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 recent emergence of using artificial intelligence (AI) models to aid RO, another level of complexity has been added. Helping to assess the quality of a model's prediction and understand its decision is critical to supporting human-AI collaboration and trust calibration. To address this, we propose CIME4R-an open-source interactive web application for analyzing RO data and AI predictions. CIME4R supports users in (i) comprehending a reaction parameter space, (ii) investigating how an RO process developed over

SUBMITTER: Humer C 

PROVIDER: S-EPMC11636728 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature