Spectral Similarity Masks Structural Diversity at Hydrophobic Water Interfaces
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arXiv
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| Autori principali: | , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866910906279002112 |
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| author | Wang, Yong Li, Yifan Du, Linhan Zhang, Chunyi Agosta, Lorenzo Andrade, Marcos Calegari Selloni, Annabella Car, Roberto |
| author_facet | Wang, Yong Li, Yifan Du, Linhan Zhang, Chunyi Agosta, Lorenzo Andrade, Marcos Calegari Selloni, Annabella Car, Roberto |
| contents | The air-water and graphene-water interfaces represent quintessential examples of the liquid-gas and liquid-solid boundaries, respectively. While the sum-frequency generation (SFG) spectra of these interfaces exhibit certain similarities, a consensus on their signals and interpretations has yet to be reached. Leveraging deep learning, we accessed fully first-principles SFG spectra for both systems, addressing recent experimental discrepancies. Despite both interfaces exhibiting microscopically hydrophobic characteristics, our findings reveal that similarities in SFG signals do not translate into comparable interfacial microscopic properties. Instead, graphene-water and air-water interfaces exhibit fundamental differences in SFG-active thicknesses, hydrogen-bonding networks, and dynamic diffusion behavior. These distinctions underscore the stronger confinements imposed by the solid-liquid interface compared with the weaker constraints of the gas-liquid interface. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_05593 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Spectral Similarity Masks Structural Diversity at Hydrophobic Water Interfaces Wang, Yong Li, Yifan Du, Linhan Zhang, Chunyi Agosta, Lorenzo Andrade, Marcos Calegari Selloni, Annabella Car, Roberto Computational Physics Materials Science The air-water and graphene-water interfaces represent quintessential examples of the liquid-gas and liquid-solid boundaries, respectively. While the sum-frequency generation (SFG) spectra of these interfaces exhibit certain similarities, a consensus on their signals and interpretations has yet to be reached. Leveraging deep learning, we accessed fully first-principles SFG spectra for both systems, addressing recent experimental discrepancies. Despite both interfaces exhibiting microscopically hydrophobic characteristics, our findings reveal that similarities in SFG signals do not translate into comparable interfacial microscopic properties. Instead, graphene-water and air-water interfaces exhibit fundamental differences in SFG-active thicknesses, hydrogen-bonding networks, and dynamic diffusion behavior. These distinctions underscore the stronger confinements imposed by the solid-liquid interface compared with the weaker constraints of the gas-liquid interface. |
| title | Spectral Similarity Masks Structural Diversity at Hydrophobic Water Interfaces |
| topic | Computational Physics Materials Science |
| url | https://arxiv.org/abs/2504.05593 |