A mixed-integer nonlinear program (MINLP) algorithm to optimize catalyst turnover number (TON) and product yield by simultaneously modulating discrete variables—catalyst types—and continuous variables—temperature, residence time, and catalyst loading—was implemented and validated.

Photoredox decarboxylative cross-coupling via iridium−nickel dual catalysis has emerged as a valuable method for C(sp 2 )−C(sp 3 ) bond formation. Herein we describe the application of a segmented flow ("microslug") reactor equipped with a newly designed photochemistry module for material-efficient reaction screening and optimization. Through the deployment of a self-optimizing algorithm, optimal flow conditions for the model reaction were rapidly developed, simultaneously accounting for the effects of continuous variables (temperature and time) and discrete variables (base and catalyst). Temperature was found to be a critical parameter with regard to reaction rates and hence productivity in subsequent scale-up in flow. The optimized conditions identified at microscale were found to directly transfer to a Vapourtec UV-150 continuous flow photoreactor, enabling predictable scaleup operation at a scale of hundreds of milligrams per hour. This optimization approach was then expanded to other halide coupling partners that were low-yielding in batch reactions, highlighting the practical application of this optimization platform in the development of conditions for photochemical synthesis in continuous flow.

Electrochemical CO 2 reduction is a promising process to store intermittent renewable energy in the form of chemical bonds and to meet the demand for hydrocarbon chemicals without relying on fossil fuels. Researchers in the field have used gas diffusion electrodes (GDEs) to supply CO 2 to the catalyst layer from the gas phase. This approach allows us to bypass mass transfer limitations imposed by the limited solubility and diffusion of CO 2 in the liquid phase at a laboratory scale. However, at a larger scale, pressure differences across the porous gas diffusion layer can occur. This can lead to flooding and electrolyte breakthrough, which can decrease performance. The aim of this study is to understand the effects of the GDE structure on flooding behavior and CO 2 reduction performance. We approach the problem by preparing GDEs from commercial substrates with a range of structural parameters (carbon fiber structure, thickness, and cracks). We then determined the liquid breakthrough pressure and measured the Faradaic efficiency for CO at an industrially relevant current density. We found that there is a trade-off between flooding resistance and mass transfer capabilities that limits the maximum GDE height of a flow-by electrolyzer. This trade-off depends strongly on the thickness and the structure of the carbon fiber substrate. We propose a design strategy for a hierarchically structured GDE, which might offer a pathway to an industrial scale by avoiding the trade-off between flooding resistance and CO 2 reduction performance.

Recent advances in Pd-catalyzed carbon–nitrogen cross-coupling have enabled the use of soluble organic bases instead of insoluble or strong inorganic bases that are traditionally employed. The single-phase nature of these reaction conditions facilitates their implementation in continuous flow systems, high-throughput optimization platforms, and large-scale applications. In this work, we utilized an automated microfluidic optimization platform to determine optimal reaction conditions for the couplings of an aryl triflate with four types of commonly employed amine nucleophiles: anilines, amides, primary aliphatic amines, and secondary aliphatic amines. By analyzing trends in catalyst reactivity across different reaction temperatures, base strengths, and base concentrations, we have developed a set of general recommendations for Pd-catalyzed cross-coupling reactions involving organic bases. The optimization algorithm determined that the catalyst supported by the dialkyltriarylmonophosphine ligand AlPhos was the most active in the coupling of each amine nucleophile. Furthermore, our automated optimization revealed that the phosphazene base BTTP can be used to facilitate the coupling of secondary alkylamines and aryl triflates.

Electrochemical CO2 reduction has the potential to use excess renewable electricity to produce hydrocarbon chemicals and fuels. Gas diffusion electrodes (GDEs) allow overcoming the limitations of CO2 mass transfer but are sensitive to flooding from (hydrostatic) pressure differences, which inhibits upscaling. We investigate the effect of the flooding behavior on the CO2 reduction performance. Our study includes six commercial gas diffusion layer materials with different microstructures (carbon cloth and carbon paper) and thicknesses coated with a Ag catalyst and exposed to differential pressures corresponding to different flow regimes (gas breakthrough, flow-by, and liquid breakthrough). We show that physical electrowetting further limits the flow-by regime at commercially relevant current densities (≥200 mA cm–2), which reduces the Faradaic efficiency for CO (FECO) for most carbon papers. However, the carbon cloth GDE maintains its high CO2 reduction performance despite being flooded with the electrolyte due to its bimodal pore structure. Exposed to pressure differences equivalent to 100 cm height, the carbon cloth is able to sustain an average FECO of 69% at 200 mA cm–2 even when the liquid continuously breaks through. CO2 electrolyzers with carbon cloth GDEs are therefore promising for scale-up because they enable high CO2 reduction efficiency while tolerating a broad range of flow regimes.