Featured image of post matscipy: materials science at the atomic scale with Python

matscipy: materials science at the atomic scale with Python

Authors: Petr Grigorev, Lucas Frérot, Fraser Birks, Adrien Gola, Jacek Golebiowski, Jan Grießer, Johannes L. Hörmann, Andreas Klemenz, Gianpietro Moras, Wolfram G. Nöhring, Jonas A. Oldenstaedt, Punit Patel, Thomas Reichenbach, Thomas Rocke, Lakshmi Shenoy, Michael Walter, Simon Wengert, Lei Zhang, James R. Kermode, Lars Pastewka

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.

Cover art: made with Blender, BCC edge dislocation junction data provided by Petr Grigorev.

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