3 papers
physics.chem-ph2026
Generative Chemical Language Models for Energetic Materials Discovery
Andrew Salij, R. Seaton Ullberg, Megan C. Davis +5
The discovery of new energetic materials remains a pressing challenge hindered by limited availability of high-quality data. To address this, we have developed generative molecular…
cond-mat.mtrl-sci2025
Hierarchical Multi-agent Large Language Model Reasoning for Autonomous Functional Materials Discovery
Samuel Rothfarb, Megan C. Davis, Ivana Matanovic +3
Artificial intelligence is reshaping scientific exploration, but most methods automate procedural tasks without engaging in scientific reasoning, limiting autonomy in discovery. We…
cond-mat.mtrl-sci2024
Design of Amine-Functionalized Materials for Direct Air Capture Using Integrated High-Throughput Calculations and Machine Learning
Megan C. Davis, Wilton J. M. Kort-Kamp, Ivana Matanovic +2
Direct air capture (DAC) of carbon dioxide is a critical technology for mitigating climate change, but current materials face limitations in efficiency and scalability. We discover…