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[This corrects the article DOI: 10.1021/acs.energyfuels.3c04147.].

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Conversion of steel industry off-gases to value-added chemicals enabled by renewable electricity can significantly reduce the environmental burden of the steelmaking process. Herein, we demonstrate that CO2 reduction by H2, both contained in steel mill off-gases, to form syngas via the reverse water-gas-shift reaction is effectively performed by nanosecond pulsed discharges at atmospheric pressure. The experimental results suggest the following: (i) An optimum interelectrode distance exists, maximizing CO2 conversion. (ii) CO2 conversion at constant SEI follows a nonmonotonic trend with H2 excess. CO2 conversion increases with H2 excess up to H2:CO2 = 3:1 upon shifting the chemical equilibrium. At larger H2:CO2, both gas cooling, promoted by the high H2 content, and hindered CO2 collisions in a highly diluted stream hamper CO2 conversion. (iii) SEI enhances CO2 conversion, but the effect decreases with increasing SEI due to equilibrium limitations. A stoichiometric H2:CO2 feed ratio in the plasma reactor is recommended for higher energy efficiency. Intensifying MeOH productivity via SEI elevation is not advised as a 2-fold SEI increase results only in 17% higher MeOH throughput.

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Sustainability is vital in solving global societal problems. Still, it requires a holistic view by considering renewable energy and carbon sources, recycling waste streams, environmentally friendly resource extraction and handling, and green manufacturing. Flow chemistry at the microscale can enable continuous sustainable manufacturing by opening up new operating windows, precise residence time control, enhanced mixing and transport, improved yield and productivity, and inherent safety. Furthermore, integrating microfluidic systems with alternative energy sources, such as microwaves and plasmas, offers tremendous promise for electrifying and intensifying modular and distributed chemical processing. This review provides an overview of microflow chemistry, electrification, their integration toward sustainable manufacturing, and their application to biomass upgrade (a select number of other processes are also touched upon). Finally, we identify critical areas for future research, such as matching technology to the scale of the application, techno-economic analysis, and life cycle assessment.

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Artificial intelligence and specifically machine learning applications are nowadays used in a variety of scientific applications and cutting-edge technologies, where they have a transformative impact. Such an assembly of statistical and linear algebra methods making use of large data sets is becoming more and more integrated into chemistry and crystallization research workflows. This review aims to present, for the first time, a holistic overview of machine learning and cheminformatics applications as a novel, powerful means to accelerate the discovery of new crystal structures, predict key properties of organic crystalline materials, simulate, understand, and control the dynamics of complex crystallization process systems, as well as contribute to high throughput automation of chemical process development involving crystalline materials. We critically review the advances in these new, rapidly emerging research areas, raising awareness in issues such as the bridging of machine learning models with first-principles mechanistic models, data set size, structure, and quality, as well as the selection of appropriate descriptors. At the same time, we propose future research at the interface of applied mathematics, chemistry, and crystallography. Overall, this review aims to increase the adoption of such methods and tools by chemists and scientists across industry and academia.

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Herein, the pivotal role of secondary nucleation in a crystallization-enhanced deracemization process is reported. During this process, complete and rapid deracemization of chiral conglomerate crystals of an isoindolinone is attained through fast microwave-assisted temperature cycling. A parametric study of the main factors that affect the occurrence of secondary nucleation in this process, namely agitation rate, suspension density, and solute supersaturation, confirms that an enhanced stereoselective secondary nucleation rate maximizes the deracemization rate. Analysis of the system during a single temperature cycle showed that, although stereoselective particle production during the crystallization stage leads to enantiomeric enrichment, undesired kinetic dissolution of smaller particles of the preferred enantiomer occurs during the dissolution step. Therefore, secondary nucleation is crucial for the enhancement of deracemization through temperature cycles and as such should be considered in further design and optimization of this process, as well as in other temperature cycling processes commonly applied in particle engineering.