Alkaline metal salt-promoted MgO sorbents are effective for CO₂ capture, but they face challenges with decreased CO₂ capture performance and powder elutriation in practical applications, arising due to the loss of pore structures and poor mechanical strength of alkaline metal salt-promoted MgO sorbent powder. Herein, granulation technology was employed to resolve the above problem. The optimized alkaline metal salt-promoted MgO sorbent pellets exhibited a CO₂ capture capacity of 11.46 mmol·g^–1 and a mechanical strength of 11.14 MPa. This mechanical strength was nearly three times greater than that of alkaline metal salt-promoted MgO sorbent pellets without granulation promoters. After 20 cycles, CO₂ capture capacity stabilized at 8.71 mmol·g^–1, while mechanical strength was maintained at 8.92 MPa. Through characterization, it was revealed that the pore structure generated by the pyrolysis of the granulation promoters notably increased the specific surface area, leading to high CO₂ capture capacity. Meanwhile, the strengthened mechanical strength of the alkaline metal salt-promoted MgO sorbent pellets was primarily due to the in situ formation of a γ-AlOOH sol-gel cluster skeleton. Thus, this study provides an effective technological pathway to enhance the performance of the alkaline metal salt-promoted MgO sorbent pellets for industrial applications.

Graphdiyne represents an emerging nanofiller of mixed matrix membranes for high-performance alcohol recovery by pervaporation due to its unique alkyne-rich and porous framework and hydrophobicity. However, such membranes often encounter a persistent challenge of nanofiller agglomeration within the polymer matrix, which diminishes the efficacy of graphdiyne during alcohol recovery. This study proposes a multilevel dispersion strategy that synergistically combines in situ confined growth, ultrasonication, atomization, and rotational shearing throughout membrane preparation to mitigate particle aggregation. The particle agglomeration scale in the polydimethylsiloxane matrix can be effectively reduced from 660 nm of triphenylamine-based graphdiyne to about 291 nm compared to the general stirring-casting method. The mixed matrix membrane loaded with 2.5 wt % triphenylamine-based graphdiyne demonstrated a permeate flux of 2.35 kg·m^–2·h^–1 alongside a separation factor of 11.31 for a 5 wt % ethanol/water solution. Compared to the stirring-casting method, these performances represent enhancements of 41% in permeate flux and 80% in separation factor. Furthermore, a 96 h-continuous pervaporation test indicated the robust stability of the membrane, underscoring the potential for industrial alcohol recovery.

Reverse water-gas shift reaction represents a strategic pathway for CO₂ utilization. Despite its potential, reverse water-gas shift reaction via conventional thermal-catalysis faces several challenges, including low equilibrium conversion rates due to thermodynamic constraints, high energy consumption, and insufficient product selectivity. Here, this study demonstrates an evident synergetic effect between plasma and Ag/ZnO, on enhancing reverse water-gas shift reaction. The plasma catalytic system achieved significantly improved performance with a remarkable CO₂ conversion rate of 76.5%, a high CO selectivity of 96.8%, and a CO yield of 74.1%, along with an energy efficiency as high as 0.19 mmol·kJ^–1, surpassing the plasma alone system and ZnO catalytic systems. Results from X-ray photoelectron spectroscopy and Auger electron spectroscopy confirm the presence of electronic metal-support interactions between Ag and ZnO, which facilitates the formation of electron-deficient Ag sites and partially reduced ZnO_x species. These reactive sites, along with oxygen vacancies created during reduction treatment, enhance the adsorption and activation of H₂ and CO₂, offering a dominant plasma-assisted surface reaction pathway for the improved reverse water-gas shift reaction. These findings underscore the crucial role of electronic metal-support interactions in manipulating surface environments to facilitate efficient plasma-assisted catalytic reactions, with significant implications for the rational design of catalysts capable of converting CO₂ efficiently under mild conditions.

Surface-grafted polymer brushes with controlled properties and nanoscale thickness are ideal candidates for transparent coatings to prevent biofouling. However, maintaining long-term antibacterial performance in natural environments remains a significant challenge. In this study, we present a metalated polymer brush (Mt-PB) coating that combines excellent transparency with antimicrobial properties. The coating is prepared by incorporating transition metal ions (e.g., Cu and Ag) into surface-grafted polymer brushes through cooperative in situ reduction. Due to the ultra-thinness of the metalated brush layer (Cu-PB, ~60.07 nm; Ag-PB, ~57.45 nm), the resulting coating exhibits high optical transmittance (~86%) and superior antibacterial efficiency (~99.99% inhibition rate against E. coli and S. aureus). Additionally, the Mt-PB-coated lens demonstrates excellent antibacterial and antifouling durability, as evidenced by underwater detection tests that provide high-resolution images and stable transparency (Δ < 2%) for over a month of underwater exposure. These findings offer a promising strategy for developing transparent and antifouling coatings suitable for underwater optical devices.

Perturbed-chain statistical associating fluid theory has emerged as a powerful thermodynamic framework for predicting drug-polymer miscibility and stability in amorphous solid dispersions. This review provides a comprehensive overview of the theoretical foundations of perturbed-chain statistical associating fluid theory, including its forma, the meanings of key parameters in physics, and common strategies for parameterization. Its applications to solid–liquid and liquid–liquid equilibrium calculations are highlighted, particularly in the construction of phase diagrams and the prediction of phase separation phenomena such as amorphous-amorphous and liquid–liquid phase separation. The utility of perturbed-chain statistical associating fluid theory in amorphous solid dispersions is illustrated through its roles in solubility prediction, stability assessment, drug release mechanism analysis, and rational formulation and process design. In addition, perturbed-chain statistical associating fluid theory is critically compared with alternative predictive methods, including solubility parameter theory, Flory–Huggins models, molecular simulation approaches, and machine learning. Finally, this review outlines the key challenges and future directions for integrating perturbed-chain statistical associating fluid theory with data-driven and multi-scale modeling approaches to advance model-informed amorphous solid dispersion design.

