A methodology for chemical routes development and evaluation on the basis of data-mining is presented. A section of the Reaxys database was converted into a network, which was used to plan hypothetical synthesis routes to convert a bio-waste feedstock, limonene, to a bulk intermediate, benzoic acid. The route evaluation considered process conditions and used multiple indicators, including exergy, E-factor, solvent score, reaction reliability and route redox efficiency, in a multi-criteria environmental sustainability evaluation. The proposed methodology is the first route evaluation based on data mining, explicitly using reaction conditions, and is amenable to full automation.

Data-mining of Reaxys and network analysis of the combined literature and in-house reactions set were used to generate multiple possible reaction routes to convert a bio-waste feedstock, limonene, into a pharmaceutical API, paracetamol. The network analysis of data provides a rich knowledge-base for generation of the initial reaction screening and development programme. Based on the literature and the in-house data, an overall flowsheet for the conversion of limonene to paracetamol was proposed. Each individual reaction–separation step in the sequence was simulated as a combination of the continuous flow and batch steps. The linear model generation methodology allowed us to identify the reaction steps requiring further chemical optimisation. The generated model can be used for global optimisation and generation of environmental and other performance indicators, such as cost indicators. However, the identified further challenge is to automate model generation to evolve optimal multi-step chemical routes and optimal process configurations.

The algorithmic, large-scale use and analysis of reaction databases such as Reaxys is currently hindered by the absence of widely adopted standards for publishing reaction data in machine readable formats. Crucial data such as yields of all products or stoichiometry are frequently not explicitly stated in the published papers and, hence, not reported in the database entry for those reactions, limiting their usefulness for algorithmic analysis. This paper presents a possible extension to the IUPAC RInChI standard via an auxiliary layer, termed ProcAuxInfo, which is a standardised, extensible form in which to report certain key reaction parameters such as declaration of all products and reactants as well as auxiliaries known in the reaction, reaction stoichiometry, amounts of substances used, conversion, yield and operating conditions. The standard is demonstrated via creation of the RInChI including the ProcAuxInfo layer based on three published reactions and demonstrates accurate data recoverability via reverse translation of the created strings. Implementation of this or another method of reporting process data by the publishing community would ensure that databases, such as Reaxys, would be able to abstract crucial data for big data analysis of their contents.

Tetrafluoropropene (R1234yf) is the most likely replacement for tetrafluoroethane (R134a), a widely used refrigerant, propellant, and solvent, characterized by a very high global warming potential. In this study, solvation properties of R1234yf were studied experimentally and computationally for solubility of artemisinin, a precursor to the important biopharmaceutical API, and extraction of artemisinin from biomass. R1234yf was shown to be a poorer solvent than R134a for artemisinin. COSMO-RS calculations of solvation in R1234yf suggest that the decrease in performance is likely due to entropic effects. However, R1234yf was effectively used in solid–liquid extraction of Artemisia annua. The new solvent has shown an increased selectivity to the target metabolite artemisinin. This should allow for design of more selective separation processes based on the new solvent molecule with a low global warming potential of 4 relative to CO2.Keywords: Artemisinin; COSMO-RS; Extraction; R1234yf; R134a; Solubility;

Two new types of phenolic resin-derived synthetic carbons with bi-modal and tri-modal pore-size distributions were used as supports for Pd catalysts. The catalysts were tested in chemoselective hydrogenation and hydrodehalogenation reactions in a compact multichannel flow reactor. Bi-modal and tri-modal micro-mesoporous structures of the synthetic carbons were characterised by N2 adsorption. HR-TEM, PXRD and XPS analyses were performed for characterising the synthesised catalysts. N2 adsorption revealed that tri-modal synthetic carbon possesses a well-developed hierarchical mesoporous structure (with 6.5 nm and 42 nm pores), contributing to a larger mesopore volume than the bi-modal carbon (1.57 cm3 g−1versus 1.23 cm3 g−1). It was found that the tri-modal carbon promotes a better size distribution of Pd nanoparticles than the bi-modal carbon due to presence of hierarchical mesopore limitting the growth of Pd nanoparticles. For all the model reactions investigated, the Pd catalyst based on tri-modal synthetic carbon (Pd/triC) show high activity as well as high stability and reproducibility. The trend in reactivities of different functional groups over the Pd/triC catalyst follows a general order alkyne ≫ nitro > bromo ≫ aldehyde.

