2022 Annual Meeting

Session: Applications of Data Science to High Throughput Experimentation

Chair

Elizabeth Nance, UNIVERSITY OF WASHINGTON

Co-Chairs

Presentations

08:00 AM

(88a) A Bayesian Experimental Design Framework for Optimizing Microbial Communities
Victor Zavala, Ophelia Venturelli, Jaron Thompson

08:15 AM

(88b) Solution Coating of Polymer Blend Libraries for High-Throughput Experimentation Via Passive Mixing
Aaron L. Liu, Ezgi Melis Dogan-Guner, Michael McBride, Rahul Venkatesh, Miguel A. Gonzalez, Jun Amano, Elsa Reichmanis, Martha Grover, Carson Meredith

08:45 AM

(88d) Design of an Automatic Platform for Machine-Learning Model Based Molecular Property Optimization
Matthew McDonald, Brent Koscher, Richard Canty, Seung Kyun Ha, Kevin P. Greenman, Charles J. McGill, Rafael Gomez-Bombarelli, William Green, Klavs Jensen, Camille Bilodeau

09:00 AM

(88e) Simulating Closed-Loop Catalyst Discovery Processes Using an Experimental Band Gap Surrogate Model
Kirby Broderick, Zachary Ulissi

09:15 AM

(88f) Improved Characterization of Membrane Transport Properties through Advanced Data Analytics
Xinhong Liu, Jonathan Ouimet, Laurianne Lair, William Phillip, Alexander Dowling

09:30 AM

(88g) Autonomous Optimization of Robotic Process Parameters for Accurate Experiments
Martin Seifrid

09:45 AM

(88h) High-Throughput Screening of Binary and Ternary Organic Redox Active Materials-Based Deep Eutectic Solvents
Maria Politi, Jaime Rodriguez, Stuart Adler, David Beck, Lilo Pozzo