Topics in Catalysis最新文献

The growing need for clean and sustainable energy has an increased interest in dimethyl ether (DME) as a promising alternative fuel, due to its high cetane number, soot-free combustion, and low emissions. This study investigates Fe_1−xM_xWO₄ (M = Cu²⁺ or Ni²⁺) nanocomposites as solid acid catalysts for methanol dehydration to DME, a clean fuel with high cetane number and low emissions. Catalysts (x = 0.1–0.9) were synthesized via co-precipitation and characterized using XRD, FTIR, XPS, pyridine-TPD, and nitrogen sorption. Catalytic performance was evaluated in a fixed-bed reactor, assessing substitution ratios, calcination temperatures, and promoter effects. Fe_0.3Cu_0.7WO₄ with 15 wt% Zr⁴⁺ achieved 89% methanol conversion at 350 °C, while Fe_0.7Ni_0.3WO₄ with 10 wt% SO₄²⁻ reached 91% conversion at 300 °C, both with high DME selectivity. Enhanced acidity and surface area from doping make these catalysts promising for sustainable DME production. Moreover, the most active catalysts showed excellent reusability over four regeneration cycles without significant loss of activity or selectivity. Moreover, the use of SO₄²⁻ and Zr⁴⁺ as dopants offers a scalable and relatively environmentally friendly approach that supports potential industrial applications.

Nickel-promoted molybdenum carbide (Mo₂C) catalysts supported on γ-Al₂O₃ were synthesized via incipient wetness impregnation and evaluated for dry methane reforming (DMR). Comprehensive physicochemical characterizations including XRD, SEM-EDS, H₂-TPR, XPS, TPSR, and TG-DSC were conducted to elucidate structure-performance relationships. Non-promoted Mo₂C exhibited poor catalytic stability due to oxidation during DMR. The incorporation of nickel significantly enhanced catalytic activity and stability by promoting the in-situ re-carburization of oxidized Mo species and facilitating methane activation. The optimized Ni/Mo molar ratio of 1:1 led to the formation of a stable Ni-Mo synergistic phase, which exhibited superior resistance to sintering and deactivation.

This study employed machine learning (ML) to predict nitrogen dioxide (NO₂) pollution in Marylebone Road, London a high-traffic urban corridor using historical data from 2015 to 2022 to forecast concentrations for the period January 2023 to January 2025. Four ML models were developed and evaluated: Linear Regression, Random Forest, LightGBM, and an Ensemble Stacking model. These models incorporated meteorological and pollutant data and were assessed using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R-squared (R²). The Ensemble Stacking model outperformed the others, achieving an R² of 0.9723, MAE of 3.91 µg/m³, and RMSE of 6.25 µg/m³. In comparison, the Linear Regression model showed the lowest performance (R² = 0.8307, MAE = 11.55, RMSE = 15.45), while Random Forest (R² = 0.9232) and LightGBM (R² = 0.9719) demonstrated intermediate accuracy. The best-performing ensemble model was further used to simulate NO₂ trends with and without titanium dioxide (TiO₂) catalyst intervention, assuming a 28% NO₂ reduction. Temporal analysis revealed that NO, NO₂, and NOₓ concentrations peaked during colder months (November–January) and weekdays. Correlation analysis showed a weak negative relationship between NO₂ and ozone (O₃) (R² = 0.26), moderate positive correlations with black carbon (BC) (R² = 0.597) and sulfur dioxide (SO₂) (R² = 0.654), and a very weak positive correlation with particulate matter (PM2.5) (R² = 0.143). The study concludes that ensemble stacked ML models are effective for predicting NO₂ concentrations and that TiO₂ nanocatalyst interventions hold promise for reducing NO₂, BC, and SO₂ levels in urban environments.

This work investigates the stability and electron transport kinetics of lindane, a persistent organic contaminant, as it adsorbs onto graphene. The most stable configuration comprises strong interactions between the chlorine atoms of lindane and the (Pi )-electron-rich surface of graphene, as seen by a dominant Boltzmann population (X(_{i})=0.8157 at 298.15 K). By looking at overall reactivity measures like electronegativity, hardness, and electrophilicity, along with specific measures like the Fukui function, this study seeks to understand the interactions at the molecular level that influence how sensors work. dipole moment ((mu )=2.02 D). Fukui function analysis shows that these interactions lead to a significant redistribution of charge, with chlorine atoms acting as the main redox-active sites. The results highlight graphene’s capacity to stabilise adsorbed molecules and promote electron transport, increasing its potential for use in environmental remediation and pollution sensing. Important information about the design of graphene-based sensors for the efficient detection of persistent organic pollutants is provided by the study.

