Oxidation Of Carbon Monoxide Research Articles

Cobalt-Containing Oxide Catalysts Obtained by The Sol-Gel Method with Auto-Combustion in The Reaction of Low-Temperature Oxidation of Carbon Monoxide

The reaction of low-temperature oxidation of carbon monoxide is important in the context of air purification and reduction of automotive emissions. Along with the search for active catalytic systems for carbon monoxide oxidation, the development of new energy-saving methods of catalyst synthesis also seems important. Cobalt-iron, cobalt-manganese, cobalt-chromium, cobalt-copper binary and cobalt-manganese-iron, cobalt-copper-iron-containing triple oxide systems for low-temperature oxidation of carbon monoxide into carbon dioxide were synthesized by the sol-gel method with auto-combustion. The samples were analyzed by X-ray diffraction, IR spectral and derivatographic methods of analysis, their specific surface area was measured by the BET method, micro-photographs were taken on a scanning electron microscope. It was established that the resulting binary and ternary cobalt-containing oxide systems are multiphase systems containing ferrites, manganites, and oxides of cobalt, copper, manganese, and iron. The resulting catalysts are active in the low-temperature oxidation of carbon monoxide at 145-180 °C. The activation energy of the CO oxidation reaction on the analyzed oxide systems was revealed by the Arrhenius equation is placed in the range of 17-33 kJ/mol. In the systems, an intensifying effect of the influence of its components on the catalytic activity is observed in the oxide and spinel phases. The Co-Cr=2:1 system, which, along with chromite, also contains cobalt oxide, which is active at a much lower temperature – 145 °C than systems with a Co-Cr=1:1 and 1:2 ratios. A similar dependence was obtained in the Co-Fe=2:1 system, i.e. in a sample that, along with cobalt ferrite, also contains cobalt oxide. On this catalyst, 100% conversion of CO to CO2 occurs at a temperature of 200 °C, and a Co-Fe = 1:2 sample with a stoichiometric ratio of metals, in which the ferritization reaction completely occurs, as experiments have shown, is active only at temperatures above 300 °C. The intensifying effect of the influence of the components on its activity is also observed in three-component systems, in which the complete conversion of CO occurs at a temperature of 145-160 °C. The appearance of various structural defects during short-term combustion of the gel without additional heat treatment, which can potentially be considered as catalytically active centers, on the one hand, and the presence of oxide and spinel phases in the composition of catalysts, which exhibit a mutual reinforcing effect, on the other hand, is demonstrative advantage of this method for the synthesis of active catalysts for low-temperature oxidation of carbon monoxide to dioxide.

High catalytic performance of CuCe/Ti for CO oxidation and the role of TiO2

CuCe/Ti-A and CuCe/Ti-R catalysts were prepared using anatase TiO2 (TiO2-A) and rutile TiO2 (TiO2-R) as supports using the incipient wetness impregnation method for the carbon monoxide (CO) oxidation reaction and were compared with a CuCe-C catalyst prepared using the co-precipitation method. The CuCe/Ti-A catalyst exhibited the highest activity, with complete CO conversion at 90 °C, when the gas hourly space velocity was 24000 ml·g−1·h−1 and the CO concentration was approximately 1% (vol). A series of characterizations of the catalysts revealed that the CuCe/Ti-A catalyst has a larger specific surface area, more Cu+ species and oxygen vacancies, and the Cu species of CuCe/Ti-A catalyst is more readily reduced. In situ FT-IR results indicate that the bicarbonate species generated on the CuCe/Ti-A catalyst have lower thermal stability than the carbonate species on CuCe/Ti-R, and will decompose more readily to form CO2. Therefore, CuCe/Ti-A has excellent catalytic activity for CO oxidation.

