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Defense Waste Processing Facility Nitric-Glycolic Flowsheet Chemical Process Cell Chemistry: Part 2

The conversions of nitrite to nitrate, the destruction of glycolate, and the conversion of glycolate to formate and oxalate were modeled for the Nitric-Glycolic flowsheet using data from Chemical Process Cell (CPC) simulant runs conducted by Savannah River National Laboratory (SRNL) from 2011 to 2016. The goal of this work was to develop empirical correlation models to predict these values from measurable variables from the chemical process so that these quantities could be predicted a-priori from the sludge or simulant composition and measurable processing variables. The need for these predictions arises from the need to predict the REDuction/OXidation (REDOX) state of the glass from the Defense Waste Processing Facility (DWPF) melter. This report summarizes the work on these correlations based on the aforementioned data. Previous work on these correlations was documented in a technical report covering data from 2011-2015. This current report supersedes this previous report. Further refinement of the models as additional data are collected is recommended. The glass REDOX depends on the concentrations of nitrate and manganese (oxidants), and of glycolate, formate, oxalate, carbon, and antifoam (reductants) in the melter feed. The waste sludge contains nitrite, nitrate, manganese (Mn), and oxalate. Virtually all of the nitrite is converted to nitrate or NO+NO 2 +N 2 O gases in the CPC. The portion of the nitrite converted to nitrate increases the amount of nitrate in the sludge. The amount of glycolate in the final melter feed depends on the amount of the glycolic acid feed that is destroyed. Similarly, the amounts of formate and oxalate formed during the decomposition of glycolic acid are required. The material balance on carbon was found to not close in most cases. Generally, there was less carbon at the end of testing compared to the inputs. The most uncertain product variable was glycolate, so material balances were performed where the glycolate concentration was adjusted, usually upward, to close the balance. Correlation versus the original, as-measured, data was generally poor, but correlation against the material balance adjusted values was greatly improved. It was also shown that the correlation of the measured REDOX versus the predicted REDOX was much better when the material balance adjusted glycolate values were used. Three data series were primarily used during the regressions of the data; these series were 1) Sludge Batch 9 NG flowsheet simulant runs NG51-62 (SB9-NG); 2) Scaled Runs + Bounding Hydrogen Runs (SR+BH); and 3) Runs GN43-50 and 57 (43-50,57). The glycolate destruction was found to correlate with acid stoichiometry (AS), percent reducing acid (PRA), and for some data series, headspace to simulant volume ratio (HSV), mercury (Hg), and nitrate. Although glycolate destruction for pairs of data series (e.g., [SB9-NG] and [SR+BH]) were found to depend on HSV, the combination of all three data series was not found to have significant dependence on this variable. The best model for glycolate destruction depended on AS, nitrate, and Hg. This model predicted the product glycolate compositions of the data to within 92-106%. The conversion of glycolate to formate was high when noble metals and Hg were not present, with values up to 100%. When noble metals and Hg were present, this conversion ranged from zero to 7%, and was dependent on AS. Lower AS gave higher conversions to formate. The conversion to oxalate was found to depend on the AS and the initial concentration of nitrite. An alternative fit versus AS and the form of ruthenium (Ru) used is a possible alternative. This fit was somewhat less statistically significant. This second model predicts that more oxalate is formed when Ru-nitrosyl nitrate is used rather than Ru chloride. The conversion of glycolate to oxalate ranged from zero to 6%. The conversion of nitrite to nitrate depended primarily on AS and PRA, with HSV and Hg being significant when these variables were varied. For multiple series of data, nitrite was also needed to SRNL-STI-2017-00172 5HYLVLRQ viL distinguish between data series, and the effect of HSV became insignificant. The best model for nitrite to nitrate conversion depended on AS, PRA, nitrite, and Hg. The 95% confidence intervals on the predicted values of glycolate destruction, glycolate to oxalate conversion, and nitrite to nitrate conversion were used to determine the uncertainty in the predicted REDOX when starting with only the composition of the sludge, AS, and PRA. Using the 95% confidences on an individual value (that is the confidence in getting a particular value for one single test as opposed to what the mean would be for multiple tests), the uncertainty in the predicted REDOX was calculated. The uncertainty in the actual product composition glycolate, oxalate, formate, and nitrate concentrations translated to an uncertainty in the REDOX value of ±0.1,which is approximately the uncertainty claimed in the REDOX model itself.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Work function determination of promising electrode materials for thermionic converters

Work performed on this contract was primarily for the evaluation of selected electrode materials for thermionic energy converters. The original objective was to characterize selected nickel based superalloys up to temperatures of 1400 K. It was found that an early selection, Inconel 800 produced a high vapor pressure which interfered with the vacuum emission measurements. The program then shifted to two other areas. The first area was to obtain emission from the superalloys in a cesiated atmosphere. The cesium plasma helps to suppress the vaporization interference. The second area involved characterization of the Lanthanum-Boron series as thermionic emitters. These final two areas resulted in three journal publications which are attached to this report.

