Papers › FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions
FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions
Anuroop Sriram, Benjamin Kurt Miller, Ricky T. Q. Chen, Brandon M. Wood
Material discovery is a critical area of research with the potential to revolutionize various fields, including carbon capture, renewable energy, and electronics. However, the immense scale of the chemical space makes it challenging to explore all possible materials experimentally. In this paper, we introduce FlowLLM, a novel generative model that combines large language models (LLMs) and Riemannian flow matching (RFM) to design novel crystalline materials. FlowLLM first fine-tunes an LLM to learn an effective base distribution of meta-stable crystals in a text representation. After converting to a graph representation, the RFM model takes samples from the LLM and iteratively refines the coordinates and lattice parameters. Our approach significantly outperforms state-of-the-art methods, increasing the generation rate of stable materials by over three times and increasing the rate for stable, unique, and novel crystals by ∼50% - a huge improvement on a difficult problem. Additionally, the crystals generated by FlowLLM are much closer to their relaxed state when compared with another leading model, significantly reducing post-hoc computational cost.
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5caf35d04f053859 · report
Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Unconditional Crystal Generation | MP20 | FlowLLM | DFT Stable, Unique, Novel Rate | 4.7 | #2 of 3 | Archive leaderboard | report |
| Unconditional Crystal Generation | MP20 | FlowLLM | Validity | 90.81 | #2 of 3 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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