The study of alloys using computational methods has been a difficult task due to the usually unknown stoichiometry and local atomic ordering of the different structures experimentally. In order to combat this, first-principles methods have been coupled with statistical methods such as the Cluster Expansion formalism in order to construct the energy hull diagram, which helps to determine if an alloyed structure can exist in nature. Traditionally, density functional theory (DFT) has been used in such workflows. In this work we propose to use chemically accurate many-body variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC) methods to construct the energy hull diagram of an alloy system, due to the fact that such methods have a weaker dependence on the starting wavefunction and density functional, scale similarly to DFT with the number of electrons, and have had demonstrated success for a variety of materials. To carry out these simulations in a high-throughput manner, we propose a method called Jastrow sharing, which involves recycling the optimized Jastrow parameters between alloys with different stoichiometries. We show that this eliminates the need for extra VMC Jastrow optimization calculations and results in a significant computational cost savings (on average 1/4 savings of total computational time). Since it is a novel post-transition metal chalcogenide alloy series that has been synthesized in its few-layer form, we used monolayer $GaS_xSe_{1-x}$ as a case study for our workflow. By extensively testing our Jastrow sharing procedure for monolayer $GaS_xSe_{1-x}$ and quantifying the cost savings, we demonstrate how a pathway towards chemically accurate high-throughput simulations of alloys can be achieved using many-body VMC and DMC methods.
University of California, Irvine（加州大学尔湾分校）；University of New Mexico（新墨西哥大学）；Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院）；Massachusetts Institute of Technology（麻省理工学院）；University of California, San Diego（加州大学圣地亚哥分校）；Johns Hopkins University（约翰斯·霍普金斯大学）；Stony Brook University（石溪大学）；University of Arizona（亚利桑那大学）；Los Alamos National Lab（洛斯阿拉莫斯国家实验室）；University of Tennessee, Knoxville（田纳西大学诺克斯维尔分校）
Chemical short-range order controls deformation pathways in a complex concentrated alloy
Federal University of São Carlos（圣卡洛斯联邦大学）；Uppsala University（乌普萨拉大学）；Wallenberg Initiative Materials Science for Sustainability, Uppsala University（乌普萨拉大学瓦伦堡可持续发展材料科学倡议）；Massachusetts Institute of Technology（麻省理工学院）；The University of Manchester（曼彻斯特大学）；Baylor University（贝勒大学）；AF Research Laboratory, Materials and Manufacturing Directorate, Wright-Patterson AFB（赖特-帕特森空军基地材料与制造局空军研究实验室）
Crystal Nucleation in Al-Ni Alloys: an Unsupervised Chemical and Topological Learning Approach
结晶是材料凝固的基本过程，决定了材料的微观结构。在原子尺度上的复杂现象的驱动下，它对合金的理解仍然是难以捉摸的。采用大尺度分子动力学模拟方法研究了典型过冷Al-Ni二元合金的均匀形核途径。一个无监督的拓扑学习分析表明，成核集首先从化学排序，其次是键取向排序的基础晶相。我们的研究结果还表明，不同的多晶型物的选择，这取决于组合物。Al 50 Ni 50的形核过程是一个单一的台阶，B2短程有序的出现，而Al 25 Ni 75的形核过程是一个向L12相的台阶形核过程。进一步讨论了纯Al和纯Ni对应物形核的影响。
Kinetic Pathways of Phase Decomposition Using Steepest-Entropy-Ascent Quantum Thermodynamics Modeling. Part I: Continuous and Discontinuous Transformations
Edge Dislocation Mediated Anomalous Charge Transfer in Face Centered Cubic High Entropy Alloys
School of Materials Science and Technology, IIT-BHU（印度理工联合学院瓦拉纳西分校材料科学与技术学院）；National Centre for Computational Sciences, Oak Ridge National Laboratory（橡树岭国家实验室国家计算科学中心）；Department of Metallurgy and Materials Engineering, IIEST Shibpur（IIEST Shibpur冶金与材料工程系）
Mo-Re-W Alloys for High Temperature Applications: Phase Stability, Elasticity, and Thermal Property Insights via Multi-Cell Monte Carlo and Machine Learning
Alloy engineering of Magnetic phases in two-dimensional Chromium Trihalides
Institute of Physics, University of São Paulo（圣保罗大学物理研究所）；Department of Theoretical and Computational Chemistry, National University of Córdoba（科尔多瓦国立大学理论与计算化学系）；Department of Materials Engineering, University of São Paulo（圣保罗大学材料工程系）
Concentration-Dependent Tungsten Effects on Chemical Short-Range Order and Deformation Behavior in Ni-W alloys
Central Iron and Steel Research Institute（钢铁研究总院）；Northwestern University（西北大学）；University of Virginia（弗吉尼亚大学）；Hebei University（河北大学）；Xiangtan University（湘潭大学）；Yangjiang Advanced Alloys Laboratory（阳江先进合金实验室）；Northwestern University Center for Atom Probe Tomography (NUCAPT)（西北大学原子探针断层扫描中心 (NUCAPT)）；The NUANCE Center, Northwestern University（西北大学NUANCE中心）
Benchmarking Chemically Scalable Machine-Learning Interatomic Potentials for Large-Scale Simulations of Multicomponent Alloys
State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences（中国科学院力学研究所非线性力学国家重点实验室）；Department of Materials Science and Engineering, Faculty of Mechanical Engineering, Delft University of Technology（代尔夫特理工大学机械工程学院材料科学与工程系）；Faculty of Engineering Technology, University of Twente（特温特大学工程技术学院）；Laboratory for multiscale mechanics and medical science, SV LAB, School of Aerospace, Xi’an Jiaotong University（西安交通大学航天学院SV多尺度力学与医学科学实验室）；College of Physical Science and Technology, Bohai University（渤海大学物理科学与技术学院）
Mechanistic insights into hydrogen reduction of multicomponent oxides via in-situ high-energy X-ray diffraction
Max Planck Institute for Sustainable Materials（马克斯·普朗克可持续材料研究所）；Institute of Hydrogen Technology, Helmholtz-Zentrum hereon GmbH（赫姆霍兹-海伦有限责任公司氢能技术研究所）；Delft University of Technology（代尔夫特理工大学）
High-Entropy Hydrides for Fast and Reversible Hydrogen Storage at Room Temperature: Binding-Energy Engineering via First-Principles Calculations and Experiments
Expert-Grounded Automatic Prompt Engineering for Extracting Lattice Constants of High-Entropy Alloys from Scientific Publications using Large Language Models
University of Virginia（弗吉尼亚大学）；Pennsylvania State University（宾夕法尼亚州立大学）
Ductility and Brittle Fracture of Tungsten by Disconnection Pile-up on Twin Boundaries
Lawrence Livermore National Laboratory（劳伦斯利弗莫尔国家实验室）；Los Alamos National Laboratory（洛斯阿拉莫斯国家实验室）；University of California Irvine（加州大学尔湾分校）；University of California Los Angeles（加州大学洛杉矶分校）；Lehigh University（理海大学）；Northwestern University（西北大学）
