Search Results (3,588)

To address the challenges of low solar energy utilization efficiency and rapid recombination of photogenerated charge carriers in photocatalytic hydrogen evolution, this study successfully constructed a composite photocatalyst of ZnIn₂S₄ (ZIS) supported on N-doped hollow carbon spheres (N-HCS), denoted as ZIS/N-HCS, via a combination of template etching and in situ growth strategies. Characterization results demonstrate that this hollow structure possesses a high specific surface area (48.41 m²/g) and a narrowed bandgap (2.41 eV), achieve broad-spectrum light absorption, thereby enabling the catalyst to generate a local hot spot temperature of 136 °C under AM1.5G conditions. The optimized ZIS/N-HCS-0.30 sample exhibited a significantly enhanced photocurrent response (8.26 μA cm⁻²) and improved charge separation efficiency. When evaluated at a set solution temperature of 20 °C, the material exhibited a photocatalytic hydrogen evolution rate of 17.03 mmol g⁻¹·h⁻¹, which is 7.06 times higher than that of pure ZIS. Furthermore, it demonstrated excellent cycling stability. This work elucidates the synergistic role of the hollow photothermal structure in enhancing solar energy utilization and catalytic reaction kinetics, providing a new strategy for designing efficient solar-driven hydrogen production systems. Full article

This study addresses the critical issue of environmental pollution from plastic waste by investigating an effective chemical recycling method for polyethylene terephthalate (PET) via neutral catalytic hydrolysis. We utilized a recoverable and regenerable composite catalyst based on cracking zeolite and γ-Al₂O₃, which possesses both Brønsted and Lewis acidic sites that facilitate the depolymerization of PET into its constituent monomers, terephthalic acid (TPA) and ethylene glycol (EG). This investigation reveals that the catalytic performance is strongly dependent on the total acid site concentration and the specific nature of these sites. A key finding is that a balanced acidic profile with a high proportion of Brønsted acid sites is crucial for enhancing PET hydrolysis attributed to a significant decrease in the activation energy of the reaction. The experiments were conducted in a stirred stainless-steel autoclave reactor, where key parameters such as temperature (210–230 °C), the PET-to-water ratio (1:2 to 1:5), and reaction time were systematically varied. Under optimal conditions of 210 °C and a 6 h reaction time, the process achieved near-complete PET depolymerization (99.5%) and a high TPA yield (90.24%). The catalyst demonstrated remarkable recyclability, maintained its activity over multiple cycles and was easily regenerated. Furthermore, the recovered TPA was of high quality, with a purity of 98.74% as confirmed by HPLC, and exhibited a melt crystallization temperature 14 °C lower than that of the commercial standard. These results not only demonstrate the efficiency and sustainability of neutral catalytic hydrolysis using zeolite/alumina composites but also provide valuable insights for designing advanced catalysts with tunable acidic properties. By demonstrating the importance of tuning acidic properties, specifically the balance between Brønsted and Lewis sites, this work lays a foundation for developing more effective catalysts that can advance circular economy goals for PET recycling. Full article

Chlorobenzoic acids (CBAs) are a group of chlorinated persistent environmental pollutants with hard biodegradability, high water solubility, and well-documented carcinogenic and endocrine-disrupting properties. Electrocatalytic hydrodechlorination (ECH) is a highly efficient method under mild conditions without harmful by-products, but the ECH process commonly requires adding precious metal catalysts such as palladium (Pd). To address the economic constraints and more effective utilization of Pd, a palladium/manganese dioxide (Pd/MnO₂) composite catalyst was developed in this study by chemical deposition. This method utilized the excellent electrochemical activity of MnO₂ as a carrier as well as the hydrogen storage and activation capacity of Pd. The test showed the optimal Pd loading was 7.5%, and the removal percent of 2,4-dichlorobenzoic acid (2,4-DCBA), a typical CBA, reached 97.3% using 0.5 g/L of Pd/MnO₂ after 120 min of electrochemical reaction. Under these conditions, the dechlorination percent can also be as high as 89.6%. A higher current density enhanced the dechlorination efficiency but showed the lower current utilization efficiency. In practical applications, current density should be minimized on the premise of compliance with the water treatment requirement. Mechanistic studies showed that MnO₂ synergistically promoted hydrolysis dissociation and hydrogen spillover and facilitated Pd-mediated adsorption of atomic hydrogen (H*) for dehydrogenation of 2,4-DCBA. The presence of MnO₂ can effectively disperse the loaded Pd and reduce the amount of Pd via the above process. The catalyst exhibited excellent stability over multiple cycles, and the 2,4-DCBA removal could still reach more than 80% after the five cycles. This work establishes electrocatalytic strategies for effectively reducing Pd usage and maintaining high removal of typical CBAs to support CBA-related water treatment. Full article

