An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties

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An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties
Title:
An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties
Journal Title:
Matter
Publication Date:
20 December 2021
Citation:
Ren, Tian, S. I. P., 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://doi.org/10.1016/j.matt.2021.11.032
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.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the A*STAR - AME Programmatic Fund (Accelerated Materials Development for Manufacturing Program)
Grant Reference no. : A1898b0043

This research / project is supported by the National Research Foundation - Campus for Research Excellence and Technological Enterprise (CREATE) program; Singapore Massachusetts Institute of Technology (MIT) Alliance for Research and Technology’s Low Energy Electronic Systems (LEES) research program
Grant Reference no. : NA

This research / project is supported by the MITei (Cambridge) - Total Energies SE research grant
Grant Reference no. : NA

This research / project is supported by the Korea Government - Institute of Information & Communications Technology Planning & Evaluation (IITP); Artificial Intelligence Innovation Hub
Grant Reference no. : 2021-0-02068

This research / project is supported by the Ministry of Education - Academic Research Fund
Grant Reference no. : R-279-000-532-114

This research / project is supported by the China - National Key Research and Development Program
Grant Reference no. : 2017YFB0702901

This research / project is supported by the National Natural Science Foundation of China - NA
Grant Reference no. : 91641128

This research / project is supported by the National Research Foundation (NRF) fellowship grant - NA
Grant Reference no. : NRFF13-2021-0106

This research / project is supported by the China - National Key Research and Development Program
Grant Reference no. : 2017YFB0701502

G.X. is grateful for the support by the Scientific Computing and Data Analysis section of the Research Support Division at Okinawa Institute of Science and Technology Graduate University (OIST). A.G.A. acknowledges support from Solar Energy Research Institute of Singapore (SERIS). SERIS is a research institute at the National University of Singapore (NUS). SERIS is supported by the National University of Singapore (NUS), the National Research Foundation Singapore (NRF), the Energy Market Authority of Singapore (EMA), and the Singapore Economic Development Board (EDB).
Description:
ISSN:
2590-2385
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