Amides, which contain both oxygen and nitrogen, are present in many potential feedstocks for renewable fuels. There is a consequent need to study the hydrodenitrogenation (HDN) and hydrodeoxygenation (HDO) of amides. This work studies the HDN and HDO of hexadecanamide with sulfided NiMo/(gamma )-(hbox {Al}_2hbox {O}_3) and NiMo/(hbox {TiO}_2) catalysts. The experiments are conducted in a batch reactor, with decalin as a solvent. Hexadecanamide is found to easily undergo either dehydration into hexadecanenitrile or deammonization into palmitic acid. Hydrotreating of hexadecanamide consequently occurs either through an initial HDO step (dehydration) into hexadecanonitrile, followed by reduction and HDN of the resulting hexadecylamine, or through an initial HDN step (deammonization) followed by HDO of the resulting palmitic acid. On both NiMo/(gamma )-(hbox {Al}_2hbox {O}_3) and NiMo/(hbox {TiO}_2), HDN of the amide is slower than HDO. The secondary amine, dihexadecylamine, is a major intermediate, formed through condensation reactions between hexadecylamine and palmitic acid or by the self-condensation of hexadecylamine. Thus, after the initial dehydration or deammonization step, hydrotreating of the primary amide follows the pathways associated with the HDN of primary amines and the HDO of primary carboxylic acids. NiMo/(hbox {TiO}_2) is a more active amide hydrotreating catalyst than NiMo/(gamma )-(hbox {Al}_2hbox {O}_3). This is attributed to (hbox {TiO}_2) catalyzing the initial dehydration (HDO) step, as well as to more complete sulfidation of Mo and the better incorporation of the Ni promoter in the (hbox {MoS}_2) phase on (hbox {TiO}_2).

Both the Sustainable Development Goal and the European Green Deal prioritized a waste-free, climate-neutral future. But due to human activities and climate change, the environment is getting polluted day by day. The mining activities release numerous toxic heavy metal ions into the surrounding area. Their presence in the air, soil, and water affects human beings as well as plants and animals. This suggests the utilization of various innovative approaches for environmental health. Graphene as a two-dimensional, environmentally friendly nanomaterial has shown its versatile application in several fields owing to its exceptional physical, chemical, and mechanical properties. This comprehensive review summarized popular contaminants found near coal mines, including Eu, Cd, As, and Hg, as well as air pollutants such as SO₂, CO₂, and others, and how graphene-based nanocomposites can be utilized to reduce them. The review discussed the basic properties of two-dimensional graphene sheets and their composites, as well as why they are being considered as possible alternative materials for the detection and removal of coal mining pollutants. Researchers have found that graphene-based nanocomposites are better in the adsorption and removal of these contaminants because they have better electrical, optical, and surface properties. The large surface area of graphene and its ability to functionalize diverse materials position it at the forefront in pollution management. The review further analyzes the current status, challenges in the removal of these contaminants, and future prospects.

Ni supported on SiO₂ with various morphologies such as nanocubes, nanorods, nanospheres and dendritic mesoporous silica (DMS) are prepared and employed for zero emission hydrogen production (Turquoise hydrogen). The fresh calcined catalysts possessed NiO (200) planes predominantly while in the reduced samples Ni⁰ (111) planes are majorly exposed irrespective of SiO₂ morphology. Among these the Ni-DMS demonstrated a higher rate of H₂ production while, the Ni/nanorods showed inferior activity. Formation of Ni silicate was found only in case of Ni/nanorods. Ionic Ni reduced below 600 °C seems to exhibit better CH₄ cracking rate, as was depicted from H₂-TPR results. Variation in graphitic carbon was found due to difference in SiO₂ morphology as well as the reducibility of nickel interacted with SiO₂.

Using an annular structured reactor the oxidation of CO and H₂ over silver was studied at temperatures employed during the industrial partial oxidation of methanol to formaldehyde. Silver tubes were systematically exposed to different atmospheres and imaged at regular intervals using scanning electron microscopy to gain insight into both reaction activity and catalyst restructuring. The reactant feed has a profound effect on restructuring, and a “dynamic steady-state morphology” is identified for each gas mixture. The exposed catalysts show clear signs of stepped surface faceting, grain growth and formation of small pinholes (< 1 μm). H₂ oxidation conditions promote the formation of numerous angular surface cavities (> 3 μm). Addition of steam to the feed, however, inhibits the formation of stepped facets. Silver is active towards both CO and H₂ oxidation, and co-feeding both reactants has a synergistic effect. Addition of steam leaves the H₂ oxidation activity unaffected but completely inhibits the formation of CO₂ via CO oxidation. The results clearly show that the effects of H₂O formation are very different from those of H₂O addition and that CO is not a precursor towards CO₂ in the silver-catalysed methanol to formaldehyde system, in which steam is usually co-fed. The systematic approach taken here allows the effects of temperature and gas composition to be decoupled, and the results can be used in future studies to ascribe restructuring features to various reactants.

Calcium Zirconium Titanium Oxide Multiwalled Carbon nanotubes nanocomposites was synthesized by solution combustion method. A carbon paste electrode was used to create a Voltammetric resolution for Copper Zirconium Titanium Oxide Multiwalled Carbon nanotubes nanocomposites. The electrochemical oxidation was carried out in 0.2 M Phosphate buffer solution at scan rate 0.05Vs⁻¹. Electrochemical investigation of L-Dopa, Uric Acid and Tyrosine was studied by scan rate varation by this it has confirmed all analytes shows diffusion controlled process, by varying the concentration of the analytes limit of detection and quantification are obtained and by pH studies number of protons and electron are obtained. Simultaneous study was carried out for L-Dopa, Uric Acid and L-Tyrosine. The CZTO MWCNT nanocomposites MCPE was used for investigation of UA in real sample.