High‐Throughput Combinatorial Metal Complex Synthesis

Abstract High‐throughput combinatorial metal complex synthesis has emerged as a powerful tool for rapidly generating and screening diverse libraries of metal complexes, enabling accelerated discovery in fields such as catalysis, medicinal chemistry, and materials science. By systematically combining building blocks under mild and efficient conditions, researchers can explore broad chemical spaces, increasing the likelihood of identifying complexes with desired properties. This method streamlines hit identification and optimisation, especially when integrated with high‐throughput screening and data‐driven approaches like machine learning. Despite challenges such as scalability and purity control, recent advancements in automation and predictive modelling are enhancing the efficiency of combinatorial synthesis, opening new avenues for the development of metal‐based catalysts, therapeutic agents, and functional materials.

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Publication Details

Journal
Angewandte Chemie
Published
2024-12-23
DOI
https://doi.org/10.1002/ange.202420204
Primary Topic
Catalysis and Oxidation Reactions
Type
article
Field-Weighted Citation Impact
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article

High‐Throughput Combinatorial Metal Complex Synthesis

Angelo Frei, A. Welsh, David R. Husbands
Angewandte Chemie
Catalysis and Oxidation Reactions
article

High‐Throughput Combinatorial Metal Complex Synthesis

Angelo Frei, A. Welsh, David R. Husbands
article en

Abstract

Abstract High‐throughput combinatorial metal complex synthesis has emerged as a powerful tool for rapidly generating and screening diverse libraries of metal complexes, enabling accelerated discovery in fields such as catalysis, medicinal chemistry, and materials science. By systematically combining building blocks under mild and efficient conditions, researchers can explore broad chemical spaces, increasing the likelihood of identifying complexes with desired properties. This method streamlines hit identification and optimisation, especially when integrated with high‐throughput screening and data‐driven approaches like machine learning. Despite challenges such as scalability and purity control, recent advancements in automation and predictive modelling are enhancing the efficiency of combinatorial synthesis, opening new avenues for the development of metal‐based catalysts, therapeutic agents, and functional materials.

Angewandte ChemieVol. 137(6)
University of Bern (CH), University of York (GB)
Industry, innovation and infrastructure
Openalex Percentile: Top 87%
Catalysis and Oxidation Reactions
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