5 citations · 8 across the 8 of their papers we have counts for
4 papers · 1 filter
NIMO: A Software Platform for Closed-Loop Materials Exploration with Diverse AI Algorithms
Ryo Tamura, Naruki Yoshikawa, Koji Tsuda +1
Self-driving laboratories (SDLs), where artificial intelligence proposes subsequent experiments and robotic systems execute them, are rapidly becoming the vanguard of materials dis…
LLM-guided phase diagram construction through high-throughput experimentation
Ryo Tamura, Haruhiko Morito, Yuna Oikawa +7
Constructing phase diagrams for multicomponent alloys requires extensive experimental measurements and is a time-consuming task. Here we investigate whether large language models (…
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…
CRYSIM: Prediction of Symmetric Structures of Large Crystals with GPU-based Ising Machines
Chen Liang, Diptesh Das, Jiang Guo +3
Solving black-box optimization problems with Ising machines is increasingly common in materials science. However, their application to crystal structure prediction (CSP) is still i…