Frontiers of Chemical Science and Engineering最新文献

The reduced mechanism based on the minimized reaction network method can effectively solve the rigidity problem in the numerical calculation of turbulent internal combustion engine. The optimization of dynamic parameters of the reduced mechanism is the key to reproduce the experimental data. In this work, the experimental data of ignition delay times and laminar flame speeds were taken as the optimization objectives based on the machine-learning model constructed by radial basis function interpolation method, and pre-exponential factors and activation energies of H₂ combustion mechanism were optimized. Compared with the origin mechanism, the performance of the optimized mechanism was significantly improved. The error of ignition delay times and laminar flame speeds was reduced by 24.3% and 26.8%, respectively, with 25% decrease in total mean error. The optimized mechanism was used to predict the ignition delay times, laminar flame speeds and species concentrations of jet stirred reactor, and the predicted results were in good agreement with experimental results. In addition, the differences of the key reactions of the combustion mechanism under specific working conditions were studied by sensitivity analysis. Therefore, the machine-learning model is a tool with broad application prospects to optimize various combustion mechanisms in a wide range of operating conditions.

In light of the challenges associated with catalyst separation and recovery, as well as the low production efficiency resulting from intermittent operation for titanium silicalite-1 (TS-1) catalyzed phenol hydroxylation to dihydroxybenzene in the slurry bed, researchers keep on exploring the use of a continuous fixed bed to replace the slurry bed process in recent years. This study focuses on preparing a TS-1 coated structured catalyst on SiC foam, which exhibits significant process intensification in performance. We investigated the kinetics of this structured catalyst and compared it with those of extruded TS-1 catalyst; the dynamic equations of the two catalysts were obtained. It was observed that both catalysts followed E-R adsorption mechanism model, with an effective internal diffusion factor ratio between structured and extruded TS-1 of approximately 7.71. It was confirmed that the foamed SiC-based structured TS-1 catalyst exhibited significant improvements in phenol hydroxylation in fixed-bed reactor due to its well-developed pore structure, good thermal conductivity, excellent internal mass transfer performance, and short reactant diffusion distance, leading to higher utilization efficiency of active components. This finding also provides a foundation for designing and developing phenol hydroxylation processes in fixed-bed using structured catalysts through computational fluid dynamics calculations.

This study investigated the interaction between the furfural residue and polyvinyl chloride co-pyrolysis using an infrared heating method. Various analytical techniques including production distribution analysis, thermal behavior, pyrolysis kinetic, simulated distillation and gas chromatography-mass spectrography (GCMS), and X-ray photoelectron spectroscopy were utilized to elucidate the pyrolysis characterization and reaction mechanism during the co-pyrolysis. Initially, the yield of co-pyrolysis oil increased from 35.12% at 5 °C·s⁻¹ to 37.70% at 10 °C·s⁻¹, but then decreased to 32.07% at 20 °C·s⁻¹. Kinetic and thermodynamic parameters suggested non-spontaneous and endothermic behaviors. GCMS analysis revealed that aromatic hydrocarbons, especially mono- and bi-cyclic ones, are the predominant compounds in the oil due to the presence of H radicals in polyvinyl chloride, suggesting an enhancement in oil quality. Meanwhile, the fixed chlorine content increased to 65.11% after co-pyrolysis due to the interaction between inorganic salts in furfural residues and chlorine from polyvinyl chloride.

The photocatalytic reduction of CO₂ into formic acid is a feasible approach to alleviate the effects of global climate change and achieve chemical energy storage. It is important to design highly active photocatalysts to improve the selectivity and yield of formic acid. In this study, TiO₂-based catalysts were prepared and loaded with Pd nanoparticles via an impregnation process. The Pd/H-TiO₂ catalyst demonstrated superior CO₂ reduction activity and a high formic acid production rate of 14.14 mmol_cat·g⁻¹·h⁻¹. The excellent catalytic performance observed in the presence of a Pd/H-TiO₂ catalyst is ascribed to the synergy between O_v and Pd. The presence of O_v led to increase in CO₂ adsorption while Pd loading enhanced the photogenerated electron-hole pair separation. Electron transfer from H-TiO₂ to Pd also contributed to CO₂ activation.

