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.

Analysis of Adsorbed Polyphosphate Changes on Milled Titanium Dioxide, Using Low-Field Relaxation NMR and Photoelectron Spectroscopy.

In this study, changes in the adsorbed amount and surface structure of sodium hexametaphosphate (SHMP) were investigated for aluminum-doped TiO2 pigment undergoing milling. Relaxation NMR was utilized as a potential at-line technique to monitor the effect of milling on surface area and surface chemistry, while XPS was used primarily to consider the dispersant structure. Results showed that considerable amounts of weakly adsorbed SHMP could be removed with washing, and the level of dispersant removal increased with time, highlighting destructive effects of sustained high-energy milling. Nonetheless, there were no significant chemical changes to the dispersant, although increases to the bridging oxygen (BO) peak full width at half-maximum (FWHM) suggested some chemical degradation was occurring with excess milling. Relaxation NMR revealed a number of important features. Results with unmilled material indicated that dispersant adsorption could be tracked with pseudo-isotherms using the relative enhancement rate (Rsp), where the Rsp decreased with dispersant coverage, owing to partial blocking of the quadrupolar surface aluminum. Milled samples were also tracked, with very accurate calibrations of surface area possible from either T1 or T2 relaxation data for systems without dispersant. Behavior was considerably more complicated with SHMP, as there appeared to be an interplay between the dispersant surface coverage and relaxation enhancement from the surface aluminum. Nevertheless, findings highlight that relaxation NMR could be used as a real-time technique to monitor the extent of milling processes, so long as appropriate industrial calibrations can be achieved.

Bayesian Self-Optimization for Telescoped Continuous Flow Synthesis.

The optimization of multistep chemical syntheses is critical for the rapid development of new pharmaceuticals. However, concatenating individually optimized reactions can lead to inefficient multistep syntheses, owing to chemical interdependencies between the steps. Herein, we develop an automated continuous flow platform for the simultaneous optimization of telescoped reactions. Our approach is applied to a Heck cyclization-deprotection reaction sequence, used in the synthesis of a precursor for 1-methyltetrahydroisoquinoline C5 functionalization. A simple method for multipoint sampling with a single online HPLC instrument was designed, enabling accurate quantification of each reaction, and an in-depth understanding of the reaction pathways. Notably, integration of Bayesian optimization techniques identified an 81 % overall yield in just 14 h, and revealed a favorable competing pathway for formation of the desired product.

On-Demand Electrochemical Synthesis of Tetrakisacetonitrile Copper(I) Triflate and Its Application in the Aerobic Oxidation of Alcohols.

An on-demand electrochemical synthesis of copper(I) triflate under both batch and continuous flow conditions has been developed. A major benefit of the electrochemical methodology is that the only byproduct of the reaction is hydrogen gas, which obviates the need for workup and purification, and water is not incorporated into the product. Upon completion of the electrochemical synthesis, solutions are directly transferred or dispensed into reaction mixtures for the catalytic oxidation of benzyl alcohol with no requirement for workup or purification.

Process Monitoring of Moisture Content and Mass Transfer Rate in a Fluidised Bed with a Low Cost Inline MEMS NIR Sensor.

PURPOSE: The current trend for continuous drug product manufacturing requires new, affordable process analytical techniques (PAT) to ensure control of processing. This work evaluates whether property models based on spectral data from recent Fabry-Pérot Interferometer based NIR sensors can generate a high-resolution moisture signal suitable for process control. METHODS: Spectral data and offline moisture content were recorded for 14 fluid bed dryer batches of pharmaceutical granules. A PLS moisture model was constructed resulting in a high resolution moisture signal, used to demonstrate (i) endpoint determination and (ii) evaluation of mass transfer performance. RESULTS: The sensors appear robust with respect to vibration and ambient temperature changes, and the accuracy of water content predictions (±13 % ) is similar to those reported for high specification NIR sensors. Fusion of temperature and moisture content signal allowed monitoring of water transport rates in the fluidised bed and highlighted the importance water transport within the solid phase at low moisture levels. The NIR data was also successfully used with PCA-based MSPC models for endpoint detection. CONCLUSIONS: The spectral quality of the small form factor NIR sensor and its robustness is clearly sufficient for the construction and application of PLS models as well as PCA-based MSPC moisture models. The resulting high resolution moisture content signal was successfully used for endpoint detection and monitoring the mass transfer rate.