Multiphysics Simulation for the Performance of Tubular Solid Oxide Fuel Cells Operated on Coal Syngas

Solid oxide fuel cells (SOFCs) can be operated directly on coal syngas, but the various contaminants in coal syngas affect the performance and durability of the device. In the present study, three-dimensional multiphysics simulations were developed to investigate the performance degradation of tubular SOFCs operated on coal syngas. The numerical model includes charge conservation, species transport within the electrodes and the channels, and heat transfer within the device. These physical processes are coupled by the chemical/electrochemical reactions, which are represented by a Butler-Volmer type formula. Based on the thermodynamic database about impurities interaction with the Ni-YSZ composite anode, the contaminants are assumed to be adsorbed on the anode surface and form secondary phases. These formed phases affect the microstructural properties, electrical conductivity, and the number of active sites available for electrochemical reactions (i.e., hydrogen and carbon monoxide oxidation). During the cell operation, the contaminants diffuse from the fuel channel/anode interface to the anode/electrolyte interface, causing further irreversible degradation. The in-house developed multiphysics simulation is designed to be robust for prediction of interaction between anode materials with different types of contaminants (e.g., PH3, H2S, H2Se, AsH3, and user-defined). With the model parameters calibrated in the previous study, the performance of the tubular SOFCs with different levels/types of contaminants is predicted. The tolerance limits of the SOFC cell on single and multiple contaminants are also predicted with the simulations. Furthermore, the degradation resulted from Ni coarsening and redistribution, are also implemented into the model to mimic the performance of realistic SOFCs operating on coal syngas. The performance degradation investigation in this study provides guidance for experimental testing with syngas exposure, which is eventually beneficial to the cost reduction of the coal syngas clean-up technology.

Physical properties, engine performance, and exhaust emissions of waste fish oil biodiesel/bioethanol/diesel fuel blends

In the current study, the physicochemical, engine performance, and exhaust emission of different ternary fuel blends containing waste fish oil (WFO) biodiesel, bioethanol, and petro-diesel have been investigated. WFO Biodiesel was prepared from waste fish oil via transesterification method. Different physiochemical properties including the kinematic viscosity, density, flash point, pour point, cloud point, and heat value have been measured for different fuel blends and compared with the neat petro-diesel. The performance and exhaust emission of engine have been also studied using different fuel blends using a single-cylinder diesel engine in full load condition at 1800 rpm. It was found that the engine torque, engine power, and thermal efficiency of the ternary fuel blends was reduced by 2.45%, 9.25%, 2.35% averagely in comparison with the neat petro-diesel, respectively. The average break specific fuel consumption was also increased by 10.44% compared to the neat petro-diesel. The emission of carbon monoxide (CO), carbon dioxide (CO2), unburned hydrocarbons (UHC), and nitrogen oxides (NOx) was also measured. It was also found that the utilization of ternary fuel blends results in a considerable reduction in CO and UHC emission by 50.55% and 43.87% on average compared to the neat petro-diesel, respectively. The emission of NOx was also increased by 28.25% on average compared to the neat petro-diesel. It was also found that the NOx emission can be adjusted by tuning the WFO biodiesel and bioethanol contents of the ternary fuel blends.

(Invited) Designing Transport into Multifunctional Materials for Energy & Power

Designing electrodes and catalytic platforms as architectures in which the entire volume of the porous “reactor” is wired continuously in three dimensions for electron, ion, and molecular transport expands the reactive electrochemical and catalytic turf beyond the limited footprint imposed by a two-dimensional cross-section or a single three-phase boundary per supported nanoparticle. Amplifying the electron/ion/molecularly wired interfacial area by hundreds of square centimeters per cross-sectional square centimeter converts redox reactions that lose morphological control at high local current density into more uniformly reactive events that experience low local current density. Similar distributed arrangement of the reacting species in architected catalytic platforms imparts resilience of the supported catalyst. Aperiodic architectures such as foams and sponges effectively distribute the available reactive, electron/ion/molecularly wired interfaces while maintaining a co-continuous mapping of void and solid to facilitate ingress/egress of reactants and products. Examples from our work with electrode architectures show the power of controlling energy-storage reactions locally by distributing them within electron-wired high-surface interiors. The arrangement ensures that per area current remains low throughout the volume of the electrode, yet the electrified area sums to provide device-relevant current. The intimate interfacial contact we achieve for copper nanoparticles supported on ceria aerogels yields active, selective, and stable architected catalysts for preferential oxidation of carbon monoxide in hydrogen feedstreams.