Jacobson, D.↗

Deep flaws in weldments of aluminum and titanium

Surface flawed specimens of 2219-T87 and 6Al-4V STA titanium weldments were tested to determine static failure modes, failure strength, and fatigue flaw growth characteristics. Thicknesses selected for this study were purposely set at values where, for most test conditions, abrupt instability of the flaw at fracture would not be expected. Static tests for the aluminum weldments were performed at room, LN2 and LH2 temperatures. Titanium static tests for tests were performed at room and LH2 temperatures. Results of the static tests were used to plot curves relating initial flaw size to leakage- or failure-stresses (i.e. "failure" locus curves). Cyclic tests, for both materials, were then performed at room temperature, using initial flaws only slightly below the previously established failure locus for typical proof stress levels. Cyclic testing was performed on pairs of specimens, one with and one without a simulated proof test cycle. Comparisons were made then to determine the value and effect of proof testing as affected by the various variables of proof and operating stress, flaw shape, material thickness, and alloy.

Masters, J. N.↗

Linking constituent phase properties to ductility and edge stretchability of two DP 980 steels

Two DP 980 steels were characterized with multiple methods to determine its microstructure characteristics, tensile properties and edge stretchability. The first (DP980-B) is a commercial grade DP980 steel produced by AK Steel, while the second (DP980-T) is a modification of the first one by a tempering process. Both contain two individual phases: ferrite and martensite with body centered cubic (BCC) and tetragonal (BCT) crystal structure respectively. ASTM standard tensile tests were performed for both materials, revealing that DP980-B has higher work hardening and larger total elongation than DP980-T. Standard hole piercing and subsequent hole expansion and extrusion tests were also performed. The critical hole expansion ratio (HER) of hole pierced sheet at different nominal clearances, on the other hand, show an opposite trend: the HER of DP980-T almost doubles that of DP980-B. This indicates the tensile ductility and edge stretchability are determined by different mechanisms due to different deformation modes. The ductility of sheet metal during uniaxial tension is determined by deformation instability, i.e. necking, due to less constraint at the region of deformation and fracture will occur quickly after necking. The contribution of post-necking deformation to the total elongation is insignificant for the high strength grades such as DP980 steels. The ductility during hole-expansion, however, is mainly determined by material fracture behavior that is dependent on phase property disparity and material intrinsic fracture parameters. With the individual phase properties for both DP steels determined by in situ tensile tests under high energy X-ray diffraction, the results show that DP980-T steel has lower property disparities between the two phases than DP980-B steel, due to the tempering process. This explains why the DP980-T steel has higher HER than DP980-B steel: lower phase disparity will lead to less local deformation during loading. The higher work hardening rate for DP980-B steel contributes to its higher uniform elongation compared with DP980-T steel based on the maximum load condition of deformation instability. An integrated finite element simulation framework for studying hole expansion is also presented here, based on the calculated individual phase properties from the combined high energy x-ray diffraction (HEXRD) and elastic plastic self-consistent modeling. The simulation results correlate well with the experimental results on the HER difference between the two materials.

36 MATERIALS SCIENCE↗

Non-Electricity Based Renewable Fuels: Theory and Computation for Solar Thermochemical Hydrogen

Dominated by photovoltaics and wind, current renewable energy sources generate mostly electricity, but 80% of the global final energy consumption occurs in form of fuels. Therefore, direct solar fuel generation would be a major breakthrough for the energy transition. Solar thermochemical hydrogen (STCH) is one of the very few potential routes towards scalable renewable fuels, but currently suffers from lack of an oxide working material that could optimally perform energy conversion within the thermodynamic boundary conditions. Theory and computation can contribute in two distinct ways, through materials search and discovery, but also by providing detailed mechanistic models for specific systems so to advance our understanding of possible design strategies. To enable high-throughput materials screening, we developed a defect graph neural network (dGNN) machine learning approach,[1] which accelerates the prediction of defect formation energies by replacing the tedious density functional theory (DFT) supercell calculations for all possible defect sites. This approach enables high-throughput database screening of oxides, which was integrated with thermodynamic modeling to extract the reduction entropies as additional selection criterion for STCH. Once potential candidate materials are identified, detailed models can guide materials design by predicting performance characteristics. One challenge is to quantitatively predict thermochemical equilibria at high concentrations when the redox active defects start to interact with each other, thereby impeding the formation of additional defects. Introducing a model for the free energy of defect interaction, parametrized on the basis of DFT data, we simulated the complete STCH redox cycle for (Sr,Ce)MnO3 alloys, achieving near-quantitative agreement with experimental data.[2] The analysis of these simulations reveals how defect interactions diminish the reduction entropy and H2 yield, suggesting to include these interactions in design considerations. Finally, we revisit the popular van't Hoff method for analyzing reduction enthalpies and entropies. This method is not ideal, as it involves a temperature-dependent convolution of gas-phase and solid-state entropies, causing uncertainties in the same order of magnitude as the physical quantities of interest. To avoid this problem, we suggest a simple alternative approach which can be applied to experimental and simulated data alike.

