thickness control
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2021 ◽  
pp. 2101763
Author(s):  
June‐Chul Shin ◽  
Yeon Ho Kim ◽  
Kenji Watanabe ◽  
Takashi Taniguchi ◽  
Chul‐Ho Lee ◽  
...  

2021 ◽  
pp. 113887
Author(s):  
Hongchao Deng ◽  
Hidefumi Mitsuno ◽  
Ryohei Kanzaki ◽  
Takamichi Nakamoto
Keyword(s):  

2021 ◽  
Author(s):  
Vikas Dixit ◽  
Bryan Gauntt ◽  
Taehun Lee

Abstract The automation of both, transmission electron microscopy (TEM) imaging and lamella preparation using focused ion beam (FIB) has gathered an enormous momentum in last few years, especially in the semiconductor industry. The process development of current and future microprocessors requires a precise control on the patterning of a multitude of ultrafine layers, several of which are in the order of nanometers. The statistical accuracy and reliability of TEM based metrology and failure analysis of such complex and refined structures across the wafer needs a large-scale sampling, which is feasible only with an automation. An inherent requirement of automating TEM sample preparation entails a need of a robust and repeatable methodology that provides both, a good thickness control and an accurate targeting, on the intended feature in the ultra-thin lamella. In this work, key factors that impact both these aspects of a TEM lamella preparation will be discussed. In addition, steps needed to ensure that FIB toolsets consistently and reliably produce high quality samples, will be highlighted.


Author(s):  
Akihiko Fujii ◽  
Tomohisa Oizumi ◽  
Nao Kuwahara ◽  
Genya Uzurano ◽  
Tomoki Saito ◽  
...  

2021 ◽  
Vol 23 (8) ◽  
Author(s):  
Zhiying Zhao ◽  
Qing Guo ◽  
Linqi Cao ◽  
Suju Jiang ◽  
Fangfang Mao ◽  
...  

Seikei-Kakou ◽  
2021 ◽  
Vol 33 (8) ◽  
pp. 286-288
Author(s):  
Kazuya Hioki ◽  
Kazumasa Fujiwara ◽  
Sachi Yawaka

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