Improved Device Performance of MoTe2 nanoribbon Transistors with Solution-processed Ternary HfAlOx High-k Dielectric

Author(s):  
Yuan Liu ◽  
Zijian Xie ◽  
Li Yang ◽  
Xiaokun Wen ◽  
Wenyu Lei ◽  
...  
ACS Photonics ◽  
2019 ◽  
Vol 6 (12) ◽  
pp. 3159-3165 ◽  
Author(s):  
Sungho Nam ◽  
Mujeeb Ullah Chaudhry ◽  
Kornelius Tetzner ◽  
Christopher Pearson ◽  
Chris Groves ◽  
...  

2014 ◽  
Vol 50 ◽  
pp. 323-328 ◽  
Author(s):  
Raluca C. Frunză ◽  
Brigita Kmet ◽  
Marko Jankovec ◽  
Marko Topič ◽  
Barbara Malič

2020 ◽  
pp. 1-1 ◽  
Author(s):  
Md Mobaidul Islam ◽  
Jewel Kumer Saha ◽  
Ravindra Naik Bukke ◽  
Md Mehedi Hasan ◽  
Mohammad Masum Billah ◽  
...  

2016 ◽  
Vol 108 (23) ◽  
pp. 233506 ◽  
Author(s):  
Ao Liu ◽  
Guoxia Liu ◽  
Huihui Zhu ◽  
Byoungchul Shin ◽  
Elvira Fortunato ◽  
...  

2018 ◽  
Author(s):  
Seng Nguon Ting ◽  
Hsien-Ching Lo ◽  
Donald Nedeau ◽  
Aaron Sinnott ◽  
Felix Beaudoin

Abstract With rapid scaling of semiconductor devices, new and more complicated challenges emerge as technology development progresses. In SRAM yield learning vehicles, it is becoming increasingly difficult to differentiate the voltage-sensitive SRAM yield loss from the expected hard bit-cells failures. It can only be accomplished by extensively leveraging yield, layout analysis and fault localization in sub-micron devices. In this paper, we describe the successful debugging of the yield gap observed between the High Density and the High Performance bit-cells. The SRAM yield loss is observed to be strongly modulated by different active sizing between two pull up (PU) bit-cells. Failure analysis focused at the weak point vicinity successfully identified abnormal poly edge profile with systematic High k Dielectric shorts. Tight active space on High Density cells led to limitation of complete trench gap-fill creating void filled with gate material. Thanks to this knowledge, the process was optimized with “Skip Active Atomic Level Oxide Deposition” step improving trench gap-fill margin.


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