Technology(KAIST),Daejeon 34141,South Korea;[2]Memory Metrology&Inspection Technology Team,Memory Manufacturing Technology Center,Samsung Electronics Co.Ltd.,Gyeonggi-do 18448,South Korea;[3]School of Electrical Engineering,Korea Advanced Institute of Science and Technology(KAIST),Daejeon 34141,South Korea

出　　处：《Light(Advanced Manufacturing)》索引2021年第2卷第1期,共11页

基　　金：supported by the Industry–Academia Cooperation Program of Samsung Electronics Co.,Ltd. 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 device.It vertically stacks more than 100 semiconductor material layers to provide more storage capacity and better energy efficiency than 2D NAND flash memory devices.In 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 layers.To date,electron microscopes have been used in production facilities to characterise multilayer semiconductor devices by imaging cross-sections of samples.However,this approach is not suitable for total inspection because of the wafer-cutting procedure.Here,we propose a non-destructive method for thickness characterisation of multilayer semiconductor devices using optical spectral measurements and machine learning.For>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 error.We also develop outlier detection models that can correctly classify normal and outlier devices.This is an important step towards the total inspection of ultra-high-density 3D NAND flash memory devices.It is expected to have a significant impact on the manufacturing of various multilayer and 3D devices. 关键词：NAND MULTILAYER CHARACTER

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

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