A novel carboxylated lactose/sodium lignosulfonate/polyacrylic acid hydrogel composites with self-reduction capacity was successfully synthesized by self-assembly method. The hydrogel with well-developed porous structure provided abundant anchoring points and reduction capacity for transforming Ag⁺ into silver nanoparticles. Silver nanoparticles dispersed among the network of hydrogel and the composites exhibited catalytic capacity. The catalytic performance was evaluated via degradation of p-nitrophenol, rhodamine B, methyl orange and methylene blue, which were catalyzed with corresponding reaction rate constants of 0.04338, 0.07499, 0.04891, and 0.00628 s^–1, respectively. In addition, the catalyst exhibited stable performance under fixed-bed condition and the corresponding conversion rate still maintained more than 80% after 540 min. Moreover, the catalytic performance still maintained effective in tap water and simulated seawater. The catalytic efficiency still remained 99.7% with no significant decrease after 8 cycles.

An onboard facility shows promise in efficiently converting floating plastics into valuable products, such as methanol, negating the need for regional transport and land-based treatment. Gasification presents an effective means of processing plastics, requiring their transformation into gasification-compatible feedstock, such as hydrochar. This study explores hydrochar composition modeling, utilizing advanced algorithms and rigorous analyses to unravel the intricacies of elemental composition ratios, identify influential factors, and optimize hydrochar production processes. The investigation begins with decision tree modeling, which successfully captures relationships but encounters overfitting challenges. Nevertheless, the decision tree vote analysis, particularly for the H/C ratio, yielding an impressive R² of 0.9376. Moreover, the research delves into the economic feasibility of the marine plastics-to-methanol process. Varying payback periods, driven by fluctuating methanol prices observed over a decade (ranging from 3.3 to 7 yr for hydrochar production plants), are revealed. Onboard factories emerge as resilient solutions, capitalizing on marine natural gas resources while striving for near-net-zero emissions. This comprehensive study advances our understanding of hydrochar composition and offers insights into the economic potential of environmentally sustainable marine plastics-to-methanol processes.

The reliance on fossil fuels intensifies CO₂ emissions, worsening political and environmental challenges. CO₂ capture and conversion present a promising solution, influenced by industrialization and urbanization. In recent times, catalytic conversion of CO₂ into fuels and chemical precursors, particularly methane, are gaining traction for establishing a sustainable, carbon-neutral economy due to methane’s advantages in renewable energy applications. Though homogeneous and heterogeneous catalysts are available for the conversion of CO₂ to methane, the efficiency is found to be higher in heterogeneous catalysts. Therefore, this review focuses only on the heterogeneous catalysts. In this context, the efficient heterogeneous catalysts with optimum utility are yet to be obtained. Therefore, the quest for suitable catalyst for the catalytic conversion of CO₂ to CH₄ is still continuing and designing efficient catalysts requires assessing their synthetic feasibility, often achieved through computational methods like density functional theory simulations, providing insights into reaction mechanisms, rate-limiting steps, catalytic cycle, activation of C=O bonds and enhancing understanding while lowering costs. In this context, this review examines the conversion of CO₂ to CH₄ using seven distinct types of catalysts, including single and double atom catalysts, metal organic frameworks, metalloporphyrins, graphdiyne and graphitic carbon nitrite and alloys with some case studies. The main focus of this review is to offer a detailed and extensive examination of diverse catalyst design approaches and their utilization in CH₄ production, with a specific emphasis on computational aspects. It explores the array of design methodologies used to identify reaction pathways and investigates the critical role of computational tools in their refinement and enhancement. We believe this review will help budding researchers to explore the possibilities of designing catalysts for the CO₂ to CH₄ conversion from computational framework.

