Photoredox Iridium–Nickel Dual-Catalyzed Decarboxylative Arylation Cross-Coupling: From Batch to Continuous Flow via Self-Optimizing Segmented Flow Reactor

From Structure to Function: Designing Iridium Catalysts with Spin-Forbidden Excitation for Low-Energy Light-Driven Reactions

Herein we describe a comprehensive study of ligand effects on optoelectronic properties of a series of Ir(III) catalysts which undergo formally spin-forbidden excitation using low-energy light. We demonstrate that electronic and steric tuning of several variables can be explained by their impact on the HOMO and LUMO energies of the complex. Density functional theory calculations of the catalysts' adiabatic triplet energies agree with the experimental results to within 0.05 eV on average. As many of these subtle effects are independent of each other, the merger of them in a single complex tends to have an additive effect and we thus succeeded in developing a family of highly oxidizing iridium photocatalysts that operate by spin-forbidden excitation.

Emerging trends in the optimization of organic synthesis through high-throughput tools and machine learning

The discovery of the optimal conditions for chemical reactions is a labor-intensive, time-consuming task that requires exploring a high-dimensional parametric space. Historically, the optimization of chemical reactions has been performed by manual experimentation guided by human intuition and through the design of experiments where reaction variables are modified one at a time to find the optimal conditions for a specific reaction outcome. Recently, a paradigm change in chemical reaction optimization has been enabled by advances in lab automation and the introduction of machine learning algorithms. Therein, multiple reaction variables can be synchronously optimized to obtain the optimal reaction conditions, requiring a shorter experimentation time and minimal human intervention. Herein, we review the currently used state-of-the-art high-throughput automated chemical reaction platforms and machine learning algorithms that drive the optimization of chemical reactions, highlighting the limitations and future opportunities of this new field of research.

Decarboxylative Cross-Coupling Enabled by Fe and Ni Metallaphotoredox Catalysis

Decarboxylative cross-coupling of carboxylic acids and aryl halides has become a key transformation in organic synthesis to form C(sp2)-C(sp3) bonds. In this report, a base metal pairing between Fe and Ni has been developed with complementary reactivity to the well-established Ir and Ni metallaphotoredox reactions. Utilizing an inexpensive FeCl3 cocatalyst along with a pyridine carboxamidine Ni catalyst, a range of aryl iodides can be preferentially coupled to carboxylic acids over boronic acid esters, triflates, chlorides, and even bromides in high yields. Additionally, carboxylic acid derivatives containing heterocycles, N-protected amino acids, and protic functionality can be coupled in 23-96% yield with a range of sterically hindered, electron-rich, and electron-deficient aryl iodides. Preliminary catalytic and stoichiometric reactions support a mechanism in which Fe is responsible for the activation of carboxylic acid upon irradiation with light and a NiI alkyl intermediate is responsible for activation of the aryl iodide coupling partner followed by reductive elimination to generate product.

A Unified Method for Oxidative and Reductive Decarboxylative Arylation with Orange Light-Driven Ir/Ni Metallaphotoredox Catalysis

Carboxylic acids and their derivatives are powerful building blocks in dual Ir/Ni metallaphotoredox methods of decarboxylative arylation due to their abundance as feedstock compounds. However, the library of accessible carboxylic acids is limited by trends in radical stability, often necessitating the development of specific systems for challenging substrates. Herein, we disclose the application of a new Ir(III) photocatalyst and low-energy orange light Ir/Ni metallaphotoredox system with broad applicability in activating both native carboxylic acids and redox-active esters (RAEs). This method represents the first known example of complementary oxidative and reductive decarboxylative paradigms with broadly similar reaction conditions, unlocking the reactivity for challenging substrates. We further show a wide scope of aryl halide and acid coupling partners in both regimes, with added advantages over blue-light-catalyzed aryl alkylation for photosensitive substrates.

