吞吐量
组合综合
化学
组合化学
纳米技术
计算机科学
材料科学
电信
无线
作者
A. Welsh,David R. Husbands,Angelo Frei
标识
DOI:10.1002/ange.202420204
摘要
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 (BBs) 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 (HTS) 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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