Quantitative reaction monitoring using parahydrogen-enhanced benchtop NMR spectroscopy

The parahydrogen-induced polarisation (PHIP) NMR signal enhancement technique is used to study H2 addition to Vaska's complex (trans-[IrCl(CO)(PPh3)2]) with both standard high-field (9.4 T) NMR and benchtop (1 T) NMR detection. Accurate and repeatable rate constants of (0.84 ± 0.03) dm3 mol-1 s-1 and (0.89 ± 0.03) dm3 mol-1 s-1 were obtained for this model system using standard high-field and benchtop NMR, respectively. The high-field NMR approach is shown to be susceptible to systematic errors associated with interference from non-hyperpolarised signals, which can be overcome through a multiple-quantum filtered acquisition scheme. This challenge is avoided when using benchtop NMR detection because the non-hyperpolarised signals are much weaker due to the lower magnetic field, enabling the use of a simpler and more efficient single RF pulse detection scheme. Method validation against several experimental parameters (NMR relaxation, %pH2 enrichment and temperature) demonstrates the robustness of the benchtop NMR approach but also highlights the need for sample temperature control throughout reaction monitoring. A simple temperature equilibration protocol, coupled with use of an insulated sample holder while manipulating the sample outside the spectrometer, is found to provide sufficient temperature stabilisation to ensure that accurate and repeatable rate constants are obtained. Finally, the benchtop NMR reaction monitoring protocol is applied to the analysis of a complex mixture, where multiple reaction products form simultaneously. H2 addition to a mixture of three Vaska's complex derivatives was monitored, revealing the presence of competitive reaction pathways within the mixture.

Flow-Chemistry-Enabled Synthesis of 5-Diethylboryl-2,3'-bipyridine and Its Self-Assembly Dynamics

5-Diethylboryl-2,3'-bipyridine (1), which is inaccessible by conventional batch methods, was synthesized by using a flow microreactor. Compound 1 was obtained as an equilibrium mixture of a cyclic trimer and a cyclic tetramer in solution, the latter of which was crystallized in benzene by vapor diffusion of hexane at 7 °C. The dynamic nature of this system was confirmed by solvent- and concentration-dependent experiments. Notably, the dynamics was verified by using flow NMR spectroscopy, which revealed that the time required to reach equilibrium was influenced by the solvent ratio (<18 s, 24-28 s, and 34-42 s in 2 : 1, 1 : 1, and 1 : 2 mixtures of [D₆ ]acetone and C₆ D₆ , respectively). Compound 1 and 3-[4'-(diethylboryl)phenyl]pyridine (2) exhibited different self-assembly behavior in solution and crystals. Density functional theory calculations suggested that this difference was largely due to enhanced planarity between two consecutive aromatic rings.

Autonomous Multi-Step and Multi-Objective Optimization Facilitated by Real-Time Process Analytics

Autonomous flow reactors are becoming increasingly utilized in the synthesis of organic compounds, yet the complexity of the chemical reactions and analytical methods remains limited. The development of a modular platform which uses rapid flow NMR and FTIR measurements, combined with chemometric modeling, is presented for efficient and timely analysis of reaction outcomes. This platform is tested with a four variable single-step reaction (nucleophilic aromatic substitution), to determine the most effective optimization methodology. The self-optimization approach with minimal background knowledge proves to provide the optimal reaction parameters within the shortest operational time. The chosen approach is then applied to a seven variable two-step optimization problem (imine formation and cyclization), for the synthesis of the active pharmaceutical ingredient edaravone. Despite the exponentially increased complexity of this optimization problem, the platform achieves excellent results in a relatively small number of iterations, leading to >95% solution yield of the intermediate and up to 5.42 kg L^-1 h^-1 space-time yield for this pharmaceutically relevant product.

Modern advancements in continuous-flow aided kinetic analysis

Although kinetic analysis has traditionally been conducted in a batch vessel, continuous-flow aided kinetic analysis continues to swell in popularity.