Self-Driving Laboratories for Chemistry and Materials Science

Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through the automation of experimental workflows, along with autonomous experimental planning, SDLs hold the potential to greatly accelerate research in chemistry and materials discovery. This review provides an in-depth analysis of the state-of-the-art in SDL technology, its applications across various scientific disciplines, and the potential implications for research and industry. This review additionally provides an overview of the enabling technologies for SDLs, including their hardware, software, and integration with laboratory infrastructure. Most importantly, this review explores the diverse range of scientific domains where SDLs have made significant contributions, from drug discovery and materials science to genomics and chemistry. We provide a comprehensive review of existing real-world examples of SDLs, their different levels of automation, and the challenges and limitations associated with each domain.

Addressing Reproducibility Challenges in High-Throughput Photochemistry

Light-mediated reactions have emerged as an indispensable tool in organic synthesis and drug discovery, enabling novel transformations and providing access to previously unexplored chemical space. Despite their widespread application in both academic and industrial research, the utilization of light as an energy source still encounters challenges regarding reproducibility and data robustness. Herein we present a comprehensive head-to-head comparison of commercially available batch photoreactors, alongside the introduction of the use of batch and flow photoreactors in parallel synthesis. Hence, we aim to establish a reliable and consistent platform for light-mediated reactions in high-throughput mode. Herein, we showcase the identification of several platforms aligning with the rigorous demands for efficient and robust high-throughput experimentation screenings and library synthesis.

A Slug Flow Platform with Multiple Process Analytics Facilitates Flexible Reaction Optimization

Flow processing offers many opportunities to optimize reactions in a rapid and automated manner, yet often requires relatively large quantities of input materials. To combat this, the use of a flexible slug flow reactor, equipped with two analytical instruments, for low-volume optimization experiments are reported. A Buchwald-Hartwig amination toward the drug olanzapine, with 6 independent optimizable variables, is optimized using three different automated approaches: self-optimization, design of experiments, and kinetic modeling. These approaches are complementary and provide differing information on the reaction: pareto optimal operating points, response surface models, and mechanistic models, respectively. The results are achieved using <10% of the material that would be required for standard flow operation. Finally, a chemometric model is built utilizing automated data handling and three subsequent validation experiments demonstrate good agreement between the slug flow reactor and a standard (larger scale) flow reactor.

Recent advances and applications in high-throughput continuous flow

High-throughput continuous flow technology has emerged as a revolutionary approach in chemical synthesis, offering accelerated experimentation and improved efficiency. With the aid of process analytical technology and automation, this system not only enables rapid optimisation of reaction conditions at the millimole to the picomole scale, but also facilitates automated scale-up synthesis. It can even achieve the self-planning and self-synthesis of small drug molecules with artificial intelligence incorporated in the system. The versatility of the system is highlighted by its compatibility with both electrochemistry and photochemistry, and its significant applications in organic synthesis and drug discovery. This highlight summarises its recent developments and applications, emphasising its significant impact on advancing research across multiple disciplines.

MicroCycle: An Integrated and Automated Platform to Accelerate Drug Discovery

We herein describe the development and application of a modular technology platform which incorporates recent advances in plate-based microscale chemistry, automated purification, in situ quantification, and robotic liquid handling to enable rapid access to high-quality chemical matter already formatted for assays. In using microscale chemistry and thus consuming minimal chemical matter, the platform is not only efficient but also follows green chemistry principles. By reorienting existing high-throughput assay technology, the platform can generate a full package of relevant data on each set of compounds in every learning cycle. The multiparameter exploration of chemical and property space is hereby driven by active learning models. The enhanced compound optimization process is generating knowledge for drug discovery projects in a time frame never before possible.

Identifying general reaction conditions by bandit optimization

Reaction conditions that are generally applicable to a wide variety of substrates are highly desired, especially in the pharmaceutical and chemical industries1-6. Although many approaches are available to evaluate the general applicability of developed conditions, a universal approach to efficiently discover these conditions during optimizations is rare. Here we report the design, implementation and application of reinforcement learning bandit optimization models7-10 to identify generally applicable conditions by efficient condition sampling and evaluation of experimental feedback. Performance benchmarking on existing datasets statistically showed high accuracies for identifying general conditions, with up to 31% improvement over baselines that mimic state-of-the-art optimization approaches. A palladium-catalysed imidazole C-H arylation reaction, an aniline amide coupling reaction and a phenol alkylation reaction were investigated experimentally to evaluate use cases and functionalities of the bandit optimization model in practice. In all three cases, the reaction conditions that were most generally applicable yet not well studied for the respective reaction were identified after surveying less than 15% of the expert-designed reaction space.

