1 citations · 1 across the 4 of their papers we have counts for
4 papers
Crystal-structure design by agentic AI in a language of motifs
Dinh-Khiet Le, Minh-Quyet Ha, Hong-Phuc Vu-Dinh +6
Data-driven materials discovery interpolates more reliably than it extrapolates and seldom reveals new structure types. We present MatEvolve, an agentic-AI framework that designs c…
Synergistic Fusion of Multi-Source Knowledge via Evidence Theory for High-Entropy Alloy Discovery
Minh-Quyet Ha, Dinh-Khiet Le, Duc-Anh Dao +6
Discovering novel high-entropy alloys (HEAs) with desirable properties is challenging due to the vast compositional space and complex phase formation mechanisms. Efficient explorat…
Categorical data clustering: 25 years beyond K-modes
Tai Dinh, Wong Hauchi, Philippe Fournier-Viger +4
The clustering of categorical data is a common and important task in computer science, offering profound implications across a spectrum of applications. Unlike purely numerical dat…
Explainable Machine Learning for Materials Discovery: Predicting the Potentially Formable Nd-Fe-B Crystal Structures and Extracting Structure-Stability Relationship
Tien-Lam Pham, Duong-Nguyen Nguyen, Minh-Quyet Ha +3
New Nd-Fe-B crystal structures can be formed via the elemental substitution of LATX host structures, including lanthanides LA, transition metals T, and light elements X as B, C, N,…