固体中的原子间相互作用势

近年来，原子间相互作用势广泛应用物理、化学、材料科学中，文章综合评述了金属和半导体中原子间相互作用势研究的发展状况以及各种势函数的范围和存在的总理２，总结了近年来金属合金以及半导体化合物中原子间相互作用势的应用情况，并讨论了固体中原子间相互作用势的发展方向。     

六角密堆结构钇的解析型键序作用势

为了构建拟合势需要的数据库,采用密度泛函理论方法计算了六角密堆结构钇(hcp-Y)的晶格参数、弹性常数、内聚能、结构能差以及相关的点、面缺陷性质. 基于解析型键序作用势,构建了hcp-Y的多体作用势模型. hcp-Y势模型是通过拟合Y的晶格参数、弹性常数、体弹模量、内聚能、空位形成能和不同相之间的结构能差而构建.分析发现,所得到的势模型能够很好地描述hcp-Y的自填隙原子形成能、空位形成能、双空位键能以及其它体性质,同时,构建的势模型用来研究Y的热动力学性质的相关结果也比较理想.     

新的相互作用势对MD模拟钙钛矿结构MgSiO3热力学性质的影响

通过分析势能曲线解释了钙钛矿结构MgSiO3熔化模拟过程中模拟熔化温度存在较大差异的原因，并进一步研究了对势参数在分子动力学模拟中的影响. 通过调整已有的经验势得到了一组新的势参数，以此来进行分子动力学研究，得到的常温常压下摩尔体积与Belonoshko和Dubrovinsky的结果符合较好，并且其状态方程、常压下热容和常压下热膨胀系数与他人的实验值都较好地吻合. 另外，所得到的熔化温度也与以前的研究进行了比较.     

金属Nb的Finnis-Sinclair势开发及势函数形式对材料性能的影响

对于计算材料科学的研究者来说,经常由于找不到合适的原子间势而工作受阻.本文将在Finnis-Sinclair势的框架下,通过开发金属Nb的Finnis-Sinclair势而给出较详细的原子间势拟合、检验、修正的过程.首先建立原子间势与材料宏观性能之间的关系,然后通过再现金属Nb的结合能、体模量、表面能、空位形成能及平衡点阵常数的实验数据的方法拟合金属Nb的Finnis-Sinclair势.利用所构建的原子间势计算金属Nb的弹性常数、剪切模量及柯西压力来检验势函数.讨论势函数曲线形状对间隙形成能的影响,进而根据间隙能的计算数据修正已构建的原子间势.讨论截断距离的处理方法.本文的结果一方面为构建原子间势函数库提供资料,为构建与Nb相关的合金原子间势奠定基础;另一方面,为开发和改善原子间势质量提供方法和依据.     

动态载荷下铁相变的原子模拟研究进展

铁的α?ε相变是金属高压相变研究领域的经典范例,随着测试技术的进步,其相变机制与动力学研究不断深入,基于激光加载的原位X射线观察结合非平衡分子动力学模拟研究是解决该问题最有效的手段之一。为此,综述了铁在动态载荷下塑性与相变的原子模拟研究进展,综合分析了铁的高压势函数,平面应变加载下晶体的各向异性、冲击强度、应变率、应变梯度、各种初始晶体缺陷等对铁相变机制的影响,以及铁的相变与层裂,同时报道了铁在非平面加载下响应规律研究的最新进展,最后进行了归纳总结和展望。     

Fe-Cr-V-Ni-Si-C系多元合金的原子间互作用势的构建及应用

使用第一性原理赝势方法及量子化学从头算方法计算的物理量以及最小二乘法拟合的数据构建了多元合金Fe-Cr-V-Ni-Si-C系的原子间互作用势，并利用该原子间互作用势计算了实验合金N5(Fe9.07Cr7.56V0.8Ni0.49 Mo0.96Mn1.52Si3.3C)，N6(Fe9.65Cr7.72V1.17Ni0.50Mo0.91Mn1.42Si3.3C)，N7(Fe9.81Cr7.65V1.58Ni0.46Mo0.86Mn1.35Si3.3C)，N8(Fe10.05Cr7.59V2.24Ni0.40M     