Effects of different biofuels and their mixtures with diesel fuel on diesel engine performance and exhausts

In this study, a compression ignition engine that ran on recycled used cooking oil (RUCO), Jatropha curcas (JC), Pongamia Pinnata (PP), and petroleum diesel fuel (PDF) was investigated for its energy, performance, and exhaust emissions. The 20 % by volume RUCO, JC, and PP biofuel mix with PDF is taken. According to the American Society for Testing and Material (ASTM) standard, the blend qualities are evaluated. Viscosity, density, flash point, and heating value have all been tested for the 20 % blend. The outcome indicated that for a 20 % mix, the viscosity, density and flash point were all greater than in the PDF but heat value lower. Because studies have demonstrated that diesel engines can operate on 20 % replacement without any modifications, this study focused on 20 % blend. The engine was tested with loads (Ls) ranging from 0 % to 100 % of its entire capacity while the compression ratios (CRs) was varied. The experimental result demonstrated that the thermal efficiency, as measured by the PDF, was much greater than that of the DRUCO20, DJC20, and DPP20 blends. After the addition of RUCO, JC, and PP to PDF, the temperature of the exhaust gases reduced, and the engine used more gasoline as a result. It was discovered that an engine emissions of hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx) were lower than those of PDF. Even though it produced a greater amount of carbon dioxide (CO2) emissions, the DRUCO20 was superior to both the DCJ20 and the DPP20.

Comparative Study of the Atmospheric Gas Composition Detection Capabilities of FY-3D/HIRAS-I and FY-3E/HIRAS-II Based on Information Capacity

Fengyun-3E (FY-3E)/Hyperspectral Infrared Atmospheric Sounder-II (HIRAS-II) is an extension Fengyun-3D (FY-3D)/HIRAS-I. It is crucial to fully explore and analyze the detection capabilities of these two instruments for atmospheric gas composition. Based on the observed spectral data from the infrared hyperspectral detection instruments FY-3D/HIRAS-I and FY-3E/HIRAS-II, simulated radiance data and Jacobian matrices are obtained using the Rapid Radiative Transfer Model RTTOV (Radiative Transfer for TOVS (TIROS Operational Vertical Sounder)). By perturbing temperature (T), surface temperature (Tsurf), water vapor (H2O), ozone (O3), carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), and nitrous oxide (N2O), the brightness temperature differences before and after the perturbations are calculated to analyze the sensitivity of temperature and various atmospheric gas components. The Improved Optimal Sensitivity Profile (OSP) algorithm is used to select the channels for atmospheric gas retrieval. The observation error covariance and background error covariance matrices are calculated, and then the information capacity is calculated, specifically the degrees of freedom for signal(DFS) and the entropy reduction (ER). Based on this, a comparative analysis is conducted on the information capacity of atmospheric water vapor and ozone components contained in the hyperspectral detection data from HIRAS-I and HIRAS-II instruments, respectively, to explore the retrieval capabilities of the two instruments for atmospheric gas components. We selected clear-sky data from the African oceanic region and the Chinese Yangtze River Delta terrestrial region for quantitative analysis of the information capacity of HIRAS-I and HIRAS-II. The results show that FY-3D/HIRAS-I and FY-3E/HIRAS-II exhibit different sensitivities to atmospheric gas components. In different experimental regions, temperature and water vapor show the most dramatic sensitivity changes, followed by ozone, methane, and nitrous oxide, while carbon monoxide and carbon dioxide exhibit the lowest variability. Regarding channel selection, HIRAS-II identifies more gas channels compared to HIRAS-I. The experiments concluded that HIRAS-II has a significantly higher information capacity than HIRAS-I, and the information capacity of atmospheric gas components varies across different experimental regions. Water vapor and ozone exhibit the highest information capacity, followed by nitrous oxide and methane, while carbon monoxide and carbon dioxide demonstrate the lowest capacity. The H2O ER (DFS) contained in FY-3E/HIRAS-II is 1.51 (0.35) higher than that in FY-3D/HIRAS-I, the O3 ER (DFS) in FY-3E/HIRAS-II is 1.51 (0.36) higher than that in FY-3D/HIRAS-I, while the N2O ER (DFS) in FY-3E/HIRAS-II is 0.17 (0.19) higher and the CH4 ER (DFS) is 0.07 (0.04) higher than that in FY-3D/HIRAS-I.

