Process analysis in micro-reactors: challenges and solutions with Raman spectrometry

Nordon, Alison and Littlejohn, David and Mozharov, Sergey and Girkin, John; (2011) Process analysis in micro-reactors: challenges and solutions with Raman spectrometry. In: Proceedings of SPIE 7929. SPIE, WA, USA. ISBN 978-0-81948-466-6 (https://doi.org/10.1117/12.874227)

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Abstract

With the increasing interest in the exploitation of micro-reactors, there is a growing demand for process monitoring and control methods suitable for application in this environment. At present off-line analysis methods such as chromatography and mass spectrometry are the dominant tools in the field. Although these methods provide exceptionally rich chemical information they require removal of samples from the system and the analysis is not instantaneous. In many microfluidic applications these limitations outweigh their benefits due to the importance of real-time detection and the desired ability to analyze the fluid in different locations in the micro-reactor non-invasively. Therefore optical detection methods such as fluorescence and Raman spectroscopy are becoming increasingly popular in this field, with most attention being drawn to miniature integrated optical sensors. However, integration of sensors into a micro-reactor can change the flow conditions and make the system difficult to scale out. It is also impossible to move the integrated sensor along the flow path. These issues make on-chip process analysis a challenging subject that is still at the early stages of development. This paper discusses opportunities for non-invasive process analysis in micro-reactors focusing the main attention on Raman spectrometry as a powerful technique, whose potential in this field has not been widely recognized yet. With a specially developed probe we demonstrate ability to monitor fluid delivery stability and perform fast real-time analysis of a model esterification reaction. The discussed approach brings unique benefits to kinetics studies, efficient process optimization and process control.

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