arXiv subjects

Pierre Villars

Publications and source records attributed to Pierre Villars.

3 recordsLinked to original sources

arXiv2021

OPTIMADE, an API for exchanging materials data

The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification.

cond-mat.mtrl-sci↗

arXiv2021

Data-driven relationship of atomic structure and physical properties as the holistic view on the materials science fundamentals

The fundamental relationship of the atomic structure (represented by its atomic property parameters, APPs) and its physical properties of a specific inorganic substance can be realized in the bottom-up data-centric and the top-down knowledge physics-centric ways. Nowadays these two approaches compete and enhance one another qualitatively and quantitatively. We present our own holistic method and implementation, based on the PAULING FILE peer-reviewed inorganic substances database, the world largest materials database containing under one shelter crystallographic structures, phase diagrams and large variety of physical properties of single-phase inorganic substances. In addition we present generated machine-learning data, as well as simulated DFT physics-centered data, which are in close connection and comparison with the PAULING FILE peer-reviewed reference data.

cond-mat.mtrl-sci↗

arXiv2018

Quantitative trends in 8 physical properties of 115000 inorganic compounds gained by machine learning

We applied the decision trees (random forest) machine-learning technique for the large experimental materials dataset PAULING FILE, compiled from the world's peer-reviewed literature. The training and validation data were extracted from the hundreds of thousands of publications in materials science (1891-2017). Then, for the nearly 115'000 distinct inorganic compounds we predicted 8 thermodynamic, mechanical, and electronic properties, using the only crystalline structures as an input. For the predicted physical properties we observed certain periodical patterns in all unary, binary, ternary, and quaternary compounds. We also solved a reversed task of predicting the possible crystalline structure based on a given combination of values of the 8 mentioned properties. Therefore our observations may play a role of the periodic table, formulated not for the chemical elements, but for the entire set of materials.

cond-mat.mtrl-sci↗