构建用于晶体结构性质研究的神经网络模型

Mathematical modeling in materials science of electronic component Pub Date : 2021-10-27 DOI:10.29003/m2461.mmmsec-2021/31-34

O. Uvarova, S. Uvarov

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摘要

本文研究了一种基于人工神经网络的模型构建机制，用于获取原子系统的内聚能值。内聚能可以计算体系的总能量。它是结构最重要的特征之一。对Si、Ge和C的单组分晶体结构进行了计算实验。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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CONSTRUCTION OF NEURAL NETWORK MODEL FOR STUDYING OF CRYSTAL STRUCTURES PROPERTIES

The paper considers a mechanism for constructing a model based on artificial neural network for obtaining the values of the cohesive energy of a system of atoms. Cohesive energy allows for calculation of total energy of system. It is one of the most important characteristics of a structure. A computational experiment is carried out for one-component crystal structures of Si, Ge and C.

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Mathematical modeling in materials science of electronic component

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