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The ReactALL Platform: Experimental Data and Case Studies

Joel M. Hawkins, David M. Pfisterer, Russell F. Algera, Sébastien Monfette

2024Organic Process Research & Development5 citationsDOI

Abstract

The generation of scale-relevant data to predict performance in a manufacturing setting is a cornerstone of process chemistry. Modern, data-rich experimentation is routinely performed in automated laboratory reactors at the 50–100 mL scale, but there remains a gap between the data-rich experimentation scale and that associated with high-throughput experimentation. Filling this gap would offer access to scale-relevant data but with less material and increased parallelization. The new ReactALL medium-scale reactor platform aims to fill this gap. Here, we present four case studies aimed at evaluating the capabilities of this new platform and providing experimental data obtained from the reactor prototype.

Topics & Concepts

CornerstoneScale (ratio)Computer scienceThroughputProcess (computing)Process engineeringSCALE-UPExperimental dataEngineeringOperating systemMathematicsPhysicsArtWirelessVisual artsClassical mechanicsStatisticsQuantum mechanicsInnovative Microfluidic and Catalytic Techniques InnovationMachine Learning in Materials ScienceComputational Drug Discovery Methods
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