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Electrosynthetic Screening and Modern Optimization Strategies for Electrosynthesis of Highly Value‐added Products
Author(s) -
Dörr Maurice,
Hielscher Maximilian M.,
Proppe Jonny,
Waldvogel Siegfried R.
Publication year - 2021
Publication title -
chemelectrochem
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.182
H-Index - 59
ISSN - 2196-0216
DOI - 10.1002/celc.202100318
Subject(s) - toolbox , electrosynthesis , context (archaeology) , computer science , selection (genetic algorithm) , biochemical engineering , relation (database) , added value , value (mathematics) , chemistry , data mining , artificial intelligence , engineering , machine learning , electrode , electrochemistry , biology , paleontology , programming language , finance , economics
Unlike common analytical techniques such as cyclic voltammetry, statistics‐based optimization tools are not yet often in the toolbox of preparative organic electrochemists. In general, experimental effort is not optimally utilized because the selection of experimental conditions is based on the one‐variable‐at‐a‐time principle. We will summarize statistically motivated optimization approaches already used in the context of electroorganic synthesis. We discuss the central ideas of these optimization methods which originate from other fields of chemistry in relation to electrosynthetic applications.