An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties
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...
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/164192 |
| _version_ | 1824456534240788480 |
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| author | 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 |
| author2 | School of Materials Science and Engineering |
| author_facet | School of Materials Science and Engineering 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 |
| author_sort | Ren, Zekun |
| collection | NTU |
| description | 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. |
| first_indexed | 2025-02-19T03:55:38Z |
| format | Journal Article |
| id | ntu-10356/164192 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:55:38Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1641922023-01-09T04:24:39Z An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties 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 School of Materials Science and Engineering Institute of Materials Research and Engineering, A*STAR Engineering::Materials Auto Encoders General Inverse Design 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. Agency for Science, Technology and Research (A*STAR) National Research Foundation (NRF) This research is supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) program through the Singapore Massachusetts Institute of Technology (MIT) Alliance for Research and Technology’s Low Energy Electronic Systems (LEES) research program. F.O., S.S., and Q. Liang acknowledge support from Total Energies Research grant funded through MITei. Y.J. acknowledges the support from the Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (No. 2021-0-02068, Artificial Intelligence Innovation Hub). J.L. and X.W. acknowledge support from the Ministry of Education Academic Research Fund R-279-000-532-114,. Y.L. is supported by the National Key Research and Development Program of China (Grant Nos. 2017YFB0702901 and 2017YFB0701502) and the National Natural Science Foundation of China (Grant No. 91641128). S.J. and K.H. acknowledge funding from the Accelerated Materials Development for Manufacturing Program at A*STAR via the AME Programmatic Fund by the Agency for Science, Technology and Research under Grant No. A1898b0043. 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). Q.Li is supported by the National Research Foundation (NRF) fellowship grant NRFF13-2021-0106. 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). 2023-01-09T04:24:39Z 2023-01-09T04:24:39Z 2022 Journal Article 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 2590-2385 https://hdl.handle.net/10356/164192 10.1016/j.matt.2021.11.032 2-s2.0-85121929536 1 5 314 335 en A1898b0043 Matter © 2021 Published by Elsevier Inc. All rights reserved. |
| spellingShingle | Engineering::Materials Auto Encoders General Inverse Design 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 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 |
| title_full | An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties |
| title_fullStr | An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties |
| title_full_unstemmed | An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties |
| title_short | An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties |
| title_sort | invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties |
| topic | Engineering::Materials Auto Encoders General Inverse Design |
| url | https://hdl.handle.net/10356/164192 |
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