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报告题目：Molecular dynamics simulations of heat transport using machine-learned potentials: A lecture based on GPUMD

报告嘉宾：樊哲勇，渤海大学 教授

报告时间：2025年10月29日 15:30

报告地点：成人视频 中心校区物理楼333会议室

主持人：姚明光

报告摘要

　　Molecular dynamics (MD) simulations play an important role in understanding and engineering heat transport properties of complex materials. Essential requirement for reliably predicting heat transport properties is the use of accurate and efficient interatomic potentials. Recently, machine-learned potentials have shown great promise in providing the required accuracy for a broad range of materials. In this lecture, we introduce the graphics processing units molecular dynamics (GPUMD) package and the neuroevolution potential (NEP) that enable accurate and efficient modelling of heat transport in various materials and nanostructures via MD simulations. We will delve into the fundamentals of ballistic-to-diffusive heat transport, the exact expressions of atomistic heat current, the equilibrium MD (EMD) method, nonequilibrium MD (NEMD) method, the homogeneous nonequilibrium MD (HNEMD) method, and the related spectral decomposition methods.

嘉宾简介

　　樊哲勇教授，毕业于南京大学，博士后工作于厦门大学和芬兰阿尔托大学，现为渤海大学物理科学与技术学院教授、硕士生导师。他长期从事分子动力学模拟的方法与程序开发以及材料高效计算方面的研究，主导开发了广为使用的GPUMD软件和高效的NEP机器学习势函数框架。在《Nature Communications》、《Physics Reports》、《PNAS》等学术期刊上发表了超过100篇论文，总引用5000余次，H因子42。出版了《CUDA 编程：基础与实践》与《分子动力学模拟》两部专著。

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