SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations

By Shinhyun Choi, S. H. Tan, Zefan Li, Yunjo Kim, Chanyeol Choi, Pai-Yu Chen, Hanwool Yeon, Shimeng Yu, Jeehwan Kim. Nature Materials, 2018

627 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Polymers and Plastics

View Paper: https://www.semanticscholar.org/paper/0848bcfb1238bf66357bb5ec9f3c44a96b5c2a07

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. J. Joshua Yang
2. Qiangfei Xia
3. Abu Sebastian
4. M. Le Gallo
5. Zhongrui Wang
6. Wei Dang Lu
7. Hao Jiang
8. Feng Miao

In Polymers and Plastics

1. Abu Sebastian
2. Husam N. Alshareef

Citations in the corpus

• An artificial spiking afferent nerve based on Mott memristors for neurorobotics (2020, background): “Given the physical limit of transistors and their lack of desirable dynamics, memristors have attracted special attention owing to their high integration intensity 14 , low power consumption 15 , analog behavior 16 – 18 , and diffusive dynamics 13,19 – 21 , etc.”
• Three-dimensional memristor circuits as complex neural networks (2020, background): “Emerging non-volatile devices 4,5 , such as memris-tors 6–8 , can directly implement synaptic weights and efficiently carry out resource-hungry matrix operations inside ensemble arrays 9–17 .”