Electron spectroscopy of ionic liquids: experimental identification of atomic orbital contributions to valence electronic structure.

The atomic contributions to valence electronic structure for 37 ionic liquids (ILs) are identified using a combination of variable photon energy XPS, resonant Auger electron spectroscopy (RAES) and a subtraction method. The ILs studied include a diverse range of cationic and anionic structural moieties. We introduce a new parameter for ILs, the energy difference between the energies of the cationic and anionic highest occupied fragment orbitals (HOFOs), which we use to identify the highest occupied molecular orbital (HOMO). The anion gave rise to the HOMO for 25 of the 37 ILs studied here. For 10 of the ILs, the energies of the cationic and anionic HOFOs were the same (within experimental error); therefore, it could not be determined whether the HOMO was from the cation or the anion. For two of the ILs, the HOMO was from the cation and not from the anion; consequently it is energetically more favourable to remove an electron from the cation than the anion for these two ILs. In addition, we used a combination of area normalisation and subtraction of XP spectra to produce what are effectively XP spectra for individual ions; this was achieved for 10 cations and 14 anions.

A Hybridised Optimisation of an Automated Photochemical Continuous Flow Reactor.

A new hybridized algorithm that combines process optimisation with response surface mapping was developed and applied in an automated continuous flow reaction. Moreover, a photochemical cascade CSTR was developed and characterised by chemical actinometry, showing photon flux density of ten times greater than previously reported in batch. The success of the algorithm was then evaluated in the aerobic oxidation of sp³ C-H bonds using benzophenone as photosensitizer in the newly developed photo reactor.

Kinetic Treatments for Catalyst Activation and Deactivation Processes based on Variable Time Normalization Analysis.

Progress reaction profiles are affected by both catalyst activation and deactivation processes occurring alongside the main reaction. These processes complicate the kinetic analysis of reactions, often directing researchers toward incorrect conclusions. We report the application of two kinetic treatments, based on variable time normalization analysis, to reactions involving catalyst activation and deactivation processes. The first kinetic treatment allows the removal of induction periods or the effect of rate perturbations associated with catalyst deactivation from kinetic profiles when the quantity of active catalyst can be measured. The second treatment allows the estimation of the activation or deactivation profile of the catalyst when the order of the reactants for the main reaction is known. Both treatments facilitate kinetic analysis of reactions suffering catalyst activation or deactivation processes.

Direct Synthesis of Multiplexed Metal-Nanowire-Based Devices by Using Carbon Nanotubes as Vector Templates.

We present the synthesis of metal nanowires in a multiplexed device configuration using single-walled carbon nanotubes (SWNTs) as nanoscale vector templates. The SWNT templates control the dimensionality of the wires, allowing precise control of their size, shape, and orientation; moreover, a solution-processable approach enables their linear deposition between specific electrode pairs in electronic devices. Electrical characterization demonstrated the successful fabrication of metal nanowire electronic devices, while multiscale characterization of the different fabrication steps revealed details of the structure and charge transfer between the material encapsulated and the carbon nanotube. Overall the strategy presented allows facile, low-cost, and direct synthesis of multiplexed metal nanowire devices for nanoelectronic applications.

Thermal stability of dialkylimidazolium tetrafluoroborate and hexafluorophosphate ionic liquids: ex situ bulk heating to complement in situ mass spectrometry.

