Unified Model for Crystalline Material Generation
Astrid Klipfel, Ya\"el Fr\'egier, Adlane Sayede, Zied, Bouraoui

TL;DR
This paper introduces two unified generative models for crystal materials that simultaneously consider lattice and atomic positions using periodic equivariant architectures, enabling the creation of thermodynamically stable crystal structures.
Contribution
The paper presents novel models that integrate lattice and atomic position generation with equivariant architectures, advancing crystal material design.
Findings
Models can learn arbitrary lattice deformations
Generated structures reach thermodynamic stability
Code and data are publicly available
Abstract
One of the greatest challenges facing our society is the discovery of new innovative crystal materials with specific properties. Recently, the problem of generating crystal materials has received increasing attention, however, it remains unclear to what extent, or in what way, we can develop generative models that consider both the periodicity and equivalence geometric of crystal structures. To alleviate this issue, we propose two unified models that act at the same time on crystal lattice and atomic positions using periodic equivariant architectures. Our models are capable to learn any arbitrary crystal lattice deformation by lowering the total energy to reach thermodynamic stability. Code and data are available at https://github.com/aklipf/GemsNet.
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Taxonomy
TopicsMachine Learning in Materials Science · Quasicrystal Structures and Properties · X-ray Diffraction in Crystallography
