activity
20222026
most citedA machine learning-based classification approach for phase diagram prediction

46 citations · 92 across the 7 of their papers we have counts for

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2 papers · 1 filter

cond-mat.mtrl-sci2025★ 3 cited

aLLoyM: A large language model for alloy phase diagram prediction

Yuna Oikawa, Guillaume Deffrennes, Taichi Abe +2

Large Language Models (LLMs) are general-purpose tools with wide-ranging applications, including in materials science. In this work, we introduce aLLoyM, a fine-tuned LLM specifica…

cond-mat.mtrl-sci2025

Active Learning for Predicting the Enthalpy of Mixing inBinary Liquids Based on Ab Initio Molecular Dynamics

Quentin Bizot, Ryo Tamura, Guillaume Deffrennes

The enthalpy of mixing in the liquid phase is an important property for predicting phase formation in alloys. It can be estimated in a large compositional space from pair wise inte…