Framework materials such as zeolites and mesoporous silicas are commonly used for many applications, especially catalysis and separation. Here zeolite-mesoporous silica composite catalysts (employing zeolite Y, ZSM-5, KIT-6, SBA-15 and MCM-41 mesoporous silica) were prepared (with different weight percent of zeolite Y and ZSM-5) and assessed for catalytic cracking (using n-heptane, as the model compound at 550 °C) with the aim to improve the selectivity/yield of light olefins of ethylene and propylene from n-heptane. Physicochemical properties of the parent zeolites and the prepared composites were characterized comprehensively using several techniques including X-ray diffraction, nitrogen physisorption, scanning electron microscopy, fourier transform infrared spectroscopy, pulsed-field gradient nuclear magnetic resonance and thermogravimetric analysis. Catalytic cracking results showed that the ZY/ZSM-5/KIT-6 composite (20:20:60 wt %) achieved a high n-heptane conversion of 85% with approximately 6% selectivity to ethylene/propylene. In contrast, the ZY/ZSM-5/SBA-15 composite achieved a higher conversion of 95% and an ethylene/propylene ratio of 8%, indicating a more efficient process in terms of both conversion and selectivity. Magnetic resonance relaxation analysis of the ZY/ZSM-5/KIT-6 (20:20:60) catalyst confirmed a micro-mesoporous environment that influences n-heptane diffusion and mass transfer. As zeolite Y and ZSM-5 have micropores, n-heptane can move and undergo hydrogen transfer reactions, whereas KIT-6 has mesopores that facilitate n-heptane’s accessibility to the active sites of zeolite Y and ZSM-5.

Herein, we introduced a nitrogen-alkali lignin-doped phenolic resin (N@AL_nPR) to produce palladium nanoparticles through an in situ reduction of palladium in an aqueous phase, without the need for additional reagents or a reducing atmosphere. The phenolic resin nanospheres and the resulting palladium nanoparticles were extensively characterized. Alkali lignin created a highly conducive environment for nitrogen incorporation, dispersion, reduction, and stabilization of palladium, leading to a distinct catalytic performance of palladium nanoparticles in vanillin hydrodeoxygenation. Under specific conditions of 1 mmol of vanillin, 40 mg of catalyst, 1 MPa H₂, 90 °C, and 3 h, the optimized Pd/N@AL₃₀PR catalyst exhibited a nearly complete conversion of vanillin, 98.9% selectivity toward p-creosol, and good stability for multiple reuses. Consequently, an environmentally friendly lignin-based catalyst was developed and used for the efficient hydrodeoxygenation conversion of lignin-based platform compounds.

The Fe-Mn bimetallic catalyst is a potential candidate for the conversion of CO₂ into value-added chemicals. The interaction between the two metals plays a significant role in determining the catalytic performance, however which remains controversial. In this study, we aim to investigate the impact of tuning the proximity of Fe-Mn bimetallic catalysts with similar nanoparticle size. And its effect on the physicochemical properties of the catalysts and corresponding performance were investigated. It was found that closer Fe-Mn proximity resulted in enhanced CO₂ hydrogenation activity and inhibited CH₄ formation. The physiochemical properties of prepared catalysts were characterized using X-ray diffraction, H₂ temperature programmed reduction, and X-ray photoelectron spectroscopy, revealing that a closer Fe-Mn distance promoted electron transfer from Mn to Fe, thereby facilitating Fe carburization. The adsorption behavior of CO₂ and the identification of reaction intermediates were analyzed using CO₂-temperature programed desorption and in situ Fourier transform infrared spectroscopy, confirming the intimate Fe-Mn sites contributed to CO₂ adsorption and the formation of HCOO* species, ultimately leading to increased CO₂ conversion and hydrocarbon production. The discovery of a synergistic effect at the intimate Fe-Mn sites in this study provides valuable insights into the relationship between active sites and promoters.