85 citations · 131 across the 12 of their papers we have counts for
5 papers · 1 filter
Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions
Yuri Alexeev, Maximilian Amsler, Paul Baity +124
Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of e…
Formulation Graphs for Mapping Structure-Composition of Battery Electrolytes to Device Performance
Vidushi Sharma, Maxwell Giammona, Dmitry Zubarev +5
Advanced computational methods are being actively sought for addressing the challenges associated with discovery and development of new combinatorial material such as formulations.…
Beyond Chemical Language: A Multimodal Approach to Enhance Molecular Property Prediction
Eduardo Soares, Emilio Vital Brazil, Karen Fiorela Aquino Gutierrez +4
We present a novel multimodal language model approach for predicting molecular properties by combining chemical language representation with physicochemical features. Our approach,…
Human-AI Co-Creation Approach to Find Forever Chemicals Replacements
Juliana Jansen Ferreira, Vinícius Segura, Joana G. R. Souza +4
Generative models are a powerful tool in AI for material discovery. We are designing a software framework that supports a human-AI co-creation process to accelerate finding replace…
Domain-agnostic and Multi-level Evaluation of Generative Models
Girmaw Abebe Tadesse, Jannis Born, Celia Cintas +4
While the capabilities of generative models heavily improved in different domains (images, text, graphs, molecules, etc.), their evaluation metrics largely remain based on simplifi…