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|Title:||An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties||Authors:||Ren, Zekun
Tian, Isaac Parker Siyu
Aberle, Armin G.
|Keywords:||Engineering::Materials||Issue Date:||2022||Source:||Ren, Z., Tian, I. P. S., Noh, J., Oviedo, F., Xing, G., Li, J., Liang, Q., Zhu, R., Aberle, A. G., Sun, S., Wang, X., Liu, Y., Li, Q., Jayavelu, S., Hippalgaonkar, K., Jung, Y. & Buonassisi, T. (2022). An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties. Matter, 5(1), 314-335. https://dx.doi.org/10.1016/j.matt.2021.11.032||Project:||A1898b0043||Journal:||Matter||Abstract:||Realizing general inverse design could greatly accelerate the discovery of new materials with user-defined properties. However, state-of-the-art generative models tend to be limited to a specific composition or crystal structure. Herein, we present a framework capable of general inverse design (not limited to a given set of elements or crystal structures), featuring a generalized invertible representation that encodes crystals in both real and reciprocal space, and a property-structured latent space from a variational autoencoder (VAE). In three design cases, the framework generates 142 new crystals with user-defined formation energies, bandgap, thermoelectric (TE) power factor, and combinations thereof. These generated crystals, absent in the training database, are validated by first-principles calculations. The success rates (number of first-principles-validated target-satisfying crystals/number of designed crystals) ranges between 7.1% and 38.9%. These results represent a significant step toward property-driven general inverse design using generative models, although practical challenges remain when coupled with experimental synthesis.||URI:||https://hdl.handle.net/10356/164192||ISSN:||2590-2385||DOI:||10.1016/j.matt.2021.11.032||Schools:||School of Materials Science and Engineering||Organisations:||Institute of Materials Research and Engineering, A*STAR||Rights:||© 2021 Published by Elsevier Inc. All rights reserved.||Fulltext Permission:||none||Fulltext Availability:||No Fulltext|
|Appears in Collections:||MSE Journal Articles|
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