Volume 1 Issue 4, April 2018

Catalysis is a complex, multidimensional and multiscale field of research. Machine learning is helping to build better models, understand catalysis research and generate new knowledge about catalysis.

The solid electrolyte interphase that forms on graphite anodes plays a vital role in the performance of lithium-ion batteries. Now research shows that the formation of lithium fluoride deposits — one of the main components of the solid electrolyte interphase — is strongly influenced by the electrocatalytic activity of the anode.

Tensile strain of a solid surface can result in either strengthening or weakening of bonds with adsorbates. Adsorption energies of different adsorbate/site combinations may be shifted in different directions — a striking violation of the Brønsted–Evans–Polanyi relation.

Discerning the precise mechanisms of photocatalytic energy conversion has long been a challenge. A computational multiscale approach reveals insights into the reaction pathways and rate-limiting steps of the oxygen evolution reaction, the bottleneck for water splitting on TiO₂ surfaces.

For electrocatalysts, the activity and stability is determined by the surface — often just a few atomic layers thick. Now atom probe tomography is used to examine the changing surface of an oxygen evolution catalyst at near-atomic-scale resolution, linking structure to activity and stability.

CO is a vital building block in organic synthesis but, due to its toxicity, storage and transport can be problematic. This review focuses on the methods — both chemical and electrochemical — for the in situ generation of CO from CO₂, and its subsequent incorporation into chemicals through catalytic means.

Despite the central role that the solid electrolyte interphase plays on the efficiency of Li-ion batteries, little is known about its formation mechanism. It is now shown that LiF forms on graphite anodes as a result of the electrocatalytic transformation of HF impurities present in the electrolyte.

Scaling relationships provide powerful predictive opportunities in catalysis, but at the same time also reflect the limitations related to the design of new catalytic systems. Now, theoretical studies show how mechanical strain on catalyst surfaces can be engineered to break scaling relations.

Plasma catalysis holds promise for overcoming the limitations of conventional catalysis. Now, a kinetic model for ammonia synthesis is reported to predict optimal catalysts for use with plasmas. Reactor measurements at near-ambient conditions confirm the predicted catalytic rates, which are similar to those obtained in the Haber–Bosch process.

The creation of artificial reaction networks whose dynamics are programmable and predictable is a central goal in synthetic biology. This work describes an enzymatic reaction network that can generate tunable complex dynamics based on delayed and self-adapting substrate competition.

Electrochemical routes for the production of hydrogen peroxide would reduce the waste inherent in the current anthraquinone process, and also make distributed and on-site production more feasible. Here, inexpensive reduced graphene oxide is proven to be a stable and selective catalyst for oxygen reduction at remarkably low overpotentials.

A high reaction barrier is often assumed as the limiting factor in photocatalytic oxygen evolution reactions on titanium dioxide. Now, it is shown that the hole concentration at the semiconductor’s surface is the actual bottleneck in determining the catalytic efficiency.

Morphological changes in catalyst structure are known to occur during electrocatalysis, and understanding such changes is important to gain insight into the catalytic process. Now, in the case of iridium oxide, these surface changes are probed in atomic-scale detail during the oxygen evolution reaction, and correlated with activity and stability.