High-Throughput Screening and Prediction of High Modulus of Resilience Polymers Using Explainable Machine Learning
Author:
Affiliation:
1. Department of Mechanical Engineering, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
2. Department of Mechanical Engineering, University of Connecticut, Storrs, Connecticut 06269, United States
Funder
Air Force Research Laboratory
Air Force Office of Scientific Research
Division of Civil, Mechanical and Manufacturing Innovation
3M
Publisher
American Chemical Society (ACS)
Subject
Physical and Theoretical Chemistry,Computer Science Applications
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.3c00131
Reference57 articles.
1. Resilience in Palliative Care
2. Ultrahigh Elastic Strain Energy Storage in Metal-Oxide-Infiltrated Patterned Hybrid Polymer Nanocomposites
3. Superelasticity and reversible energy absorption of polyurethane cellular structures with sand filler
4. Storing energy and powering small systems with mechanical springs made of carbon nanotube yarn
5. Benefits and Challenges of Mechanical Spring Systems for Energy Storage Applications
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