Automated self-optimization, intensification, and scale-up of photocatalysis in flow

The optimization, intensification, and scale-up of photochemical processes constitute a particular challenge in a manufacturing environment geared primarily toward thermal chemistry. In this work, we present a versatile flow-based robotic platform to address these challenges through the integration of readily available hardware and custom software. Our open-source platform combines a liquid handler, syringe pumps, a tunable continuous-flow photoreactor, inexpensive Internet of Things devices, and an in-line benchtop nuclear magnetic resonance spectrometer to enable automated, data-rich optimization with a closed-loop Bayesian optimization strategy. A user-friendly graphical interface allows chemists without programming or machine learning expertise to easily monitor, analyze, and improve photocatalytic reactions with respect to both continuous and discrete variables. The system's effectiveness was demonstrated by increasing overall reaction yields and improving space-time yields compared with those of previously reported processes.

Parallel multi-droplet platform for reaction kinetics and optimization

We present an automated droplet reactor platform possessing parallel reactor channels and a scheduling algorithm that orchestrates all of the parallel hardware operations and ensures droplet integrity as well as overall efficiency. We design and incorporate all of the necessary hardware and software to enable the platform to be used to study both thermal and photochemical reactions. We incorporate a Bayesian optimization algorithm into the control software to enable reaction optimization over both categorical and continuous variables. We demonstrate the capabilities of both the preliminary single-channel and parallelized versions of the platform using a series of model thermal and photochemical reactions. We conduct a series of reaction optimization campaigns and demonstrate rapid acquisition of the data necessary to determine reaction kinetics. The platform is flexible in terms of use case: it can be used either to investigate reaction kinetics or to perform reaction optimization over a wide range of chemical domains.

ChemBeads-Enabled Photoredox High-Throughput Experimentation Platform to Improve C(sp2)-C(sp3) Decarboxylative Couplings

Enthusiasm surrounding nickel/photoredox C(sp2)-C(sp3) cross-couplings is very high; however, these methods are sometimes challenged by complex drug-like substrates in discovery chemistry. In our hands this has been especially true of the decarboxylative coupling, which has lagged behind other photoredox couplings in internal adoption and success. Herein, the development of a photoredox high-throughput experimentation platform to optimize challenging C(sp2)-C(sp3) decarboxylative couplings is described. Chemical-coated glass beads (ChemBeads) and a novel parallel bead dispenser are used to expedite the high-throughput experimentation process and identify improved coupling conditions. In this report, photoredox high-throughput experimentation is utilized to dramatically improve low-yielding decarboxylative C(sp2)-C(sp3) couplings, and libraries, using conditions not previously identified in the literature.

A Brief Introduction to Chemical Reaction Optimization

From the start of a synthetic chemist's training, experiments are conducted based on recipes from textbooks and manuscripts that achieve clean reaction outcomes, allowing the scientist to develop practical skills and some chemical intuition. This procedure is often kept long into a researcher's career, as new recipes are developed based on similar reaction protocols, and intuition-guided deviations are conducted through learning from failed experiments. However, when attempting to understand chemical systems of interest, it has been shown that model-based, algorithm-based, and miniaturized high-throughput techniques outperform human chemical intuition and achieve reaction optimization in a much more time- and material-efficient manner; this is covered in detail in this paper. As many synthetic chemists are not exposed to these techniques in undergraduate teaching, this leads to a disproportionate number of scientists that wish to optimize their reactions but are unable to use these methodologies or are simply unaware of their existence. This review highlights the basics, and the cutting-edge, of modern chemical reaction optimization as well as its relation to process scale-up and can thereby serve as a reference for inspired scientists for each of these techniques, detailing several of their respective applications.

