Anja Bieberle-Hütter

Knowledge of the reaction rate constants can be vital in understanding electrochemical reaction mechanisms and their rate-determining processes. Although first-principles methods, such as density functional theory (DFT), provide valuable insight into reaction free energies and rate constants, they commonly use idealized assumptions. As a different approach, this study demonstrates the estimation of rate constants from electrochemical data. Specifically, this study estimates rate constants from electrochemical impedance spectroscopy (EIS) data of the oxygen evolution reaction (OER) with a hematite Fe₂O₃ anode often used in photoelectrochemical cells. Unlike the common approach of equivalent circuit fitting with resistances and capacitances, the electrochemistry of the OER in this work is represented by a microkinetic model and physicochemical quantities. The estimated rate constants directly correspond to the OER reaction steps, and a single set of rate constants is obtained that is optimized for multiple potentials simultaneously. The estimation is conducted using maximum likelihood estimation. The effectiveness of the estimation method is shown using synthetic measurements first; intermediate species coverages are simulated as well. Then, the rate constants are estimated directly from experimental EIS measurements. Though accuracy is currently limited due to the model that does not account for all processes at the interface, such as, for example, diffusive transport, the estimated rate constants do represent the experimental interface and are perfectly suited for kinetic analysis and systematic parameter studies of the electrochemical system. Additionally, this approach enables analyses of differences between electrode materials, validation of models, and prediction of electrochemical data of different material systems, which is time-consuming and costly to obtain experimentally. This research demonstrates how combining potential- and frequency-dependent EIS experiments with microkinetic modeling enables the estimation of reaction rates and intermediate species coverages, aiding in identifying reaction mechanisms directly from experiments.

Knowledge of the reaction rate constants can be vital in understanding electrochemical reaction mechanisms and their rate-determining processes. Although first-principles methods, such as density functional theory (DFT), provide valuable insight into reaction free energies and rate constants, they commonly use idealizing assumptions. As an alternative, this study demonstrates the estimation of the rate constants of the oxygen evolution reaction (OER) from electrochemical impedance measurements of a photo-electrochemical cell with a hematite anode, providing insight into the rate constants directly from measurements. Estimation is conducted using maximum likelihood estimation, minimizing the weighted error between a microkinetic model of the OER and measurements at multiple frequencies and potentials. In this way, a single set of rate constants is obtained that is optimized for multiple potentials simultaneously. The effectiveness of the estimation method is shown using synthetic measurements. Furthermore, this study shows that rate constants can be estimated from experimental measurements. However, accuracy is limited, potentially because additional processes, such as diffusive transport, are not included in the current model. The estimated rate constants are best suited for comparative analysis, rather than as absolute values, which may be influenced by specific samples. This enables analysis of differences between materials, validation of models, and prediction of electrochemical data of different material systems. This research demonstrates how combining potential and frequency dependent electrochemical impedance spectroscopy (EIS) experiments with microkinetic modeling enables the estimation of reaction rates and intermediate species coverages without relying on idealized atomistic configurations, aiding in identifying reaction mechanisms directly from experiments.

A central challenge in water electrolysis lies with the oxygen evolution reaction (OER) where the formation of molecular oxygen (O₂) is hindered by the constraint of angular momentum conservation. While the reactants OH⁻ or H₂O are diamagnetic, the O₂ product has a paramagnetic triplet ground state, requiring a change in spin configuration when being formed. This constraint has prompted interest in spin‐selective catalysts as a means to facilitate OER. In this context, the roles of magnetism and chirality‐induced spin selectivity (CISS) in promoting the OER reaction have recently been investigated through both theoretical and experimental studies. However, pinpointing the key principles and their relative contribution in mediating spin‐enhancement remains a significant challenge. This roadmap offers a forward‐looking perspective on current experimental trends and theoretical developments in spin‐enhanced OER electrocatalysis and outlines strategic directions for integrating incisive experiments and operando approaches with computational modeling to disentangle key mechanisms. By providing a conceptual framework and identifying critical knowledge gaps, this perspective aims to guide researchers toward dedicated experimental and computational studies that will deepen our understanding of spin‐induced OER enhancement and accelerate the development of next‐generation catalysts.

Photoelectrochemical (PEC) water splitting is a promising method for the energy transition. However, it is still hampered because the performance of the electrodes is too low. Herein, bismuth manganate (BMO) is investigated as a photoanode absorber material for PEC. BMO thin films are prepared by a sol–gel method with and without a bismuth oxide (BO) overlayer. It is found that the BO overlayer forms BO nanoislands after annealing. Under visible light illumination, BMO with BO nanoislands results in a nearly tenfold increase of the current density compared to pristine BMO at the same applied potential. This increased performance is related to a decrease in the charge transfer resistance and in the amount of recombinations based on the formation of a favorable heterojunction between BMO and BO. The application of overlayers on electrode materials in combination with suitable band alignment is an effective strategy to improve the performance of PEC electrodes.

Magnetic exchange force microscopy (MExFM) is an important experimental technique for mapping the magnetic structure of surfaces with atomic resolution relying on the spin‐dependent short‐range exchange interaction between a magnetic tip and a magnetic surface. RuO₂ is a significant compound with applications in heterogeneous catalysis and electrocatalysis. It has been characterized recently as an antiferromagnetic (AFM) material, and its magnetism has been predicted somewhat surprisingly to play an important role in its catalytic properties. In the current study, we explore theoretically whether MExFM can visualize the magnetic surface structure of RuO₂. We use density functional theory (DFT) calculations to extract the exchange interactions between a ferromagnetic Fe tip interacting with an AFM RuO₂(110) surface, as a function of tip‐surface distance and the position of the tip over the surface. Mimicking the MExFM experiment, these data are then used to calculate the normalized frequency shift of an oscillating cantilever tip versus the minimum tip‐surface distance, and construct corrugation height line profiles. It is found that the exchange interaction between tip and surface is strongest for a parallel configuration of the spins of the tip and of the surface; it is weakest for an anti‐parallel orientation. In a corrugation profile, this gives rise to a sizable height difference of 25 pm between the spin‐up and spin‐down Ru atoms in the RuO₂(110) surface at a normalized frequency shift =−10.12 fNm^1/2. The O atoms in the surface are not or hardly visible in the corrugation profile.

Chemical models are built up from chemical reactions and parameters. Each of these parameters has a degree of uncertainty. Sensitivity analysis has proven to be an important tool to quantify and trace this uncertainty to specific input parameters. In this study, the methodology of a prominent global sensitivity analysis method, that is, Sobol's variance‐based method, is presented for chemical modeling with a focus on microkinetic modeling. Sobol's method is developed to be used as an analysis framework, which—once set‐up for microkinetic modeling—can easily be used for different models. This analysis framework is successfully demonstrated by means of two case studies from the field of microkinetic modeling: 1) CO oxidation and 2) oxygen evolution reaction (OER) at the photoanode in a photo‐electrochemical cell. The results give insight into the influence of each input parameter on the output uncertainty. For CO oxidation, it is found that the temperature and chemisorption energies have most impact on the output. For the OER model, the valence band energy and solvent reorganization energy are most influential. Based on this, a workflow is proposed incorporating the sensitivity analysis into the modeling process, aimed at reducing the output uncertainty and at validating and optimizing the model.

The future challenges in modeling nano-photocatalysts involve combining different methods in a hierarchical way, a path that will provide understanding on how to design catalysts for producing fuel needed for a sustainable life in the future.