first-principles calculations↗

Thermally Stabilized Transmit/Receive Modules

RF-hybrid technologies enable smaller packaging and mass reduction in radar instruments, especially for subsystems with dense electronics, such as electronically steered arrays. We are designing thermally stabilized RF-hybrid T/R modules using new materials for improved thermal performance of electronics. We are combining advanced substrate and housing materials with a thermal reservoir material, and develop new packaging techniques to significantly improve thermal-cycling reliability and performance stability over temperature.

thermal cycling stress↗

A framework to evaluate machine learning crystal stability predictions

The rapid adoption of machine learning in various scientific domains calls for the development of best practices and community agreed-upon benchmarking tasks and metrics. We present Matbench Discovery as an example evaluation framework for machine learning energy models, here applied as pre-filters to first-principles computed data in a high-throughput search for stable inorganic crystals. We address the disconnect between (1) thermodynamic stability and formation energy and (2) retrospective and prospective benchmarking for materials discovery. Alongside this paper, we publish a Python package to aid with future model submissions and a growing online leaderboard with adaptive user-defined weighting of various performance metrics allowing researchers to prioritize the metrics they value most. To answer the question of which machine learning methodology performs best at materials discovery, our initial release includes random forests, graph neural networks, one-shot predictors, iterative Bayesian optimizers and universal interatomic potentials. We highlight a misalignment between commonly used regression metrics and more task-relevant classification metrics for materials discovery. Accurate regressors are susceptible to unexpectedly high false-positive rates if those accurate predictions lie close to the decision boundary at 0 eV per atom above the convex hull. The benchmark results demonstrate that universal interatomic potentials have advanced sufficiently to effectively and cheaply pre-screen thermodynamic stable hypothetical materials in future expansions of high-throughput materials databases.

Riebesell, Janosh↗

Inertially enhanced mass transport using 3D-printed porous flow-through electrodes with periodic lattice structures

Significance The efficient utilization of electrical energy is an increasingly important challenge, especially as renewable energy sources become cheaper and demand increases. Electrochemical reactors utilizing flow-through electrodes (FTEs) provide an attractive path toward the efficient utilization of electrical energy. Their commercial viability and ultimate adoption hinge on attaining high current densities to drive cost competitiveness. There are limited opportunities for engineering FTE materials, as these are often random, disordered media. Alternatively, three-dimensional (3D)–printed FTEs provide the opportunity to quickly explore the impact of engineered electrode architectures on device performance. We demonstrate that 3D-printed FTEs have the potential to exceed the performance of conventional materials by using the expanded design freedom to engineer the internal flow.

30 DIRECT ENERGY CONVERSION↗

Wear in particle based CSP systems from particle abrasion and attrition at high temperature

High temperature particle-based receivers offer distinct advantages over conventional molten salt receivers due to their ability to achieve temperatures above 700 ºC, direct absorption of solar energy as they fall through a beam of concentrated sunlight, and the relative ease of storage (and retrieval using a secondary working fluid) in insulated storage tanks. The use of particles, however, also raises concerns with material degradation from the flow of hot or cold particles through discharge hoppers or along the inner receiver surfaces and other system components (e.g. tubes, valves etc.), depending on operating mode of the receiver. The flow of particles over surfaces may result in loss of material from abrasive wear, impact erosion from impingement under gravitational fall and particle attrition as particles fall and move on top of each other. In the present study, the performance of candidate materials and particles were evaluated through a series of abrasion erosion and particle attrition experiments at room temperature as well as at 800 °C. Candidate materials were subject to abrasive wear from particles at low particle to material velocities inside a resistance heated kiln, and analyzed for changes in mass and surface morphology using cross-sectional scanning electron microscopy (SEM) and energy dispersive x-ray spectroscopy (EDS) tests. The wear rate for different specimens was noted to be largely driven by the strength of chromia scales built on the specimens from exposure to high temperature. Particle attrition measurements explored the susceptibility of particles to breakdown from particle to particle interaction and the generation of fines from this process. At the low velocities expected in particle based CSP plants, the particles tested exhibited near negligible breakdown. However, changes in the particle hardness at 800 ºC resulted in a significantly higher particle breakdown to sizes <40 microns raising potential environmental concerns. In addition to particle breakdown, it was also noted that the sample had oxides from the stainless steel test setup mixed in with the particles. Similar oxides can be expected to turn up in the utility scale particle based CSP plants as well. The presence of oxide was also noted to affect the solar absorptivity of the mixture compared to a clean initial specimen, potentially resulting in a change in the overall efficiency of the CSP plant.

