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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7

Impact of Biofuel Blending on Hydrocarbon Speciation and Particulate Matter from a Medium-Duty Multimode Combustion Strategy

The U.S. Department of Energy’s Co-Optima initiative simultaneous focused on diversifying fuel sources, improving efficiency, and reducing emissions through using novel combustion strategies and sustainable fuel blends. For medium-duty/heavy-duty diesel engines, research in this area has led to the development of a multimode strategy that uses premixed charge compression ignition (PCCI) at low loads and conventional diesel combustion (CDC) at mid–high loads. The aim of this study was to understand how emissions were impacted when using PCCI instead of CDC at low loads and switching to an oxygenated biofuel blend. It provides a detailed speciation of the hydrocarbon (HC) and particulate matter (PM) emissions from a multimode medium-duty engine operating at low loads in PCCI and CDC modes and high loads in CDC. The effect of the oxygenated biofuel blend on emissions was studied at all three mode–load conditions using #2 ULSD and a bio-derived fuel (25% hexyl hexanoate (HHN)) blended in #2 ULSD. The PCCI mode effectively decreased NOx, total HC, and PM/PN emissions, with a substantial decrease in larger particles (≥50 nm). A PM/PN reduction was observed at high loads with the 25% HHN fuel. While the total HC emissions were not impacted by fuel type, the detailed HC analysis exposed changes in the HC’s composition.

09 BIOMASS FUELS↗

Experimental study of sprays with isooctane, hexane, ethanol and their binary mixtures under different flash boiling intensities

Here, this work investigated the behaviors of single-component and multi-component sprays under different flash boiling intensities. Isooctane, hexane, ethanol, isooctane-hexane, and isooctane-ethanol mixtures were used as test fuels. The pressure ratio of the ambient pressure over saturation pressure (R p ) was used as the indicator of the superheated degree. Macroscopic characteristics of the sprays under 10 different R p (1.1 to 0.14) were investigated using Diffused Backlight Imaging (DBI). Droplet size, which revealed the spray microscopic characteristics, was also investigated using Phase Doppler Anemometry (PDA). The results showed that ambient pressure reduction led to higher flash boiling intensity, significant spray morphology changes, and smaller droplet size, regardless of the fuel type and blend ratios. Spray collapse was observed for all sprays once R p dropped below 0.3. Spray collapse dramatically increased the liquid penetration length, expanded the near-field spray angle, and reduced the far-field angle for sprays with all the fuels. Fuel properties, such as the latent heat of vaporization, had significant impacts on droplet size distributions, thus altering the liquid penetration length and spray angles. Under similar R p , sprays with high ethanol content generally had larger droplet sizes compared with other fuel sprays due to the high latent heat of vaporization. The larger droplets caused the high ethanol content sprays to be more resistant to the plume trajectory change, resulting in a smaller far-field spray angle variations with changing R p . At R p of 0.28, sprays with the similar latent heat of vaporization have similar droplet sizes, and droplet sizes at different radial locations were also similar to each other.

42 ENGINEERING↗

Mechanistic verification of empirical UO 2 fuel fracture models

Standard UO 2 fuel pellets used in light-water reactors fracture during irradiation due to the large thermal gradient in the radial direction. Over the decades, numerous researchers have explored fuel cracking from experimental and modeling points of view. To date, there have been both empirical and mechanistic approaches to predict the number of fragments that form in UO 2 . The empirical models only consider maximum power and burnup as inputs. Existing mechanistic approaches for normal operation have not accounted for irradiation effects. Here, this work employs a mechanistic fuel cracking model using the extended finite element method to explore radial crack formation while including a sensitivity analysis that accounts for the randomization of tensile strength within the fuel, the strength randomization criteria (uniform or volume-weighted Weibull), power ramping rates, computational mesh density, maximum power level, and irradiation (burnup) effects. The results indicate that the uncertainty in this mechanistic modeling approach envelopes the predicted values from three different empirical correlations in almost all cases. This means that, for computationally intensive analyses involving UO 2 fragmentation, the empirical correlations can be used. However, since the mechanistic calculations bound those of the empirical correlations, there is confidence in the applicability of the mechanistic approach developed in this work to generate a correlation for fuel types where limited data exists (e.g., doped-UO 2 , U 3 Si 2 ).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Historical and Future Global Irrigation Energy Consumption by Fuel and Region

