Browsing by Author "Chen, Pengyu"

Now showing 1 - 4 of 4
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    Data for "Stability of Cubic Single Network Phases in Diblock Copolymer Melts"
    (2022-07-25) Chen, Pengyu; Mahanthappa, Mahesh K; Dorfman, Kevin D; dorfman@umn.edu; Dorfman, Kevin D; Dorfman Research Group
    This dataset contains the self-consistent field theory (SCFT) simulation results and data for geometric analysis in "Stability of cubic single networks in diblock copolymer melts" by Chen et. al. (DOI: 10.1002/pol.20220318). SCFT was used to investigate the stability of cubic single and double network phases. Geometric analysis, including the calculations of mean curvatures and interfacial areas per unit volume of the domain interface, was used to understand the metastability of the single network phases. With this dataset, users should be able to regenerate the calculations and figures that appeared in the paper.
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    Data for A soft crystalline packing with no metallic analogue
    (2024-04-08) Chen, Pengyu; Dorfman, Kevin D; dorfman@umn.edu; Dorfman, Kevin D; Dorfman Research Group - University of Minnesota Department of Chemical Engineering and Materials Science
    This dataset contains the input and output files for self-consistent field theory (SCFT) simulations in the associate paper.
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    Data for Alternating Gyroid Stabilized by Surfactant-like Triblock Terpolymers in IS/SO/ISO Ternary Blends
    (2023-03-22) Chen, Pengyu; Bates, Frank S; Dorfman, Kevin D; dorfman@umn.edu; Dorfman, Kevin, D; Dorfman Research Group - University of Minnesota Department of Chemical Engineering and Materials Science
    This dataset contains the self-consistent field theory (SCFT) simulation results in the associated paper (https://doi.org/10.1021/acs.macromol.2c02485)
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    Data for Gaming self-consistent field theory: Generative block polymer phase discovery
    (2023-10-18) Chen, Pengyu; Dorfman, Kevin D; dorfman@umn.edu; Dorfman, Kevin D; Dorfman Research Group - University of Minnesota Department of Chemical Engineering and Materials Science
    This dataset contains the input and output files for self-consistent field theory (SCFT) simulations and the training of generative adversarial networks (GANs) in the associated paper.