2 papers
cond-mat.mtrl-sci2026
Data-driven Design of Metal-Organic Frameworks with Tunable Negative Thermal Expansion
Prathami Divakar Kamath, Francesco Tavani, Alin Marin Elena +6
Materials with negative thermal expansion (NTE) are essential for applications requiring precise control of thermal expansion. Owing to their exceptional chemical tunability, flexi…
cond-mat.mtrl-sci2025
System of Agentic AI for the Discovery of Metal-Organic Frameworks
Theo Jaffrelot Inizan, Sherry Yang, Aaron Kaplan +12
Generative models and machine learning promise accelerated material discovery in MOFs for CO2 capture and water harvesting but face significant challenges navigating vast chemical…