Experimental investigation and numerical modelling of CO and HCN release during the combustion of flexible polyurethane foam

The combustion of flexible polyurethane foam (FPUF) in fires releases relatively large amounts of carbon monoxide (CO) and hydrogen cyanide (HCN), threatening the lives of those exposed thereto. It is therefore necessary to use computational fluid dynamics method to explore the distribution of CO and HCN in a fire involving the combustion of FPUF. However, the release of CO and HCN varies significantly with the combustion conditions, which makes the numerical modelling challenging. In the present research, the yields of CO and HCN during the combustion of a non-flame-retardant FPUF were determined using a steady-state tube furnace (SSTF) facility, considering the effect of the ventilation condition. Meanwhile, a pyrolysis and combustion model of FPUF was constructed based on the fire dynamics simulator (FDS), and a four-step chemistry model was proposed to deal with the reactions in the gas phase. The experimental results showed that the yields of CO and HCN both increased with the limitation of ventilation, which was more pronounced in under-ventilated conditions. Meanwhile, the numerical simulation applying the four-step chemistry model predicted the variations in the yields of CO and HCN under ventilated conditions. In addition, when the appropriate kinetic parameters were applied to the reactions governing the oxidation of CO and HCN, the comparative results indicated that the global average deviations between the predicted and experimental yields could be reduced to 13.61 % (CO) and 8.19 % (HCN), respectively.

Nb2S2C Monolayers with Transition Metal Atoms Embedded at the S Vacancy Are Promising Single-Atom Catalysts for CO Oxidation.

Single atoms anchored on stable and robust two-dimensional (2D) materials are attractive catalysts for carbon monoxide (CO) oxidation. Here, 3d (Fe-Zn), 4d (Ru-Cd), and 5d (Os-Hg) transition metal-decorated Nb2S2C monolayers were systematically studied as potential single-atom catalysts for low-temperature CO oxidation reactions by performing first-principles calculations. Sulfur vacancies are essential for stabilizing the transition metals anchored on the surface of defective Nb2S2C. After estimating the structure stability, the aggregation trend of the embedded metal atoms, and adsorption strength of reactants and products, Zn-decorated defective Nb2S2C is predicted to be a promising catalyst to facilitate CO oxidation through the Langmuir-Hinshelwood (LH) mechanism with an energy barrier of only 0.25 eV. Our investigation indicates that defective carbosulfides can be promising substrates to generate efficient and low-cost single-atom catalysts for low-temperature CO oxidation.

Production of waste tyre pyrolysis oil as the replacement for fossil fuel for diesel engines with constant hydrogen injection via air intake manifold

The increasing global demand for alternative fuels as a replacement for fossil fuels has sparked a surge in the use of non-fossil fuel sources. While many alternative fuels already offer improved performance characteristics, ongoing research seeks to further enhance their quality. This particular study focuses on elevating fuel quality by introducing hydrogen into waste tire pyrolysis oil. To conduct the investigation, experimental tests were performed using three different fuel combinations: standard diesel, 15% (W15) waste tire pyrolysis oil blends, and 30% (W30) biodiesel blends. Additionally, each of these blends was enriched with 5 L/min of hydrogen gas. The experiments were conducted in a naturally aspirated, direct injection, four-cylinder, inline, four-stroke diesel engine, operating at various speeds of 1000 rpm, 1500 rpm, 2000 rpm, and 2500 rpm. The study assessed the parameters such as torque, power, specific fuel consumption, carbon monoxide, carbon dioxide, and nitrogen oxide emissions. Furthermore, this research explored the viability of utilizing waste tire pyrolysis oil blends with hydrogen as fuel in compression ignition engines without any modifications, as their fuel qualities were observed to be comparable to standard diesel fuel. Encouragingly, the results indicated that the addition of hydrogen to waste tire pyrolysis biodiesel improved the combustion process and led to a reduction in harmful gas emissions. Despite waste tyre pyrolysis oil possessing a lower heating value in comparison to diesel, the findings revealed that this heating value could be effectively enhanced by introducing hydrogen through the engine's inlet manifold. Among the blends tested, W15 emerged as a particularly promising alternative fuel for diesel engines due to its favorable performance and reduced environmental impact, as evidenced by lower carbon monoxide, carbon dioxide, and nitrogen dioxide emissions.