Brilliant blue, as a pigment food additive, has all the characteristics of printing and dyeing wastewater and belongs to persistent and refractory organic compounds. The photocatalysis–Fenton reaction system consists of two parts: photocatalytic reaction and Fenton reaction. Electrons promote the decomposition of H₂O₂ to produce •OH. In addition, the effective separation of e- and h⁺ by light strengthens the direct oxidation of h⁺, and h⁺ reacts directly with OH⁻ to produce •OH, which can further promote the removal of organic pollutants. In this paper, g-C₃N₄ and Fe/g-C₃N₄ photocatalysts were prepared by the thermal polycondensation method. Fe/g-C₃N₄ of 15 wt% can reach 98.59% under the best degradation environment, and the degradation rate of g-C₃N₄ is only 7.6% under the same conditions. The photocatalytic activity of the catalysts was further studied. Through active species capture experiments, it is known that •OH and •O₂⁻ are the main active species in the system, and the action intensity of •OH is greater than that of •O₂⁻. The degradation reaction mechanism is that H₂O₂ combines with Fe²⁺ in Fe/g-C₃N₄ to generate a large amount of •OH and Fe³⁺, and the combination of Fe-N bonds accelerates the cycle of Fe³⁺/Fe²⁺ and promotes the formation of •OH, thereby accelerating the degradation of target pollutants. •O₂⁻ can reduce Fe³⁺ to Fe²⁺, Fe²⁺ reacts with H₂O₂ to produce •OH, which promotes degradation, and •O₂⁻ itself also plays a role in degradation. In addition, under the optimal experimental conditions obtained by response surface experiments, the fitting degree of first-order reaction kinetics is 0.96642, and the fitting degree of second-order reaction kinetics is 0.57884. Therefore, this reaction is more in line with first-order reaction kinetics. The adsorption rate is only proportional to the concentration of Fe/g-C₃N₄. Full article

Microbial metabolism is intricately governed by thermodynamic constraints that dictate energetic efficiency, growth dynamics, and metabolic pathway selection. Previous research has primarily examined these principles under carbon-limited conditions, demonstrating how microbes optimize their proteomic resources to balance metabolic efficiency and growth rates. This study extends this thermodynamic framework to explore microbial metabolism under various non-carbon nutrient limitations (e.g., nitrogen, phosphorus, sulfur). By integrating literature data from a range of species, it is shown that growth under anabolic nutrient limitations consistently yields more negative Gibbs free energy ($\Delta G$) values for the net catabolic reaction (NCR) per unit of biomass than carbon-limited scenarios. The findings suggest three potentially complementary hypotheses: (1) proteome allocation hypothesis: microbes favor faster enzymes to reduce the proteome fraction used for catabolism, thus freeing proteome resources for additional nutrient transporters; (2) coupled transport contribution hypothesis: the more negative $\Delta G$ of the NCR may in part stem from the increased reliance on ATP-coupled or energetically driven transport mechanisms for nutrient uptake under limitation; (3) bioenergetic efficiency hypothesis: microbes prefer pathways with a more negative $\Delta G$ to enhance the cellular energy status, such as membrane potentials or the ATP/ADP ratio, to support nutrient uptake under anabolic limitations. This integrative thermodynamic analysis broadens the understanding of microbial adaptation strategies and offers valuable insights for biotechnological applications in metabolic engineering and microbial process optimization. Full article

The growth of lithium dendrites and the associated “dead lithium” issue significantly impair the performance and cycle life of lithium metal batteries. This study utilizes a phase-field model under constant-current discharge conditions to simulate the dissolution process of lithium dendrites. The results demonstrate that the non-uniform dissolution of lithium dendrites is a primary cause of their stripping and subsequent dead lithium formation. Specifically, a high charging voltage and a high reaction rate constant aggravate dendrite growth and dead lithium accumulation. Although a high discharging voltage accelerates dendrite dissolution, it readily induces stripping at the dendrite roots, generating more dead lithium. In contrast, increasing the temperature, enhancing the interface mobility, adjusting the anisotropy strength to a moderate level, and constructing semi-circular initial nuclei can effectively mitigate dead lithium by promoting a more uniform dissolution process. This research provides a theoretical foundation for optimizing battery operational parameters and electrode designs to improve capacity and safety. Full article

