Inverse design of promising electrocatalysts for CO2 reduction via generative models and bird swarm algorithm
Directly generating material structures with optimal properties is a long-standing goal in material design. Traditional generative models often struggle to efficiently explore the global chemical space, limiting their utility to localized space. Here, we present a framework named Material Generation...
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| Published in | Nature communications Vol. 16; no. 1; pp. 1053 - 10 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
26.01.2025
Nature Publishing Group Nature Portfolio |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2041-1723 2041-1723 |
| DOI | 10.1038/s41467-024-55613-z |
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| Abstract | Directly generating material structures with optimal properties is a long-standing goal in material design. Traditional generative models often struggle to efficiently explore the global chemical space, limiting their utility to localized space. Here, we present a framework named Material Generation with Efficient Global Chemical Space Search (MAGECS) that addresses this challenge by integrating the bird swarm algorithm and supervised graph neural networks, enabling effective navigation of generative models in the immense chemical space towards materials with target properties. Applied to the design of alloy electrocatalysts for CO
2
reduction (CO
2
RR), MAGECS generates over 250,000 structures, achieving a 2.5-fold increase in high-activity structures (35%) compared to random generation. Five predicted alloys— CuAl, AlPd, Sn
2
Pd
5
, Sn
9
Pd
7
, and CuAlSe
2
are synthesized and characterized, with two showing around 90% Faraday efficiency for CO
2
RR. This work highlights the potential of MAGECS to revolutionize functional material development, paving the way for fully automated, artificial intelligence-driven material design.
Designing materials with optimal properties is a longstanding challenge, as current methods struggle to explore the vast chemical space effectively. Here, the authors combine generative model with optimization methods to design novel and highly active alloy electrocatalysts for CO
2
electroreduction. |
|---|---|
| AbstractList | Directly generating material structures with optimal properties is a long-standing goal in material design. Traditional generative models often struggle to efficiently explore the global chemical space, limiting their utility to localized space. Here, we present a framework named Material Generation with Efficient Global Chemical Space Search (MAGECS) that addresses this challenge by integrating the bird swarm algorithm and supervised graph neural networks, enabling effective navigation of generative models in the immense chemical space towards materials with target properties. Applied to the design of alloy electrocatalysts for CO
2
reduction (CO
2
RR), MAGECS generates over 250,000 structures, achieving a 2.5-fold increase in high-activity structures (35%) compared to random generation. Five predicted alloys— CuAl, AlPd, Sn
2
Pd
5
, Sn
9
Pd
7
, and CuAlSe
2
are synthesized and characterized, with two showing around 90% Faraday efficiency for CO
2
RR. This work highlights the potential of MAGECS to revolutionize functional material development, paving the way for fully automated, artificial intelligence-driven material design.
Designing materials with optimal properties is a longstanding challenge, as current methods struggle to explore the vast chemical space effectively. Here, the authors combine generative model with optimization methods to design novel and highly active alloy electrocatalysts for CO
2
