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With the rise of self-driving labs (SDLs) and automated experimentation across chemical and materials sciences, there is a considerable challenge in designing the best autonomous lab for a given problem based on published studies alone. Determining what digital and physical features are germane to a specific study is a critical aspect of SDL design that needs to be approached quantitatively. Even when controlling for features such as dimensionality, every experimental space has unique requirements and challenges that influence the design of the optimal physical platform and algorithm. Metrics such as optimization rate are therefore not necessarily indicative of the capabilities of an SDL across different studies. In this perspective, we highlight some of the critical metrics for quantifying performance in SDLs to better guide researchers in implementing the most suitable strategies. We then provide a brief review of the existing literature under the lens of quantified performance as well as heuristic recommendations for platform and experimental space pairings. Assessing the performance of self-driving labs (SDLs) is challenging due to the specificities of each experiment. In this Perspective, the authors review recent literature of SDLs for materials science and chemistry and suggest how to report SDL performance more effectively. [ABSTRACT FROM AUTHOR]

Synthesis of hindered amines using the atom-efficient hydroaminomethylation (HAM) route remains a challenge. Here, we report a general and accelerated HAM in segmented flow, achieved via a cooperative effect between rhodium (Rh)/N-Xantphos and a co-catalyst (2-Fluoro-4-methylbenzoic acid) to increase the reactivity by 70 fold when compared to Rh/Xantphos in batch reactors. The cooperation between Rh and the co-catalyst facilitates the cleavage of the H–H bond and drives the equilibrium-limited condensation step forward. Online reaction optimization expands the scope to include alkyl, aryl, and primary amines. In-flow solvent tuning enables selectivity switching from amine to enamine without the need for changing the ligand. Furthermore, leveraging the ionic nature of the catalyst, we present a robust Rh recovery strategy up to 4 recycles without loss of activity. Flow chemistry enables intensified production of hindered amines. Here the authors present a rapid and reusable catalyst to operate in a segmented flow reactor for olefin hydroaminomethylation to selectively produce hindered amines or enamines. [ABSTRACT FROM AUTHOR]

Tube-in-tube flow reactors are emerging as a highly efficient flow chemistry strategy for performing various types of gas-liquid reactions due to their unique characteristics, such as high specific interfacial area, enhanced mass transfer and mixing, reduced material consumption, and safe handling of toxic and flammable gases. In this article we discuss the most recent advancements in utilizing tube-in-tube flow reactors for fundamental and applied studies of high-pressure gas-liquid reactions with carbon monoxide, hydrogen, and syngas. General guidelines for successful assembly of such flow chemistry platforms are discussed. In addition, a perspective on future potential directions for further development of the tube-in-tube flow reactors such as scale-up and increased robustness are provided. [ABSTRACT FROM AUTHOR]