Related Experiment Video
Updated: Feb 20, 2026

Probing the Structure and Dynamics of Interfacial Water with Scanning Tunneling Microscopy and Spectroscopy
Published on: May 27, 2018
How Artificial Intelligence Can Advance Electrochemical Science and Identify Water Molecule Orientation on Platinum
Yitao He1,2, Jiří Červenka2
1Department of New Energy Science and Engineering, School of Energy and Environment, Anhui University of Technology, Ma'anshan 243002, China.
None:
Electrochemistry lies at the heart of modern energy technologies, yet connecting atomic-level insights to macroscopic performance remains an enduring challenge. Quantum-based simulations, such as density functional theory, have illuminated many fundamental processes, but their reach is limited by the complexity of real electrochemical environments. Bridging these scales requires a new conceptual framework that can expose the hidden connections between theory and experiment. Here, we argue that the thoughtful integration of artificial intelligence (AI) can transform electrochemical research by unifying theory, experiment, and data-driven inference. AI-assisted frameworks can accelerate convergence between computation and experiment, revealing hidden physical relationships and enabling closed-loop discovery. Realizing this vision will require developing transparent, interpretable AI models that earn the same scientific trust as human reasoning, unlocking deeper understanding and innovation across the electrochemical sciences.
Related Concept Videos
Interfacial Electrochemical Methods: Overview
Potentiometry: Types of Electrodes
The Standard Hydrogen Electrode (SHE) is a widely used reference electrode that maintains zero potential across all temperatures. However, its need for a continuous hydrogen gas supply renders it impractical for everyday use.
An alternative to SHE is the Saturated Calomel Electrode (SCE). This electrode features an...
Potentiometry: Membrane Electrodes

