A Brief Introduction to Chemical Reaction Optimization

Abstract

From the start of a synthetic chemist’s training, experiments are conducted based on recipes from textbooks and manuscripts that achieve clean reaction outcomes, allowing the scientist to develop practical skills and some chemical intuition. This procedure is often kept long into a researcher’s career, as new recipes are developed based on similar reaction protocols, and intuition-guided deviations are conducted through learning from failed experiments. However, when attempting to understand chemical systems of interest, it has been shown that model-based, algorithm-based, and miniaturized high-throughput techniques outperform human chemical intuition and achieve reaction optimization in a much more time- and material-efficient manner; this is covered in detail in this paper. As many synthetic chemists are not exposed to these techniques in undergraduate teaching, this leads to a disproportionate number of scientists that wish to optimize their reactions but are unable to use these methodologies or are simply unaware of their existence. This review highlights the basics, and the cutting-edge, of modern chemical reaction optimization as well as its relation to process scale-up and can thereby serve as a reference for inspired scientists for each of these techniques, detailing several of their respective applications.

Circularity in polymers: addressing performance and sustainability challenges using dynamic covalent chemistries

“…Prediction and exploration of physical properties and ne-tuning of chemical reaction behavior in DCvC-based polymers also can be enhanced through emerging articial intelligence options, polymer-specic notations, and databases (e.g., BigSMILES, CRIPT). [245][246][247] Aside from material-based concerns, social and behavioral challenges associated with waste plastics recovery also limit closed-loop recycling of polymer plastics waste. [17][18][19][20][21] Long-lasting solutions toward circularity will require not only multidisciplinary scientic advances but policy reform from industry and government, and elimination of social barriers to recycling.…”

“…, BigSMILES, CRIPT). 245–247 Aside from material-based concerns, social and behavioral challenges associated with waste plastics recovery also limit closed-loop recycling of polymer plastics waste. 17–21 Long-lasting solutions toward circularity will require not only multidisciplinary scientific advances but policy reform from industry and government, and elimination of social barriers to recycling.…”

Efficient degassing and ppm-level oxygen monitoring flow chemistry system

“…Recent advances in continuous-flow systems show their large potential in the automation of chemistry and chemical analyses. [1][2][3][4][5][6][7][8] By utilising continuous-flow platforms, computerassisted screening of the photophysical properties of molecular probes can significantly accelerate reaction discovery. [9][10][11] This shows the importance of developing continuous-flow analogues of experimental techniques that are currently used in regular batch processing.…”

Self-Optimizing Flow Reactors Get a Boost by Multitasking

“…The use of a liquid handler to make up the reaction mixture also enabled this study to include categorical variables (e.g., solvent and ligand) in the optimization problem, a consideration that is very difficult to handle in standard optimization approaches. 4 In the early days of self-optimizing flow reactors, the lack of requirement for any a priori reaction knowledge (e.g., mechanistic proposals and pre-existing data sets) was seen as a benefit. What could be better than getting optimum reaction conditions at the touch of a button, without having to do any prior research?…”

“…While such iterative processes have also been reported using batch processing, flow chemistry allows a response to each individual experiment and is generally easier to automate. The use of a liquid handler to make up the reaction mixture also enabled this study to include categorical variables (e.g., solvent and ligand) in the optimization problem, a consideration that is very difficult to handle in standard optimization approaches …”