Irrigation energy use is a significant component of agricultural production costs, contributing directly to the energy and emissions intensity of crop production and ultimately to food prices. Understanding the existing structure of irrigation energy consumption help achieve food-energy-water security and environmental goals. We present a comprehensive global data set detailing country-level irrigation energy consumption, emphasizing the comparative use of electric, diesel, and emerging solar pumps. To our knowledge, no such data set exists. We draw from a literature review to develop a logistic transformed regression model to estimate the shares of fuel sources for irrigation across countries over historical years to construct a global data set of country-level irrigation energy consumption by multiple fuel sources. Additionally, we compare our estimates of irrigation energy use with agricultural energy use as reported by the International Energy Agency and other external sources. We then use this data to project future irrigation energy use with the Global Change Analysis Model, which is a multisector dynamics model, to showcase the usage of this data set. Projections under the reference scenario show a global shift in fuel types for irrigation pumping, while patterns vary across regions, with India and Pakistan leading in solar-powered irrigation growth and countries like the USA and China continuing to rely primarily on grid electricity. This data set provides a resource to understand the role of irrigation fuel choices within the broader energy sector, as well as the connected agricultural, land use, and water sectors under alternative future scenarios, enabling informed decision making toward efficient agricultural practices.

Global Change Analysis Model (GCAM)↗

Qualification and Quantification of Porosity at the Top of the Fuel Pins in Metallic Fuels Using Image Processing

Approximately 130,000 metal fuel pins were irradiated in the Experimental Breeder Reactor II (EBR-II) during its 30 years of operation to develop and characterize existing and prospective fuels. For many of the metal fuel irradiation experiments, neutron radiography imaging was performed to characterize fuel behavior, such as fuel axial expansion. While several fuel expansion results obtained from neutron radiography imaging have been published, the analysis of neutron radiography for the purpose of describing statistical properties of porous matter formed on top of the fuel pins, also referred to as fluff in previous publications, is significantly less represented in the literature with just a single paper so far. This study aims to validate and augment results reported in previous publications using automated image processing. The paper describes the statistical properties of the porous matter in terms of nine parameters derived from radiography images and correlates those parameters with such fuel properties as composition, expansion, temperature, and burnup. The reported results are based on 1097 fuel pins of eight different fuel compositions. For three major fuel types, U-10Zr, U-8Pu-10Zr, and U-19Pu-10Zr, a clear negative correlation is found between the Pu content and five parameters describing the amount of porous matter generated. The parameters describing granularity properties, however, showed either negative correlation or nonlinear dependency from fuel composition. The parameters describing the amount showed a positive correlation with fuel axial expansion, while granularity parameters showed a negative correlation with axial expansion. The dependency on cladding temperature was found to be weak. A positive correlation is demonstrated for volume parameters and fuel burnup. In general, reported results confirm and validate findings published in previous studies using a much larger number of pins and automated processing techniques, which easily lend themselves to reproducibility, thus avoiding subjective bias.

36 MATERIALS SCIENCE↗

Uncertainty analysis for VERA problem 2 using the cell-code Condor v2.8.05

Condor is a cell-level neutronic calculation code that applies multi-group collision probabilities with heterogeneous response coupling method within generic geometry configurations. Under the Condor's code continuous development, the incorporation of up-to-date methodologies and state-of-the-art practices in reactor analysis represents a driving force. In this work, the capabilities of Condor v2.8.05 to develop an uncertainty analysis for realistic PWR-kind fuel assemblies are studied. The Total Monte Carlo approach is applied to quantify the impact of fabrication tolerances in the code's results for reactivity and power distributions, by means of randomly sampled input values using the VERA problem 2 as basis. The VERA problem 2 proposes a series of Westinghouse 2D 17 x 17-type fuel lattices, to be calculated reflected at beginning-of-life without Xe. The configurations correspond to a modern PWR. Selected neutronic parameters from Condor runs are thus analyzed in terms of the observed spread as well as the obtained distributions for the randomly perturbed cases, showing the capability of the code to handle the required input data, as well as its ability to provide valuable insights regarding uncertainty quantification.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Core Design Optimization of the Westinghouse Lead Fast Reactor

