Exploring large language models for microstructure evolution in materials

TL;DR

This study explores the use of large language models to generate code for microstructure evolution simulations in materials, demonstrating their potential and limitations in handling complex multi-physics PDEs.

Contribution

First investigation into applying LLMs for microstructure modeling code generation, highlighting capabilities and current limitations in materials science research.

Findings

LLMs can generate multi-physics microstructure simulation code

Effective for simpler PDEs but struggle with complex coupled systems

Potential to accelerate materials research and education

Abstract

There is a significant potential for coding skills to transition fully to natural language in the future. In this context, large language models (LLMs) have shown impressive natural language processing abilities to generate sophisticated computer code for research tasks in various domains. We report the first study on the applicability of LLMs to perform computer experiments on microstructure pattern formation in model materials. In particular, we exploit LLM's ability to generate code for solving various types of phase-field-based partial differential equations (PDEs) that integrate additional physics to model material microstructures. The results indicate that LLMs have a remarkable capacity to generate multi-physics code and can effectively deal with materials microstructure problems up to a certain complexity. However, for complex multi-physics coupled PDEs for which a detailed understanding of the problem is required, LLMs fail to perform the task efficiently, since much more detailed instructions with many iterations of the same query are required to generate the desired output. Nonetheless, at their current stage of development and potential future advancements, LLMs offer a promising outlook for accelerating materials education and research by supporting beginners and experts in their physics-based methodology. We hope this paper will spur further interest to leverage LLMs as a supporting tool in the integrated computational materials engineering (ICME) approach to materials modeling and design.