Towards 4th industrial revolution efficient and sustainable continuous flow manufacturing of active pharmaceutical ingredients

The convergence of end-to-end continuous flow synthesis with downstream processing, process analytical technology (PAT), artificial intelligence (AI), machine learning and automation in ensuring improved accessibility of quality medicines on demand.

Chemputation and the Standardization of Chemical Informatics

The explosion in the use of machine learning for automated chemical reaction optimization is gathering pace. However, the lack of a standard architecture that connects the concept of chemical transformations universally to software and hardware provides a barrier to using the results of these optimizations and could cause the loss of relevant data and prevent reactions from being reproducible or unexpected findings verifiable or explainable. In this Perspective, we describe how the development of the field of digital chemistry or chemputation, that is the universal code-enabled control of chemical reactions using a standard language and ontology, will remove these barriers allowing users to focus on the chemistry and plug in algorithms according to the problem space to be explored or unit function to be optimized. We describe a standard hardware (the chemical processing programming architecture-the ChemPU) to encompass all chemical synthesis, an approach which unifies all chemistry automation strategies, from solid-phase peptide synthesis, to HTE flow chemistry platforms, while at the same time establishing a publication standard so that researchers can exchange chemical code (χDL) to ensure reproducibility and interoperability. Not only can a vast range of different chemistries be plugged into the hardware, but the ever-expanding developments in software and algorithms can also be accommodated. These technologies, when combined will allow chemistry, or chemputation, to follow computation-that is the running of code across many different types of capable hardware to get the same result every time with a low error rate.

Sampling and Analysis in Flow: The Keys to Smarter, More Controllable, and Sustainable Fine-Chemical Manufacturing

Process analytical technology (PAT) is a system designed to help chemists better understand and control manufacturing processes. PAT systems operate through the combination of analytical devices, reactor control elements, and mathematical models to ensure the quality of the final product through a quality by design (QbD) approach. The expansion of continuous manufacturing in the pharmaceutical and fine-chemical industry requires the development of PAT tools suitable for continuous operation in the environment of flow reactors. This requires innovative approaches to sampling and analysis from flowing media to maintain the integrity of the reactor content and the analyte of interest. The following Review discusses examples of PAT tools implemented in flow chemistry for the preparation of small organic molecules, and applications of self-optimization tools.

The exposome paradigm to predict environmental health in terms of systemic homeostasis and resource balance based on NMR data science

The environment, from microbial ecosystems to recycled resources, fluctuates dynamically due to many physical, chemical and biological factors, the profile of which reflects changes in overall state, such as environmental illness caused by a collapse of homeostasis. To evaluate and predict environmental health in terms of systemic homeostasis and resource balance, a comprehensive understanding of these factors requires an approach based on the "exposome paradigm", namely the totality of exposure to all substances. Furthermore, in considering sustainable development to meet global population growth, it is important to gain an understanding of both the circulation of biological resources and waste recycling in human society. From this perspective, natural environment, agriculture, aquaculture, wastewater treatment in industry, biomass degradation and biodegradable materials design are at the forefront of current research. In this respect, nuclear magnetic resonance (NMR) offers tremendous advantages in the analysis of samples of molecular complexity, such as crude bio-extracts, intact cells and tissues, fibres, foods, feeds, fertilizers and environmental samples. Here we outline examples to promote an understanding of recent applications of solution-state, solid-state, time-domain NMR and magnetic resonance imaging (MRI) to the complex evaluation of organisms, materials and the environment. We also describe useful databases and informatics tools, as well as machine learning techniques for NMR analysis, demonstrating that NMR data science can be used to evaluate the exposome in both the natural environment and human society towards a sustainable future.

Recent Applications of Benchtop Nuclear Magnetic Resonance Spectroscopy

Benchtop nuclear magnetic resonance (NMR) spectroscopy uses small permanent magnets to generate magnetic fields and therefore offers the advantages of operational simplicity and reasonable cost, presenting a viable alternative to high-field NMR spectroscopy. In particular, the use of benchtop NMR spectroscopy for rapid in-field analysis, e.g., for quality control or forensic science purposes, has attracted considerable attention. As benchtop NMR spectrometers are sufficiently compact to be operated in a fume hood, they can be efficiently used for real-time reaction and process monitoring. This review introduces the recent applications of benchtop NMR spectroscopy in diverse fields, including food science, pharmaceuticals, process and reaction monitoring, metabolomics, and polymer materials.

