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Scaling Up Reactors for Microwave-Assisted Chemistry via ANN Optimization

Scaling up efficient reactions in microwave-assisted chemistry to the level of industrial technology is slowed down by natural difficulties in development of large-scale and highly productive reactors.

Published onJan 26, 2020
Scaling Up Reactors for Microwave-Assisted Chemistry via ANN Optimization
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Abstract

Scaling up efficient reactions in microwave-assisted chemistry to the level of industrial technology is slowed down by natural difficulties in development of large-scale and highly productive reactors. This paper addresses this issue by demonstrating that a particular microwave reactor can be designed with the help of computer optimization that maximizes energy coupling. We outline an approach based on the application of an efficient neural network optimization technique to a microwave reactor. This technique is used here to optimize the geometry of a system designed as a direct enlargement of an existing small, laboratory-scale reactor. Viability of our approach is illustrated by examples of three-parameter optimization of larger systems guaranteeing, for a given reactant, at least 90% energy efficiency.

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Holmes, A. O., Murphy, E., & Yakovlev, V. V. (2013). Scaling Up Reactors for Microwave-Assisted Chemistry via ANN Optimization. 14th International Conference on Microwave and High Frequency Heating.

*denotes a WPI undergraduate student author

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