CIME4R: Exploring iterative, AI-guided chemical reaction optimization campaigns in their parameter space

Abstract Chemical reaction optimization (RO) is an iterative process that results in large, high-dimensional datasets. Current tools allow for only limited analysis and understanding of parameter spaces, making it hard for scientists to review or follow changes throughout the process. With the recen...

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Autori principali:	Christina Humer, Rachel Nicholls, Henry Heberle, Moritz Heckmann, Michael Pühringer, Thomas Wolf, Maximilian Lübbesmeyer, Julian Heinrich, Julius Hillenbrand, Giulio Volpin, Marc Streit
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	BMC 2024-05-01
Serie:	Journal of Cheminformatics
Soggetti:	Reaction optimization Explainable AI Artificial intelligence Bayesian optimization Interpretable
Accesso online:	https://doi.org/10.1186/s13321-024-00840-1
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