High-Throughput Routes to Biomaterials Discovery

Many existing clinical treatments are limited in their ability to completely restore decreased or lost tissue and organ function, an unenviable situation only further exacerbated by a globally aging population. As a result, the demand for new medical interventions has increased substantially over the past 20 years, with the burgeoning fields of gene therapy, tissue engineering, and regenerative medicine showing promise to offer solutions for full repair or replacement of damaged or aging tissues. Success in these fields, however, inherently relies on biomaterials that are engendered with the ability to provide the necessary biological cues mimicking native extracellular matrixes that support cell fate. Accelerating the development of such "directive" biomaterials requires a shift in current design practices toward those that enable rapid synthesis and characterization of polymeric materials and the coupling of these processes with techniques that enable similarly rapid quantification and optimization of the interactions between these new material systems and target cells and tissues. This manuscript reviews recent advances in combinatorial and high-throughput (HT) technologies applied to polymeric biomaterial synthesis, fabrication, and chemical, physical, and biological screening with targeted end-point applications in the fields of gene therapy, tissue engineering, and regenerative medicine. Limitations of, and future opportunities for, the further application of these research tools and methodologies are also discussed.

Advanced Real-Time Process Analytics for Multistep Synthesis in Continuous Flow*

In multistep continuous flow chemistry, studying complex reaction mixtures in real time is a significant challenge, but provides an opportunity to enhance reaction understanding and control. We report the integration of four complementary process analytical technology tools (NMR, UV/Vis, IR and UHPLC) in the multistep synthesis of an active pharmaceutical ingredient, mesalazine. This synthetic route exploits flow processing for nitration, high temperature hydrolysis and hydrogenation reactions, as well as three inline separations. Advanced data analysis models were developed (indirect hard modeling, deep learning and partial least squares regression), to quantify the desired products, intermediates and impurities in real time, at multiple points along the synthetic pathway. The capabilities of the system have been demonstrated by operating both steady state and dynamic experiments and represents a significant step forward in data-driven continuous flow synthesis.

Lithium-7 qNMR as a method to quantify lithium content in brines using benchtop NMR

A novel ⁷Li quantitative NMR (qNMR) method to analyze lithium was developed to determine the lithium content in real brine samples using benchtop NMR instruments. The method was validated, and limits of detection and quantification of 40 and 100 ppm, respectively, were determined. Linearity, precision, and bias were also experimentally determined, and the results are presented herein. The results were compared to those obtained using atomic absorption (AA) spectroscopy, currently one of the few validated methods for the quantification of lithium. The method provides both accurate and precise results, as well as excellent correlation with AA. The absence of matrix effects, combined with no need for sample preparation or deuterated solvents, shows potential applicability in the mining industry.

Renewable dimethyl carbonate for tertiary amine quaternisation: kinetic measurements and process optimisation

This paper has successfully optimised tertiary amine quaternisation with dimethyl carbonate. Intensification of the conventionally quite moderate operating conditions has resulted in substantially higher production capacities.

Oscillatory flow reactors for synthetic chemistry applications

Oscillatory flow reactors (OFRs) superimpose an oscillatory flow to the net movement through a flow reactor. OFRs have been engineered to enable improved mixing, excellent heat- and mass transfer and good plug flow character under a broad range of operating conditions. Such features render these reactors appealing, since they are suitable for reactions that require long residence times, improved mass transfer (such as in biphasic liquid-liquid systems) or to homogeneously suspend solid particles. Various OFR configurations, offering specific features, have been developed over the past two decades, with significant progress still being made. This review outlines the principles and recent advances in OFR technology and overviews the synthetic applications of OFRs for liquid-liquid and solid-liquid biphasic systems.

An automated flow platform for accurate determination of gas–liquid–solid reaction kinetics

An automated flow platform based on a tube-in-tube contactor and micro-packed bed reactor is developed to measure the kinetics of gas–liquid–solid hydrogenation reactions.