Characterizing the electrical double layer at oxide-electrolyte interfaces using machine learning potential simulations

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• Prof. Annabella Selloni, Princeton University
• Monday 04 November 2024, 14:30-15:00
• Zoom link: https://zoom.us/j/92447982065?pwd=RkhaYkM5VTZPZ3pYSHptUXlRSkppQT09.

If you have a question about this talk, please contact Dr Fabian Berger.

The electrical double layer (EDL) at metal oxide-electrolyte interfaces critically affects fundamental processes in water splitting, batteries, and corrosion. However, limitations in the microscopic-level understanding of the EDL have been a major bottleneck in controlling these interfacial processes. We used ab initio-based machine learning potential simulations incorporating long-range electrostatics to investigate the structure and chemistry of the EDL at the prototypical anatase TiO2-electrolyte interface under various pH conditions. Our simulations show that the larger capacitance of the EDL under basic relative to acidic conditions originates primarily from the higher affinity of the cations for the oxide surface and gives rise to distinct charging mechanisms on negative and positive surfaces. These results are validated by the agreement between the computed EDL capacitance and experimental data.

This talk is part of the Lennard-Jones Centre series.

This talk is included in these lists:

• Hanchen DaDaDash
• Lennard-Jones Centre
• Zoom link: https://zoom.us/j/92447982065?pwd=RkhaYkM5VTZPZ3pYSHptUXlRSkppQT09

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