Non-Nernstian effects and kinetics-informed descriptors in electrocatalysis

Prof. Dr. Georg Kastlunger,
Technical University of Denmark
Fysikvej, Kongens Lyngby, Denmark
geokast@dtu.dk

Thermodynamic descriptors are among the most central tools to predict electrocatalytic activity. They are mostly founded on the analysis of reaction thermodynamics or empirical correlations with experiments, often masking the influence of the kinetics and reaction conditions at play. However, a deep atomistic understanding of complex reaction mechanisms in electrocatalysis aids not only the discovery of improved catalytic materials but also the choice of ideal reaction environments for tailored products.
In my talk, I will present density functional theory-based studies on electrocatalytic reaction mechanisms with a special focus on water splitting, electrochemical CO(2) reduction and biomass electrovalorization. I will discuss how non-Nernstian effects influence electrocatalytic observables1 and their essential role in rationalizing improved descriptors from first principle kinetics even for simple reactions such as hydrogen evolution.2 I will describe how these electrochemical descriptors are essential to resolve the potential, pH and electrolyte dependence of multistep reaction networks,3 highlighting that a descriptor-based search for novel catalysts can be drastically refined if the mechanisms and relevant driving forces are analyzed appropriately.
1. Tripathi, A., Ocampo-Restrepo, V. K., Nørskov, J. & Kastlunger, G. Field effects explain the unintuitive potential response of electrochemical oxygen evolution in acid. RSC Sustainability 3, 2659–2668 (2025).
2. Patel, D. M., Ghan, S., Vishart, A. L. & Kastlunger, G. Improved hydrogen evolution activity descriptors from first-principles electrochemical kinetics. Electrochim Acta 543, 147476 (2025).
3. Kastlunger, G., Heenen, H. H. & Govindarajan, N. Combining First-Principles Kinetics and Experimental Data to Establish Guidelines for Product Selectivity in Electrochemical CO 2 Reduction. ACS Catal 13, 5062–5072 (2023).

Abstract: This study investigates the molecular representation of the lignin-derived oligomers in fast pyrolysis bio-oils, aiming to improve phase equilibrium predictions in thermodynamic calculations.

Abstract: This talk addresses the challenges of predicting phase equilibria in fast pyrolysis bio-oil, a highly complex mixture derived from renewable biomass. Accurate thermodynamic models are essential for designing efficient separation and upgrading processes; however, their development is hindered by limited experimental data and complex molecular interactions. The presentation evaluates the performance of COSMO-SAC and UNIFAC-based models for bio-oil systems and highlights current limitations. Approaches to improve model accuracy and their relevance for sustainable bio-oil refining will be discussed.