2022 Annual Meeting

Session: Machine Learning in Materials Discovery

Chair

John Ekerdt, University of Texas-Austin

Co-Chair

Presentations

12:30 PM

(154a) Data-Driven Protein Design
Andrew Ferguson

12:56 PM

(154b) Low-Dimensional Fluctuating Interfaces for Efficient Separations
Narayana Aluru

01:22 PM

(154c) Enabling Catalyst Discovery through High-Throughput Experimentation and Machine Learning
Jochen Lauterbach

01:48 PM

(154d) Predicting the Transition Temperature of Multi-Responsive Poly(N-isopropylacrylamide)-Based Microgels Using a Cluster-Based Partial Least Squares Modelling Approach
Seyed Saeid Tayebi, Prashant Mhaskar, Todd Hoare

02:04 PM

(154e) Designing Metamorphic Materials with a Machine-Learning Guided Genetic Algorithm
Kuan-Lin Chen, Rebecca Schulman

02:20 PM

(154f) Establishing Structure-Function Relationships in Low-Dimensional Mxenes Using Machine Learning
Tej Choksi, Pranav Roy, Lavie Rekhi, Hong Li, See Wee Koh

02:36 PM

(154g) High Strength Polymer Composites Design for Lightweight Vehicles Via Stacked Transfer Learning and Explainable Artificial Intelligence
Jaewook Lee, Dongil Shin, En Sup Yoon