matscipy: materials science at the atomic scale with Python

Abstract

Behaviour of materials is governed by physical phenomena that occur at an extreme range of length and time scales. Computational modelling requires multiscale approaches. Simulation techniques operating on the atomic scale serve as a foundation for such approaches, providing necessary parameters for upper-scale models. The physical models employed for atomic simulations can vary from electronic structure calculations to empirical force fields. However, construction, manipulation and analysis of atomic systems are independent of the given physical model but dependent on the specific application. matscipy implements such tools for applications in materials science, including fracture, plasticity, tribology and electrochemistry. Statement of need The Python package matscipy contains a set of tools for researchers using atomic-scale models in materials science. In atomic-scale modelling, the primary numerical object is a discrete point in three-dimensional space that represents the position of an individual atom. Simulations are often dynamical, where configurations change over time and each atom carries a velocity. Complexity emerges from the interactions of many atoms, and numerical tools are required for generating initial atomic configurations and for analysing output of such dynamical simulations, most commonly to connect local geometric arrangements of atoms to physical processes. An example, described in more detail below, is the detection of the tip of a crack that moves through a solid body. We never see individual atoms at macroscopic scales. To understand the behaviour of everyday objects, atomic-scale information needs to be transferred to the continuum scale. This is the Grigorev et al. (2024). matscipy: materials science at the atomic scale with Python. Journal of Open Source Software, 9(93), 5668. https: //doi.org/10.21105/joss.05668.