electroreduction. Abstract Directly generating material structures with optimal properties is a long-standing goal in material design. Traditional generative models often struggle to efficiently explore the global chemical space, limiting their utility to localized space. Here, we present a framework named Material Generation with Efficient Global Chemical Space Search (MAGECS) that addresses this challenge by integrating the bird swarm algorithm and supervised graph neural networks, enabling effective navigation of generative models in the immense chemical space towards materials with target properties. Applied to the design of alloy electrocatalysts for CO2 reduction (CO2RR), MAGECS generates over 250,000 structures, achieving a 2.5-fold increase in high-activity structures (35%) compared to random generation. Five predicted alloys— CuAl, AlPd, Sn2Pd5, Sn9Pd7, and CuAlSe2 are synthesized and characterized, with two showing around 90% Faraday efficiency for CO2RR. This work highlights the potential of MAGECS to revolutionize functional material development, paving the way for fully automated, artificial intelligence-driven material design. Directly generating material structures with optimal properties is a long-standing goal in material design. Traditional generative models often struggle to efficiently explore the global chemical space, limiting their utility to localized space. Here, we present a framework named Material Generation with Efficient Global Chemical Space Search (MAGECS) that addresses this challenge by integrating the bird swarm algorithm and supervised graph neural networks, enabling effective navigation of generative models in the immense chemical space towards materials with target properties. Applied to the design of alloy electrocatalysts for CO2 reduction (CO2RR), MAGECS generates over 250,000 structures, achieving a 2.5-fold increase in high-activity structures (35%) compared to random generation. Five predicted alloys- CuAl, AlPd, Sn2Pd5, Sn9Pd7, and CuAlSe2 are synthesized and characterized, with two showing around 90% Faraday efficiency for CO2RR. This work highlights the potential of MAGECS to revolutionize functional material development, paving the way for fully automated, artificial intelligence-driven material design.Directly generating material structures with optimal properties is a long-standing goal in material design. Traditional generative models often struggle to efficiently explore the global chemical space, limiting their utility to localized space. Here, we present a framework named Material Generation with Efficient Global Chemical Space Search (MAGECS) that addresses this challenge by integrating the bird swarm algorithm and supervised graph neural networks, enabling effective navigation of generative models in the immense chemical space towards materials with target properties. Applied to the design of alloy electrocatalysts for CO2 reduction (CO2RR), MAGECS generates over 250,000 structures, achieving a 2.5-fold increase in high-activity structures (35%) compared to random generation. Five predicted alloys- CuAl, AlPd, Sn2Pd5, Sn9Pd7, and CuAlSe2 are synthesized and characterized, with two showing around 90% Faraday efficiency for CO2RR. This work highlights the potential of MAGECS to revolutionize functional material development, paving the way for fully automated, artificial intelligence-driven material design. Directly generating material structures with optimal properties is a long-standing goal in material design. Traditional generative models often struggle to efficiently explore the global chemical space, limiting their utility to localized space. Here, we present a framework named Material Generation with Efficient Global Chemical Space Search (MAGECS) that addresses this challenge by integrating the bird swarm algorithm and supervised graph neural networks, enabling effective navigation of generative models in the immense chemical space towards materials with target properties. Applied to the design of alloy electrocatalysts for CO2 reduction (CO2RR), MAGECS generates over 250,000 structures, achieving a 2.5-fold increase in high-activity structures (35%) compared to random generation. Five predicted alloys— CuAl, AlPd, Sn2Pd5, Sn9Pd7, and CuAlSe2 are synthesized and characterized, with two showing around 90% Faraday efficiency for CO2RR. This work highlights the potential of MAGECS to revolutionize functional material development, paving the way for fully automated, artificial intelligence-driven material design.Designing materials with optimal properties is a longstanding challenge, as current methods struggle to explore the vast chemical space effectively. Here, the authors combine generative model with optimization methods to design novel and highly active alloy electrocatalysts for CO2 electroreduction. |
| ArticleNumber | 1053 |
| Author | Song, Zhilong Lu, Shuaihua Wang, Jinlan Fan, Linfeng Ling, Chongyi Zhou, Qionghua |
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| Cites_doi | 10.1021/ar1001318 10.1038/s41467-022-34453-9 10.1002/anie.202316907 10.1016/j.jocs.2019.06.004 10.1021/acsami.8b08428 10.1038/s41524-022-00850-3 10.1080/0952813X.2015.1042530 10.6084/m9.figshare.27986531.v1 10.1016/j.chempr.2021.11.009 10.1038/s41467-020-17263-9 10.1103/PhysRevB.54.11169 10.1126/science.aat2663 10.1039/D0SC00594K 10.1038/s41929-018-0142-1 10.1038/s41929-023-01041-z 10.5281/zenodo.14207637 10.1016/j.checat.2021.05.006 10.1038/s41524-021-00552-2 10.1002/adma.202109426 10.1021/acscatal.9b04368 10.1016/j.apcatb.2021.120030 10.1016/j.jcou.2021.101542 10.1021/acs.langmuir.8b02837 10.1002/advs.202100566 10.1038/s41467-018-05761-w 10.1021/cr000018s 10.1021/acscatal.3c01584 10.1016/j.electacta.2020.135976 10.1038/s41929-022-00744-z 10.1038/s41586-020-2242-8 10.1021/acs.chemrev.7b00435 10.1021/jacs.1c13740 10.1016/j.commatsci.2018.05.018 10.1021/acscatal.0c04525 10.1002/aisy.202200042 10.1021/acscatal.5b02888 10.1063/1.5019779 10.1103/PhysRevLett.120.145301 10.1038/s42256-020-00271-1 10.1126/sciadv.aax9324 10.1038/s41524-020-00440-1 10.1038/s41524-021-00526-4 10.1016/j.apcatb.2019.118447 10.1002/smtd.201800121 10.1039/D3MH00157A 10.1021/acscentsci.0c00426 10.1002/anie.201507458 10.1103/PhysRevB.85.115104 10.1038/nmat1752 10.1016/j.commatsci.2012.10.028 10.1021/jacs.6b10740 10.1038/s41586-018-0337-2 10.1093/nsr/nwac111 10.1021/acscatal.9b02312 10.1016/j.matt.2019.08.017 10.1038/ncomms15438 10.1021/acs.chemrev.0c01303 |
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| References | M Zhong (55613_CR3) 2020; 581 L Wang (55613_CR37) 2021; 1 EMD Siriwardane (55613_CR19) 2022; 8 AR Oganov (55613_CR10) 2011; 44 J Noh (55613_CR12) 2020; 11 C Wang (55613_CR43) 2021; 49 M Beheshti (55613_CR42) 2020; 341 Y Deng (55613_CR40) 2018; 10 J Klankermayer (55613_CR29) 2016; 55 J Greeley (55613_CR49) 2006; 5 K Tran (55613_CR8) 2018; 1 J Noh (55613_CR14) 2019; 1 L Fan (55613_CR54) 2022; 144 L Peng (55613_CR35) 2020; 264 Z Yao (55613_CR20) 2021; 3 V Stevanović (55613_CR50) 2012; 85 A Vasileff (55613_CR45) 2019; 9 H Yang (55613_CR26) 2019; 35 Y Zhao (55613_CR18) 2021; 8 DA Torelli (55613_CR39) 2016; 6 55613_CR58 55613_CR57 S Lu (55613_CR22) 2018; 9 K Choudhary (55613_CR23) 2020; 6 P-P De Breuck (55613_CR25) 2021; 7 55613_CR61 55613_CR62 55613_CR21 L Yu (55613_CR31) 2023; 13 SP Ong (55613_CR60) 2013; 68 J Artz (55613_CR28) 2018; 118 P Zhang (55613_CR53) 2022; 13 S Lu (55613_CR13) 2022; 9 C Peng (55613_CR52) 2024; 63 T Xie (55613_CR55) 2018; 120 G Kresse (55613_CR59) 1996; 54 Z Gu (55613_CR47) 2018; 2 B Sanchez-Lengeling (55613_CR11) 2018; 361 X Liu (55613_CR32) 2017; 8 Z Han (55613_CR4) 2023; 6 D Bagchi (55613_CR38) 2022; 34 T Long (55613_CR15) 2021; 7 S Ma (55613_CR36) 2017; 139 X Chen (55613_CR44) 2020; 10 H Arakawa (55613_CR30) 2001; 101 55613_CR34 X Zhang (55613_CR41) 2021; 291 B Lee (55613_CR48) 2022; 4 55613_CR33 KT Butler (55613_CR1) 2018; 559 B Weng (55613_CR9) 2020; 11 B Kim (55613_CR17) 2020; 6 X-B Meng (55613_CR27) 2016; 28 Y Feng (55613_CR46) 2018; 34 S Lu (55613_CR6) 2022; 8 JA Esterhuizen (55613_CR5) 2022; 5 S Kim (55613_CR16) 2020; 6 L Chanussot (55613_CR51) 2021; 11 Z Song (55613_CR7) 2023; 10 L Ward (55613_CR24) 2018; 152 KT Schütt (55613_CR56) 2018; 148 B Huang (55613_CR2) 2021; 121 |
