The automation of ab initio simulations is essential in view of performing high-throughput (HT) computational screenings oriented to the discovery of novel materials with desired physical properties. In this work, we propose algorithms and implementations that are relevant to extend this approach beyond density functional theory (DFT), in order to automate many-body perturbation theory (MBPT) calculations. Notably, a novel algorithm pursuing the goal of an efficient and robust convergence procedure for GW and BSE simulations is provided, together with its implementation in a fully automated framework. This is accompanied by an automatic GW band interpolation scheme based on maximally-localized Wannier functions, aiming at a reduction of the computational burden of quasiparticle band structures while preserving high accuracy. The proposed developments are validated on a set of representative semiconductor and metallic systems.
The HTC-Claw: Automating Discovery through High-Throughput Computational Campaigns
State Key Laboratory of Metal Matrix Composites, School of Materials Science and Engineering, Shanghai Jiao Tong University（上海交通大学材料科学与工程学院金属基复合材料国家重点实验室）
From MLIPs to Microstructure: A High-Throughput Computational Framework to Design Spinodal Alloys in High-Dimensional Composition Spaces via Analytic Derivatives of CALPHAD Model Predictions
Automated Workflow for Non-Empirical Wannier-Localized Optimal Tuning of Range-Separated Hybrid Functionals
University of California Berkeley（加州大学伯克利分校）；Lawrence Berkeley National Laboratory（劳伦斯伯克利国家实验室）；Université catholique de Louvain (UCLouvain)（天主教鲁汶大学）；Matgenix SRL（Matgenix有限责任公司）；Weizmann Institute of Science（魏茨曼科学研究所）；University of Massachusetts Amherst（马萨诸塞大学阿默斯特分校）；Kavli Energy NanoScience Institute at Berkeley（加州大学伯克利分校卡弗里能源纳米科学研究所）
Application of batch learning for boosting high-throughput ab initio success rates and reducing computational effort required using data-driven processes
GEWUM: General Exploration Workflow for the Utopia of Materials: A Unified Platform for Automated Structure Generation, Selection, and Validation
Suzhou Laboratory（苏州实验室）；Research and Development Institute of Northwestern Polytechnical University in Shenzhen（深圳西北工业大学研究院）；School of Naval Architecture and Maritime, Zhejiang Ocean University（浙江海洋大学船舶与海事学院）；School of Physical Science and Technology, Northwestern Polytechnical University（西北工业大学物理科学与技术学院）
High-throughput computation of electric polarization in solids via Berry flux diagonalization
University of Chicago（芝加哥大学）；Argonne National Laboratory（阿贡国家实验室）；Lawrence Berkeley National Laboratory（劳伦斯伯克利国家实验室）；University of California, Berkeley（加州大学伯克利分校）；Matgenix SRL（Matgenix有限公司）；Kavli Energy NanoSciences Institute at Berkeley（加州大学伯克利分校卡弗里纳米科学能源研究所）
Towards an automated workflow in materials science for combining multi-modal simulative and experimental information using data mining and large language models
Karlsruhe Institute of Technology (KIT)（卡尔斯鲁厄理工学院）；Karlsruhe University of Applied Sciences (HKA)（卡尔斯鲁厄应用技术大学）
Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows
Institute of Physical Metallurgy and Materials Physics, RWTH Aachen University（亚琛工业大学物理冶金与材料物理研究所）；Faculty of Georesources and Materials Engineering, RWTH Aachen University（亚琛大学地质资源与材料工程学院）
Noise-Aware Optimization in Nominally Identical Manufacturing and Measuring Systems for High-Throughput Parallel Workflows
organization= IMDEA Materials Institute , addressline= C Eric Kandel 2 , city= Getafe , postcode= 28906 , state= Madrid , country= Spain；organization= Applied Mathematics \& Computational Research Division, Lawrence Berkeley National Laboratory , city= Berkeley , state= CA , country= USA
dpti: An Automated Thermodynamic Integration Workflow for Phase Diagram Calculations with Machine Learning Interatomic Potentials
University of Alabama at Birmingham（阿拉巴马大学伯明翰分校）；Princeton University（普林斯顿大学）；University of Science and Technology of China（中国科学技术大学）；Suzhou Institute for Advanced Research, University of Science and Technology of China（中国科学技术大学苏州高等研究院）；Suzhou Big Data & AI Research and Engineering Center（苏州大数据与人工智能研究与工程中心）；AI for Science Institute（科学智能研究所）；DP Technology（深势科技）；Institute of Applied Physics and Computational Mathematics（应用物理与计算数学研究所）；College of Engineering, Peking University（北京大学工学院）
VibroML: an automated toolkit for high-throughput vibrational analysis and dynamic instability remediation of crystalline materials using machine-learned potentials
High-Throughput Study of Antisolvents on the Stability of Multicomponent Metal Halide Perovskites through Robotics-Based Synthesis and Machine Learning Approaches
Integration of Scanning Probe Microscope with High-Performance Computing: fixed-policy and reward-driven workflows implementation
University of Tennessee（田纳西大学）；Oxford Instruments Asylum Research（牛津仪器庇护研究公司）；Pacific Northwest National Laboratory（太平洋西北国家实验室）；National Cheng Kung University（国立成功大学）；the Pennsylvania State University（宾夕法尼亚州立大学）
