An open-source data-analysis framework 2DMAT has been developed for experimental measurements of two-dimensional material structures. 2DMAT offers five analysis methods: (i) Nelder-Mead optimization, (ii) grid search, (iii) Bayesian optimization, (iv) replica exchange Monte Carlo method, and (v) population-annealing Monte Carlo method. Methods (ii) through (v) are implemented by parallel computation,which is efficient not only for personal computers but also for supercomputers.The current version of 2DMAT is applicable to total-reflection high-energy positron diffraction (TRHEPD), surface X-ray diffraction (SXRD), and low-energy electron diffraction (LEED) experiments by installing corresponding forward problem solvers that generate diffraction intensity data from a given dataset of the atomic positions. The analysis methods are general and can be applied also to other experiments and problems.
This paper introduces persistent homology, which is a powerful tool to characterize the shape of data using the mathematical concept of topology. We explain the fundamental idea of persistent homology from scratch using some examples. We also review some applications of persistent homology to materials researches and software for persistent homology data analysis. HomCloud, one of persistent homology software, is especially featured in this paper.
Agentic programs: an emerging form of scientific software in computational materials science
Research Institute of Advanced Materials, Seoul National University（首尔国立大学先进材料研究所）；Department of Materials Science and Engineering, Seoul National University（首尔国立大学材料科学与工程系）；Center for AI and Natural Sciences, Korea Institute for Advanced Study（韩国高等研究院人工智能与自然科学中心）
In this paper we present CTRAMER (Charge Transfer RAtes from Molecular dynamics, Electronic structure, and Rate theory), an open source software package for calculating interfacial charge transfer (CT) rate constants in organic photovoltaic (OPV) materials based on ab initio calculations and molecular dynamics simulations. The software is based on identifying representative donor acceptor geometries within interfacial structures obtained from molecular dynamics simulation of donor acceptor blends and calculating the corresponding Fermi s golden rule CT rate constants within the framework of th…
Computational acceleration of performance-metric-based materials discovery via high-throughput screening and machine learning methods is becoming widespread. Nevertheless, development and optimization of the opto-electronic properties that depend on dilute concentrations of point defects in new materials have not significantly benefited from these advances. Here, we present an informatics and simulation suite to computationally accelerate these processes. This will enable faster and more fundamental materials research, and reduce the cost and time associated with the materials development cycl…
Recent research in materials science opens exciting perspectives to design novel quantum materials and devices, but it calls for quantitative predictions of properties which are not accessible in standard first principles packages. PAOFLOW is a software tool that constructs tight-binding Hamiltonians from self-consistent electronic wavefunctions by projecting onto a set of atomic orbitals. The electronic structure provides numerous materials properties that otherwise would have to be calculated via phenomenological models. In this paper, we describe recent re-design of the code as well as the …
Extended defects in crystals, such as dislocations, stacking faults and grain boundaries, play a crucial role in determining a wide variety of materials properties. Extended defects can also lead to novel electronic properties in two-dimensional materials, as demonstrated by recent discoveries of emergent electronic phenomena in twisted graphene bilayers. This paper describes several approaches to construct crystallographic models of two-dimensional extended defects in crystals for first-principles electronic structure calculations, including (i) crystallographic models to parameterize general…
Epoxy is widely used primarily as a matrix material in the manufacture of polymer matrix composite. Epoxy behavior under compression load has to be understood before the mechanical behavior of polymer matrix composite can be accurately predicted. Simulation model combined with experiment and image analysis have been used to investigate internal response of epoxy polymeric materials subjected to compressive loads. In the experiment, small carbon-based material rods are inserted in the epoxy. The samples are held in one side and subjected to compressive load on the other side. All the samples sw…
Perturbo is a software package for first-principles calculations of charge transport and ultrafast carrier dynamics in materials. The current version focuses on electron-phonon interactions and can compute phonon-limited transport properties such as the conductivity, carrier mobility and Seebeck coefficient. It can also simulate the ultrafast nonequilibrium electron dynamics in the presence of electron-phonon scattering. Perturbo uses results from density functional theory and density functional perturbation theory calculations as input, and employs Wannier interpolation to reduce the computat…
NIMO: A Software Platform for Closed-Loop Materials Exploration with Diverse AI Algorithms
Center for Basic Research on Materials, National Institute for Materials Science（材料基础研究所，日本国家材料科学研究所）；Graduate School of Frontier Sciences, The University of Tokyo（东京大学前沿科学研究生院）；Center for Green Research on Energy and Environmental Materials, National Institute for Material Science（能源与环境材料绿色研究中心，日本国家材料科学研究所）
