Accelerated parametrization of catalyst performance in organic electrosynthesis

Nikolaienko P, Mayrhofer KJ (2022)


Publication Type: Journal article, Review article

Publication year: 2022

Journal

Book Volume: 35

Article Number: 101103

DOI: 10.1016/j.coelec.2022.101103

Abstract

The increasing availability of renewable electrical energy from wind and solar power is becoming an enabler for the next phase in the global energy transition, namely the coupling of different energy sectors. Besides electrochemical energy conversion for daily and seasonal energy storage, the synthesis of organic fine chemicals or commodities by direct utilization of electricity has enormous potential to contribute to the reduction of greenhouse gas emissions. Electrical energy has already proven to be a perfect replacement for reducing and oxidizing chemical reagents in various reactions, sometimes even succeeding with superb selectivity or even unique molecular interconnectivity. Non-aqueous electrochemical processes in organic media have received much attention over the last decades as a methodology to achieve high electrode potentials and stability of generated active species, inaccessible in an aqueous medium. Because of the exceptional flexibility of the approach and the many influential parameters, however, the discovery and development of novel electrochemical processes commonly comprise extensive experimentation based on batch cell preparation accompanied by post-mortem analysis. The state-of-the-art approaches are cumbersome and time-consuming and often lack the information depth that could be obtained with direct analysis of intermediates and products. This perspective aims to overview current advances in the development of intensive methods for organic electrosynthetic catalyst search protocols and optimization. Novel high-throughput experimentation strategies for fast probing of large numbers of materials and solution compositions, combined with time-resolved product analysis and automated data analysis as well as artificial intelligence, will in the future accelerate the implementation of renewable energy in chemical industry processes.

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How to cite

APA:

Nikolaienko, P., & Mayrhofer, K.J. (2022). Accelerated parametrization of catalyst performance in organic electrosynthesis. Current Opinion in Electrochemistry, 35. https://dx.doi.org/10.1016/j.coelec.2022.101103

MLA:

Nikolaienko, Pavlo, and Karl J.J. Mayrhofer. "Accelerated parametrization of catalyst performance in organic electrosynthesis." Current Opinion in Electrochemistry 35 (2022).

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