An Investigation of the Effect of Propylene Gas Flame on Emissions and Temperature Distribution of a Preheated Metal Plate

This study investigates the effect of the propylene gas flame on the emissions and temperature distribution of the metal plate during the preheating process. Experimental tests were carried out using a preheating system with a cylindrical chamber for emissions measurement and a metal plate placed near the torch head. Emissions were measured using a gas analyzer, while the temperature distribution of the metal plate was measured using an infrared thermal camera and thermocouples. The findings reveal that the emissions decrease as the equivalence ratio is increased as it approaches a ratio of 1. However, when the appropriate equivalence ratio is reached, NOx emissions will rise and then gradually fall. The peak temperature of propane fuel is higher than that of other fuels because of the concentrated flame. Propane fuel can achieve a peak temperature of 347.65 °C, surpassing both propylene fuel (275.45 °C) and acetylene fuel (335.45 °C). Using a propylene gas flame results in a reduction in emissions of carbon monoxide and nitrogen oxides compared to a propane flame. But, acetylene fuel produces the most NOx emissions, reaching 450.79 ppm for the experimental conditions. Additionally, the temperature distribution of the preheated metal plate was more uniform with the propylene gas flame, indicating improved heat transfer. However, the peak temperature of the metal plate was slightly lower when using the propylene gas flame.

Effective utilization of waste plastic derived fuel in CI engine using multi objective optimization through RSM

This study provides the prediction that plastic pyrolysis oil (PPO) is equivalent to petroleum diesel in CI engines. The four input parameters have been considered to enhance performance and reduced emissions. The input parameters of engine trials, like fuel blend (PPO and diesel), compression ratio, nanoparticle concentration, and injection timing, were studied with the response surface methodology (RSM) using the central composite rotating design (CCRD) matrix. The main goal is to identify the ideal values of input parameters that will provide the highest achievable brake thermal efficiency (BTE), the lowest possible brake-specific fuel consumption (BSFC), and the lowest possible emission like carbon monoxide (CO), unburnt hydrocarbons (HC) and nitrogen oxides (NOx). The optimal engine output responses for BTE, BSFC, in-cylinder pressure, heat release rate (HRR), and ignition delay, respectively. Along witha composite desirability of 0.89 under optimum operating conditions. After the regression analysis, 16.56% PPO blend ratio, 53.53 ppm Al2O3 nanoparticle concentration, 18.06 compression ratio, and 20.95 °bTDC injection timing were received the optimized engine settings. Optimal engine input parameters were validated through actual engine trials and compared with optimized responses and found satisfactory and acceptable errors (less than 5%). The current study establishes vital input parameters providing the best engine performance, combustion characteristics, and lower emissions during engine trials. So current investigation declared PPO with Al2O3 nanoparticles is potential fuel for the CI engine.

Prediction of combustion, performance, and emission parameters of ethanol powered spark ignition engine using ensemble Least Squares boosting machine learning algorithms