Thermal decomposition (TD) products of the ionic liquids (ILs) [CnC1Im][BF4] and [CnC1Im][PF6] ([CnC1Im]+ = 1-alkyl-3-methylimidazolium, [BF4]- = tetrafluoroborate, and [PF6]- = hexafluorophosphate) were prepared, ex situ, by bulk heating experiments in a bespoke setup. The respective products, CnC1(C3N2H2)BF3 and CnC1(C3N2H2)PF5 (1-alkyl-3-methylimidazolium-2-trifluoroborate and 1-alkyl-3-methylimidazolium-2-pentafluorophosphate), were then vaporized and analyzed by direct insertion mass spectrometry (DIMS) in order to identify their characteristic MS signals. During IL DIMS experiments we were subsequently able, in situ, to identify and monitor signals due to both IL vaporization and IL thermal decomposition. These decomposition products have not been observed in situ during previous analytical vaporization studies of similar ILs. The ex situ preparation of TD products is therefore perfectly complimentary to in situ thermal stability measurements. Experimental parameters such as sample surface area to volume ratios are consequently very important for ILs that show competitive vaporization and thermal decomposition. We have explained these experimental factors in terms of Langmuir evaporation and Knudsen effusion-like conditions, allowing us to draw together observations from previous studies to make sense of the literature on IL thermal stability. Hence, the design of experimental setups are crucial and previously overlooked experimental factors.

Experimental validation of calculated atomic charges in ionic liquids.

A combination of X-ray photoelectron spectroscopy and near edge X-ray absorption fine structure spectroscopy has been used to provide an experimental measure of nitrogen atomic charges in nine ionic liquids (ILs). These experimental results are used to validate charges calculated with three computational methods: charges from electrostatic potentials using a grid-based method (ChelpG), natural bond orbital population analysis, and the atoms in molecules approach. By combining these results with those from a previous study on sulfur, we find that ChelpG charges provide the best description of the charge distribution in ILs. However, we find that ChelpG charges can lead to significant conformational dependence and therefore advise that small differences in ChelpG charges (<0.3 e) should be interpreted with care. We use these validated charges to provide physical insight into nitrogen atomic charges for the ILs probed.

Atomic charges of sulfur in ionic liquids: experiments and calculations.

Experimental near edge X-ray absorption fine structure (NEXAFS) spectra, X-ray photoelectron (XP) spectra and Auger electron spectra are reported for sulfur in ionic liquids (ILs) with a range of chemical structures. These values provide experimental measures of the atomic charge in each IL and enable the evaluation of the suitability of NEXAFS spectroscopy and XPS for probing the relative atomic charge of sulfur. In addition, we use Auger electron spectroscopy to show that when XPS binding energies differ by less than 0.5 eV, conclusions on atomic charge should be treated with caution. Our experimental data provides a benchmark for calculations of the atomic charge of sulfur obtained using different methods. Atomic charges were computed for lone ions and ion pairs, both in the gas phase (GP) and in a solvation model (SMD), with a wide range of ion pair conformers considered. Three methods were used to compute the atomic charges: charges from the electrostatic potential using a grid based method (ChelpG), natural bond orbital (NBO) population analysis and Bader's atoms in molecules (AIM) approach. By comparing the experimental and calculated measures of the atomic charge of sulfur, we provide an order for the sulfur atoms, ranging from the most negative to the most positive atomic charge. Furthermore, we show that both ChelpG and NBO are reasonable methods for calculating the atomic charge of sulfur in ILs, based on the agreement with both the XPS and NEXAFS spectroscopy results. However, the atomic charges of sulfur derived from ChelpG are found to display significant, non-physical conformational dependence. Only small differences in individual atomic charge of sulfur were observed between lone ion (GP) and ion pair IL(SMD) model systems, indicating that ion-ion interactions do not strongly influence individual atomic charges.

NEXAFS spectroscopy of ionic liquids: experiments versus calculations.

Experimental near edge X-ray absorption fine structure (NEXAFS) spectra are reported for 12 ionic liquids (ILs) encompassing a range of chemical structures for both the sulfur 1s and nitrogen 1s edges and compared with time-dependent density functional theory (TD-DFT) calculations. The energy scales for the experimental data were carefully calibrated against literature data. Gas phase calculations were performed on lone ions, ion pairs and ion pair dimers, with a wide range of ion pair conformers considered. For the first time, it is demonstrated that TD-DFT is a suitable method for simulating NEXAFS spectra of ILs, although the number of ions included in the calculations and their conformations are important considerations. For most of the ILs studied, calculations on lone ions in the gas phase were sufficient to successfully reproduce the experimental NEXAFS spectra. However, for certain ILs - for example, those containing a protic ammonium cation - calculations on ion pairs were required to obtain a good agreement with experimental spectra. Furthermore, significant conformational dependence was observed for the protic ammonium ILs, providing insight into the predominant liquid phase cation-anion interactions. Among the 12 investigated ILs, we find that four have an excited state that is delocalised across both the cation and the anion, which has implications for any process that depends on the excited state, for example, radiolysis. Considering the collective experimental and theoretical data, we recommend that ion pairs should be the minimum number of ions used for the calculation of NEXAFS spectra of ILs.