Westinghouse is pursuing an advanced Nuclear Power Plant design based on Lead Fast Reactor (LFR) technology for global commercialization. To achieve an optimal combination of key attributes, such as safety, sustainability, and economic competitiveness, Westinghouse and ANL partnered in developing and applying a formalized core design optimization strategy. An LFR analysis workflow was developed to automate a suite of reactor physics, fuels performance, safety, and economics simulations on a selected LFR concept. The workflow streamlines analysis of a wide range of LFR designs with different dimensions and fuel types to assess their viability and economic performance, significantly reducing human processing time and risks of processing errors. The LFR optimization exercise was defined, resulting in selection of the design constraints (geometric, neutronics, thermo-mechanical, safety, thermal-hydraulics, and economics) and performance metrics researched (minimization of both the fuels LCOE and the first core inventory cost). A total of 14 varied design parameters were considered, including assembly dimensions, coolant temperature, and enrichment distribution throughout the core. The LFR analysis workflow was connected to DAKOTA for sensitivity and optimization analyses. Due to the extremely large size of the potential LFR optimization solution space relative to the computing time required to characterize one LFR solution, a multi-stage optimization approach was proposed to breakdown the problem into several stages with more reasonable sizes. This optimization approach enabled finding various viable core solutions with different cost tradeoffs that were considered by Westinghouse and justify selection of a smaller core with multi-batch 2-year cycle length.

Stauff, Nicolas E.↗

Advanced Light-Duty Spark Ignition Engine Research: Co-Optimization of Fuels and Engines and Partnership to Advance Combustion Engines (FY2020 Annual Progress Report)

This report covers recent progress on research tasks that support both the Co-Optimization of Fuels and Engines (Co-Optima) initiative and the Partnership to Advance Combustion Engines (PACE) consortium. The Co-Optima tasks further the science-base needed by industry stakeholders to co-evolve the next generation of highly efficient direct injection spark ignition (DISI) engines and new gasoline-type fuels. The research emphasis is on fuel effects on multimode spark ignition (SI) engine operation, which uses traditional non-dilute stoichiometric operation for peak load and power but reverts to lean operation at lower loads to provide higher fuel economy. This work focuses on determining desirable fuel specifications in terms of well-established metrics like research octane number (RON) and motor octane number, but it also involves the assessment of new fuel metrics, including fuel sooting propensity and phi-sensitivity. The PACE task supports the development of predictive computational fluid dynamics (CFD) modeling, which promises to unlock new strategies for high-efficiency combustion while minimizing tailpipe emissions. Here, the primary fuel is a regular E10 gasoline (i.e., a regular gasoline blend containing 10% ethanol), and focus is on fuel-spray dynamics and soot emissions. Soot-formation pathways are studied to determine how the pathways change with injection strategies and the thermal state of the engine (i.e., cold-starting vs. fully warmed-up operation). This PACE task also contributed to the development of an optimal E10 gasoline surrogate fuel, as reported in detail elsewhere

33 ADVANCED PROPULSION SYSTEMS↗

Model predictive control of mixing controlled compression ignition operation for low reactivity fuels

Using gasoline or other low reactivity fuels with a pilot injection or port fuel injection in a compression ignition engine has shown great potential in reducing NOx emissions while keeping high thermal efficiency compared to diesel. However, excessive combustion noise is caused by a high maximum pressure rise rate in the cylinder due to the higher fractions of premixed charge of the low-reactivity fuel. This noise can result in structural damage to engine components and as such, combustion noise limits the range of the operating parameters and makes the control of such engines challenging. In this study, a simulation environment was built up in MATLAB/Simulink leveraging a physics-based zero-dimension combustion model to capture the in-cylinder pressure time traces as well as metrics relevant to thermal efficiency and combustion noise. Here, in order to also facilitate the control of emissions, machine learning models were investigated to capture NOx emissions. A kernel-based extreme learning machine (K-ELM) performed best and had a coefficient of correlation (R-squared) of 0.998. The combustion and NOx emission models are valid for not only conventional gasoline fuel but also oxygenated alternative fuel blends at three different pilot injection strategies. In order to track key combustion metrics while keeping noise and emissions within constraints, a model predictive control (MPC) was applied for a compression ignition engine operating with a range of potential fuels and fuel injection strategies. The MPC is validated under different scenarios, including a load step change, fuel type change, and injection strategy change, with proportional–integral (PI) control as the baseline. The simulation results show that MPC reduces about 26% of ringing intensity in the transient process and 17% at the steady state for E30. Generally, MPC can optimize the overall performance through modifying the main injection timing, pilot fuel mass, and exhaust gas recirculation (EGR) fraction.