•A robust method was developed for identification and quantification of dihydroartemisinic acid in crude plant extract.•13 genotypes of A. annua used in various breeding programmes screened for superior metabolic profile.•Multivariate analysis was used to identify biosynthetic associations among 5 artemisinin related compounds.An improved liquid chromatography-tandem mass spectrometry (LC–MS/MS) protocol for rapid analysis of co-metabolites of A. annua in raw extracts was developed and extensively characterized. The new method was used to analyse metabolic profiles of 13 varieties of A. annua from an in-field growth programme in Madagascar. Several multivariate data analysis techniques consistently show the association of artemisinin with dihydroartemisinic acid. These data support the hypothesis of dihydroartemisinic acid being the late stage precursor to artemisinin in its biosynthetic pathway.Figure optionsDownload full-size imageDownload as PowerPoint slide

A flow process for direct amination of a pharmaceutically relevant substrate using a Pd-NHC based catalyst was demonstrated in a lab-scale mini-plant and in a pilot-scale plant. The lab-scale mini-plant was used to determine catalyst stability under recycling conditions. Results in the mini-plant have shown the maximum space–time yield between the three types of reactor systems: a batch reactor, a mini-plant and a pilot plant. A comprehensive life-cycle assessment study of the synthesis of organometallic catalysts and their impact on the overall LCA of flow vs. batch syntheses was developed. Combined with a simplified economic analysis, the LCA study confirmed the benefits of switching to flow.

High catalytic activity for the telomerisation of isoprene with methanol with an unusual regioselectivity towards tail-to-tail telomerisation products was achieved with a heterogeneous (DVB-resin-PPh3-Pd-dvds) catalyst synthesised by supporting palladium-(dvds) on a commercial triphenylphosphine–divinylbenzene resin, with potential for continuous operation. The high activity is a function of the presence of the (dvds) ligand while the regioselectivity is attributed to the combination of (dvds) and PPh3 ligands associated with the palladium centre. The loss of activity upon recycling the catalyst is due to the loss of associated (dvds) ligand during reaction and during the recycle process.

The direct chemical conversion of cocoa butter triglycerides, a material available as a postmanufacture waste stream from the food industry, to 1-decene by way of ethenolysis is reported. The conversion of the raw waste material was made possible by use of 1 mol % of the [RuCl2(iBu-phoban)2(3-phenylindenyl)] catalyst. The process has been investigated in both batch and flow conditions, where the latter approach employs a Teflon AF-2400 tube-in-tube gas–liquid membrane contactor to deliver ethylene to the reaction system. These preliminary studies culminate in a continuous processing system, which maintained a constant output over a 150 min period tested.Keywords: Flow chemistry; Food waste; Green chemistry; Metathesis; Triglycerides; Valorization

Self-optimization of chemical reactions enables faster optimization of reaction conditions or discovery of molecules with required target properties. The technology of self-optimization has been expanded to discovery of new process recipes for manufacture of complex functional products. A new machine-learning algorithm, specifically designed for multiobjective target optimization with an explicit aim to minimize the number of “expensive” experiments, guides the discovery process. This “black-box” approach assumes no a priori knowledge of chemical system and hence particularly suited to rapid development of processes to manufacture specialist low-volume, high-value products. The approach was demonstrated in discovery of process recipes for a semibatch emulsion copolymerization, targeting a specific particle size and full conversion.

An immersion Raman probe was used in emulsion copolymerization reactions to measure monomer concentrations and particle sizes. Quantitative determination of monomer concentrations is feasible in two-monomer copolymerizations, but only the overall conversion could be measured by Raman spectroscopy in a four-monomer copolymerization. The feasibility of measuring monomer conversion and particle size was established using partial least-squares (PLS) calibration models. A simplified theoretical framework for the measurement of particle sizes based on photon scattering is presented, based on the elastic-sphere-vibration and surface-tension models.

Oxygenation of α-pinene using photochemically generated singlet oxygen (1O2) was studied in detail in several continuous flow photochemical reactors. Ferrioxalate actinometry and reaction kinetic data were used to compare light sources and reactor geometries, such as the immersed-well, an annular recirculating and microfluidic reactors. It is shown that reactor miniaturization, control of intensity and of spectral composition of light, and elevated oxygen pressure are the crucial factors for safe and efficient photo-oxygenation reactions. Higher quantum yields were generally obtained with the microreactor-LED assemblies due to better energy utilization, compared to all other systems studied. For the single-phase microreactor-LED system, an optimization model has been developed that revealed a broad optimal design window.

