Open AccessAn artificial neural network as a predictor of electrical characteristics of nanoelectronic device channel based on a low-dimensional heterostructure
Author(s) -
Н. А. Ветрова,
K. P. Pchelintsev,
В. Д. Шашурин
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1695/1/012152
Subject(s) - heterojunction , artificial neural network , materials science , semiconductor , computer science , quantum , electronic engineering , artificial intelligence , optoelectronics , nanotechnology , engineering , physics , quantum mechanics
In this paper a computational algorithm for calculating current density of low-dimensional semiconductor heterostructures based on an artificial neural network is proposed. The neural network training is performed using the quantum-mechanical model of Green’s Functions.