Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/117626
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Applied Physics | - |
| dc.contributor | Research Institute for Smart Energy | - |
| dc.contributor | Department of Mechanical Engineering | - |
| dc.contributor | Department of Industrial and Systems Engineering | - |
| dc.contributor | Research Institute for Advanced Manufacturing | - |
| dc.creator | Gong, S | - |
| dc.creator | Zhai, Y | - |
| dc.creator | Jin, C | - |
| dc.creator | Xu, H | - |
| dc.creator | Xia, Q | - |
| dc.creator | Li, W | - |
| dc.creator | Ying, Y | - |
| dc.creator | Wu, J | - |
| dc.creator | She, X | - |
| dc.creator | Wang, Z | - |
| dc.creator | Lv, X | - |
| dc.creator | Wu, C | - |
| dc.creator | Chan, K | - |
| dc.creator | Zhao, X | - |
| dc.creator | Zhang, X | - |
| dc.creator | Lau, SP | - |
| dc.date.accessioned | 2026-02-26T03:47:32Z | - |
| dc.date.available | 2026-02-26T03:47:32Z | - |
| dc.identifier.uri | http://hdl.handle.net/10397/117626 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Nature Publishing Group | en_US |
| dc.rights | Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. | en_US |
| dc.rights | ©The Author(s) 2025 | en_US |
| dc.rights | The following publication Gong, S., Zhai, Y., Jin, C. et al. Interface engineering of single-molecular heterojunction catalysts for CO2 electroreduction in strong acid medium. Nat Commun 16, 8704 (2025) is available at https://doi.org/10.1038/s41467-025-63722-6. | en_US |
| dc.title | Interface engineering of single-molecular heterojunction catalysts for CO₂ electroreduction in strong acid medium | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.volume | 16 | - |
| dc.identifier.doi | 10.1038/s41467-025-63722-6 | - |
| dcterms.abstract | Electrochemical carbon dioxide reduction reaction (CO2RR) under strongly acidic conditions enables high CO2 utilization. However, especially in proton exchange membrane (PEM) electrode assembly reactors, achieving selective CO2RR in such environments remains challenging due to uncontrolled interfacial water diffusion at high current densities. Here, we develop a nickel-based heterogeneous molecular electrocatalyst (NiPc-NH2/CNT-SHP) featuring amino (-NH2) functional groups and grafted long-chain hydrophobic molecules. Under acidic conditions, -NH2 is in situ protonated to form amino cations (-NH3⁺). The positively charged -NH3⁺ groups and hydrophobic molecules effectively disrupt the protonated water (H3O+)-rich network, inhibiting the invasion of H3O+ and thereby suppressing the hydrogen evolution reaction, while enhancing selectivity for acidic CO2RR. The catalyst achieves nearly 100% Faradaic efficiency for CO at current densities from 50 to 400 mA cm−2, with approximately 76% CO2 utilization efficiency in a flow cell, and sustains over 80% selectivity for more than 200 h in a self-designed PEM–porous solid electrolyte reactor. These findings highlight interfacial water management as a key design principle for efficient acidic CO2 electroreduction. | - |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Nature communications, 2025, v. 16, 8704 | - |
| dcterms.isPartOf | Nature communications | - |
| dcterms.issued | 2025 | - |
| dc.identifier.scopus | 2-s2.0-105017756095 | - |
| dc.identifier.pmid | 41027872 | - |
| dc.identifier.eissn | 2041-1723 | - |
| dc.identifier.artn | 8704 | - |
| dc.description.validate | 202602 bcch | - |
| dc.description.oa | Version of Record | en_US |
| dc.identifier.FolderNumber | OA_Scopus/WOS | en_US |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | The authors thank the following funding agencies for supporting this work: X.Z. acknowledges the Hong Kong Polytechnic University (CD9B, WZ4Q, CDBZ), and the National Natural Science Foundation of China (22205187), Shenzhen Municipal Science and Technology Innovation Commission (JCYJ20230807140402006), and Department of Science and Technology of Guangdong Province (2023A1515110123, 2024A1515012390). K.C. acknowledges the Hong Kong Polytechnic University (CD4L). S.P.L. acknowledges the Hong Kong Polytechnic University (1-CD7U, 1-BBDV). X.L. acknowledges Zhenjiang Key Research and Development Program (GY2021004), and Jiangsu Funding Program for Excellent Postdoctoral Talent (2024ZB736), and the China Postdoctoral Science Foundation (GZC20240614). X.H.Z. acknowledges the Start-up Research Fund of Southeast University and the Big Data Computing Center of Southeast University. The authors acknowledge Shiyanjia Lab (www.shiyanjia.com) for supporting the XPS and TEM analysis. | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | CC | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| s41467-025-63722-6.pdf | 2.13 MB | Adobe PDF | View/Open |
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