2024 AIChE Annual Meeting

Session: Applications of Data Science to Molecules and Materials

Chair

Johannes Hachmann, University at Buffalo, SUNY

Presentations

03:30 PM

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

04:00 PM

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

04:30 PM

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

05:00 PM

(435d) Camd.Jl: A Generalized Computer-Aided Molecular Design Framework
Pierre Walker, Matthew Cox, Sriteja Mantha, Alejandro Gallegos, Yasemin Basdogan, Zhen-Gang Wang

05:15 PM

(435e) Data-Driven Electrolyte Design for Lithium Metal Batteries
Solomon Oyakhire, Yi Cui, Stacey Bent

05:30 PM

(435f) Residual Learning-Based Model for Lithium-Ion Battery End-of-Life Prediction
Jaewook Lee, Seyeong Park, Seongmin Heo