MagGen: A Graph-Aided Deep Generative Model for Inverse Design of Permanent Magnets-Reference-Cited by-同舟云学术

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MagGen: A Graph-Aided Deep Generative Model for Inverse Design of Permanent Magnets

Published:2024-03-14 Issue:12 Volume:15 Page:3221-3228
ISSN:1948-7185
Container-title:The Journal of Physical Chemistry Letters
language:en
Short-container-title:J. Phys. Chem. Lett.

Author:

Mal Sourav¹,Seal Gaurav²,Sen Prasenjit¹³^ORCID

Affiliation:

1. Harish-Chandra Research Institute, a CI of Homi Bhabha National Institute, Chhatnag Road, Jhunsi, Prayagraj 211019, India

2. Indian Institute of Science Education and Research Thiruvananthapuram, Thiruvananthapuram, Kerala 695551, India

3. Department of Physics, Indian Institute of Science Education and Research, Tirupati, Karkambadi Road, Tirupati 517507, India

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpclett.4c00068

Reference55 articles.

1. Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach

2. What Is High-Throughput Virtual Screening? A Perspective from Organic Materials Discovery

3. Discovery of Manganese-Based Solar Fuel Photoanodes via Integration of Electronic Structure Calculations, Pourbaix Stability Modeling, and High-Throughput Experiments

4. First principles high throughput screening of oxynitrides for water-splitting photocatalysts

5. High-throughput screening of high-capacity electrodes for hybrid Li-ion–Li–O2 cells

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