To clarify the characteristics of CO₂–formation water–rock reactions in tight sandstones and their effects on CO₂-enhanced oil recovery (EOR) efficiency and storage efficiency, this study takes the tight oil reservoirs of the Changqing Jiyuan Oilfield as the research object. A variety of experimental techniques, including ICP-OES elemental analysis, powder X-ray diffraction, and scanning electron microscopy, were employed to systematically investigate the mechanisms and main influencing factors of water–rock reactions during CO₂ geological storage. The study focused on analyzing the roles of mineral composition, reservoir pore structure, and formation water chemistry in the reaction process. It explored the potential impacts of reaction products on reservoir properties. Furthermore, based on the experimental results, a coupled reservoir numerical simulation of CO₂ injection for EOR and storage was conducted to comprehensively evaluate the influence of mineralization processes on CO₂ EOR performance and long-term storage efficiency. Results show that the tight sandstone reservoirs in Jiyuan Oilfield are mainly composed of calcite, quartz, and feldspar. The dominant water–rock reactions during CO₂ formation–water interactions are calcite dissolution and feldspar dissolution. Among these, calcite dissolution is considered the controlling reaction due to its significant effect on the chemical composition of formation water, and the temporal variation in other elements shows a clear correlation with the calcite dissolution process. Further analysis reveals that water–rock reactions lead to permeability reduction in natural fractures near injection wells, thereby effectively improving CO₂ EOR efficiency, enhancing sweep volume, and increasing reservoir recovery. At the end of the EOR stage, mineralized CO₂ storage accounts for only 0.53% of the total stored CO₂. However, with the extension of time, mineralized storage gradually increases, reaching a substantial 31.08% after 500 years. The study also reveals the effects of reservoir temperature, pressure, and formation water salinity on mineralization rates, emphasizing the importance of mineral trapping for long-term CO₂ storage. These findings provide a theoretical basis and practical guidance for the joint optimization of CO₂ EOR and geological sequestration. Future research may further focus on the dynamic evolution of water–rock reactions under different geological conditions to enhance the applicability and economic viability of CO₂ storage technologies. Full article

2,5-diformylfuran (DFF) is a significant biomass derivative that is employed in a variety of industries. One approach to synthesizing it is through the oxidation of 5-hydroxymethylfurfural (HMF). The challenges in DFF production arise from the need for extreme conditions, issues with overoxidation, and the limitations of noble materials used in neutral or acidic environments. By using a mildly alkaline electrolyte, DFF can be produced electrochemically alongside hydrogen gas generation, eliminating extreme conditions and allowing for the study of a wide range of transition metals. Moreover, the performance of bimetallic electrocatalysts has been studied, and it has been found to be more active in many kinds of processes, particularly Layered Double Hydroxides (LDH). Electrodeposition, once widely chosen among various LDH production methods, is preferred for producing controlled and uniform thin layers. This work examines the electrocatalytic properties of NiCo-LDH and NiFe-LDH in the production of DFF. Cobalt, which exhibits strong adsorption, will be compared to iron, which has a weak adsorption characteristic toward HMF. This study demonstrates that NiCo-LDH gives 1.49 V vs. RHE onset potential, 600 mV lower compared to NiFe-LDH (1.55 V vs. RHE) for HMF oxidation reaction. NiCo-LDH also converts twice the amount of HMF compared to NiFe-LDH for the same amount of charge passed at 0.25 mA/cm⁻² in 0.1 M Na₂B₄O₇. However, strong adsorption promotes reactant activation and reduces the energy barrier while reducing DFF selectivity in NiCo-LDH (23.4%) due to overoxidation, compared to NiFe-LDH (31.6%). In order to achieve optimal electrocatalyst performance, a careful balance of adsorption strength and reaction pathway management is required. Proper optimization of these parameters is essential to improve efficiency and selectivity in the electrocatalytic process. Full article

Galactooligosaccharides (GOS) typically consist of 2-8 D-galactose units linked together, terminating in a D-glucose unit. GOS are commonly used in dairy products, infant formulas, and functional foods. GOS offer beneficial properties for food processing, such as low caloric value, mild clean taste, and excellent solubility in water. Additionally, GOS function as non-digestible prebiotics, supporting microbiota balance and offering benefits such as promoting infant health, immune modulation, laxative effects, and potential metabolic advantages. β-galactosidase plays a key role in GOS production, catalyzing both hydrolysis and transglycosylation reactions. In this study, a putative GH2 family β-galactosidase from Kosakonia oryzendophytica (Koor β-gal) was identified. The enzyme exhibited optimal activity at pH 7.0 and 45–50 °C with the addition of 1 mM Mg²⁺, showing a specific activity of approximately 288.6 U/mg towards o-nitrophenyl-β-D-galactopyranoside (ONPG). After optimizing the reaction conditions, Koor β-gal successfully produced 124.7 g/L of GOS from 300 g/L D-lactose, achieving a GOS yield of 41.6%. LC-MS analysis revealed that the primary products consisted of GOS with degrees of polymerization (DP) ranging from 2 to 4. Additionally, Koor β-gal was heterologously expressed in Bacillus subtilis following comprehensive optimization of the promoter and 5′-UTR, resulting in an enzyme activity in culture filtrate of 106.2 U/mL after 60 h. Full article

