Real-time simplex optimization of flow-injection systems for chemical analysis

Simultaneous self-optimisation of yield and purity through successive combination of inline FT-IR spectroscopy and online mass spectrometry in flow reactions

Self-optimisation constitutes a very helpful tool for chemical process development, both in lab and in industrial applications. However, research on the application of model-free autonomous optimisation strategies (based on experimental investigation) for complex reactions of high industrial significance, which involve considerable intermediate and by-product formation, is still in an early stage. This article describes the development of an enhanced autonomous microfluidic reactor platform for organolithium and epoxide reactions that incorporates a successive combination of inline FT-IR spectrometer and online mass spectrometer. Experimental data is collected in real-time and used as feedback for the optimisation algorithms (modified Simplex algorithm and Design of Experiments) without time delay. An efficient approach to handle intricate optimisation problems is presented, where the inline FT-IR measurements are used to monitor the reaction’s main components, whereas the mass spectrometer’s high sensitivity permits insights into the formation of by-products. To demonstrate the platform’s flexibility, optimal reaction conditions of two organic syntheses are identified. Both pose several challenges, as complex reaction mechanisms are involved, leading to a large number of variable parameters, and a considerable amount of by-products is generated under non-ideal process conditions. Through multidimensional real-time optimisation, the platform supersedes labor- and cost-intensive work-up procedures, while diminishing waste generation, too. Thus, it renders production processes more efficient and contributes to their overall sustainability.

Graphical abstract

Large-scale flow analysis: From repetitive assays to expert analyzers

Flow analysis is usually associated with repetitive assays, as all samples of a batch are generally handled in the same way. By exploiting computer-controlled devices (e.g. pumps, valves, injectors, commuters, and samplers), this scenario has been expanded, as a proper manifold dimensioning can be set for each sample. Initially, this dimensioning relied on previous information about each sample, added to the operating software prior to analysis of a given sample lot. Further, real-time decisions relying on feedback mechanisms started to be exploited for improving the analytical figures of merit, simplifying the laboratory management, and allowing real-time system optimization and fault detection. This is the essence of the expert flow analyzers, which involve manifold re-dimensioning by means of flow/manifold programming, often relying on multicommutation. The development of flow analysis from repetitive to real-time defined assays, the involved terminology, and trends on further development are highlighted in this review. Applications involve segmented and unsegmented flow analysis of agronomical, clinical, environmental, industrial, pharmaceutical, and geological samples.

Self-optimising processes and real-time-optimisation of organic syntheses in a microreactor system using Nelder–Mead and design of experiments

Comparing an enhanced simplex algorithm with model-free design of experiments, this work presents a flexible platform for multi-objective, real-time optimisation.