AROPS: A Framework of Automated Reaction Optimization with Parallelized Scheduling

With the development of automated experimental platforms and optimization algorithms, chemists can easily optimize chemical reactions in an automated and high-throughput fashion. However, the modules in existing automated experimental platforms are operated in a linear fashion without orchestrating with the optimization algorithm, thus leaving room for further efficiency improvement. Here, we introduced a framework of automated reaction optimization with parallelized scheduling (AROPS) to realize the integration of the optimization algorithm and module scheduling. AROPS relies on a customized Bayesian optimizer to solve multi-reactor/analyzer reaction optimization problems with three different scheduling modes to arrange tasks for various experimental modules. In addition, a mechanism based on probability of improvement (PI) for discarding unpromising ongoing experiments was developed to facilitate freeing up valuable experimental resources in parallelized optimization. We tested the performance of AROPS using a hardware emulator on three representative benchmark reactions encountered in organic synthesis, illustrating that AROPS can trade off optimization time and cost according to the chemists' preference.

Multivariate curve resolution for kinetic modeling and scale-up prediction

Abstract

An imine synthesis was investigated in a nearly isothermal oscillating segmented flow microreactor at different temperatures using non-invasive Raman spectroscopy. Multivariate curve resolution provided a calibration-free approach for obtaining kinetic parameters. The two different multivariate curve resolution approaches, soft and hard modeling, were applied and contrasted, leading to similar results. Taking heat and mass balance into account, the proposed kinetic model was applied for a model-based scale-up prediction. Finally, the reaction was performed in a 0.5 L semi-batch reactor, followed by in-line Raman spectroscopy and off-line gas chromatography analysis. The successful scale-up was demonstrated with a good agreement between measured and predicted concentration profiles.

Highlights

• Oscillation segmented flow reactor with inline Raman spectroscopy.

• Multivariate Curve Resolution with hard and soft constraints.

• High quality kinetic model for scale-up predictions.

Graphical abstract

Automated optimization under dynamic flow conditions

The combination of feedback optimization with dynamic operations leads to enhanced data-rich experimentation in flow.

Carboxylic Acids as Adaptive Functional Groups in Metallaphotoredox Catalysis

The development of palladium-catalyzed cross-coupling methods for the activation of C(sp2)-Br bonds facilitated access to arene-rich molecules, enabling a concomitant increase in the prevalence of this structural motif in drug molecules in recent decades. Today, there is a growing appreciation of the value of incorporating saturated C(sp3)-rich scaffolds into pharmaceutically active molecules as a means to achieve improved solubility and physiological stability, providing the impetus to develop new coupling strategies to access these challenging motifs in the most straightforward way possible. As an alternative to classical two-electron chemistry, redox chemistry can enable access to elusive transformations, most recently, by interfacing abundant first-row transition-metal catalysis with photoredox catalysis. As such, the functionalization of ubiquitous and versatile functional handles such as (aliphatic) carboxylic acids via metallaphotoredox catalysis has emerged as a valuable field of research over the past eight years.In this Account, we will outline recent progress in the development of methodologies that employ aliphatic and (hetero)aromatic carboxylic acids as adaptive functional groups. Whereas recent decarboxylative functionalization methodologies often necessitate preactivated aliphatic carboxylic acids in the form of redox-active esters or as ligands for hypervalent iodine reagents, methods that enable the direct use of the native carboxylic acid functionality are highly desired and have been accomplished through metallaphotoredox protocols. As such, we found that bench-stable aliphatic carboxylic acids can undergo diverse transformations, such as alkylation, arylation, amination, and trifluoromethylation, by leveraging metallaphotoredox catalysis with prevalent first-row transition metals such as nickel and copper. Likewise, abundant aryl carboxylic acids are now able to undergo halogenation and borylation, enabling new entry points for traditional, primarily palladium- or copper-catalyzed cross-coupling strategies. Given the breadth of the functional group tolerance of the employed reaction conditions, the late-stage functionalization of abundant carboxylic acids toward desired targets has become a standard tool in reaction design, enabling the synthesis of various diversified drug molecules. The rapid rise of this field has positively inspired pharmaceutical discovery and will be further accelerated by novel reaction development. The achievement of generality through reaction optimization campaigns allows for future breakthroughs that can render protocols more reliable and applicable for industry. This article is intended to highlight, in particular, (i) the employment of aliphatic and (hetero)aryl carboxylic acids as powerful late-stage adaptive functional handles in drug discovery and (ii) the need for the further development of still-elusive and selective transformations.We strongly believe that access to native functionalities such as carboxylic acids as adaptive handles will further inspire researchers across the world to investigate new methodologies for complex molecular targets.

