2024 AIChE Annual Meeting

Session: Automated Molecular and Materials Discovery: Integrating Machine Learning, Simulation, and Experiment

We invite contributions that focus on the use of high-throughput experimentation, computational modeling and simulation, and/or artificial intelligence, machine learning, and data science to advance the goal of autonomous, closed-loop molecular and materials discovery and engineering.

Chair

Co-Chairs

Yaxin An, Virginia Tech (Virginia Polytechnic Institute)

Presentations

12:30 PM

(673a) High-Throughput Virtual Screening and Hybrid Computational/Experimental Active Learning for Novel Hydrogel-Nanoparticle Sensors for Fentanyl Detection
Armin Shayesteh Zadeh, Alexander Winton, Matthew Coppock, Joseph M. Palomba, Andrew Ferguson

12:45 PM

(673b) Computational Discovery of Metal-Organic Frameworks with High Water Uptake Capacity for Next-Generation Membranes
Akash Ball, Shuwen Yue, Gianmarco Terrones, Heather Kulik

01:00 PM

(673c) Bespoke Nanoparticle Synthesis and Chemical Knowledge Discovery Via Autonomous Experimentations
Hyuk Jun Yoo, Nayeon Kim, Heeseung Lee, Daeho Kim, Leslie C. O. Tiong, Hyobin Nam, Chansoo Kim, Seung Yong Lee, Kwan-Young Lee, Donghun Kim, Sang Soo Han

01:15 PM

(673d) Multi-Objective Bayesian Optimisation for Sustainable Reactions Development
Jiyizhe Zhang, Alexei A. Lapkin

01:30 PM

(673e) Improving Uncertainty Estimation Based on Latent Space Distance for Graph Neural Network Potentials
Joseph Musielewicz, John Kitchin

01:45 PM

(673f) Multi-Objective Inverse Molecular Design of CO2 Capturing Agents
Zisheng Zhang, Jenny Yang, Anastassia Alexandrova

02:00 PM

(673g) Computational Protein-Ligand Co-Design for Enhancing Extracellular Electron Transfer in Lactiplantibacillus Plantarum
Vladimir Porokhin, Soha Hassoun, Anne Brown

02:15 PM

(455f) Machine Learning-Enabled Exploration of the Electrochemical Stability of Real-Scale Metallic Nanoparticles
Sang Soo Han