The more the better: on the formation of single-phase high entropy alloy nanoparticles as catalysts for the oxygen reduction reaction.

High entropy alloys (HEAs) are an important new material class with significant application potential in catalysis and electrocatalysis. The entropy-driven formation of HEA materials requires high temperatures and controlled cooling rates. However, catalysts in general also require highly dispersed materials, i.e., nanoparticles. Only then a favorable utilization of the expensive raw materials can be achieved. Several recently reported HEA nanoparticle synthesis strategies, therefore, avoid the high-temperature regime to prevent particle growth. In our work, we investigate a system of five noble metal single-source precursors with superior catalytic activity for the oxygen reduction reaction. Combining in situ X-ray powder diffraction with multi-edge X-ray absorption spectroscopy, we address the fundamental question of how single-phase HEA nanoparticles can form at low temperatures. It is demonstrated that the formation of HEA nanoparticles is governed by stochastic principles and the inhibition of precursor mobility during the formation process favors the formation of a single phase. The proposed formation principle is supported by simulations of the nanoparticle formation in a randomized process, rationalizing the experimentally found differences between two-element and multi-element metal precursor mixtures.

A Flexible Theory for Catalysis: Learning Alkaline Oxygen Reduction on Complex Solid Solutions within the Ag-Pd-Pt-Ru Composition Space.

Compositionally complex materials such as high-entropy alloys and oxides have the potential to be efficient platforms for catalyst discovery because of the vast chemical space spanned by these novel materials. Identifying the composition of the most active catalyst materials, however, requires unraveling the descriptor-activity relationship, as experimentally screening the multitude of possible element ratios quickly becomes a daunting task. In this work, we show that inferred adsorption energy distributions of *OH and *O on complex solid solution surfaces within the space spanned by the system Ag-Pd-Pt-Ru are coupled to the experimentally observed electrocatalytic performance for the oxygen reduction reaction. In total, the catalytic activity of 1582 alloy compositions is predicted with a cross-validated mean absolute error of 0.042 mA/cm2 by applying a theory-derived model with only two adjustable parameters. Trends in the discrepancies between predicted electrochemical performance values of the model and the measured values on thin film surfaces subsequently provide insight into the alloys' surface compositions during reaction conditions. Bridging this gap between computationally modeled and experimentally observed catalytic activities, not only reveals insight into the underlying theory of catalysis but also takes a step closer to realizing exploration and exploitation of high-entropy materials.

Bayesian Optimization of High-Entropy Alloy Compositions for Electrocatalytic Oxygen Reduction*.

Active, selective and stable catalysts are imperative for sustainable energy conversion, and engineering materials with such properties are highly desired. High-entropy alloys (HEAs) offer a vast compositional space for tuning such properties. Too vast, however, to traverse without the proper tools. Here, we report the use of Bayesian optimization on a model based on density functional theory (DFT) to predict the most active compositions for the electrochemical oxygen reduction reaction (ORR) with the least possible number of sampled compositions for the two HEAs Ag-Ir-Pd-Pt-Ru and Ir-Pd-Pt-Rh-Ru. The discovered optima are then scrutinized with DFT and subjected to experimental validation where optimal catalytic activities are verified for Ag-Pd, Ir-Pt, and Pd-Ru binary alloys. This study offers insight into the number of experiments needed for optimizing the vast compositional space of multimetallic alloys which has been determined to be on the order of 50 for ORR on these HEAs.

What Atomic Positions Determines Reactivity of a Surface? Long-Range, Directional Ligand Effects in Metallic Alloys.

