Machine Learning Models and Dimensionality Reduction for Prediction of Polymer Properties
Author:
Affiliation:
1. Materials Science Division, Argonne National Laboratory, Lemont, Illinois 60439, United States
2. Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois 60637, United States
Funder
Basic Energy Sciences
Publisher
American Chemical Society (ACS)
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.macromol.3c02401
Reference61 articles.
1. Multiblock Polymers: Panacea or Pandora’s Box?
2. Influence of Additives on the Interfacial Width and Line Edge Roughness in Block Copolymer Lithography
3. Directed Self-Assembly of High χ Poly(styrene-b-(lactic acid-alt-glycolic acid)) Block Copolymers on Chemical Patterns via Thermal Annealing
4. Comprehensive Phase Behavior of Poly(isoprene-b-styrene-b-ethylene oxide) Triblock Copolymers
5. Phase Behavior of Nonfrustrated ABC Triblock Copolymers: Weak and Intermediate Segregation
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