Application of Spectroscopy Techniques for Monitoring (Bio)Catalytic Processes in Continuously Operated Microreactor Systems

In the last twenty years, the application of microreactors in chemical and biochemical industrial processes has increased significantly. The use of microreactor systems ensures efficient process intensification due to the excellent heat and mass transfer within the microchannels. Monitoring the concentrations in the microchannels is critical for a better understanding of the physical and chemical processes occurring in micromixers and microreactors. Therefore, there is a growing interest in performing in-line and on-line analyses of chemical and/or biochemical processes. This creates tremendous opportunities for the incorporation of spectroscopic detection techniques into production and processing lines in various industries. In this work, an overview of current applications of ultraviolet–visible, infrared, Raman spectroscopy, NMR, MALDI-TOF-MS, and ESI-MS for monitoring (bio)catalytic processes in continuously operated microreactor systems is presented. The manuscript includes a description of the advantages and disadvantages of the analytical methods listed, with particular emphasis on the chemometric methods used for spectroscopic data analysis.

Review of quantitative and qualitative methods for monitoring photopolymerization reactions

Authomatic in-situ monitoring and characterization of photopolymerization.

Effect of Cationic Groups on the Selectivity of Ternary Antimicrobial Polymers

Antimicrobial polymers (AMPs) have emerged as a promising approach to combat multidrug-resistant pathogens. Developed from binary polymers, which contain cationic and hydrophobic groups, ternary polymers are enhanced by adding neutral hydrophilic monomers to improve their biocompatibility. Cationic groups have attracted significant attention owing to their pivotal role in AMPs. Although many studies have investigated the effect of cationic groups on antimicrobial activity of binary AMPs, there is a lack of comprehensive and systematic evaluation for ternary AMPs. Therefore, a library of 31 statistical amphiphilic ternary polymers containing different cationic groups, including primary amine, guanidine and sulfonium groups was prepared to investigate the impact of cationic groups on antimicrobial activity and biocompatibility. We show that the cationic balance appears to be a critical factor influencing polymers' antibacterial activity and selectivity. Our results reveal that the polymers that have the ratio of the cationic groups ranging between 50-60%, coupled with a cationic/hydrophobic ratio in the range of [1.4-2] and an appropriate neutral hydrophilic/hydrophobic balance, exhibited the highest selectivity toward mammalian cells. Furthermore, selectivity can be improved with suitable cationic moieties and good neutral hydrophilic candidates. In the present study, a lysine-mimicking monomer and PEG chain were the best choices for cationic and hydrophilic sources to develop the most selective AMPs, displaying an impressive selectivity for HC₅₀ and IC₅₀ greater than 83 and 21, respectively. This study elucidates a structure-property-performance relationship for ternary AMPs, which contributes to the development of AMPs capable of selectively targeting gram-negative pathogens. This article is protected by copyright. All rights reserved.

Synthesis of multifunctional poly(carbamoyl ester)s containing dual-cleavable linkages and an AIE luminogen via Passerini-type multicomponent polymerization

We conducted Passerini multicomponent polymerizations with aldehydes, carboxylic acids, and isocyanide and afforded novel functional poly(carbamoyl ester)s with dual-cleavable linkages and an aggregation-induced emission luminogen.

An integrated resource-efficient microfluidic device for parallelised studies of immobilised chiral catalysts in continuous flow via miniaturized LC/MS-analysis

Dual-μReactor catalysis screening: a novel method combining multiple miniaturized packed-bed reactors and on-line HPLC/MS-analysis on one single microfluidic device.

Generation and Characterization of a Library of Novel Biologically Active Functional Surfactants (Surfmers) Using Combined High-Throughput Methods

We report the first successful combination of three distinct high-throughput techniques to deliver the accelerated design, synthesis, and property screening of a library of novel, bio-instructive, polymeric, comb-graft surfactants. These three-dimensional, surface-active materials were successfully used to control the surface properties of particles by forming a unimolecular deep layer on the surface of the particles via microfluidic processing. This strategy deliberately utilizes the surfactant to both create the stable particles and deliver a desired cell-instructive behavior. Therefore, these specifically designed, highly functional surfactants are critical to promoting a desired cell response. This library contained surfactants constructed from 20 molecularly distinct (meth)acrylic monomers, which had been pre-identified by HT screening to exhibit specific, varied, and desirable bacterial biofilm inhibitory responses. The surfactant's self-assembly properties in water were assessed by developing a novel, fully automated, HT method to determine the critical aggregation concentration. These values were used as the input data to a computational-based evaluation of the key molecular descriptors that dictated aggregation behavior. Thus, this combination of HT techniques facilitated the rapid design, generation, and evaluation of further novel, highly functional, cell-instructive surfaces by application of designed surfactants possessing complex molecular architectures.

High-throughput experimentation meets artificial intelligence: a new pathway to catalyst discovery

High throughput experimentation in heterogeneous catalysis provides an efficient solution to the generation of large datasets under reproducible conditions. Knowledge extraction from these datasets has mostly been performed using statistical methods, targeting the optimization of catalyst formulations. The combination of advanced machine learning methodologies with high-throughput experimentation has enormous potential to accelerate the predictive discovery of novel catalyst formulations that do not exist with current statistical design of experiments. This perspective describes selective examples ranging from statistical design of experiments for catalyst synthesis to genetic algorithms applied to catalyst optimization, and finally random forest machine learning using experimental data for the discovery of novel catalysts. Lastly, this perspective also provides an outlook on advanced machine learning methodologies as applied to experimental data for materials discovery.

Tailoring polymer dispersity and shape of molecular weight distributions: methods and applications

The width and shape of molecular weight distributions can significantly affect the properties of polymeric materials and thus are key parameters to control. This mini-review aims to critically summarise recent approaches developed to tailor molecular weight distributions and highlights the strengths and limitations of each technique. Special emphasis will also be given to applications where tuning the molecular weight distribution has been used as a strategy to not only enhance polymer properties but also to increase the fundamental understanding behind complex mechanisms and phenomena.

Synthesis of a well-defined alternating copolymer of 1,1-diphenylethylene and tert-butyldimethylsilyloxymethyl substituted styrene by anionic copolymerization: toward tailored graft copolymers with controlled side chain densities

Well-defined alternating copolymers comprising 1,1-diphenylethylene (DPE) and styrene derivative having sterically bulky tert-butyldimethylsilyloxymethyl group at the meta position (St-TBS) were successfully synthesized.

Mapping Dithiobenzoate-Mediated RAFT Polymerization Products via Online Microreactor/Mass Spectrometry Monitoring

2-cyano-2-propyl dithiobenzoates (CPDB)-mediated reversible addition-fragmentation chain transfer (RAFT) polymerization was monitored by online flow microreactor/mass spectrometry. This enabled the reactions to be followed in a time-resolved manner, closely resolving product patterns in the reaction mixtures at any point in time. RAFT polymerization was investigated for low RAFT to monomer ratios, enabling the monitoring of the early stages of a typical RAFT polymerization. The expected transition from pre- to the RAFT main equilibrium is observed. However, very high abundancies for cross-termination products were also identified, both in the pre- and main equilibrium stage. This is a somewhat surprising result as such products have always been expected, but to date have not been observed in the majority of studies. Product isolation and NMR analysis revealed that cross-termination occurs in the para position of the benzoate ring and becomes fully irreversible via re-aromatization of the ring in a H-shift reaction. The present data suggest a pronounced chain-length dependence of the cross-termination reaction, which would explain why the products are seen here, but not in other studies.

On the direct use of CO2 in multicomponent reactions: introducing the Passerini four component reaction

We introduce a novel isocyanide-based multicomponent reaction, the Passerini four component reaction (P-4CR), by replacing the carboxylic acid component of a conventional Passerini three component reaction (P-3CR) with an alcohol and CO₂. Key to this approach is the use of a switchable solvent system, allowing the synthesis of a variety of α-carbonate-amides. The reaction was first investigated and optimized using butanol, isobutyraldehyde, tert-butyl isocyanide and CO₂. Parameters investigated included the effect of reactant equivalents, reactant concentration, solvent, catalyst, catalyst concentration and CO₂ pressure. Of the other parameters, the purity of the aldehyde and its tendency to oxidize was one of the most critical parameters for a successful P-4CR. After optimization, a total of twelve (12) P-4CR compounds were synthesized with conversions ranging between 16 and 82% and isolated yields between 18 and 43%. Their structures were confirmed via¹H and ¹³C NMR, FT-IR and high resolution mass spectrometry (ESI-MS). In addition, three (3) hydrolysis products of P-4CR (α-hydroxyl-amides) were successfully isolated with yields between 23 and 63% and fully characterized (¹H, ¹³C NMR, FT-IR and ESI-MS) as well.

We introduce a novel isocyanide-based multicomponent reaction, the Passerini four component reaction (P-4CR), by replacing the carboxylic acid component of a conventional Passerini three component reaction (P-3CR) with an alcohol and CO₂.

Sequence-definition from controlled polymerization: the next generation of materials

An overview is given on the state-of-the-art in synthesis of sequence-controlled and sequence-defined oligomers and polymers.