Engineering and Technologynpj Computational Materials
Deep Generative Modeling of Two-Dimensional Crystals
P. Lyngby and K. Thygesen
This research by P. Lyngby and K.S. Thygesen delves into the innovative use of a Crystal Diffusion Variational Autoencoder (CDVAE) paired with a lattice decoration protocol (LDP) to create new two-dimensional crystals. The findings showcase how CDVAE excels in generating a wider array of stable 2D materials compared to LDP.
Related Publications
Explore these studies to deepen your understanding
Adjacent work that informs or extends this paper's methodology and findings.
Chemistry
Defining shapes of two-dimensional crystals with undefinable edge energies
L. Wang, S. N. Shirodkar, et al.
Engineering and Technology
Large-area transfer of two-dimensional materials free of cracks, contamination and wrinkles via controllable conformal contact
Y. Zhao, Y. Song, et al.
Engineering and Technology
Deep learning for three-dimensional segmentation of electron microscopy images of complex ceramic materials
Y. Hirabayashi, H. Iga, et al.
Physics
A quantum critical Bose gas of magnons in the quasi-two-dimensional antiferromagnet YbCl<sub>3</sub> under magnetic fields
Y. Matsumoto, S. Schnierer, et al.