Activation and deactivation of a robust immobilized Cp*Ir-transfer hydrogenation catalyst: a multielement in situ X-ray absorption spectroscopy study.

A highly robust immobilized [Cp*IrCl2]2 precatalyst on Wang resin for transfer hydrogenation, which can be recycled up to 30 times, was studied using a novel combination of X-ray absorption spectroscopy (XAS) at Ir L3-edge, Cl K-edge, and K K-edge. These culminate in in situ XAS experiments that link structural changes of the Ir complex with its catalytic activity and its deactivation. Mercury poisoning and "hot filtration" experiments ruled out leached Ir as the active catalyst. Spectroscopic evidence indicates the exchange of one chloride ligand with an alkoxide to generate the active precatalyst. The exchange of the second chloride ligand, however, leads to a potassium alkoxide-iridate species as the deactivated form of this immobilized catalyst. These findings could be widely applicable to the many homogeneous transfer hydrogenation catalysts with Cp*IrCl substructure.

X-ray spectroscopy for chemistry in the 2-4 keV energy regime at the XMaS beamline: ionic liquids, Rh and Pd catalysts in gas and liquid environments, and Cl contamination in γ-Al2O3.

The 2-4 keV energy range provides a rich window into many facets of materials science and chemistry. Within this window, P, S, Cl, K and Ca K-edges may be found along with the L-edges of industrially important elements from Y through to Sn. Yet, compared with those that cater for energies above ca. 4-5 keV, there are relatively few resources available for X-ray spectroscopy below these energies. In addition, in situ or operando studies become to varying degrees more challenging than at higher X-ray energies due to restrictions imposed by the lower energies of the X-rays upon the design and construction of appropriate sample environments. The XMaS beamline at the ESRF has recently made efforts to extend its operational energy range to include this softer end of the X-ray spectrum. In this report the resulting performance of this resource for X-ray spectroscopy is detailed with specific attention drawn to: understanding electrostatic and charge transfer effects at the S K-edge in ionic liquids; quantification of dilution limits at the Cl K- and Rh L3-edges and structural equilibria in solution; in vacuum deposition and reduction of [Rh(I)(CO)2Cl]2 to γ-Al2O3; contamination of γ-Al2O3 by Cl and its potential role in determining the chemical character of supported Rh catalysts; and the development of chlorinated Pd catalysts in `green' solvent systems. Sample environments thus far developed are also presented, characterized and their overall performance evaluated.

Deciphering complexity in Pd-catalyzed cross-couplings.

Understanding complex reaction systems is critical in chemistry. While synthetic methods for selective formation of products are sought after, oftentimes it is the full reaction signature, i.e., complete profile of products/side-products, that informs mechanistic rationale and accelerates discovery chemistry. Here, we report a methodology using high-throughput experimentation and multivariate data analysis to examine the full signature of one of the most complicated chemical reactions catalyzed by palladium known in the chemical literature. A model Pd-catalyzed reaction was selected involving functionalization of 2-bromo-N-phenylbenzamide and multiple bond activation pathways. Principal component analysis, correspondence analysis and heatmaps with hierarchical clustering reveal the factors contributing to the variance in product distributions and show associations between solvents and reaction products. Using robust data from experiments performed with eight solvents, for four different reaction times at five different temperatures, we correlate side-products to a major dominant N-phenyl phenanthridinone product, and many other side products.

Development and Experimental Validation of a Dispersity Model for In Silico RAFT Polymerization.