This research concentrates on the application of machine learning techniques to predict combustion, performance, and emission parameters in a dual-fuel spark ignition (SI) engine powered by neat gasoline and E20 ethanol dual fuel. The goal is to overcome the limitations posed by repeated engine experiments and nonlinear test results. In order to optimise engine parameters, the research seeks to develop efficient machine learning models with high generalizability and employ an optimisation strategy to determine the optimal engine settings. Input for training and evaluating machine learning algorithms, such as Artificial Neural Networks (ANN), and Ensemble LS Boosting was derived from experimental data from a combustion test engine, which includes Neat gasoline, and Ethanol dual fuel blend E20 at various load conditions. The dataset includes engine combustion, performance, and emission indices such as brake thermal efficiency (BTE), Exhaust Gas Temperature (EGT), Hydrocarbons (HC), Carbon monoxide (CO), Carbon dioxide (CO2), and Nitrogen oxides (NOx), under various operating conditions. Load and brake-specific fuel consumption (BSFC) were training input attributes. Using a comprehensive experimental database of input-output engine parameters, the Artificial Neural Network (ANN) and Ensemble LS Boosting were constructed. The training data points were resampled to generate multiple training datasets for training different models. 50 test samples were used to evaluate the generalisation capability of the machine learning models, while BTE, EGT, CO, CO2, HC and NOx, were the primary parameters subject to prediction. The optimal machine learning method was determined by comparing R-squared (R2) values, root mean square error (RMSE), mean square error (MSE), and mean absolute error (MAE). Using multiple hyperparameter tuning iterations, the agreement between actual and predicted values for diverse Ensemble LS Boost algorithms was evaluated. The Ensemble LS Boost model exhibits the maximum level of agreement between predicted and experimental engine parameters across all datasets when compared to the other ANN models. This finding was corroborated by additional research based on test datasets, specifically the test sample interpolation data, which measures generalisation ability. The study also focuses on developing and applying two unique, interactive Simulink models for the Spark Ignition (SI) engine that are tailored for Neat Gasoline and Ethanol E20 test fuels under all loads. The key component of the model-based development technique in MATLAB and Simulink was the incorporation of sophisticated machine learning algorithms, i.e., Ensemble Least-Squares (LS) Boosting, to the model-based development workflow which produced reliable results. Implementing an Ensemble LS Boost machine learning framework is therefore highly recommended as an efficient method for predicting and optimising the combustion, performance, and emission characteristics of dual-fuel gasoline engines utilising Ethanol-based dual-fuel blends.

Nanocatalyst for carbon monoxide oxidation based on palladium(II), copper(II) salts, and carbon fiber material

The phase composition, textural, and activity of catalysts for the carbon monoxide low-temperature oxidation based on two series of non-woven carbon fiber material samples CFM-I and CFM-II, and K2PdCl4, Cu(NO3)2, KBr basic components were studied in this work. Catalysts and CFMs were studied by XRD, nitrogen and water vapor adsorption/desorption, and atomic absorption spectrophotometry methods. It has been found that the basic components K2PdCl4 and Cu(NO3)2 deposited on a microporous carbon surface undergo changes and form an X-ray amorphous Pd0 phase and a paratacamite—Cu2(OH)3Cl nanocrystalline phase. The catalysts were tested at carbon monoxide initial concentrations of 300 mg/m3 with an effective contact time of the catalyst with the gas–air mixture from 0.12 to 0.50 s. Catalysts provide air purification from CO to concentrations below MPCCO (20 mg/m3) and can be used in respiratory devices. The maximum catalytic activity is observed when the content of palladium in the catalyst is 1.70⋅10−4 mol/g and the content of copper (ІІ) is 4.68⋅10−4 mol/g.

A Novel Model for Transforming Harmful Vehicle Exhaust Emissions into Useful Products

This paper puts forward a vehicle exhaust emission treatment model based on the oxidation of pollutant gases and then reaction with calcium oxide. Our model can remove major pollutants, that is carbon dioxide, carbon monoxide and nitrogen oxide, from car exhaust by converting them into calcium carbonate and calcium nitrate respectively. This model provides a simple, easy and effective measure to control the vehicle exhaust emissions.

Promotional effect of Mn on Pt/Al2O3 catalysts in HC, CO, and NOx oxidation for controlling diesel emission

Emissions from diesel engines, including hydrocarbons (HCs), carbon monoxide (CO), and nitric oxide (NO), cause serious environmental and human health problems. Diesel oxidation catalysts (DOCs) are drawing attention for their ability to eliminate such harmful exhausts effectively. Here, we report significantly improved activities of Pt-based catalysts, which are widely used as DOCs, in the oxidation of HC, CO, and NOx after Mn addition. Mn-doped Pt/Al2O3 showed significantly lower light-off temperatures in the oxidation of HC, CO, and NOx than those of the unmodified Pt/Al2O3 catalysts, by as much as 30 °C. The size of Pt particles was reduced from 71 nm to 33 nm after Mn addition, as evidenced by X-ray diffraction analysis and transmittance electron microscopy. Additionally, the interaction between CO and Pt on Mn-doped catalysts was weakened, and the CO adsorbed on Pt was readily oxidized even at room temperature, as confirmed by diffuse reflectance infrared Fourier-transform spectroscopy and CO temperature-programmed desorption experiments. The results of this study provide insights towards the improvement of the activity of Pt-based DOCs used for HC, CO, and NOx oxidation, by enhancing the fundamental understanding of the Pt nature promoted with Mn.

