Software
I develop open-source software tools for computational materials science research. These packages support lattice modeling, solid-state reaction simulation, and crystallographic algorithms.
rxn-ca
A cellular automaton simulation for predicting solid-state synthesis reaction outcomes. ReactCA predicts the phases that appear during a solid-state reaction using thermodynamic data from the Materials Project.
GitHub | Documentation | Paper
Citation: M.C. Gallant, M.J. McDermott, B. Li, K.A. Persson, “ReactCA: A Cellular Automaton Simulation for Predicting Solid-State Reaction Outcomes,” Chemistry of Materials (2024).
pylattica
A simple framework for prototyping lattice evolution simulations including cellular automata, lattice gas simulations, and lattice Monte Carlo. Useful for constructing models where simulation states evolve through repeated application of rules across a network of interconnected sites.
GitHub | Documentation | Paper
Citation: M.C. Gallant, K.A. Persson, “pylattica: a package for prototyping lattice models in chemistry and materials science,” Journal of Open Source Software (2024). DOI: 10.21105/joss.06170
crystal-normal-form
A Python implementation of the Crystal Normal Form algorithm and representation, enabling canonical integer representation of 3D crystal structures to eliminate representational ambiguities.
Based on: D. Mrdjenovich, K.A. Persson, “Crystallographic map: A general lattice and basis formalism enabling efficient and discretized exploration of crystallographic phase space,” Physical Review Materials 8(3):033401 (2024). DOI: 10.1103/PhysRevMaterials.8.033401