42 ENGINEERING↗

Dicarboxylic acid emissions from a GDI engine equipped with a catalytic gasoline particulate filter

Dicarboxylic acids play an important role in atmospheric chemistry, yet their emissions from primary sources, such as internal combustion engines, has not been extensively studied. In this paper, KOH impregnated quartz filters were loaded with exhaust gases from a gasoline direct injection (GDI) engine equipped with a catalytic gasoline particulate filter (GPF). All filters were analyzed for carboxylic and dicarboxylic acids using a derivatized gas chromatography-mass spectroscopy method. Exhaust gas was sampled from pre-GPF and post-GPF locations to determine the performance of the GPF regarding acid conversion. Lean and stoichiometric engine modes were considered with non-oxygenated gasoline and 10% splash blended ethanol in gasoline (E10) to examine the impact of stoichiometry and fuel type. Acid emissions represented as much as 0.51% of total unburned hydrocarbon emissions for total monocarboxylic acids and as much as 0.40% for total dicarboxylic acids. Individual acid concentrations were as high as 38 mg/kg-fuel for monocarboxylic acids and as high as 29 mg/kg-fuel for dicarboxylic acids. Overall, the study found that fuel oxygenates had mixed impact on the acid emissions. Engine-out monocarboxylic acids were reduced when using the E10 fuel by approximately 30–45% for the stoichiometric condition and increased marginally for the lean condition. Dicarboxylic acid emissions were generally insensitive to ethanol content. However, the engine condition significantly affected the acid emissions. Lean operation produced a factor of two to an order of magnitude higher emissions rates of both monocarboxylic and dicarboxylic acids than the stoichiometric condition. The catalytic GPF eliminated between 80 and 92% of the acids emitted from the engine, allowing some acids to be emitted into the environment.

42 ENGINEERING↗

Impact of chemical ordering on thermodynamic properties of point defects and Xe substitutional in U-10Mo

The accurate knowledge of defect energetics is critical to understanding the aging and irradiation behavior of U-10Mo nuclear fuel, which is selected as the fuel type for conversion of the United States High-Performance Research Reactors (HPRRs). Furthermore, using hybrid molecular dynamics and Monte Carlo (MDMC) simulation, we studied the impact of chemical ordering on the formation energies of vacancies, interstitials, and the solution energy of the Xe substitutionals. Instead of forming a random solid solution (RSS), substantial short-range-order (SRO) develops in U-10Mo, particularly at low temperatures. Mo atoms are found to repel each other and prefer U-rich local atomic environments within the 1st nearest neighbor (1NN) cutoff. Compared to the case of a RSS, the state with equilibrated Mo ordering shifts the distributions of vacancy and interstitial formation energies due to the dependence of defect energies on the local atomic environment, without a clear effect on Xe solution energy. In the operation temperature range (100–250 °C) of U-Mo fuels, neglecting SRO can lead to an inaccurate estimate of thermal equilibrium point defect concentrations by over an order of magnitude and incorrectly predict the preference among different types of dumbbells, highlighting the critical importance of accounting for the impact of chemical ordering for accurate atomistic calculations of defect properties.

Molecular dynamics and Monte Carlo (MDMC)↗

Analysis and Design for Irradiation of High Power TRISO Fuel Compact Specimens in HFIR

Tristructural isotropic (TRISO) fuel is being proposed for use in several high-temperature advanced reactor concepts because of its structural integrity under high operating temperatures and burnup. One of these advanced reactor concepts is the Kairos Power fluoride salt-cooled high-temperature reactor (KP- FHR) under development by Kairos Power, LLC. Previous TRISO irradiation experiments were focused on qualification for high-temperature gas reactors (HTGRs), which have higher operating temperatures but lower particle powers than the KP-FHR design. To study the performance of TRISO fuel designed for HTGRs under prototypical FHR conditions, a set of experiments was designed using the MiniFuel irradiation vehicle at the Oak Ridge National Laboratory’s (ORNL) High Flux Isotope Reactor (HFIR). The experiments will irradiate 30 TRISO-containing carbon matrix compacts at inner small vertical experiment facilities in HFIR. Each compact will contain 20 TRISO particles (600 particles total) developed for HTGRs, consisting of either 14% enriched uranium dioxide uranium carbide, naturally enriched uranium dioxide, uranium carbide, or 9.6% enriched uranium dioxide fuel kernels with time- and volume-averaged silicon carbide layer temperatures between 500 and 900°C. This report summarizes the vehicle designs that have been developed, as well as the neutronic and thermal analyses completed for these irradiation experiments. These analyses show that MiniFuel compact irradiation is a versatile experiment that can be used to study a range of TRISO particle powers and fuel types while providing reasonable separation of burnup and temperature effects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Microreactor Transportation Emergency Planning Challenges

