Ion-modulated structure, proton transfer, and capacitance in the Pt(111)/water electric double layer
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arXiv
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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866908544197984256 |
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| author | Wang, Xiaoyu Chen, Junmin Zeng, Zezhu Stein, Frederick Lim, Junho Cheng, Bingqing |
| author_facet | Wang, Xiaoyu Chen, Junmin Zeng, Zezhu Stein, Frederick Lim, Junho Cheng, Bingqing |
| contents | The electric double layer (EDL) governs electrocatalysis, energy conversion, and storage, yet its atomic structure, capacitance, and reactivity remain elusive. Here we introduce a machine learning interatomic potential framework that incorporates long-range electrostatics, enabling nanosecond simulations of metal-electrolyte interfaces under applied electric bias with near-quantum-mechanical accuracy. At the benchmark Pt(111)/water and Pt(111)/aqueous KF electrolyte interfaces, we resolve the molecular structure of the EDL, reveal proton-transfer mechanisms underlying anodic water dissociation and the diffusion of ionic water species, and compute differential capacitance. We find that the nominally inert K+ and F- ions, while leaving interfacial water structure largely unchanged, screen bulk fields, slow proton transfer, and generate a prominent capacitance peak near the potential of zero charge. These results show that ion-specific interactions, which are ignored in mean-field models, are central to capacitance and reactivity, providing a molecular basis for interpreting experiments and designing electrolytes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_13727 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Ion-modulated structure, proton transfer, and capacitance in the Pt(111)/water electric double layer Wang, Xiaoyu Chen, Junmin Zeng, Zezhu Stein, Frederick Lim, Junho Cheng, Bingqing Chemical Physics Materials Science Computational Physics The electric double layer (EDL) governs electrocatalysis, energy conversion, and storage, yet its atomic structure, capacitance, and reactivity remain elusive. Here we introduce a machine learning interatomic potential framework that incorporates long-range electrostatics, enabling nanosecond simulations of metal-electrolyte interfaces under applied electric bias with near-quantum-mechanical accuracy. At the benchmark Pt(111)/water and Pt(111)/aqueous KF electrolyte interfaces, we resolve the molecular structure of the EDL, reveal proton-transfer mechanisms underlying anodic water dissociation and the diffusion of ionic water species, and compute differential capacitance. We find that the nominally inert K+ and F- ions, while leaving interfacial water structure largely unchanged, screen bulk fields, slow proton transfer, and generate a prominent capacitance peak near the potential of zero charge. These results show that ion-specific interactions, which are ignored in mean-field models, are central to capacitance and reactivity, providing a molecular basis for interpreting experiments and designing electrolytes. |
| title | Ion-modulated structure, proton transfer, and capacitance in the Pt(111)/water electric double layer |
| topic | Chemical Physics Materials Science Computational Physics |
| url | https://arxiv.org/abs/2509.13727 |