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Inverse design of two-dimensional materials with invertible neural networks

Engineering and Technology

Inverse design of two-dimensional materials with invertible neural networks

V. Fung, J. Zhang, et al.

This innovative research by Victor Fung, Jiaxin Zhang, Guoxiang Hu, P. Ganesh, and Bobby G. Sumpter introduces MatDesINNe, a groundbreaking inverse design framework that leverages invertible neural networks for materials design. Focused on band gap engineering in 2D MoS2, this framework offers near-chemical accuracy in generating high-fidelity material candidates, unlocking vital insights into metal-insulator transitions for neuromorphic applications.

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