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Production of value-added chemicals from lignocellulose is one of the key strands of the emerging bio-economy. A synthetic approach has been developed to produce p-methoxy coumarate esters from waste corn stover and corn bran, and further transform these compounds into consumer products. In the first step, p-coumaric acid (pCA) and ferulic acid (FA) are released through mild alkaline hydrolysis of corn waste, in more than 20 mg g -1 yield (10 wt % based on lignin content). Subsequently, heterogeneous solid acids catalyze the esterification of pCA with various alcohols. Amberlite IR-15 shows the best catalytic performance, owing to its optimal acid density, large surface area, and suitable pore diameter. The solid acid catalyst can be recycled with slight activity loss and regenerated by acid washing and vacuum drying. Finally, methylation of p-coumarate ester to give target product p-methoxy coumarate esters is carried out by using commercially available and low-cost inorganic bases (e. g., K 2 CO 3 ). Base-catalyzed transesterification of methyl p-methoxy coumarate to p-methoxy coumarate esters is also investigated., (© 2021 Wiley-VCH GmbH.)

Rational solvent selection remains a significant challenge in process development. Here we describe a hybrid mechanistic-machine learning approach, geared towards automated process development workflow. A library of 459 solvents was used, for which 12 conventional molecular descriptors, two reaction-specific descriptors, and additional descriptors based on screening charge density, were calculated. Gaussian process surrogate models were trained on experimental data from a Rh(CO) 2 (acac)/Josiphos catalysed asymmetric hydrogenation of a chiral α-β unsaturated γ-lactam. With two simultaneous objectives - high conversion and high diastereomeric excess - the multi-objective algorithm, trained on the initial dataset of 25 solvents, has identified solvents leading to better reaction outcomes. In addition to being a powerful design of experiments (DoE) methodology, the resulting Gaussian process surrogate model for conversion is, in statistical terms, predictive, with a cross-validation correlation coefficient of 0.84. After identifying promising solvents, the composition of solvent mixtures and optimal reaction temperature were found using a black-box Bayesian optimisation. We then demonstrated the application of a new genetic programming approach to select an appropriate machine learning model for a specific physical system, which should allow the transition of the overall process development workflow into the future robotic laboratories.

An event-driven approach based on dynamic optimization and nonlinear model predictive control (NMPC) is investigated together with inline Raman spectroscopy for process monitoring and control. The benefits and challenges in polymerization and morphology monitoring are presented, and an overview of the used mechanistic models and the details of the dynamic optimization and NMPC approach to achieve the relevant process objectives are provided. Finally, the implementation of the approach is discussed, and results from experiments in lab and pilot-plant reactors are presented.

A recently described C(sp 3 )-H activation reaction to synthesise aziridines was used as a model reaction to demonstrate the methodology of developing a process model using model-based design of experiments (MBDoE) and self-optimisation approaches in flow. The two approaches are compared in terms of experimental efficiency. The self-optimisation approach required the least number of experiments to reach the specified objectives of cost and product yield, whereas the MBDoE approach enabled a rapid generation of a process model.

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., (Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.)

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 [RuCl 2 ( i Bu-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.

In this work new methods of processing bio-feedstocks in the formulated consumer products industry are discussed. Our current approach to formulated products design is based on heuristic knowledge of formulators that allows selecting individual compounds from a library of available materials with known properties. We speculate that most of the compounds (or functions) that make up the product to be designed can potentially be obtained from a few bio-sources. In this case, it may be possible to design a sequence of transformations required to convert feedstocks into products with desired properties, analogous to a metabolic pathway of a complex organism. We conceptualize some novel approaches to processing bio-feedstocks with the aim of bypassing the step of a fixed library of ingredients. Two approaches are brought forward: one making use of knowledge-based expert systems and the other making use of applications of metabolic engineering and dynamic combinatorial chemistry.

