Stochastic phase-change neurons.

By Tomáš Tůma, A. Pantazi, M. Le Gallo, Abu Sebastian, Evangelos Eleftheriou. Nature Nanotechnology, 2016

980 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Electrical and Electronic Engineering, Materials Chemistry

View Paper: https://www.semanticscholar.org/paper/0a504a3d436a673cc28c5e2116dd8be417411733

How researchers see this paper

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

In Cellular and Molecular Neuroscience

1. Daniele Ielmini
2. Qiangfei Xia
3. H. Philip Wong
4. Danijela Marković
5. Damien Querlioz
6. Can Li
7. Hao Jiang
8. Julie Grollier

In Electrical and Electronic Engineering

1. Daniele Ielmini
2. H. Philip Wong
3. Qiangfei Xia
4. Zhongrui Wang
5. Danijela Marković
6. Damien Querlioz
7. Can Li
8. Hao Jiang

In Materials Chemistry

1. H. Philip Wong
2. Daniele Ielmini
3. Jie Deng

Citations in the corpus

• Physics for neuromorphic computing (2020, background): “The stochasticity of the phase transition between the amorphous and crystalline states has also been harnessed to implement stochastic nano-neurons whose membrane potential is represented by the phase configuration of the device 59 .”