2020 Virtual AIChE Annual Meeting

Session: Applications of Data Science in Molecular Sciences I

Chair

Ferguson, A., University of Chicago

Co-Chairs

White, A., University of Rochester
Hachmann, J., University at Buffalo, SUNY

Presentations

08:00 AM

(285a) Prediction of Adsorption Thermodynamics in MOFs and Cofs Via Ensemble Learning

08:15 AM

(285b) Message Passing Neural Networks for Partial Charge Assignment in Metal-Organic Frameworks

08:30 AM

(285c) High-Throughput Discovery of Metal-Organic Frameworks for Cooperative CO2 Adsorption

08:45 AM

(285d) Gaussian Process-Based Model Order Reduction for the Prediction of Gaseous Storage in Metal-Organic Frameworks.

09:00 AM

(285e) A Database with Automated Quantum Chemistry Calculations and Machine Learning for Functional Transition Metal Complex Discovery

09:15 AM

(285f) Do Machine-Learned Formation Energies Enable Accurate Predictions of Compound Stabilities?

09:30 AM

(285g) Physically Informed Deep Learning for Accelerated Photosensitizer Discovery

09:45 AM

(285i) Quantum Chemistry-Informed Active Learning to Accelerate the Design and Discovery of Sustainable Energy Storage Materials

10:00 AM

(285j) Color As a Source of Information in Liquid Crystal Sensors

10:15 AM

(285k) A Deep-Learning Potential for Crystalline and Amorphous Li-Si Alloys