Preferable single-atom catalysts enabled by natural language processing for high energy density Na-S batteries
Abstract Employing appropriate single-atom (SA) catalysts in room-temperature sodium-sulfur (Na-S) batteries is propitious to promote the performance, whereas a universal designing strategy for the highly-efficient single-atom catalysts is absent. In this work, we adopt natural language processing t...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-60931-x |
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| author | Ruilin Bai Yu Yao Qiaosong Lin Lize Wu Zhen Li Huijuan Wang Mingze Ma Di Mu Lingxiang Hu Hai Yang Weihan Li Shaolong Zhu Xiaojun Wu Xianhong Rui Yan Yu |
| author_facet | Ruilin Bai Yu Yao Qiaosong Lin Lize Wu Zhen Li Huijuan Wang Mingze Ma Di Mu Lingxiang Hu Hai Yang Weihan Li Shaolong Zhu Xiaojun Wu Xianhong Rui Yan Yu |
| author_sort | Ruilin Bai |
| collection | DOAJ |
| description | Abstract Employing appropriate single-atom (SA) catalysts in room-temperature sodium-sulfur (Na-S) batteries is propitious to promote the performance, whereas a universal designing strategy for the highly-efficient single-atom catalysts is absent. In this work, we adopt natural language processing techniques to screen the potential single-atom catalysts, then a binary descriptor is constructed to optimize the catalyst candidates. Atomically dispersed cobalt anchored to both nitrogen and sulfur atoms (SA Co-N/S) is selected as an ideal catalyst to significantly facilitate sulfur reduction reaction. The sulfur cathode catalyzed with SA Co-N/S almost realizes complete transformation, and the corresponding pouch cell exhibits satisfactory performance with high mass loading. In-situ X-ray absorption spectroscopy reveals the dynamical interactions between SA Co-N/S and sulfur species in the sulfur reduction reaction. Our work provides a method to select the preferable SA catalyst and to understand the interfacial catalysis dynamics in the sustainable Na-S systems. |
| format | Article |
| id | doaj-art-66f323aea060480f8218e8b046c2ef22 |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-66f323aea060480f8218e8b046c2ef222025-08-20T03:37:37ZengNature PortfolioNature Communications2041-17232025-07-0116111510.1038/s41467-025-60931-xPreferable single-atom catalysts enabled by natural language processing for high energy density Na-S batteriesRuilin Bai0Yu Yao1Qiaosong Lin2Lize Wu3Zhen Li4Huijuan Wang5Mingze Ma6Di Mu7Lingxiang Hu8Hai Yang9Weihan Li10Shaolong Zhu11Xiaojun Wu12Xianhong Rui13Yan Yu14Hefei National Research Center for Physical Sciences at the Microscale, Department of Materials Science and Engineering, University of Science and Technology of ChinaHefei National Research Center for Physical Sciences at the Microscale, Department of Materials Science and Engineering, University of Science and Technology of ChinaUniversity of Chinese Academy of SciencesInstitute of Immunology, Zhejiang University School of MedicineHefei National Research Center for Physical Sciences at the Microscale, Department of Materials Science and Engineering, University of Science and Technology of ChinaExperimental Center of Engineering and Material Science, University of Science and Technology of ChinaHefei National Research Center for Physical Sciences at the Microscale, Department of Materials Science and Engineering, University of Science and Technology of ChinaSchool of Materials Science & Engineering, Shandong UniversityIBISC Lab, Université Paris-SaclayHefei National Research Center for Physical Sciences at the Microscale, Department of Materials Science and Engineering, University of Science and Technology of ChinaDepartment of Mechanical and Materials Engineering, Western UniversityHefei National Research Center for Physical Sciences at the Microscale, Department of Materials Science and Engineering, University of Science and Technology of ChinaHefei National Research Center for Physical Sciences at the Microscale, Department of Materials Science and Engineering, University of Science and Technology of ChinaGuangdong Provincial Key Laboratory on Functional Soft Condensed Matter, School of Materials and Energy, Guangdong University of TechnologyHefei National Research Center for Physical Sciences at the Microscale, Department of Materials Science and Engineering, University of Science and Technology of ChinaAbstract Employing appropriate single-atom (SA) catalysts in room-temperature sodium-sulfur (Na-S) batteries is propitious to promote the performance, whereas a universal designing strategy for the highly-efficient single-atom catalysts is absent. In this work, we adopt natural language processing techniques to screen the potential single-atom catalysts, then a binary descriptor is constructed to optimize the catalyst candidates. Atomically dispersed cobalt anchored to both nitrogen and sulfur atoms (SA Co-N/S) is selected as an ideal catalyst to significantly facilitate sulfur reduction reaction. The sulfur cathode catalyzed with SA Co-N/S almost realizes complete transformation, and the corresponding pouch cell exhibits satisfactory performance with high mass loading. In-situ X-ray absorption spectroscopy reveals the dynamical interactions between SA Co-N/S and sulfur species in the sulfur reduction reaction. Our work provides a method to select the preferable SA catalyst and to understand the interfacial catalysis dynamics in the sustainable Na-S systems.https://doi.org/10.1038/s41467-025-60931-x |
| spellingShingle | Ruilin Bai Yu Yao Qiaosong Lin Lize Wu Zhen Li Huijuan Wang Mingze Ma Di Mu Lingxiang Hu Hai Yang Weihan Li Shaolong Zhu Xiaojun Wu Xianhong Rui Yan Yu Preferable single-atom catalysts enabled by natural language processing for high energy density Na-S batteries Nature Communications |
| title | Preferable single-atom catalysts enabled by natural language processing for high energy density Na-S batteries |
| title_full | Preferable single-atom catalysts enabled by natural language processing for high energy density Na-S batteries |
| title_fullStr | Preferable single-atom catalysts enabled by natural language processing for high energy density Na-S batteries |
| title_full_unstemmed | Preferable single-atom catalysts enabled by natural language processing for high energy density Na-S batteries |
| title_short | Preferable single-atom catalysts enabled by natural language processing for high energy density Na-S batteries |
| title_sort | preferable single atom catalysts enabled by natural language processing for high energy density na s batteries |
| url | https://doi.org/10.1038/s41467-025-60931-x |
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