This report discusses microreactor transportation emergency planning and response challenges. The emphasis of the report is on transporting a microreactor containing irradiated fuel by highway and rail. The report first discusses microreactors in general, including microreactor fuel types and the use of hazardous material in microreactor designs. The report presents a microreactor concept of operations for transport highway, rail, and vessel and presents several transportation regulatory challenges associated with microreactors. Updates contained in this report include the transportation implications of revising the uranium lung absorption category for tri-structural isotropic (TRISO) particle fuel, discussion of exercises and drills including the 2024 Naval Spent Nuclear Fuel Transportation Accident Demonstration with the Shoshone-Bannock Tribes and the State of Idaho, and Tribal and State perspectives on microreactor transportation emergency response planning. Additional microreactor transportation external engagement activities conducted during FY2024 are also discussed. The report discusses the implications of the recent East Palestine, Ohio, rail accident for transportation emergency response planning. Included in this update is a discussion of H.R. 8996, the Railroad Safety Enhancement Act of 2024.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Transportation Energy: A Comparison Including and Excluding Upstream Energy

Thirty-eight editions of the Transportation Energy Data Book (Data Book) have been published since the report began in 1976. It was designed as a desk-top reference of statistics and information that characterize transportation activity. The most recent Data Book, edition 38, has 226 tables and 70 figures in the body of the report, with an additional 51 tables in appendices. One of the most-often used tables in the Data Book is referred to by the authors as “the big energy table.” It has transportation energy use in British thermal units (Btu) by mode and fuel type. The data are compiled from about 20 different sources and combined to create a detailed picture of transportation energy use. From the first edition to edition 35 of the Data Book, electricity use in the big energy table was converted from the original kilowatt-hours (kWh) to Btu using the net generation heat rate for fossil fuels. In those days, electricity was used mainly by transit rail. As electricity began to be used in the highway modes with consumer sales of electric vehicles, that process was revisited. Since energy use in the Data Book’s big energy table for all other fuels did not include the upstream energy to create the fuel, it seemed inconsistent to include upstream energy for generation of electricity. Beginning with edition 36, electricity use for the big energy table was converted from kilowatt hours to Btu using the heat content of electricity. Using heat content instead of net generation reduced electricity use data by about two-thirds. Feedback in recent years on the change in process for electricity led to an investigation of the differences in transportation energy use when adding estimates of upstream energy use to all the fuels used in transportation. This report documents the result of that effort.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Design of Temperature Dependent Critical Experiments with SPRF/CX

This paper describes the investigation of temperature-dependent critical experiments using the Seven Percent Critical Experiments (7uPCX) and Burnup Credit Critical Experiments (BUCCX) fuel types within the Sandia Pulsed Reactor Facility/Critical Experiments (SPRF/CX) apparatus at Sandia National Laboratories (Sandia). The goal of these experiments is to test the effect of varying system temperature on the $\kappa$ eff bias of water-moderated systems. Temperatures of 5–95°C were considered in this work. Eighteen representative lattice configurations were analyzed that had variations in the number of fuel rods and water holes, as well as in the array configuration, to achieve a variety of moderation regimes. The configurations were based on those detailed in the LEU-COMP-THERM-078 and LEU- COMP-THERM-079 experiments, both of which were published in the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP Handbook).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Buffer-IPyC separation process in TRISO fuel particles simulated with Bison code

