A Validated "Pool and Split" Approach to Screening and Optimization of Copper-Catalyzed C-N Cross-Coupling Reactions

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

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 iterations, (iii) identifying critical factors of a reaction, and (iv) understanding model predictions. This facilitates making informed decisions during the RO process and helps users to review a completed RO process, especially in AI-guided RO. CIME4R aids decision-making through the interaction between humans and AI by combining the strengths of expert experience and high computational precision. We developed and tested CIME4R with domain experts and verified its usefulness in three case studies. Using CIME4R the experts were able to produce valuable insights from past RO campaigns and to make informed decisions on which experiments to perform next. We believe that CIME4R is the beginning of an open-source community project with the potential to improve the workflow of scientists working in the reaction optimization domain. SCIENTIFIC CONTRIBUTION: To the best of our knowledge, CIME4R is the first open-source interactive web application tailored to the peculiar analysis requirements of reaction optimization (RO) campaigns. Due to the growing use of AI in RO, we developed CIME4R with a special focus on facilitating human-AI collaboration and understanding of AI models. We developed and evaluated CIME4R in collaboration with domain experts to verify its practical usefulness.

Oxalamide/Amide Ligands: Enhanced and Copper-Catalyzed C-N Cross-Coupling for Triarylamine Synthesis

Triarylamines are privileged core structures that are found in versatile optoelectronic materials. New methods are constantly being sought for their preparation. Herein, a new protocol for triarylamine synthesis is presented where a wide range of diarylamines couple smoothly with aryl bromides mediated by a copper oxalamide (or amide) catalytic system. Notably, a new non-C₂-symmetric 1-isoquinolinamide-based N,N-/N,O-bidentate ligand was introduced that could tolerate bulky diarylamines. Plenty of known optoelectronic functional molecules could be synthesized in good to excellent yields. The practicality of this C-N cross-coupling was illustrated by the gram-scale synthesis of a patented thermally activated delayed fluorescence emitter for organic light-emitting diodes.

A "Pool and Split" Approach to the Optimization of Challenging Pd-Catalyzed C-N Cross-Coupling Reactions

A screening method for the rapid identification of catalytic conditions for Pd-catalyzed C-N cross-coupling reactions is reported. The strategy evaluates mixtures of precatalysts, ligands, and bases to identify productive conditions that are subsequently optimized through two deconvolution steps, which uncover the active catalyst and identify the optimal solvent and base for the catalytic system. The efficacy of this approach was demonstrated through application to a previously reported reaction, whereby both the literature conditions and additional solutions were retrieved. The same approach to Ni-catalyzed C-N cross-coupling was investigated in parallel but was found to be less successful due to limited activity of the evaluated reagent combinations. Finally, the utility of this method was showcased by identifying effective conditions for the Pd-catalyzed cross-coupling of complex molecules, which not only revealed nonobvious solutions for the processes under evaluation but also resulted in the discovery of new chemical reactions.