基于深度神经网络的液态水粗粒度模型的建立，用于模拟水环境中纳米结构的声振动

IF 1.4 4区工程技术 Q2 ENGINEERING, MULTIDISCIPLINARY

International Journal for Multiscale Computational Engineering Pub Date : 2022-01-01 DOI:10.1615/intjmultcompeng.2022044133

Zhenwei Yu, Y. Gan, Yonggang Shen

引用次数: 0

摘要

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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Development of coarse-grained models of liquid water by deep neural networks for simulating acoustic vibrations of nanostructures in aqueous environment

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来源期刊

International Journal for Multiscale Computational Engineering 工程技术-工程：综合

CiteScore

3.40

自引率

14.30%

发文量

审稿时长

>12 weeks

期刊介绍： The aim of the journal is to advance the research and practice in diverse areas of Multiscale Computational Science and Engineering. The journal will publish original papers and educational articles of general value to the field that will bridge the gap between modeling, simulation and design of products based on multiscale principles. The scope of the journal includes papers concerned with bridging of physical scales, ranging from the atomic level to full scale products and problems involving multiple physical processes interacting at multiple spatial and temporal scales. The emerging areas of computational nanotechnology and computational biotechnology and computational energy sciences are of particular interest to the journal. The journal is intended to be of interest and use to researchers and practitioners in academic, governmental and industrial communities.