Laboratory-simulated aging fails to fully replicate the complex aging behavior of asphalt binder under actual environmental conditions. This study aims to preliminarily investigate and analyze the differences between natural aging and PAV aging of asphalt binder. To achieve this objective, the asphalt binder was aged using three distinct methods: PAV aging, natural thermal-oxidative aging, and all-weather aging. The divergence in asphalt binder aging behavior was systematically investigated through encompassing low-temperature performance, chemical structure, elemental composition, molecular weight, and macroscopic and microscopic performance correlation analyses. Key findings include: the harsh environment in the cold and arid regions resulted in inferior low-temperature performance of asphalt binder after 12 months of natural thermal-oxidative and all-weather aging compared to PAV-aged asphalt binder, with the stiffness modulus at −12 °C increasing by 114.8% and 105.3%, respectively. Natural aging induced more significant asphalt binder’s chemical structural changes than PAV aging but exhibited less prominent oxidative reactions and macromolecular structure formation. Whether from a macroscopic or microscopic perspective, thermal-oxidative conditions were identified as the primary driver behind both the natural aging behavior and the aging pathway of asphalt binder. The influence of other factors on the aging behavior of asphalt binder was not significant. The poor correlation (R² < 0.62) between oxygen content, molecular weight, and low-temperature performance across different aging modes underscores a fundamental divergence in aging pathways between PAV and natural aging. This study preliminarily identifies the key differences between laboratory-accelerated aging and natural aging of asphalt binder and paves the way for optimizing the parameters of laboratory-accelerated aging protocols. Full article

To address the problem of the proton exchange membrane fuel cell (PEMFC) temperature management under stochastic disturbances, this paper integrates a PEMFC thermal model with a water pump model and establishes a nonlinear stochastic model for temperature regulation. The objective is to maintain the stack temperature at its optimal value. Due to the inherent complexity of the PEMFC electrochemical reactions, the thermal dynamics exhibit strong nonlinear characteristics. To tackle this issue, a control strategy based on the stochastic backstepping method is proposed. Furthermore, to cope with variations in membrane water content and ambient temperature during operation, we design stochastic estimator-based adaptive laws. Simulation results, considering both stochastic disturbances driven by tracking error and those driven by stack temperature and load current, indicate that the proposed control strategy effectively maintains the stack temperature at 343 K under various operating conditions, with a maximum deviation of 0.2 K, thereby confirming its effectiveness and robustness. Full article

Ammonia is a highly promising zero-carbon fuel for engines. However, it exhibits high ignition energy, slow flame propagation, and severe pollutant emissions, so it is usually burned in combination with highly reactive fuels such as hydrogen. An accurate understanding and modeling of ammonia–hydrogen combustion is of fundamental and practical significance to its application. Deep Neural Networks (DNNs) demonstrate significant potential in autonomously learning the interactions between high-dimensional inputs. This study proposed a deep neural network-based method for optimizing chemical reaction mechanism parameters, producing an optimized mechanism file as the final output. The novelty lies in two aspects: first, it systematically compares three DNN structures (Multi-layer perceptron (MLP), Convolutional Neural Network, and Residual Regression Neural Network (ResNet)) with other machine learning models (generalized linear regression (GLR), support vector machine (SVM), random forest (RF)) to identify the most effective structure for mapping combustion-related variables; second, it develops a ResNet-based surrogate model for ammonia–hydrogen mechanism optimization. For the test set (20% of the total dataset), the ResNet outperformed all other ML models and empirical correlations, achieving a coefficient of determination (R²) of 0.9923 and root mean square error (RMSE) of 135. The surrogate model uses the trained ResNet to optimize mechanism parameters based on a Stagni mechanism by mapping the initial conditions to experimental IDT. The results show that the optimized mechanism improves the prediction accuracy on laminar flame speed (LFS) by approximately 36.6% compared to the original mechanism. This method, while initially applied to the optimization of an ammonia–hydrogen combustion mechanism, can potentially be adapted to optimize mechanisms for other fuels. Full article