Fe-Cr-V-Ni-Si-C系多元合金的原子间互作用势的构建及应用

使用第一性原理赝势方法及量子化学从头算方法计算的物理量以及最小二乘法拟合的数据构建了多元合金Fe-Cr-V-Ni-Si-C系的原子间互作用势,并利用该原子间互作用势计算了实验合金N5(Fe9.07Cr7.56V0.8Ni0.49 Mo0.96Mn1.52Si3.3C),N6(Fe9.65Cr7.72V1.17Ni0.50Mo0.91Mn1.42Si3.3C),N7(Fe9.81Cr7.65V1.58Ni0.46Mo0.86Mn1.35Si3.3C),N8(Fe10.05Cr7.59V2.24Ni0.40M 关键词： F-S多体势 多元合金 第一性原理     

稀土金属间化合物RFe2Zn20-xInx的结构属性研究

RFe2Zn20(R代表稀土元素)型稀土金属间化合物因其低稀土含量和良好的铁磁性,已成为铁磁材料的研究热点之一.添加第四组元对该系列化合物的晶体结构和材料性能会产生一定影响.利用晶格反演方法获得了一系列有效的原子间相互作用势,对三元RFe2Zn20和四元RFe2Zn20-xInx化合物进行原子级模拟计算.研究表明,随着稀土元素原子量的增加,三元体系的晶格参数和体积呈线性下降,第四组元引入与否对该线性关系无直接影响.第四组元In替代Zn时,择优占据16c晶位,占满16c后选择占据96g晶位,始终不占据48f晶位.择优占位的结论符合实验观测,并与晶格反演势分析的结果一致.     

百吉帕压力下固态氩的状态方程

 利用最新的X光衍射实验数据和Ar原子的弹性散射实验结果，得到了Ar原子间的相互作用和350 GPa下的固态氩的状态方程。这个状态方程可以作为超高压力下的压标。在150 GPa以上的压标，是目前高压研究中急需的。固态氩既可作为准静水压传压介质，又可作为高压X光衍射中的压标使用。本文计算了固态氩的Grüneisen参数、Debye特征参数、定容比热和等温体模量随压力的变化，压力范围为0~150 GPa。     

稀土金属间化合物RFe2Zn20-xInx的结构属性研究

RFe₂Zn₂₀（R代表稀土元素）型稀土金属间化合物因其低稀土含量和良好的铁磁性,已成为铁磁材料的研究热点之一.添加第四组元对该系列化合物的晶体结构和材料性能会产生一定影响.利用晶格反演方法获得了一系列有效的原子间相互作用势,对三元RFe₂Zn₂₀和四元RFe₂Zn_20-xIn_x化合物进行原子级模拟计算.研究表明,随着稀土元素原子量的增加,三元体系的晶格参数和体积呈线性下降,第四组元引入与否对该线性关系无直接影响.第四组元In替代Zn时,择优占据16c晶位,占满16c后选择占据96g晶位,始终不占据48f晶位.择优占位的结论符合实验观测,并与晶格反演势分析的结果一致. 关键词： 原子间相互作用势 择优占位 晶体结构     

Point defects in L1_0 FePt studied by molecular dynamics simulations based on an analytic bond-order potential

The point defects and their related physical properties in L10 FePt are investigated by molecular dynamics simulations based on an analytic bond-order potential. The calculated results agree well with the experimental value, indicating that the analytic bond-order potential is suitable to describe the structural properties and surface energies of the FePt alloy in the L10 phase. However, the calculated vacancy formation energy of an Fe atom is higher than that of a Pt atom, which disagrees with some other p...     

Molecular dynamics study of the sputtering of Al cluster by Ar and Kr atoms

The numerical studies of the dynamics of the crystaline lattice formed by atoms requires the detailed knowledge of the forces between these atoms. In our contribution we concentrate on molecular dynamics study of sputtering of Al cluster in the form of the cube (i.e. eight Al atoms). The sputtering is due to impact of Ar and Kr atoms of energy 550 eV. We compare the use of the potential between atoms either of Molière type or the embedded atom potential which has been proposed recently. For the choice of both potential the spectra of sputtered particles were calulated and the comparison was made.     