A novel laser electrodispersion (LE) technique was employed to deposit gold nanoparticles onto Si and SiO(x) surfaces. The LE technique combines laser ablation with cascade fission of liquid metal micro-drops, which results in the formation of nanoparticles upon rapid cooling. The shape and the size distribution of the Au nanoparticles prepared by LE depend on the nature of the support. Gold nanoparticles were also deposited in the channels of microreactors fabricated by wet etching of Si and used as SE(R)RS sensors. The influence of the nanoparticle surface density as well as of the nature of the substrate on the Raman response was studied. At an appropriate surface density of the deposited nanoparticles a significant enhancement of Raman signal was observed showing the possibility to create efficient SERS substrates. Application of microfluidic devices in surface enhanced Raman spectroscopy (SERS) in continuous-flow mode with sensor regeneration is described.

Chemically surface-modified (tosyl-functionalized) carbon nanoparticles (Emperor 2000 from Cabot Corp.) are employed for the extraction and electrochemical determination of phenolic impurities such as benzophenone-3 (2-hydroxy-4-methoxybenzophenone) or triclosan (5-chloro-2-(2,4-dichlorophenoxy)phenol). The hydrophilic carbon nanoparticles are readily suspended and separated by centrifugation prior to deposition onto suitable electrode surfaces and voltammetric analysis. Voltammetric peaks provide concentration information over a 10-100microM range and an estimated limit of detection of ca. 10microM (or 2.3ppm) for benzophenone-3 and ca. 20microM (or 5.8ppm) for triclosan. Alternatively, analyte-free carbon nanoparticles immobilized at a graphite or glassy carbon electrode surface and directly immersed in analyte solution bind benzophenone-3 and triclosan (both with an estimated Langmuirian binding constants of K approximately 6000mol(-1)dm(3) at pH 9.5) and they also give characteristic voltammetric responses (anodic for triclosan and cathodic for benzophenone-3) with a linear range of ca. 1-120microM. The estimated limit of detection is improved to ca.5microM (or 1.2ppm) for benzophenone-3 and ca. 10microM (or 2.3ppm) for triclosan. Surface functionalization is discussed as the key to further improvements in extraction and detection efficiency.

Immobilisation of catalytically-active metal salts in ionic liquids, with extraction by supercritical carbon dioxide, affords continuous Friedel-Crafts acylation, with in situ-recycling of the catalyst.

Keggin tungstophosphoric acid supported onto mesoporous and meso-microporous materials was studied by ammonia microcalorimetry. Experiments were performed at high and low temperatures to separate the contributions of chemisorption and physisorption, low-temperature data being potentially important for the ambient temperature purification processes. Analysis of thermokinetic data obtained from heat output curves at an elevated temperature allows one to distinguish the transition between reaction of ammonia with the acid sites and the onset of physical sorption. Thermokinetic data are also sensitive to the pore structure of the support materials, with faster sorption registered in the case of materials with the open mesoporous structure. The SBA-15 supported acid shows the maximum ammonia uptake and the strongest acid sites among the three materials studied. The dynamics of sorption, characterized by the thermokinetic parameter, appears to be better in the two materials possessing open pore structure, mesoporous carbon Novacarb and especially the mesoporous silica SBA-15.

A system of metrics is proposed for a rough-guide evaluation of the greenness of new and existing chemical technologies as well as for the analysis of flow sheets of new processes. The proposed methodology is based on a hierarchical approach. The main feature of the proposed system is the reflection of the stakeholder relevance of various aspects of green chemistry at different levels of the hierarchy and the corresponding system boundaries. Therefore, the developed methodology provides a basis for the multiobjective comparison of alternative technologies in terms of their greenness. A novel technology for recovery of volatile organic chemicals (VOCs) using monolithic adsorbents has been evaluated in terms of its environmental efficiency using a small set of indicators assembled into a hierarchical metric. A comparison between incineration and recovery of VOCs via adsorption has been performed using the proposed methodology. The comparison highlights considerable environmental advantages of the recovery technology. Flow sheet analysis points out which stages of the adsorption process could be further improved. Indicators have been evaluated within defined system boundaries.