| References_xml | – volume: 44 start-page: 227 year: 2011 ident: 55613_CR10 publication-title: Acc. Chem. Res. doi: 10.1021/ar1001318 – ident: 55613_CR57 – volume: 13 year: 2022 ident: 55613_CR53 publication-title: Nat. Commun. doi: 10.1038/s41467-022-34453-9 – volume: 63 start-page: e202316907 year: 2024 ident: 55613_CR52 publication-title: Angew. Chem. Int. Ed. doi: 10.1002/anie.202316907 – volume: 35 start-page: 57 year: 2019 ident: 55613_CR26 publication-title: J. Comput. Sci. doi: 10.1016/j.jocs.2019.06.004 – volume: 10 start-page: 28572 year: 2018 ident: 55613_CR40 publication-title: ACS Appl. Mater. Interfaces doi: 10.1021/acsami.8b08428 – volume: 8 start-page: 164 year: 2022 ident: 55613_CR19 publication-title: npj Comput. Mater. doi: 10.1038/s41524-022-00850-3 – volume: 28 start-page: 673 year: 2016 ident: 55613_CR27 publication-title: J. Exp. Theor. Artif. Intell. doi: 10.1080/0952813X.2015.1042530 – ident: 55613_CR34 – ident: 55613_CR61 doi: 10.6084/m9.figshare.27986531.v1 – volume: 8 start-page: 769 year: 2022 ident: 55613_CR6 publication-title: Chem doi: 10.1016/j.chempr.2021.11.009 – volume: 11 year: 2020 ident: 55613_CR9 publication-title: Nat. Commun. doi: 10.1038/s41467-020-17263-9 – volume: 54 start-page: 11169 year: 1996 ident: 55613_CR59 publication-title: Phys. Rev. B doi: 10.1103/PhysRevB.54.11169 – volume: 361 start-page: 360 year: 2018 ident: 55613_CR11 publication-title: Science doi: 10.1126/science.aat2663 – volume: 11 start-page: 4871 year: 2020 ident: 55613_CR12 publication-title: Chem. Sci. doi: 10.1039/D0SC00594K – ident: 55613_CR58 – volume: 1 start-page: 696 year: 2018 ident: 55613_CR8 publication-title: Nat. Catal. doi: 10.1038/s41929-018-0142-1 – volume: 6 start-page: 1073 year: 2023 ident: 55613_CR4 publication-title: Nat. Catal. doi: 10.1038/s41929-023-01041-z – ident: 55613_CR62 doi: 10.5281/zenodo.14207637 – ident: 55613_CR33 – volume: 1 start-page: 663 year: 2021 ident: 55613_CR37 publication-title: Chem. Catal. doi: 10.1016/j.checat.2021.05.006 – volume: 7 start-page: 83 year: 2021 ident: 55613_CR25 publication-title: npj Comput. Mater. doi: 10.1038/s41524-021-00552-2 – volume: 34 start-page: 2109426 year: 2022 ident: 55613_CR38 publication-title: Adv. Mater. doi: 10.1002/adma.202109426 – volume: 10 start-page: 672 year: 2020 ident: 55613_CR44 publication-title: ACS Catal. doi: 10.1021/acscatal.9b04368 – volume: 291 start-page: 120030 year: 2021 ident: 55613_CR41 publication-title: Appl. Catal. B Environ. doi: 10.1016/j.apcatb.2021.120030 – volume: 49 start-page: 101542 year: 2021 ident: 55613_CR43 publication-title: J. CO2 Util. doi: 10.1016/j.jcou.2021.101542 – volume: 34 start-page: 13544 year: 2018 ident: 55613_CR46 publication-title: Langmuir doi: 10.1021/acs.langmuir.8b02837 – volume: 8 start-page: 14 year: 2021 ident: 55613_CR18 publication-title: Adv. Sci. doi: 10.1002/advs.202100566 – volume: 9 year: 2018 ident: 55613_CR22 publication-title: Nat. Commun. doi: 10.1038/s41467-018-05761-w – volume: 101 start-page: 953 year: 2001 ident: 55613_CR30 publication-title: Chem. Rev. doi: 10.1021/cr000018s – volume: 13 start-page: 9616 year: 2023 ident: 55613_CR31 publication-title: ACS Catal. doi: 10.1021/acscatal.3c01584 – volume: 341 start-page: 135976 year: 2020 ident: 55613_CR42 publication-title: Electrochim. Acta doi: 10.1016/j.electacta.2020.135976 – volume: 5 start-page: 175 year: 2022 ident: 55613_CR5 publication-title: Nat. Catal. doi: 10.1038/s41929-022-00744-z – volume: 581 start-page: 178 year: 2020 ident: 55613_CR3 publication-title: Nature doi: 10.1038/s41586-020-2242-8 – volume: 118 start-page: 434 year: 2018 ident: 55613_CR28 publication-title: Chem. Rev. doi: 10.1021/acs.chemrev.7b00435 – volume: 144 start-page: 7224 year: 2022 ident: 55613_CR54 publication-title: J. Am. Chem. Soc. doi: 10.1021/jacs.1c13740 – volume: 152 start-page: 60 year: 2018 ident: 55613_CR24 publication-title: Comput. Mater. Sci. doi: 10.1016/j.commatsci.2018.05.018 – volume: 11 start-page: 6059 year: 2021 ident: 55613_CR51 publication-title: ACS Catal. doi: 10.1021/acscatal.0c04525 – volume: 4 start-page: 2200042 year: 2022 ident: 55613_CR48 publication-title: Adv. Intell. Syst. doi: 10.1002/aisy.202200042 – volume: 6 start-page: 2100 year: 2016 ident: 55613_CR39 publication-title: ACS Catal. doi: 10.1021/acscatal.5b02888 – volume: 148 start-page: 241722 year: 2018 ident: 55613_CR56 publication-title: J. Chem. Phys. doi: 10.1063/1.5019779 – volume: 120 start-page: 145301 year: 2018 ident: 55613_CR55 publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.120.145301 – volume: 3 start-page: 76 year: 2021 ident: 55613_CR20 publication-title: Nat. Mach. Intell. doi: 10.1038/s42256-020-00271-1 – volume: 6 start-page: eaax9324 year: 2020 ident: 55613_CR17 publication-title: Sci. Adv. doi: 10.1126/sciadv.aax9324 – volume: 6 start-page: 173 year: 2020 ident: 55613_CR23 publication-title: npj Comput. Mater. doi: 10.1038/s41524-020-00440-1 – volume: 7 start-page: 66 year: 2021 ident: 55613_CR15 publication-title: npj Comput. Mater. doi: 10.1038/s41524-021-00526-4 – volume: 264 start-page: 118447 year: 2020 ident: 55613_CR35 publication-title: Appl. Catal. B Environ. doi: 10.1016/j.apcatb.2019.118447 – volume: 2 year: 2018 ident: 55613_CR47 publication-title: Small Methods doi: 10.1002/smtd.201800121 – volume: 10 start-page: 1651 year: 2023 ident: 55613_CR7 publication-title: Mater. Horiz. doi: 10.1039/D3MH00157A – volume: 6 start-page: 1412 year: 2020 ident: 55613_CR16 publication-title: ACS Cent. Sci. doi: 10.1021/acscentsci.0c00426 – volume: 55 start-page: 7296 year: 2016 ident: 55613_CR29 publication-title: Angew. Chem. Int. Ed. doi: 10.1002/anie.201507458 – volume: 85 start-page: 115104 year: 2012 ident: 55613_CR50 publication-title: Phys. Rev. B doi: 10.1103/PhysRevB.85.115104 – volume: 5 start-page: 909 year: 2006 ident: 55613_CR49 publication-title: Nat. Mater. doi: 10.1038/nmat1752 – ident: 55613_CR21 – volume: 68 start-page: 314 year: 2013 ident: 55613_CR60 publication-title: Comput. Mater. Sci. doi: 10.1016/j.commatsci.2012.10.028 – volume: 139 start-page: 47 year: 2017 ident: 55613_CR36 publication-title: J. Am. Chem. Soc. doi: 10.1021/jacs.6b10740 – volume: 559 start-page: 547 year: 2018 ident: 55613_CR1 publication-title: Nature doi: 10.1038/s41586-018-0337-2 – volume: 9 start-page: 9 year: 2022 ident: 55613_CR13 publication-title: Natl Sci. Rev. doi: 10.1093/nsr/nwac111 – volume: 9 start-page: 9411 year: 2019 ident: 55613_CR45 publication-title: ACS Catal. doi: 10.1021/acscatal.9b02312 – volume: 1 start-page: 1370 year: 2019 ident: 55613_CR14 publication-title: Matter doi: 10.1016/j.matt.2019.08.017 – volume: 8 year: 2017 ident: 55613_CR32 publication-title: Nat. Commun. doi: 10.1038/ncomms15438 – volume: 121 start-page: 10001 year: 2021 ident: 55613_CR2 publication-title: Chem. Rev. doi: 10.1021/acs.chemrev.0c01303 |
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| Snippet | Directly generating material structures with optimal properties is a long-standing goal in material design. Traditional generative models often struggle to... Abstract Directly generating material structures with optimal properties is a long-standing goal in material design. Traditional generative models often... |
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| Title | Inverse design of promising electrocatalysts for CO2 reduction via generative models and bird swarm algorithm |
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