Please use this identifier to cite or link to this item:
Title: An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties
Authors: Ren, Zekun
Tian, Isaac Parker Siyu
Noh, Juhwan
Oviedo, Felipe
Xing, Guangzong
Li, Jiali
Liang, Qiaohao
Zhu, Ruiming
Aberle, Armin G.
Sun, Shijing
Wang, Xiaonan
Liu, Yi
Li, Qianxiao
Jayavelu, Senthilnath
Hippalgaonkar, Kedar
Jung, Yousung
Buonassisi, Tonio
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.
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.
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

Citations 10

Updated on Dec 3, 2023

Web of ScienceTM
Citations 10

Updated on Oct 29, 2023

Page view(s)

Updated on Dec 4, 2023

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.