The carbonation of K₂CO₃ to KHCO₃ is an interesting CO₂ capture process due to its low material cost, high selectivity, and substantial CO₂ capacity. Traditionally, KHCO₃ is regenerated into K₂CO₃ through thermal decomposition. However, plasma-assisted decomposition presents a promising alternative, enabling not only CO₂ desorption but also the concurrent production of valuable products such as H₂ and CO. In this study, KHCO₃ particles in a size range of 250–355 μm were packed in a dielectric barrier discharge reactor and exposed to plasma. It was found that the decomposition of KHCO₃ in the plasma reactor is mainly driven by a thermal mechanism, and the decomposition rate was controlled by temperature increase via plasma heating. The energy consumption for decomposition is more than one order of magnitude higher compared to the thermal approach reported in the literature. However, production of CO and H₂ was achieved during plasma treatment, highlighting the potential advantage of an integrated CO₂ capture and utilization process, and the best CO₂ conversion and energy efficiency achieved were 9.0% ± 0.2% at 3.0% ± 0.1% with a syngas ratio of 0.35 ± 0.01.

In recent years, energy crisis environmental problems have attracted more and more attention. Considering the shortage of oil resources and abundant coal resources in the earth’s crust, we need to find a feasible and efficient way in the coal chemical industry. Numerous studies have shown that dimethyl oxalate produced by gas-phase CO coupling reaction can be selectively hydrogenated to methyl glycolate and deeply hydrogenated to ethylene glycol and ethanol. This paper introduces the research progress of the catalyst in the stepwise conversion process of dimethyl oxalate hydrogenation. The research progress of active sites and structure-activity relationship of each catalyst was emphasized, and the active sites and reaction conditions of the three products were summarized. In addition, the direction of future catalyst design is suggested.

This study investigates the co-pyrolysis behavior and product distribution of peanut straw and polyethylene film blends through thermogravimetric analysis and gas chromatography-mass Spectrometry. Thermogravimetric analysis results revealed distinct pyrolysis temperature intervals: 247–356 °C for peanut straw, 448–505 °C for polyethylene film, and an extended range of 247–510 °C for their mixtures. Synergistic effects, quantified through experimental-theoretical deviations, demonstrated enhanced mass conversion rates and accelerated pyrolysis kinetics in blended systems. As the mass ratio of peanut straw to polyethylene increases from 1:1 to 1:7, the bio-oil yield increased from 62.1% to 76.86%, accompanied by elevated alkane from 20.84% to 31.41% and olefin from 24.73% to 42.89%. HZSM-5 catalyst further optimized product profiles, achieving 77.08% bio-oil yield with enhanced hydrocarbon selectivity (alkanes: 35.69%; olefins: 46.16%) while suppressing oxygenates from 20.07% to 8.85%. Carbon chain distribution analysis indicated a polyethylene ratio-dependent shift toward short-chain alkanes (C6–C19), with HZSM-5 intensifying this trend through selective cracking of long-chain species (C20+). These findings establish that co-pyrolysis with catalytic intervention effectively promotes hydrocarbon production and inhibits oxygenated compounds, providing strategic insights for agricultural plastic waste valorization.

Infinite dilution activity coefficient (γ^∞) is a key thermodynamic parameter in solvent design for chemical processes. Although conductor-like screening model for segment activity coefficient (COSMO-SAC) exhibits strong prior predictive capabilities, its estimations are sometimes only qualitative rather than quantitative. Another limitation of COSMO-SAC arises from the reliance on time-intensive quantum chemistry calculations, which restricts its scalability for large-scale solvent screening. To overcome these issues, this study integrates COSMO-SAC with machine learning for accurate γ^∞ prediction of binary mixtures. By bypassing the necessity for quantum chemistry calculations, the multi-task machine learning model could rapidly predict the surface charge density distribution (σ-profiles) and molecular cavity volume (V_COSMO) of molecules and ions, while accurately distinguishing isomers. Four adjustable parameters of COSMO-SAC are optimized using more than 20000 experimental data points of γ^∞, and residual systematic errors are further corrected with the boosting ensemble strategy to improve the model performance. The resulting hybrid model reduces the mean absolute error from 0.944 to 0.102 (R²  =  0.969), representing an 89 % improvement, while preserving the physicochemical interpretability of model. This accurate and efficient approach broadens the practical applicability of σ-profiles and V_COSMO prediction, as well as γ^∞ calculations based on COSMO-SAC, facilitating the high-throughput solvent screening for diverse chemical engineering applications.

A rotating gliding arc (RGA) device driven by synergistic flow and magnetic fields was developed for enhanced nitrogen fixation. The effects of flow field distribution, magnetic field intensity, and N₂/O₂ ratio on fixation performance were investigated. A uniform tangential inlet improved arc stability, suppressed reverse breakdown, and extended the operating range of the RGA, resulting in the highest fixation efficiency. At an air flow rate of 3 L∙min^–1, the device achieved an NO_x concentration of 7623 ppm in the effluent, with an energy cost as low as 3.6 MJ·mol^–1. This configuration also enhanced plasma non-equilibrium, promoting nitrogen excitation and reactive species generation. Increasing magnetic field strength improved efficiency up to 200 mT, beyond which gains plateaued. An N₂/O₂ ratio of 6:4 yielded optimal nitrogen excitation and fixation performance.

Addressing the growing challenge of oil pollution, this study presents a green and efficient strategy for fabricating biodegradable poly(lactic acid)/poly(butylene adipate-co-terephthalate)/talc (PLA/PBAT/Talc) composite foams with high volume expansion ratio (VER), excellent compression resilience, and superior oil absorption performance via synergistic melt blending and supercritical CO₂ (scCO₂) batch foaming. By strategically incorporating PBAT (10 wt %) and talc (3 wt %) into the PLA matrix, and by optimizing the foaming temperatures, the melt strength and crystallization behavior were effectively tailored. The resultant PLA/PBAT-T3 foam achieved a VER exceeding 45 and an open-cell content (OCC) of 85%. Cyclic compression tests demonstrated that the PLA/PBAT-T3 foam fabricated at 100 °C exhibited the lowest permanent deformation, indicating superior structural integrity. Remarkably, the foam exhibited equilibrium oil absorption capacities (Q_t) of 22.2 g·g^–1 for silicone oil and 13.4 g·g^–1 for cyclohexane. A significant correlation was established, revealing that Q_t is directly proportional to the multiplication of VER and OCC. The foam also demonstrated excellent reusability, retaining over 85% of its initial absorption capacity after 10 consecutive absorption-desorption cycles. This work provides a viable strategy for engineering biodegradable and recyclable oil-sorbent materials, while also advancing the application potential of PLA-based composites in sustainable environmental remediation technologies.

Metal-organic networks (MONs) have gained much attention due to their high surface areas and tunable structures, which underpin their potential for gas adsorption and separation. However, the stability issue remains a significant bottleneck that severely restricts their broader practical deployment. Therefore, exploring strategies to address this issue is of great significance but full of challenges. Herein, we highlight recent advances in combining MONs with polymers through surface polymerization, an approach that effectively enhances stability without sacrificing porosity, thereby enabling operation under harsher environments. Beyond stability, polymer incorporation imparts additional functions, including improved gas separation and photo-responsiveness that are inaccessible to the individual components. Finally, we propose the promising research directions of the construction of molecular sieves or stimuli-responsive functional polymer layers that leverage the merits of surface polymerization for applying MONs.