403 Applications of Data Science to High Throughput Experimentation

Wednesday, November 18, 2020: 8:00 AM - 9:00 AM
Applications of Data Science to Molecules and Materials (T3) (PreRecorded+)

Description:
This session invites submissions on research that aims to leverage tools of data science for high throughput experimental work. Data-driven approaches include, but are not limited to, robotics approaches for automatic experimental work, high-throughput screening, machine learning, data mining, meta-analysis. All research areas of interest to chemical engineers are welcome. Submissions should articulate the impact of data science on the problem of interest and clearly articulate the experimental component of the work.

Sponsor:
Applications of Data Science to Molecules and Materials
Co-Sponsor(s):
Catalysis and Reaction Engineering Division (20), Computational Molecular Science and Engineering Forum (21), Information Management and Intelligent Systems (10E), Pharmaceutical Discovery, Development and Manufacturing Forum (26)
Chair:
Elizabeth Nance Email: eanance@uw.edu
Co-Chair:
Johannes Hachmann Email: hachmann@buffalo.edu


(403a) High-Throughput Approach to Studying Adsorption on Zeolite Surfaces
Hassan AlJama, Martin Head-Gordon and Alexis T. Bell


(403b) Machine Learning-Guided Flow Synthesis of Inorganic Metal Halide Perovskite Quantum Dots
Robert Epps, Amanda A. Volk, Kameel Abdel-Latif, Kristopher G. Reyes and Milad Abolhasani


(403c) High-Throughput and Data-Driven Strategies for the Design of Deep Eutectic Solvent Electrolytes
Jaime Rodriguez Jr., Shrilakshmi Bonageri, Maria Politi, Sage Scheiwiller and Lilo Pozzo


(403d) Development of a Hybrid Model to Describe the Dynamics of a Partially Known System
Dongheon Lee, Arul Jayaraman and Joseph Sang-Il Kwon


(403e) Ffiber: Framework for Fluorescent Neuroimaging Based Experimental Routines
Hawley Helmbrecht and Elizabeth Nance


(403f) Data-Driven Discovery of Polymeric Vehicles for Gene Editing:Serendipity-Inspired Design Directions.
Ramya Kumar, Ngoc Le, Zhe Tan and Theresa M. Reineke


(403g) Artificial Intelligence-Assisted Full-Map Understanding of Strain Sensing Devices and Designated Predictions for Soft Robotic Systems
Jiali Li, Haitao Yang, Kaizhuo Lim, Chuanji Pan, Xiaoli Liu, Xiaonan Wang and Po-Yen Chen
See more of this Group/Topical: Topical Conference: Applications of Data Science to Molecules and Materials
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