Automation and Microfluidics for the Efficient, Fast, and Focused Reaction Development of Asymmetric Hydrogenation Catalysis

Automation and microfluidic tools potentially enable efficient, fast, and focused reaction development of complex chemistries, while minimizing resource- and material consumption. The introduction of automation-assisted workflows will contribute to the more sustainable development and scale-up of new and improved catalytic technologies. Herein, the application of automation and microfluidics to the development of a complex asymmetric hydrogenation reaction is described. Screening and optimization experiments were performed using an automated microfluidic platform, which enabled a drastic reduction in the material consumption compared to conventional laboratory practices. A suitable catalytic system was identified from a library of Ru^II -diamino precatalysts. In situ precatalyst activation was studied with ¹ H/³¹ P nuclear magnetic resonance (NMR), and the reaction was scaled up to multigram quantities in a batch autoclave. These reactions were monitored using an automated liquid-phase sampling system. Ultimately, in less than a week of total experimental time, multigram quantities of the target enantiopure alcohol product were provided by this automation-assisted approach.

Comparative Evaluation of Light-Driven Catalysis: A Framework for Standardized Reporting of Data

Light-driven homogeneous and heterogeneous catalysis require a complex interplay between light absorption, charge separation, charge transfer, and catalytic turnover. Optical and irradiation parameters as well as reaction engineering aspects play major roles in controlling catalytic performance. This multitude of factors makes it difficult to objectively compare light-driven catalysts and provide an unbiased performance assessment. This Scientific Perspective highlights the importance of collecting and reporting experimental data in homogeneous and heterogeneous light-driven catalysis. A critical analysis of the benefits and limitations of the commonly used experimental indicators is provided. Data collection and reporting according to FAIR principles is discussed in the context of future automated data analysis. The authors propose a minimum dataset as a basis for unified collecting and reporting of experimental data in homogeneous and heterogeneous light-driven catalysis. The community is encouraged to support the future development of this parameter list through an open online repository.

Technological Innovations in Photochemistry for Organic Synthesis: Flow Chemistry, High-Throughput Experimentation, Scale-up, and Photoelectrochemistry

Photoinduced chemical transformations have received in recent years a tremendous amount of attention, providing a plethora of opportunities to synthetic organic chemists. However, performing a photochemical transformation can be quite a challenge because of various issues related to the delivery of photons. These challenges have barred the widespread adoption of photochemical steps in the chemical industry. However, in the past decade, several technological innovations have led to more reproducible, selective, and scalable photoinduced reactions. Herein, we provide a comprehensive overview of these exciting technological advances, including flow chemistry, high-throughput experimentation, reactor design and scale-up, and the combination of photo- and electro-chemistry.

Developing flow photo-thiol–ene functionalizations of cinchona alkaloids with an autonomous self-optimizing flow reactor

Continuous flow photo-thiol–ene reactions on cinchona alkaloids with a variety of organic thiols have been developed using enabling technologies such as a self-optimizing flow photochemical reactor.

Rxn Rover: automation of chemical reactions with user-friendly, modular software

Automation of chemical reactions through tools such as Rxn Rover in research and development is an enabling technology to reduce cost and waste management in technology transformations towards renewable feedstocks and energy in the chemical industry.