The exploitation of computational techniques to predict the outcome of chemical reactions is becoming commonplace, enabling a reduction in the number of physical experiments required to optimize a reaction. Here, we adapt and combine models for polymerization kinetics and molar mass dispersity as a function of conversion for reversible addition fragmentation chain transfer (RAFT) solution polymerization, including the introduction of a novel expression accounting for termination. A flow reactor operating under isothermal conditions was used to experimentally validate the models for the RAFT polymerization of dimethyl acrylamide with an additional term to accommodate the effect of residence time distribution. Further validation is conducted in a batch reactor, where a previously recorded in situ temperature monitoring provides the ability to model the system under more representative batch conditions, accounting for slow heat transfer and the observed exotherm. The model also shows agreement with several literature examples of the RAFT polymerization of acrylamide and acrylate monomers in batch reactors. In principle, the model not only provides a tool for polymer chemists to estimate ideal conditions for a polymerization, but it can also automatically define the initial parameter space for exploration by computationally controlled reactor platforms provided a reliable estimation of rate constants is available. The model is compiled into an easily accessible application to enable simulation of RAFT polymerization of several monomers.

Amine-modified polyionic liquid supports enhance the efficacy of PdNPs for the catalytic hydrogenation of CO2 to formate.

Palladium nanoparticles stabilised by aniline modified polymer immobilised ionic liquid is a remarkably active catalyst for the hydrogenation of CO2 to formate; the initial TOF of 500 h-1 is markedly higher than either unmodified catalyst or its benzylamine and N,N-dimethylaniline modified counterparts and is among the highest to be reported for a PdNP-based catalyst.

MOF-based heterogeneous catalysis in continuous flow via incorporation onto polymer-based spherical activated carbon supports.

We present an approach to harnessing the tuneable catalytic properties of complex nanomaterials for continuous flow heterogeneous catalysis by combining them with the scalable and industrially implementable properties of carbon pelleted supports. This approach, in turn, will enable these catalytic materials, which largely currently exist in forms unsuitable for this application (e.g. powders), to be fully integrated into large scale, chemical processes. A composite heterogeneous catalyst consisting of a metal-organic framework-based Lewis acid, MIL-100(Sc), immobilised onto polymer-based spherical activated carbon (PBSAC) support has been developed. The material was characterised by focused ion beam-scanning electron microscopy-energy dispersive X-ray analysis, powder X-ray diffraction, N2 adsorption, thermogravimetric analysis, atomic absorption spectroscopy, light scattering and crush testing with the catalytic activity studied in continuous flow. The mechanically robust spherical geometry makes the composite material ideal for application in packed-bed reactors. The catalyst was observed to operate without any loss in activity at steady state for 9 hours when utilised as a Lewis acid catalyst for the intramolecular cyclisation of (±)-citronellal as a model reaction. This work paves the way for further development into the exploitation of MOF-based continuous flow heterogeneous catalysis.

Automated stopped-flow library synthesis for rapid optimisation and machine learning directed experimentation.

For the discovery of new candidate molecules in the pharmaceutical industry, library synthesis is a critical step, in which library size, diversity, and time to synthesise are fundamental. In this work we propose stopped-flow synthesis as an intermediate alternative to traditional batch and flow chemistry approaches, suited for small molecule pharmaceutical discovery. This method exploits the advantages of both techniques enabling automated experimentation with access to high pressures and temperatures; flexibility of reaction times, with minimal use of reagents (µmol scale per reaction). In this study, we integrate a stopped-flow reactor into a high-throughput continuous platform designed for the synthesis of combinatory libraries with at-line reaction analysis. This approach allowed ∼900 reactions to be conducted in an accelerated timeframe (192 hours). The stopped flow approach used ∼10% of the reactants and solvents compared to a fully continuous approach. This methodology demonstrates a significantly improved synthesis success rate of smaller libraries by simplifying the implementation of cross-reaction optimisation strategies. The experimental datasets were used to train a feed-forward neural network (FFNN) model providing a framework to guide further experiments, which showed good model predictability and success when tested against an external set with fewer experiments. As a result, this work demonstrates that combining experimental automation with machine learning strategies can deliver optimised analyses and enhanced predictions, enabling more efficient drug discovery investigations across the design, make, test and analysis (DMTA) cycle.