In the past decades, the advancement of sensor technology has enabled the development and application of reliable process analytical technology in pharmaceutical manufacturing for process monitoring and control. Soft sensors as mathematical models are often coupled with process analytical technology tools to monitor critical quality attributes such as concentrations and particle sizes. Crystallinity and polymorphism changes are prevalent phenomena in pharmaceutical manufacturing. These changes may impact drug manufacturability, drug quality, and patients’ safety. Therefore, assessment of impact of crystallinity and polymorphism change has been one critical aspect of pharmaceutical chemistry, manufacturing, and control review and inspection. Chemistry, manufacturing, and control risk assessment has been largely qualitative in nature and has heavily relied on past knowledge and experience. The potential use of soft sensors to monitor such changes and establish a science supported risk-based control strategy is not widely discussed. In this work, by applying soft sensor models to key unit operations, we presented case studies to discuss the capability and potential of soft sensors in predicting critical quality attributes for key pharmaceutical unit operations, including crystallinity and polymorphism changes in selected drugs with moderate to high solid-state risk levels in drug product manufacturing. Population balance models, semi-empirical models, and statistical correlations are applied to wet granulator, fluidized bed dryer, mill, and tablet press to enable soft sensing. Sensitivity analysis using the established models is conducted to quantitatively assess the impacts of process inputs onto different outputs to support a risk-based control strategy with regulatory insights. Knowledge, experience, and discussion in these aspects can contribute to the future development of advanced technologies and the implementation of modeling tools toward advanced manufacturing.

High-entropy alloys are described as materials that have equiatomic and multi-element compositions. Their unique atomic structure may provide alternative electrocatalysts for water electrolysis over traditional and expensive noble metal-based catalysts, delivering superior catalytic activity and stability. Among various high-entropy alloys synthesis methods, electrodeposition stands out as a versatile and cost-effective approach due to its mild conditions and precise control over composition and deposition properties. This review focuses on noble metal-free high-entropy alloys prepared by electrodeposition, with applications in water electrolysis. The impacts of alloying elements and electrodeposition parameters on the morphology, composition, and electrochemical performance of the resulting coatings for hydrogen evolution reaction and oxygen evolution reaction are also examined. The roles of key alloying elements are discussed, including their individual contributions during the electrodeposition process, interactions within the bath, and effects on the final coating. The review also discusses critical deposition parameters such as bath chemistry, pH value, current density, temperature, and bath agitation, and their influences on properties and electrochemical activity of electrodeposited coatings. Finally, future research directions and recommendations in several key areas are outlined to address important knowledge gaps for further advancing the optimization and application of electrodeposited high-entropy alloys as effective electrocatalysts for water electrolysis.

The co-reaction of methanol with C₅–C₁₆ n-alkanes was investigated over microsphere catalysts with varying surface acidity and ZSM-5 as the active components. The results indicate that, as the carbon number of alkanes increases, the formation of C₁–C₄ alkanes decreases while the production of C₂–C₄ alkenes increases on the catalyst with weak outer surface acidity. This suggests that side reactions such as alkene aromatization and hydrogen transfer are suppressed. Conversely, on the catalyst with strong outer surface acidity, further reaction of olefins significantly increases, leading to a gradual decrease in light olefin yield and a corresponding increase in benzene, toluene, xylene, and heavy aromatics. Additionally, it is observed that long-chain n-alkanes (the kinetic diameter of n-hexadecane exceeds the pore size of ZSM-5 zeolite, the active component in the microspherical catalyst) cannot enter the internal pores of ZSM-5, resulting in primary cracking due to the acidic sites on the outer surface. However, long-chain n-alkanes can adjust their molecular orientation on pure ZSM-5 zeolites and enter the pore structure, leading to alkane cracking influenced by both internal and external surface acidity. These findings provide valuable guidance for the design of industrial catalysts, particularly in terms of pore size and acidity.

Polymer composite materials, known for their high specific strength and stiffness, are gradually attracting wider attention in the context of product weight reduction and environmental protection with embedded functionality (smart composites). This article provides practical examples and discusses future development trends of polymer composites fabrication, offering feasible ideas and methods for future economically viable engineering applications, where artificial intelligence can be used as an optimization tool.

Plasma catalysis technology is emerging as a promising approach for addressing energy and environmental challenges in sustainability. This review provides an overview of plasma technology and summarizes recent advances in plasma catalysis from both experimental and theoretical perspectives. Current laboratory-scale studies have demonstrated the versatility of plasma catalysis in various processes, including carbon conversion, hydrogen production, and the removal of volatile organic compounds. The inherently complex environment of plasma catalysis requires in situ characterization and theoretical modeling to elucidate the underlying reaction mechanisms, which in turn guide the rational design of efficient catalysts and optimized reactor configurations. These advances are vital for enhancing the economic feasibility and accelerating the commercialization of this technology. Nevertheless, the scale-up and practical deployment of plasma-catalytic systems from laboratory to industrial scales remain challenging. In this review, we critically examine the current state of plasma catalysis research and its applications across a wide range of reactions. Particular attention is given to in situ mechanistic studies, reactor design, catalyst development, process scale-up, and theoretical modeling. Finally, we provide a forward-looking perspective on the opportunities and future directions to address existing challenges and harness the potential of plasma catalysis toward sustainable development.