Continuous stirred-tank reactor cascade platform for self-optimization of reactions involving solids

Research-scale fully automated flow platform for reaction self-optimization with solids handling facilitates identification of optimal conditions for continuous manufacturing of pharmaceuticals while reducing amounts of raw materials consumed.

Autonomous model-based experimental design for rapid reaction development

To automate and democratize model-based experimental design for flow chemistry applications, we report the development of open-source software, Optipus. Reaction models are built in an iterative and automated fashion, for rapid reaction development.

Use of Green Solvents in Metallaphotoredox Cross-Electrophile Coupling Reactions Utilizing a Lipophilic Modified Dual Ir/Ni Catalyst System

Facilitating photoredox coupling reactions in process-friendly green solvents was achieved by the successful application of a dual Ir/Ni catalyst system with enhanced solubility properties. These photochemical reactions (specifically Br-Br sp²-sp³ cross electrophile coupling) are reported in a head to head comparison to the standard di-t-Bu bipyridine ligand Ir/Ni catalyst system. This presentation highlights the benefits of altering the solubility properties of the ligands used in the Ir/Ni dual catalyst.

Photocatalysis in the Life Science Industry

In the pursuit of new pharmaceuticals and agrochemicals, chemists in the life science industry require access to mild and robust synthetic methodologies to systematically modify chemical structures, explore novel chemical space, and enable efficient synthesis. In this context, photocatalysis has emerged as a powerful technology for the synthesis of complex and often highly functionalized molecules. This Review aims to summarize the published contributions to the field from the life science industry, including research from industrial-academic partnerships. An overview of the synthetic methodologies developed and strategic applications in chemical synthesis, including peptide functionalization, isotope labeling, and both DNA-encoded and traditional library synthesis, is provided, along with a summary of the state-of-the-art in photoreactor technology and the effective upscaling of photocatalytic reactions.

Data-science driven autonomous process optimization

Autonomous process optimization involves the human intervention-free exploration of a range process parameters to improve responses such as product yield and selectivity. Utilizing off-the-shelf components, we develop a closed-loop system for carrying out parallel autonomous process optimization experiments in batch. Upon implementation of our system in the optimization of a stereoselective Suzuki-Miyaura coupling, we find that the definition of a set of meaningful, broad, and unbiased process parameters is the most critical aspect of successful optimization. Importantly, we discern that phosphine ligand, a categorical parameter, is vital to determination of the reaction outcome. To date, categorical parameter selection has relied on chemical intuition, potentially introducing bias into the experimental design. In seeking a systematic method for selecting a diverse set of phosphine ligands, we develop a strategy that leverages computed molecular feature clustering. The resulting optimization uncovers conditions to selectively access the desired product isomer in high yield.

Rapid Optimization of Photoredox Reactions for Continuous-Flow Systems Using Microscale Batch Technology

Photoredox catalysis has emerged as a powerful and versatile platform for the synthesis of complex molecules. While photocatalysis is already broadly used in small-scale batch chemistry across the pharmaceutical sector, recent efforts have focused on performing these transformations in process chemistry due to the inherent challenges of batch photocatalysis on scale. However, translating optimized batch conditions to flow setups is challenging, and a general approach that is rapid, convenient, and inexpensive remains largely elusive. Herein, we report the development of a new approach that uses a microscale high-throughput experimentation (HTE) platform to identify optimal reaction conditions that can be directly translated to flow systems. A key design point is to simulate the flow-vessel pathway within a microscale reaction plate, which enables the rapid identification of optimal flow reaction conditions using only a small number of simultaneous experiments. This approach has been validated against a range of widely used photoredox reactions and, importantly, was found to translate accurately to several commercial flow reactors. We expect that the generality and operational efficiency of this new HTE approach to photocatalysis will allow rapid identification of numerous flow protocols for scale.

