2022 Annual Meeting

Session: Machine Learning for Soft Materials II

Chair

Co-Chairs

Pin-Kuang Lai, Stevens Institute of Technology

Presentations

03:35 PM

(656a) A New Computational-Experimental Screening Methodology Identifies More Effective Solvents for CO2 Capture
Frederick de Meyer, Alexey Orlov, Christophe Coquelet, Xavier Rozanska

03:50 PM

(656b) Characterization of Chemoresponsive Liquid Crystals Using Topological Descriptors and Machine Learning
Shengli Jiang, Victor Zavala, Nicholas L. Abbott, Nanqi Bao, Alexander Smith

04:05 PM

(656c) Physics-Informed Deep Neural Networks for Predicting Fluid Flow in Complex Porous Materials
Serveh Kamrava, Muhammad Sahimi

04:30 PM

(656d) Simulation of Neutron Dark Field Interferometry Data in Hierarchical Materials Using Small Angle Scattering Models
Katie Weigandt, Caitlyn Wolf, Ryan P. Murphy, Youngju Kim, Anis Ben Said, Sarah Robinson, M. Cyrus Daugherty, Michael Huber, David L. Jacobson, Jacob LaManna, Nikolai Klimov, Paul Kienzle, Peter Bajcsy, Daniel S. Hussey

04:45 PM

(656e) Developing an ML Algorithm to Predict the Aqueous Solubility of Polymers and Organic Compounds
Arash Tayyebi, Ali Alshami

05:25 PM

(656g) Machine Learning for the Discovery of Molecular Recognition Based on Single-Walled Carbon Nanotube Corona-Phases
Xun Gong, Nicholas J Renegar, Retsef Levi, Michael Strano

05:40 PM

(656h) Accelerated Discovery of Novel Ionic Liquid Cations Using a Continuous Latent Space Representation of Chemical Space
Jindal Shah, Pratik Dhakal

05:55 PM

(656i) Context-Aware Representations from Deep Learning for Antibody Design
Sai Pooja Mahajan, Jeffrey J. Gray