Discovery of 2D Materials using Transformer Network‐Based Generative Design

Discovery of 2D Materials using Transformer Network‐Based Generative Design

Two‐dimensional (2D) materials offer great potential in various fields like superconductivity, quantum systems, and topological materials. However, designing them systematically remains challenging due to the limited pool of fewer than 100 experimentally synthesized 2D materials. Recent advancements...

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Bibliographic Details
Main Authors: Rongzhi Dong, Yuqi Song, Edirisuriya M. D. Siriwardane, Jianjun Hu
Format: Article
Language:English
Published: Wiley 2023-12-01
Series:Advanced Intelligent Systems
Subjects:
crystal structure prediction
deep learning
transformer neural networks
materials discovery
2D materials
transformer-based materials generators
Online Access:https://doi.org/10.1002/aisy.202300141

Internet

https://doi.org/10.1002/aisy.202300141

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