Self-consistent Shaw optimized model potential: Application to the determination of structural and atomic transport properties of liquid alkali metals by molecular dynamics simulations

The ‘first-principles’ fully non-local and energy-dependent optimized model potential (OMP) derived by Shaw is developed further. In contrast to Shaw's original paper, OMP parameters are derived in a self-consistent manner that does not rely on knowledge of experimental values of the ionization and cohesive energies. To our knowledge, this is the first time that this method has been used for effective potential calculations. In an application to liquid Li, Na, and K alkali metals, we used OMP pseudopotential-based interactions between ions to carry out standard molecular dynamics simulations. In the calculations, the ionic structure for the liquid state was first checked at a temperature near the melting point. Similar accurate calculations, but for atomic transport properties, predict the temperature dependence of the self-diffusion coefficients. The theoretical results obtained are in overall agreement with available experimental measurements. Thus, one can have some confidence in the ability of the optimized model potential to give a good representation of the physical properties of these alkali ions in the liquid environment.     

Zn-Mg合金的长程Finnis-Sinclair势

通过拟合Mg的晶格能、晶格常数、弹性常数,并将其与前人的结果相比较后获得了描述Mg的最优长程Finnis-Sinclair(F-S)势函数参数,使用同样方法并引入修正因子后得到了Zn的长程F-S势参数.基于单质Zn,Mg的F-S势参数,进一步拟合合金Mg₂₁Zn₂₅,MgZn₂,Mg₂Zn₁₁的晶格常数、晶格能获得Zn-Mg原子对的F-S势参数,构建了整套描述Zn-Mg合金的长程F-S势参数.在此 关键词： 长程Finnis-Sinclair势 Zn-Mg合金 分子动力学模拟     

关于铁的势函数的研究

本文介绍了由Voter-Chan提出的嵌入式原子势模型(EAM),运用该原子势计算了单晶铁的弹性常数和在高压下的固固相变.模拟结果显示此EAM势描述铁的弹性常数与实验值有一定的偏离,但是却比较好的反映了铁在高压下的相变.此EAM势模型可以用来进一步研究铁在极端条件下的相变过程等,对相变的微观机制进行更细致深入的研究.     

Quasi-coarse-grained dynamics: modelling of metallic materials at mesoscales

A computationally efficient modelling method called quasi-coarse-grained dynamics (QCGD) is developed to expand the capabilities of molecular dynamics (MD) simulations to model behaviour of metallic materials at the mesoscales. This mesoscale method is based on solving the equations of motion for a chosen set of representative atoms from an atomistic microstructure and using scaling relationships for the atomic-scale interatomic potentials in MD simulations to define the interactions between representative atoms. The scaling relationships retain the atomic-scale degrees of freedom and therefore energetics of the representative atoms as would be predicted in MD simulations. The total energetics of the system is retained by scaling the energetics and the atomic-scale degrees of freedom of these representative atoms to account for the missing atoms in the microstructure. This scaling of the energetics renders improved time steps for the QCGD simulations. The success of the QCGD method is demonstrated by the prediction of the structural energetics, high-temperature thermodynamics, deformation behaviour of interfaces, phase transformation behaviour, plastic deformation behaviour, heat generation during plastic deformation, as well as the wave propagation behaviour, as would be predicted using MD simulations for a reduced number of representative atoms. The reduced number of atoms and the improved time steps enables the modelling of metallic materials at the mesoscale in extreme environments.     

Machine learning potential aided structure search for low-lying candidates of Au clusters

A machine learning (ML) potential for Au clusters is developed through training on a dataset including several different sized clusters. This ML potential accurately covers the whole configuration space of Au clusters in a broad size range, thus expressing a good performance in search of their global minimum energy structures. Based on our potential, the low-lying structures of 17 different sized Au clusters are identified, which shows that small sized Au clusters tend to form planar structures while large ones are more likely to be stereo, revealing the critical size for the two-dimensional (2D) to three-dimensional (3D) structural transition. Our calculations demonstrate that ML is indeed powerful in describing the interaction of Au atoms and provides a new paradigm on accelerating the search of structures.