CLAMM: a spin CLuster expansion--Monte Carlo toolkit for Alloys and Magnetic Materials

TL;DR

CLAMM is an open-source toolkit that integrates DFT data with lattice models and Monte Carlo simulations to study finite-temperature magnetism and phase behavior in alloy and magnetic materials.

Contribution

It introduces a comprehensive, modular toolkit combining data preparation, model fitting, and Monte Carlo simulation for magnetic alloys, enhancing computational materials research capabilities.

Findings

Enables simulation of phase transformations in magnetic alloys.

Supports generating special quasi-random structures.

Allows analysis of magnetic and alloy configurational entropies.

Abstract

Finite-temperature magnetism gives rise to many phenomena in alloy materials, such as magnetic phase transformations, short or medium range order in magnetic alloys, spin waves, critical phenomena, and the magnetocaloric effect. Lattice models, such as the Ising, Potts, cluster expansion, and magnetic cluster expansion models, are powerful tools for studying complex magnetic alloys and compounds. In this paper we introduce CLAMM, which is a new open source toolkit for developing custom lattice models from density functional theory (DFT) data sets. The toolkit is comprised of three main components. The first component is CLAMM_Prep, a python tool that converts data sets consisting of the Vienna Ab-initio Simulation Package (VASP) DFT simulations into a compact format. The second component, CLAMM_Fit, is also python-based and uses the compact data set to parameterize a lattice model, chosen from a set of available options (cluster expansion, Ising, and others). The third component is CLAMM_MC, which is a C++ Monte Carlo solver for generating ensembles of configurations, accounting for both magnetic and alloy configurational entropies, at different temperatures. These ensembles and their analysis can be used for simulating phase transformations and constructing phase diagrams. The code can also be used for generating special quasi-random structures and structures with user-defined short-range order. This document provides a comprehensive overview of each CLAMM tool in order to demonstrate CLAMM's potential for the computational materials community.