Self-Standing Pd-Based Nanostructures for Electrocatalytic CO Oxidation: Do Nanocatalyst Shape and Electrolyte pH Matter?

Tailoring the shape of Pd nanocrystals is one of the main ways to enhance catalytic activity; however, the effect of shapes and electrolyte pH on carbon monoxide oxidation (COOxid) is not highlighted enough. This article presents the controlled fabrication of Pd nanocrystals in different morphologies, including Pd nanosponge via the ice-cooling reduction of the Pd precursor using NaBH4 solution and Pd nanocube via ascorbic acid reduction at 25 °C. Both Pd nanosponge and Pd nanocube are self-standing and have a high surface area, uniform distribution, and clean surface. The electrocatalytic CO oxidation activity and durability of the Pd nanocube were significantly superior to those of Pd nanosponge and commercial Pd/C in only acidic (H2SO4) medium and the best among the three media, due to the multiple adsorption active sites, uniform distribution, and high surface area of the nanocube structure. However, Pd nanosponge had enhanced COOxid activity and stability in both alkaline (KOH) and neutral (NaHCO3) electrolytes than Pd nanocube and Pd/C, attributable to its low Pd-Pd interatomic distance and cleaner surface. The self-standing Pd nanosponge and Pd nanocube were more active than Pd/C in all electrolytes. Mainly, the COOxid current density of Pd nanocube in H2SO4 (5.92 mA/cm2) was nearly 3.6 times that in KOH (1.63 mA/cm2) and 10.3 times that in NaHCO3 (0.578 mA/cm2), owing to the greater charge mobility and better electrolyte-electrode interaction, as evidenced by electrochemical impedance spectroscopy (EIS) analysis. Notably, this study confirmed that acidic electrolytes and Pd nanocube are highly preferred for promoting COOxid and may open new avenues for precluding CO poisoning in alcohol-based fuel cells.

Synthesis and Properties of a Carbon Monoxide Oxidation Catalyst Based on Titanium Dioxide and Platinum Nanoparticles

Synthesis and Properties of a Carbon Monoxide Oxidation Catalyst Based on Titanium Dioxide and Platinum Nanoparticles

An experimental study on aging effects of the air–fuel ratio swing on modern gasoline three-way catalysts

Today’s governmental legislations require region specific emission standards for passenger vehicles. Continuously increasing legal requirements demand the development of more complex exhaust gas after treatment systems to further reduce harmful gases like carbon monoxide (CO), hydrocarbons (HC) and nitrogen oxides (NOx). Due to specific load profiles and other boundary conditions, the efficiency of the aftertreatment system declines over lifecycle, so that the emissions might increase. Consequently, the durability of the system becomes a critical design parameter with upcoming legislation demanding emissions stability over the vehicle life cycle. Within this publication, catalyst aging effects due to air–fuel ratio (AFR) swing are analyzed experimentally. To create catalyst aging conditions, a modern eight-cylinder turbocharged engine was modified and specific aging cycles with a variation of AFR swing amplitude and frequency were conducted. Light-off curves were used to depict the negative impact of the AFR swing on the aging catalyst systems. A higher swing frequency resulted in an increased temperature amplitude within the entrance area of the catalyst, while an elevated amplitude lead to more exothermic heat release and stronger aging over the complete catalyst, as visualized via conversion maps. A theoretical calculation of thermal loads by Arrhenius equation supports the results and indicates the direction of supplementary experimental approaches.

Unravelling the Alloy Effect of Porous Binary Pd-Based Nanostructures on Electrocatalytic Oxidation of Carbon Monoxide in Different Electrolytes

Unravelling the Alloy Effect of Porous Binary Pd-Based Nanostructures on Electrocatalytic Oxidation of Carbon Monoxide in Different Electrolytes