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cs.AI2026

Predicting Space Groups of Double Perovskites by LLM with Dynamic Few-Shot Learning

Jongwon Park, Inhyo Lee, Junhyeong Lee +1

Double perovskites (DPs) offer broad compositional tunability, but predicting the space groups (SGs) of stable structures remains difficult because available datasets are often str…

cs.AI2026

A Multi-Agent Framework for Automated Coarse-Grained Molecular Dynamics of Polymers

Joohee Choi, Junhyeong Lee, Seunghwa Ryu

Coarse-grained (CG) molecular dynamics extends polymer simulation beyond the scales accessible to all-atom (AA) methods, but bottom-up CG modeling is laborious. The CG resolution i…

cs.AI2025

Enhanced Conditional Generation of Double Perovskite by Knowledge-Guided Language Model Feedback

Inhyo Lee, Junhyeong Lee, Jongwon Park +2

Double perovskites (DPs) are promising candidates for sustainable energy technologies due to their compositional tunability and compatibility with low-energy fabrication, yet their…

cs.AI2025

IM-Chat: A Multi-agent LLM Framework Integrating Tool-Calling and Diffusion Modeling for Knowledge Transfer in Injection Molding Industry

Junhyeong Lee, Joon-Young Kim, Heekyu Kim +2

The injection molding industry faces critical challenges in preserving and transferring field knowledge, particularly as experienced workers retire and multilingual barriers hinder…

cs.AI2025

Toward Knowledge-Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human-AI Synergy

Hugon Lee, Hyeonbin Moon, Junhyeong Lee +1

Artificial intelligence (AI) is reshaping inverse design in manufacturing, enabling high-performance discovery in materials, products, and processes. However, purely data-driven ap…