The Elastic Continuum Limit of the Tight Binding Model

作者考虑固体的最简单的量力学模型，紧密的有约束力的模型，；证明在连续统限制，紧密的有约束力的模型的精力收敛到用 Cauchy 出生的统治获得的连续统弹性模型的。在这篇论文的技术基于主要光谱为大矩阵的不安理论。

Simulation of Impurity Diffusion in a Strained Nanowire Using Off-Lattice KMC

Kinetic Monte Carlo(KMC)is a stochastic model used to simulate crystal growth.However,most KMC models rely on a pre-defined lattice that neglects dislocations,lattice mismatch and strain effects.In this paper,we investigate the use of a 3D off-lattice KMC algorithm.We test this method by investigating impurity diffusion in a strained FCC nanowire.While faster than a molecular dynamics simulation,the most general implementation of off-lattice KMC is much slower than a lattice-based algorithm.An improved procedure is achieved for weakly strained systems by precomputing approximate saddle point locations based on unstrained lattice structures.In this way,one gives up some of the flexibility of the general method to restore some of the computational speed of lattice-based KMC.In addition to providing an alternative approach to nano-materials simulation,this type of simulation will be useful for testing and calibrating methods that seek to parameterize the variation in the transition rates for lattice-based KMC using continuum modeling.

Optimization-Based String Method for Finding Minimum Energy Path

We present an efficient algorithm for calculating the minimum energy path(MEP)and energy barriers between local minima on a multidimensional potential energy surface(PES).Such paths play a central role in the understanding of transition pathways between metastable states.Our method relies on the original formulation of the string method[Phys.Rev.B,66,052301(2002)],i.e.to evolve a smooth curve along a direction normal to the curve.The algorithm works by performing minimization steps on hyperplanes normal to the curve.Therefore the problem of finding MEP on the PES is remodeled as a set of constrained minimization problems.This provides the flexibility of using minimization algorithms faster than the steepest descent method used in the simplified string method[J.Chem.Phys.,126(16),164103(2007)].At the same time,it provides a more direct analog of the finite temperature string method.The applicability of the algorithm is demonstrated using various examples.

Heterogeneous Multiscale Methods: A Review

This paper gives a systematic introduction to HMM,the heterogeneous multiscale methods,including the fundamental design principles behind the HMM philosophy and the main obstacles that have to be overcome when using HMM for a particular problem.This is illustrated by examples from several application areas,including complex fluids,micro-fluidics,solids,interface problems,stochastic problems,and statistically self-similar problems.Emphasis is given to the technical tools,such as the various constrained molecular dynamics,that have been developed,in order to apply HMM to these problems.Examples of mathematical results on the error analysis of HMM are presented.The review ends with a discussion on some of the problems that have to be solved in order to make HMM a more powerful tool.

Deep potentials for materials science

To fill the gap between accurate(and expensive)ab initio calculations and efficient atomistic simulations based on empirical interatomic potentials,a new class of descriptions of atomic interactions has emerged and been widely applied;i.e.machine learning potentials(MLPs).One recently developed type of MLP is the deep potential(DP)method.In this review,we provide an introduction to DP methods in computational materials science.The theory underlying the DP method is presented along with a step-by-step introduction to their development and use.We also review materials applications of DPs in a wide range of materials systems.The DP Library provides a platform for the development of DPs and a database of extant DPs.We discuss the accuracy and efficiency of DPs compared with ab initio methods and empirical potentials.

第一性原理分子动力学中电子结构的神经网络表达

第一性原理分子动力学模拟过程中产生海量包含丰富电子结构信息的数据,未被充分利用.本文提出一种通过预测晶体材料紧束缚模型的形式,高效、准确地表达第一性原理电子结构的神经网络方法TBworks.TBworks可以结合机器学习分子动力学方法,快速实现复杂体系的分子动力学模拟和电子结构采样,计算电子关联函数以及相应的物理性质.以一维电荷密度波材料碳炔链为应用示例,本文基于TBworks研究了正则系综下的电子谱函数和光电导率,以及孤子-反孤子对湮灭的动力学过程中电子的非绝热演化,发现由于超越波恩-奥本海默近似的动力学效应对电子谱函数的低能模式的修正.该方法为研究动力学体系提供了准确、高效、可重复使用的第一性原理电子结构的代理模型,极大地提高了电子结构的计算效率和模拟尺度,使得对一些由于计算瓶颈无法或者难以进行的新奇性质和现象的研究成为可能.

Effective Maxwell Equations from Time-dependent Density Functional Theory

The behavior of interacting electrons in a perfect crystal under macroscopic external electric and magnetic fields is studied. Effective Maxwell equations for the macroscopic electric and magnetic fields are derived starting from time-dependent density functional theory. Effective permittivity and permeability coefficients are obtained.