Development of a deep-learning model for phase-separation structure of diblock copolymer based on self-consistent field analysis-Reference-Cited by-同舟云学术

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Development of a deep-learning model for phase-separation structure of diblock copolymer based on self-consistent field analysis

Published:2024-02-24 Issue: Volume: Page:1-14
ISSN:0924-3046
Container-title:Advanced Composite Materials
language:en
Short-container-title:Advanced Composite Materials

Author:

Hiraide Kazuya¹,Oya Yutaka²,Hirayama Kenta¹,Endo Katsuhiro¹,Muramatsu Mayu³

Affiliation:

1. Graduate School of Science and Technology, Keio University, 3-14-1 Hiyoshi, 223-8522, Kohoku-ku, Yokohama, Kanagawa, Japan

2. Research Institute for Science & Technology, Tokyo University of Science, 6-3-1 Niijuku, 125-8585, Katsushika-ku, Tokyo, Japan

3. Department of Mechanical Engineering, Keio University, 3-14-1 Hiyoshi, 223-8522, Kohoku-ku, Yokohama, Kanagawa, Japan

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/09243046.2024.2316421

Reference49 articles.

1. A review of the present and future utilisation of FRP composites in the civil infrastructure with reference to their important in-service properties

2. A short review on basalt fiber reinforced polymer composites

3. Thermodynamic interpretation of domain structure in solvent-cast films of A–B type block copolymers of styrene and isoprene

4. Bicontinuous microdomain morphology of block copolymers. 1. Tetrapod-network structure of polystyrene-polyisoprene diblock polymers

5. Stable and unstable phases of a diblock copolymer melt

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