•We developed a rapid method of analysis of six metabolites in A. annua extracts.•9-Epi-artemisinin was quantified in raw extracts of A. annua for the first time.•We show the method to be robust, sensitive, adequate for high throughput analysis.A rapid high-pressure liquid chromatography (HPLC) tandem mass spectrometry (TQD) method for the determination of artemisinin, 9-epi-artemisinin, artemisitene, dihydroartemisinic acid, artemisinic acid and arteannuin B in Artemisia annua extracts is described. Detection and quantification of 9-epi-artemisinin in crude extracts are reported for the first time. In this method all six metabolites are resolved and eluted within 6 min with minimal sample preparation. A recovery of between 96.25% and 103.59% was obtained for all metabolites analysed and the standard curves were linear (r2 > 0.99) over the concentration range of 0.15–10 μg mL−1 for artemisinin, 9-epi-artemisinin, artemisitene and arteannuin B, and the range of 3.75–120 μg mL−1 for dihydroartemisinic acid and artemisinic acid. All validation indices were satisfactory, showing the method to be robust, quick, sensitive and adequate for a range of applications including high throughput (HTP) analysis.A rapid method for quantification of several important co-metabolites of artemisinin in raw extracts is presented.

•An overview of closed-loop experiment systems for materials discovery.•Discussion of machine-learning algorithms for target optimization in chemical systems.•An overview of analytical methodologies for data-rich experiments.This paper presents the first overview of recent developments in techniques and methods that enable closed-loop optimization, also sometimes called ‘self optimization’, as well as discovery in different areas of molecular sciences. The closed-loop experimental platforms offer tremendous new opportunities by significantly increasing productivity, as well as enabling completely new types of experiments to be performed. Such experiments involve three main enabling technology areas: automated experimental systems, analytical instruments connected to automated chemoinformatics software and optimization or decision-making algorithms. We review the most exciting developments concerning robotic experiments, 3D printed lab-ware, experimental systems with multiple analytical instruments and advanced optimization algorithms based on machine learning approaches. A range of different chemical problems is described, which show the breadth of potential applications of this emerging experimental approach.

•Co-metabolites negatively impacting crystallization of artemisinin were identified.•Flavonoid artemetin has strongest impact on crystallization of artemisinin.•Elevated levels of artemetin were found in the problematic East African biomass.Methoxylated flavonoids casticin, artemetin and retusin were identified as putative causative factors for low crystallization yields of artemisinin from extracts. Comparative profiling of biomass grown in different countries found elevated levels (∼60% higher) of artemetin in the East African biomass, which also demonstrates poor crystallization yields. The single compound and the combined doping experiments at 0, 25 and 50 μg mL−1 doping levels showed that artemetin (at 50 μg mL−1) caused a reduction in the amount of artemisinin crystallized by ca. 60%. A combination of the three flavonoids at 50 μg mL−1 almost completely inhibited crystallization, reducing the yield by 98%. Treatment of extracts by adsorbents efficiently resolves the problem of low crystallization yield.

Two new types of phenolic resin-derived synthetic carbons with bi-modal and tri-modal pore-size distributions were used as supports for Pd catalysts. The catalysts were tested in chemoselective hydrogenation and hydrodehalogenation reactions in a compact multichannel flow reactor. Bi-modal and tri-modal micro-mesoporous structures of the synthetic carbons were characterised by N2 adsorption. HR-TEM, PXRD and XPS analyses were performed for characterising the synthesised catalysts. N2 adsorption revealed that tri-modal synthetic carbon possesses a well-developed hierarchical mesoporous structure (with 6.5 nm and 42 nm pores), contributing to a larger mesopore volume than the bi-modal carbon (1.57 cm3 g−1versus 1.23 cm3 g−1). It was found that the tri-modal carbon promotes a better size distribution of Pd nanoparticles than the bi-modal carbon due to presence of hierarchical mesopore limitting the growth of Pd nanoparticles. For all the model reactions investigated, the Pd catalyst based on tri-modal synthetic carbon (Pd/triC) show high activity as well as high stability and reproducibility. The trend in reactivities of different functional groups over the Pd/triC catalyst follows a general order alkyne ≫ nitro > bromo ≫ aldehyde.

High catalytic activity for the telomerisation of isoprene with methanol with an unusual regioselectivity towards tail-to-tail telomerisation products was achieved with a heterogeneous (DVB-resin-PPh3-Pd-dvds) catalyst synthesised by supporting palladium-(dvds) on a commercial triphenylphosphine–divinylbenzene resin, with potential for continuous operation. The high activity is a function of the presence of the (dvds) ligand while the regioselectivity is attributed to the combination of (dvds) and PPh3 ligands associated with the palladium centre. The loss of activity upon recycling the catalyst is due to the loss of associated (dvds) ligand during reaction and during the recycle process.