Over the last two decades, flow technologies have become increasingly popular in the field of organic chemistry, offering solutions for engineering and/or chemical problems. Flow reactors enhance the mass and heat transfer, resulting in rapid reaction mixing, and enable a precise control over the reaction parameters, increasing the overall process selectivity, efficiency and safety. These features allow chemists to tackle unexploited challenges in their work, with the ultimate objective making chemistry more accessible for laboratory and industrial applications, avoiding the need to store and handle toxic, reactive and explosive reagents. This review covers some of the latest and most relevant developments in the field of continuous flow chemistry with the focus on hazardous reactions.

Taming hazardous chemistry by continuous flow technology

Interpretation of variable importance in Partial Least Squares with Significance Multivariate Correlation (sMC)

An automated continuous reactor for the synthesis of organic compounds, which uses online mass spectrometry (MS) for reaction monitoring and product quantification, is presented. Quantitative and rapid MS monitoring was developed and calibrated using HPLC. The amidation of methyl nicotinate with aqueous MeNH2 was optimised using design of experiments and a self-optimisation algorithm approach to produce >93% yield.

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Online quantitative mass spectrometry for the rapid adaptive optimisation of automated flow reactors

A hybrid variable selection strategy based on continuous shrinkage of variable space in multivariate calibration.

Implementation of liquid chromatography-high resolution mass spectrometry methods for untargeted metabolomic analyses of biological samples: A tutorial.

The quality and practical usefulness of a regression model are a function of both interpretability and prediction performance. This work presents some new graphical tools for improved interpretation of latent variable regression models that can also assist in improved algorithms for variable selection. Thus, these graphs provide visualization of the explanatory variables’ content of response related as well as systematic orthogonal variation at a quantitative level. Furthermore, these graphs are able to reveal and partition the explanatory variables into those that are crucial for both interpretation and predictive performance of the model, and those that are crucial for prediction performance but confounded by large contributions of orthogonal variation. Tools for assessment of explanatory variables may not only aid interpretation and understanding of the model but also be crucial for performing variable selection with the purpose of obtaining parsimonious models with high explanatory information content aswell as predictive performance. We show by example that by just using prediction performance as criterion for variable selection, it is possible to end up with a reducedmodel where the most selective variables are lost in the selection process.

Variable importance in latent variable regression models

Continuous flow reactors (CFRs) are an emerging technology that offer several advantages over traditional batch synthesis methods, including more efficient mixing schemes, rapid heat transfer, and increased user safety. Of particular interest to the specialty chemical and pharmaceutical manufacturing industries is the significantly improved reliability and product reproducibility over time. CFR reproducibility can be attributed to the reactors achieving and maintaining a steady state once all physical and chemical conditions have stabilized. This work describes the implementation of a smart CFR with univariate physical and multivariate chemical monitoring that allows for rapid determination of steady state, requiring less than one minute. Additionally, the use of process analytical technology further enabled a significant reduction in the time and cost associated with offline validation methods. The technology implemented for this study is chemistry and hardware agnostic, making this approach a viable means of optimizing the conditions of any CFR.

Rapid Determination of Optimal Conditions in a Continuous Flow Reactor Using Process Analytical Technology

The Moffatt-Swern oxidation (MSO) is a multistep, versatile, metal-free reaction by which alcohols are transformed into aldehydes and ketones. Batch MSO requires low temperatures (−70 °C) due to a highly exothermic reaction step that generates intermediates. This work shows that a rigorous investigation of the MSO in batch can be used as a stepping-stone to its implementation in a continuous-flow reactor (CFR). This work has two parts: the first part details the investigation of MSO in batch; the second covers the translation of the knowledge derived from batch to a CFR. The MSO batch reaction was performed under cryogenic conditions with real-time process monitoring. The reaction was monitored with Raman spectroscopy and could be tracked throughout the reaction. All concentrations were validated using offline high-performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS). Two configurations of the CFR were produced. Configuration 1 used the traditional batch methodology in...

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Olav Bleie

Papers

Variable importance in latent variable regression models

Rapid Determination of Optimal Conditions in a Continuous Flow Reactor Using Process Analytical Technology

Moffat-Swern oxidation of alcohols: Translating a batch reaction to a continuous-flow reaction