2022 Annual Meeting

Session: Machine Learning in Materials Discovery

Chair

Ekerdt, J., University of Texas-Austin

Co-Chair

Chang, J., UCLA

Presentations

12:30 PM

(154a) Data-Driven Protein Design

12:56 PM

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

01:22 PM

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

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

02:04 PM

(154e) Designing Metamorphic Materials with a Machine-Learning Guided Genetic Algorithm

02:20 PM

(154f) Establishing Structure-Function Relationships in Low-Dimensional Mxenes Using Machine Learning

02:36 PM

(154g) High Strength Polymer Composites Design for Lightweight Vehicles Via Stacked Transfer Learning and Explainable Artificial Intelligence