Pseudomonas aeruginosa (PA) is a significant pathogen of clinical concern that is frequently associated with multidrug resistance, leading to respiratory tract, wound, and hospital-acquired infections. To enable rapid and accurate detection, we developed a fluorescence-based loop-mediated isothermal amplification (LAMP) method, targeting the PA-specific ecfX gene. Among ten primer sets designed, the optimal set (EC2) was identified, and reaction conditions were optimized (Bst polymerase 320 U/mL, Mg²⁺ 8 mM, dNTP 1.4 mM, inner/outer primer ratio 1:8, 64 °C, 20 min). The assay demonstrated a detection limit that was comparable to a real-time polymerase chain reaction and immunochromatographic assays, but with a markedly reduced turnaround time. No cross-reactivity was observed with non-PA pathogens, and reproducibility tests confirmed high stability. In addition, the reliability of the results was further verified using 60 standard bacterial strains, and the feasibility of the assay was validated with 2 real soil samples and 1 water sample. This LAMP method offers a simple, rapid, and sensitive tool for on-site detection of PA, with potential applications in clinical diagnostics and public health surveillance. Full article

Plastic pollution, driven by the durability and widespread use of polyolefins such as polypropylene (PP) and high-density polyethylene (HDPE), poses a formidable environmental challenge. To address this issue, we have developed an integrated multiscale framework that combines thermocatalytic experimentation, process-scale simulation, and molecular-level modeling to optimize the catalytic pyrolysis of PP and HDPE waste. Under the identified optimal conditions (300 °C, 10 wt % HMOR zeolite), liquid-oil yields of 60.8% for PP and 87.3% for HDPE were achieved, accompanied by high energy densities (44.2 MJ/kg, RON 97.5 for PP; 43.7 MJ/kg, RON 115.2 for HDPE). These values significantly surpass those typically reported for uncatalyzed pyrolysis, demonstrating the efficacy of HMOR in directing product selectivity toward valuable liquids. Above 400 °C, the process undergoes a pronounced shift toward gas generation, with gas fractions exceeding 50 wt % by 441 °C, underscoring the critical influence of temperature on product distribution. Gas-phase analysis revealed that PP-derived syngas contains primarily methane (20%) and ethylene (19.5%), whereas HDPE-derived gas features propylene (1.9%) and hydrogen (1.5%), highlighting intrinsic differences in bond-scission pathways governed by polymer architectures. Aspen Plus process simulations, calibrated against experimental data, reliably predict product distributions with deviations below 20%, offering a rapid, cost-effective tool for reactor design and scale-up. Complementary density functional theory (DFT) calculations elucidate the temperature-dependent energetics of C–C bond cleavage and radical formation, revealing that system entropy increases sharply at 500–550 °C, favoring the generation of both liquid and gaseous intermediates. By directly correlating catalyst acidity, molecular reaction mechanisms, and process-scale performance, this study fills a critical gap in plastic-waste valorization research. The resulting predictive platform enables rational design of catalysts and operating conditions for circular economy applications, paving the way for scalable, efficient recovery of fuels and chemicals from mixed polyolefin waste. Full article

The increasing atmospheric CO₂ concentration is one of the major environmental challenges, necessitating not only emission reduction but also effective carbon utilization. Non-thermal plasma-catalytic CO₂ conversion offers an efficient pathway under mild conditions by synergistically combining plasma activation with catalytic surface reactions. In this study, mesoporous ceria catalysts were synthesized by different methods and characterized using N₂ adsorption–desorption, SEM, XRD, XPS, CO₂-TPD, and XRF techniques. The materials exhibited distinct textural and electronic properties, including variations in surface area, pore structure, and basicity. Plasma-catalytic CO₂ dissociation experiments were conducted in a dielectric barrier discharge reactor at near-room temperature. Among the synthesized catalysts, Ce(mp)-4 demonstrated the highest CO₂ conversion of 32.3% at a 5 kV input voltage and superior energy efficiency, which can be attributed to its meso-macroporous structure that promotes microdischarge formation and enhances CO₂ adsorption–desorption dynamics. CO was the only product obtained, with near-100% selectivity. Catalyst stability testing showed no deactivation while spent catalyst characterization indicated carbon-containing species. The findings in this study highlight the critical role of tailored pore structure and basic-site distribution in optimizing plasma-catalytic CO₂ dissociation performance, offering a promising strategy for energy-efficient CO₂ utilization. Full article