Current Opinion in Chemical Engineering最新文献

Energy Balance Climate Models have a long history but only drew much attention in the late 1960s. This class of climate models is mainly based upon the balance of streams of energy from the sun and the emission of energy to space, but with simple mechanisms for transport of thermal energy from one location to another. The models only lead to estimates of the surface temperature. The value of these models is their simplicity and their use in understanding of aspects of climate change such as feedback mechanisms and problems of detection of faint signals imbedded in natural climate variability.

The process industries are energy intensive, mostly fossil fuel fired, and are considered difficult to decarbonize. As more electricity is either renewable or otherwise carbon free, powering more process industry operations with electricity becomes a decarbonization strategy. Thermal energy is required for increasing temperature, phase change, and endothermic reaction. Electricity can generate heat via resistance, induction, dielectric, arc, and gas compression mechanisms, among others. Electrically generated heat can be delivered with high precision and tight control. Furthermore, electricity can power the elevation of heat from lower temperatures to higher temperatures. Electricity can also facilitate chemical reactions that are thermodynamically difficult, especially the electrolysis of water to produce hydrogen. The key will be to match the right electrical heating technology at the right temperature with the right application at the right scale.

Introducing defects in TiO₂-based photocatalytic materials is a promising strategy for improving light-driven CO₂ reduction. However, defects such as oxygen vacancies are generally unstable. As a solution and to further enhance the photocatalytic activity, metal doping has been applied. This mini review aims to summarize recent progress in this particular field. Herein, we have classified metal-doped architectures into three different categories: single metal doping, alloy- and co-doping, and doping of morphologically nanoengineered TiO_2−x substrates. The direct relationship between specific metals and product selectivity remains complex, as selectivity can vary significantly among seemingly similar materials. However, numerous methods do show promise in fine-tuning selectivity towards either CO or CH₄. In terms of photocatalytic turnover, remarkable yields have been reported in isolated reports, but insufficient experimental data and divergent reaction conditions hamper a true comparison. This puts an emphasis on the need for standardized activity testing.

The transformation toward renewable energy and feedstock supply in the chemical industry requires new conceptual process design approaches. Recently, deep reinforcement learning (RL), a subclass of machine learning, has shown the potential to solve complex decision-making problems and aid sustainable process design. However, its suitability in static process design still needs to be examined. We discuss the advantages and disadvantages of RL for process design. Then, we survey state-of-the-art research through three major elements: (1) information representation, (2) agent architecture, and (3) environment and reward. Moreover, we discuss perspectives on underlying challenges and promising future works to unfold the full potential of RL for process design in chemical engineering.

Photocathodes play a vital role in photoelectrocatalytic water splitting by acting as catalysts for reducing protons to hydrogen gas when exposed to light. Recent advancements in photocathodes have focused on addressing the limitations of noble metal-based materials. These noble metal-based photocathodes rely on expensive and scarce metals such as platinum and gold as cocatalysts or ohmic back contacts, respectively, rendering the final system less sustainable and costly when applied at scale. This mini-review summarizes the important recent progress in the development of non-noble metal-based photocathodes and their performance in the hydrogen evolution reaction during photoelectrochemical (PEC) water splitting. These advancements bring non-noble metal-based photocathodes closer to their noble metal-based counterparts in terms of performance, thereby paving the way forward toward industrial-scale photoelectrolyzers or PEC cells for green hydrogen production.

Investigations on electrochemical CO₂ reduction reaction (eCO2RR) on copper (Cu) provide instructive information for the understanding and development of Cu-based catalysts and thus help improve their eCO2RR selectivity toward desired products. Although most studies on the reaction mechanism rely on computational simulations, experiments conducted on well-defined single-crystal structures are able to effectively mirror the ideal surfaces employed in simulation studies and thus convey insightful knowledge on the structure–performance correlation of Cu catalysts in eCO2RR. This mini-review provides an overview on state-of-the-art development of Cu single crystals and their facet dependency in eCO2RR in the recent years, followed by an outlook and perspective on what can be expected in the future.

This review highlights the importance of model-based approaches in accelerating vaccine manufacturing process development. The challenges of scaling up from laboratory to commercial processes are addressed through the adoption of Process Analytical Technology frameworks and Quality by Design principles. The application of various modeling approaches beyond downstream and upstream processes in vaccine production is discussed in detail. These in silico process simulation approaches enable deeper understanding of manufacturing dynamics, identification of critical process parameters, and the development of well-defined design spaces, ultimately leading to accelerated vaccine development and improved product quality. The authors stress the significance of an integrated modeling platform for vaccine manufacturing, exemplified by the Inno4Vac project. This initiative seeks to develop a comprehensive computational platform for vaccine manufacturing and stability testing, with a particular focus on stakeholder engagement and collaboration with regulatory bodies to ensure the acceptance and implementation of the platform.

The carbon dioxide reduction reaction (CO₂RR) could reduce the atmospheric CO₂ and store the excess energy obtained by renewable sources. However, proper catalysts are sought to reduce the high overpotentials needed to electroreduce CO₂ and improve the selectivity toward a desired product. Through rational synthetic control, it is possible to obtain nanocrystals (NCs) with a certain shape, which is translated into a preferential surface orientation. Given the structure sensitivity of the CO₂RR, the use of shape-controlled NCs allows for tuning the activity and selectivity of the reaction. This review analyzes the recent findings about shape-controlled NCs for the CO₂RR regarding their synthesis, shape-dependent selectivity, and how to twist their catalytic behavior and stability by compositional modifications. The importance of combining in situ and operando techniques that enable proper correlations between the structural and compositional changes of the catalyst under CO₂RR conditions, and the resulting product distribution is highlighted, aiming for a final transference to real application systems.