Design of a Combined Modular and 3D-Printed Falling Film Solution Layer Crystallizer for Intermediate Purification in Continuous Production of Pharmaceuticals

A highly scalable combined modular and 3D-printed falling film crystallization device is developed and demonstrated herein; the device uses a small, complex, printed overflow-based film distribution part that ensures formation of a well-distributed heated liquid film around a modular, tubular residence time/crystallizer section, enabling extended residence times to be achieved. A model API (ibuprofen) and impurity (ibuprofen ethyl ester) were used as a test system in the evaluation of the novel crystallizer design. The proposed crystallizer was run using three operational configurations: batch, cyclical batch, and continuous feed, all with intermittent removal of product. Results were suitable for intermediate purification requirements, and stable operation was demonstrated over multiple cycles, indicating that this approach should be compatible with parallel semicontinuous operation for intermediate purification and solvent swap applications in the manufacture of drugs.

Development of a continuous flow synthesis of FGIN-1-27 enabled by in-line 19F NMR analyses and optimization algorithms

A continuous flow synthesis of FGIN-1-27 has been developed using enabling technologies such as real-time in-line benchtop 19F NMR analysis and an optimization algorithm.

Application of reactor engineering concepts in continuous flow chemistry: a review

The adoption of flow technology for the manufacture of chemical entities, and in particular pharmaceuticals, has seen rapid growth over the past two decades with the technology now blurring the lines between chemistry and chemical engineering.

Organic thermally activated delayed fluorescence (TADF) compounds used in photocatalysis

Organic compounds that show Thermally Activated Delayed Fluorescence (TADF) have become wildly popular as next-generation emitters in organic light emitting diodes (OLEDs). Since 2016, a subset of these have found increasing use as photocatalysts. This review comprehensively highlights their potential by documenting the diversity of the reactions where an organic TADF photocatalyst can be used in lieu of a noble metal complex photocatalyst. Beyond the small number of TADF photocatalysts that have been used to date, the analysis conducted within this review reveals the wider potential of organic donor-acceptor TADF compounds as photocatalysts. A discussion of the benefits of compounds showing TADF for photocatalysis is presented, which paints a picture of a very promising future for organic photocatalyst development.

A droplet microfluidic platform for high-throughput photochemical reaction discovery

The implementation of continuous flow technology is critical towards enhancing the application of photochemical reactions for industrial process development. However, there are significant time and resource constraints associated with translating discovery scale vial-based batch reactions to continuous flow scale-up conditions. Herein we report the development of a droplet microfluidic platform, which enables high-throughput reaction discovery in flow to generate pharmaceutically relevant compound libraries. This platform allows for enhanced material efficiency, as reactions can be performed on picomole scale. Furthermore, high-throughput data collection via on-line ESI mass spectrometry facilitates the rapid analysis of individual, nanoliter-sized reaction droplets at acquisition rates of 0.3 samples/s. We envision this high-throughput screening platform to expand upon the robust capabilities and impact of photochemical reactions in drug discovery and development.

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.

Visible-light-induced addition of carboxymethanide to styrene from monochloroacetic acid

Where monochloroacetic acid is widely used as a starting material for the synthesis of relevant groups of compounds, many of these synthetic procedures are based on nucleophilic substitution of the carbon chlorine bond. Oxidative or reductive activation of monochloroacetic acid results in radical intermediates, leading to reactivity different from the traditional reactivity of this compound. Here, we investigated the possibility of applying monochloroacetic acid as a substrate for photoredox catalysis with styrene to directly produce γ-phenyl-γ-butyrolactone. Instead of using nucleophilic substitution, we cleaved the carbon chlorine bond by single-electron reduction, creating a radical species. We observed that the reaction works best in nonpolar solvents. The reaction does not go to full conversion, but selectively forms γ-phenyl-γ-butyrolactone and 4-chloro-4-phenylbutanoic acid. Over time the catalyst precipitates from solution (perhaps in a decomposed form in case of fac-[Ir(ppy)₃]), which was proven by mass spectrometry and EPR spectroscopy for one of the catalysts (N,N-5,10-di(2-naphthalene)-5,10-dihydrophenazine) used in this work. The generation of HCl resulting from lactone formation could be an additional problem for organometallic photoredox catalysts used in this reaction. In an attempt to trap one of the radical intermediates with TEMPO, we observed a compound indicating the generation of a chloromethyl radical.