During High Temperature Gas-cooled Reactor (HTGR) operation, tristructural isotropic (TRISO) coated-particle fuel undergoes irradiation-induced changes in morphology and thermomechanical properties. Experimental results from the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program show, among other things, the mechanism of gap formation between the buffer and inner pyrolytic carbon (IPyC) layers, which could be explored further via computational simulations using the Bison code. Two simulation models were developed, the debonding restricted model, where no gap formation between buffer and IPyC layers is permitted, and the debonding enabled model, where the gap between those layers is created. The inputs of the simulated models are based on the irradiation conditions from the AGR-1 experiment. The research included simulations on spherical and aspherical fuel types. Under the specific temperatures and fluences of the AGR-1 irradiation experiment, and the Bison simulations, it was concluded that the most common scenario is a gap formation along the buffer-IPyC interface, while the least possible scenario is the situation where there is no gap formation at the buffer-IPyC junction. The computational results confirmed that the sphericity of the fuel influences the thickness of the gap that occurs at the buffer-IPyC junction, in a way that with increasing aspect ratio the gap thickness increases. The results obtained for spherical and aspherical fuel are nearly identical. Finally, performed simulations match conclusions observed from the AGR-1 experiment, which as such shows that the Bison code is a good computational method for simulating the TRISO fuel. Future simulations will include the validation of performed research and comparison of the results between Bison and PARFUME codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A general predictive methodology for fuel-mixture properties up to supercritical conditions

A predictive thermodynamic model is utilized for the calculation of fuel properties of oxymethylene dimethyl ethers (OME 3–4 ), surrogates for gasoline, diesel and aviation fuel, as well as alcohol blends with gasoline and diesel. The alcohols used for these blends are methanol, ethanol, propanol, butanol and pentanol; their mixing ratio ranges from 10 to 50% by volume. The model is based on the Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) equation of state (EoS) and Vapor Liquid Equilibrium (VLE) calculations at constant temperature, density and composition. The model includes the association term, with the assumption of two association sites (2B scheme), to enable the modeling of alcohols. The pure-component parameters are estimated based on the Group Contribution (GC) method of various sources, as well as a parametrization model specifically designed for the case of OME 3–4 . The results of the computational model for the density, vapor pressure and distillation curves at various conditions, including high-pressure, high-temperature (HPHT), are compared to experimental and computational data available in the literature. In the cases where no measurements are available for the surrogates, experimental data for the corresponding target fuel are used, taking into consideration the inherent deviation in properties between real and surrogate fuel. Overall, the results are in good agreement with the data from the literature, with the average deviation not exceeding 12% for temperature (Kelvin) on the distillation curves, 10% for density and 46% for vapor pressure and the general trend being captured successfully. The use of different pure component parameter estimation techniques can further improve the prediction quality in the cases of OME3–4 and the aviation fuel surrogate, especially for the vapor pressure, leading to an average deviation lower than 18%. These results demonstrate the predictive capabilities of the model, which extend to a wide range of fuel types and pressure/temperature conditions. Through this investigation, the present work aims to establish the limits of applicability of this thermodynamic property prediction methodology.

33 ADVANCED PROPULSION SYSTEMS↗

Fabrication and Characterization of Iron-Based Catalysts for the Dehydrogenation of Fossil Fuels

For a prosperous and sustainable future, hydrogen is an encouraging solution due to its simple transition for industrial decarbonization and synergy for economic development. Paradoxically, current hydrogen production pathways release substantial amount of greenhouse gases into the atmosphere contributing to climate change. To keep up with increasing demand, hydrogen could be produced through microwave-assisted thermocatalytic dehydrogenation of fossil fuels without emitting carbon dioxide. This requires specified catalysts to meet the requirements of hydrogen yield and selectivity. The objective of the present research is to fabricate, characterize, and compare iron-based alumina (FeAlxOy) catalysts produced via solution combustion synthesis and iron-based catalysts on silicon carbide support (Fe/SiC) produced via incipient wetness impregnation. Heat mode, fuel type, and oxidizer mole ratio were varied for FeAlxOy catalysts, and metal loading was varied for Fe/SiC catalysts. Each resultant product was characterized by X-ray diffraction analysis, scanning electron microscopy, laser diffraction particle size analysis, and Brunauer-Emmett-Teller (BET) surface area analysis. Characterization suggests that fabrication of iron-based alumina nanocomposites through solution combustion synthesis in a muffle furnace using citric acid as the fuel yields the most promising catalyst.

Reyes, Victoria Isabel↗