Ligand and strain effects can tune the adsorption energy of key reaction intermediates on a catalyst surface to speed up rate-limiting steps of the reaction. As novel fields like high-entropy alloys emerge, understanding these effects on the atomic structure level is paramount: What atoms near the binding site determine the reactivity of the alloy surface? By statistical analysis of 2000 density functional theory calculations and subsequent host/guest calculations, it is shown that three atomic positions in the third layer of an fcc(111) metallic structure fourth-nearest to the adsorption site display significantly increased influence on reactivity over any second or third nearest atomic positions. Subsequently observed in multiple facets and host metals, the effect cannot be explained simply through the d-band model or a valence configuration model but rather by favorable directions of interaction determined by lattice geometry and the valence difference between host and guest elements. These results advance the general understanding of how the electronic interaction of different elements affect adsorbate-surface interactions and will contribute to design principles for rational catalyst discovery of better, more stable and energy efficient catalysts to be employed in energy conversion, fuel cell technologies, and industrial processes.

Complex-Solid-Solution Electrocatalyst Discovery by Computational Prediction and High-Throughput Experimentation*.

Complex solid solutions ("high entropy alloys"), comprising five or more principal elements, promise a paradigm change in electrocatalysis due to the availability of millions of different active sites with unique arrangements of multiple elements directly neighbouring a binding site. Thus, strong electronic and geometric effects are induced, which are known as effective tools to tune activity. With the example of the oxygen reduction reaction, we show that by utilising a data-driven discovery cycle, the multidimensionality challenge raised by this catalyst class can be mastered. Iteratively refined computational models predict activity trends around which continuous composition-spread thin-film libraries are synthesised. High-throughput characterisation datasets are then used as input for refinement of the model. The refined model correctly predicts activity maxima of the exemplary model system Ag-Ir-Pd-Pt-Ru. The method can identify optimal complex-solid-solution materials for electrocatalytic reactions in an unprecedented manner.

Symmetry controlled excited state dynamics.

Symmetry effects in internal conversion are studied by means of two isomeric cyclic tertiary aliphatic amines in a velocity map imaging (VMI) experiment on the femtosecond timescale. It is demonstrated that there is a delicate structural dependence on when coherence is preserved after the transition between the 3p and 3s Rydberg states. N-Methyl morpholine (NMM) shows unambiguous preserved coherence, consistent with previous work, which is decidedly switched off by the repositioning of oxygen within the ring. From the differences in these dynamics, and an examination of the potential energy surface following the normal modes of vibration, it becomes clear that there is a striking dependence on atom substitution, which manifests itself in the permitted modes of vibration that take the system out of the Franck-Condon region through to the 3s minimum. It is shown that the non Fermi-like behaviour of NMM is due to a conical intersection (CI) between the 3px and 3s states lying directly along the symmetry allowed path of steepest descent out of the Franck-Condon region. NMI, where the symmetry has been changed, is shown to undergo internal conversion in a more Fermi-like manner as the energy spreads through the available modes ergodically.

Putting the Disulfide Bridge at Risk: How UV-C Radiation Leads to Ultrafast Rupture of the S-S Bond.

We investigate the ultrafast photoinduced dynamics of the cyclic disulfide 1,2-dithiane upon 200 nm excitation by time-resolved photoelectron spectroscopy and show that the S-S bond breaks on an ultrafast time scale. This stands in stark contrast to excitation at longer wavelengths where the initially excited S1 state evolves as the wavepacket is guided towards a conical intersection with S0 by a torsional motion involving a partially broken bond between the sulfur atoms. This process at lower excitation energy allows for efficient (re-)population of S0 , rendering dithiane intact. At 200 nm, in contrast, the excitation leads to a manifold of higher excited states, Sn , that are primarily of Rydberg character. We are able to follow the gradual transition from the initially excited state to the dissociative receiver state in real time. The Rydberg states are intersected by a repulsive valence state that mediates a transition to the repulsive S2 surface. Therefore, we propose that the resulting diradical will eventually break apart on a longer timescale. The findings imply that upon going from UV-B to UV-C light the structural integrity of the disulfide moiety is compromised and proteins irradiated in this range will not be able to reform the initial tertiary structure, leading to loss of function.