2024 AIChE Annual Meeting

Session: Applications of Data Science to Molecules and Materials

Chair

Hachmann, J., University at Buffalo, SUNY

Presentations

03:30 PM

(435a) Successful "Closed Loop" Materials Discovery: the Power and Challenges of Machine Learning

04:00 PM

(435b) Using Machine Learning to Overcome Limitations in Electronic Structure Methodology for Chemical Discovery

04:30 PM

(435c) Accelerating Nanoporous Materials Discovery for Gas Storage and Separations via Advanced Simulation and Materials Characterization

05:00 PM

(435d) Camd.Jl: A Generalized Computer-Aided Molecular Design Framework

05:15 PM

(435e) Data-Driven Electrolyte Design for Lithium Metal Batteries

05:30 PM

(435f) Residual Learning-Based Model for Lithium-Ion Battery End-of-Life Prediction