Quantum ESPRESSO is an integrated suite of computer codes for electronic-structure calculations and materials modeling, based on density-functional theory, plane waves, and pseudopotentials (norm-conserving, ultrasoft, and projector-augmented wave). Quantum ESPRESSO stands for "opEn Source Package for Research in Electronic Structure, Simulation, and Optimization". It is freely available to researchers around the world under the terms of the GNU General Public License. Quantum ESPRESSO builds upon newly-restructured electronic-structure codes that have been developed and tested by some of the …
As data science and machine learning methods are taking on an increasingly important role in the materials research community, there is a need for the development of machine learning software tools that are easy to use (even for nonexperts with no programming ability), provide flexible access to the most important algorithms, and codify best practices of machine learning model development and evaluation. Here, we introduce the Materials Simulation Toolkit for Machine Learning (MAST-ML), an open source Python-based software package designed to broaden and accelerate the use of machine learning …
Recent advances in computational materials science present novel opportunities for structure discovery and optimization, including uncovering of unsuspected compounds and metastable structures, electronic structure, surface, and nano-particle properties. The practical realization of these opportunities requires systematic generation and classification of the relevant computational data by high-throughput methods. In this paper we present Aflow (Automatic Flow), a software framework for high-throughput calculation of crystal structure properties of alloys, intermetallics and inorganic compounds…
MPC (Magneto-Photonic Crystal) Optimisation is a feature-rich Windows software application designed to enable researchers to analyze the optical and magneto-optical spectral properties of multilayers containing gyrotropic constituents. A set of computational algorithms aimed at enabling the design optimization and optical or magneto-optical (MO) spectral analysis of 1D magnetic photonic crystals (MPC) is reported, together with its Windows software implementation. Relevant material property datasets (e.g., the optical spectra of refractive index, absorption, and gyration) of several important …
FHI-aims is a quantum mechanics software package based on numeric atom-centered orbitals (NAOs) with broad capabilities for all-electron electronic-structure calculations and ab initio molecular dynamics. It also connects to workflows for multi-scale and artificial intelligence modeling.
NIMS-OS: An automation software to implement a closed loop between artificial intelligence and robotic experiments in materials science
Center for Basic Research on Materials（材料基础研究中心）；National Institute for Materials Science（国家材料科学研究所）；Graduate School of Frontier Sciences, The University of Tokyo（东京大学前沿科学研究生院）；Research Center for Energy and Environmental Materials(GREEN)（能源与环境材料研究中心（GREEN））；Center for Advanced Battery Collaboration, Research Center for Energy and Environmental Materials (GREEN)（先进电池协作中心，能源与环境材料研究中心（GREEN））
Characterizing microstructure-material-property relations calls for software tools which extract point-cloud- and continuum-scale-based representations of microstructural objects. Application examples include atom probe, electron, and computational microscopy experiments. Mapping between atomic- and continuum-scale representations of microstructural objects results often in representations which are sensitive to parameterization; however assessing this sensitivity is a tedious task in practice. Here, we show how combining methods from computational geometry, collision analyses, and graph analy…
Orientation Mapping via Dictionary Indexing of AC-STEM Kikuchi patterns using Open-source Software
Philipps-Universität Marburg（马尔堡菲利普大学）；Marburg Center for Quantum Materials and Sustainable Technology (mar.quest) and Department of Physics, Philipps-Universität Marburg（马尔堡量子材料与可持续技术中心（mar.quest）及马尔堡菲利普大学物理系）；Institute for Ceramic Materials and Technologies (IKMT), University of Stuttgart（斯图加特大学陶瓷材料与技术研究所（IKMT））
The present paper reports on the recent activity of the data analysis software development for total-reflection high-energy positron diffraction (TRHEPD), a novel experimental technique for surface structure determination. Experiments using TRHEPD are being conducted intensively at the Slow Positron Facility, Institute of Materials Structure Science, High Energy Accelerator Research Organization, revealing surface structure of interest. The data analysis software provides a solution to the inverse problem in which the atomic positions of a surface structure are determined from the experimental…
Combinatorial experiments involve synthesis of sample libraries with lateral composition gradients requiring spatially-resolved characterization of structure and properties. Due to maturation of combinatorial methods and their successful application in many fields, the modern combinatorial laboratory produces diverse and complex data sets requiring advanced analysis and visualization techniques. In order to utilize these large data sets to uncover new knowledge, the combinatorial scientist must engage in data science. For data science tasks, most laboratories adopt common-purpose data manageme…