14 SOLAR ENERGY↗

Corrosion Testing Needs and Considerations for Additively Manufactured Materials in Nuclear Reactors

The Advanced Materials and Manufacturing Technologies (AMMT) program within the Department of Energy, Office of Nuclear Energy (DOE-NE) has developed its current recommendation for its corrosion testing strategy to deploy additively manufactured (AM) materials in advanced nuclear reactors. Additive manufacturing technologies have developed rapidly in recent years, creating new opportunities and challenges for the nuclear industry. To adopt AM technologies, the corrosion performance of AM materials needs to be adequately evaluated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Fire testing in the Boeing 707 cabin section

The goal of a FIREMEN funded contract is the definition of a laboratory test method ranking airplane interior materials by probable performance in post-crash and in-flight fires. A major task is the relation of laboratory results to full scale data. A large test facility for testing materials to the thermal threat of fuel fed and interior fires was developed with quartz lamps and a propane burner in a twenty foot fuselage section. A method was developed to analyze full scale data for the apparent heat, smoke and toxicant release rates of the material tested.

Tustin, E. A.↗

Single-Transducer, Ultrasonic Imaging Method for High-Temperature Structural Materials Eliminates the Effect of Thickness Variation in the Image

NASA Lewis Research Center's Life Prediction Branch, in partnership with Sonix, Inc., and Cleveland State University, recently advanced the development of, refined, and commercialized an advanced nondestructive evaluation (NDE) inspection method entitled the Single Transducer Thickness-Independent Ultrasonic Imaging Method. Selected by R&D Magazine as one of the 100 most technologically significant new products of 1996, the method uses a single transducer to eliminate the superimposing effects of thickness variation in the ultrasonic images of materials. As a result, any variation seen in the image is due solely to microstructural variation. This nondestructive method precisely and accurately characterizes material gradients (pore fraction, density, or chemical) that affect the uniformity of a material's physical performance (mechanical, thermal, or electrical). Advantages of the method over conventional ultrasonic imaging include (1) elimination of machining costs (for precision thickness control) during the quality control stages of material processing and development and (2) elimination of labor costs and subjectivity involved in further image processing and image interpretation. At NASA Lewis, the method has been used primarily for accurate inspections of high temperature structural materials including monolithic ceramics, metal matrix composites, and polymer matrix composites. Data were published this year for platelike samples, and current research is focusing on applying the method to tubular components. The initial publicity regarding the development of the method generated 150 requests for further information from a wide variety of institutions and individuals including the Federal Bureau of Investigation (FBI), Lockheed Martin Corporation, Rockwell International, Hewlett Packard Company, and Procter & Gamble Company. In addition, NASA has been solicited by the 3M Company and Allison Abrasives to use this method to inspect composite materials that are manufactured by these companies.

Roth, Don J.↗

Contaminant characterization of five satellite materials

An extensive laboratory test program was performed to characterize outgassing of five satellite materials. The materials were Chemglaze Z-306 over 9922 primer, M-773 adhesive, multilayer insulation, polyurethane foam, and silverized Teflon. The souces were prepared to the specifications of a typical satellite program. Dynamic thermogravimetric mass loss characteristics of these five materials were obtained in vacuum with a beam microbalance. The temperature of the material was linearly raised from 25 C to over 650 C while monitoring the mass loss, rate of mass loss, temperature, and the composition of the outgassed material by residual gas analysis. Isothermal source emission/capture coefficients/reemission parameters were obtained with an array of quartz crystal microbalances (QCM). A detailed test matrix in which the temperatures of the QCMs (-160 C, - 100 C, -40 C, and +10 C) and the source material (125 C, and 90 C, and 50 C) were varied was performed. The array of QCMs was also used to measure the spatial distribution of the source emission. The effects of vacuum ultraviolet radiation on the deposition and reemission parameters was determined.

Muscari, J. A.↗

Spectral Effects in Albedo and Rearside Irradiance Measurment for Bifacial Performance Estimation: Preprint

Albedo data are essential for accurate prediction of bifacial PV module performance. However, spectral response mismatch between PV modules and irradiance sensors used in albedometers can limit the accuracy of performance predictions. In order to provide quantitative assessment of this effect, we investigate via simulation the differences in spectrally responsive albedo measured with thermopile pyranometers and crystallinesilicon PV reference cells in comparison to a representative crystalline-silicon bifacial PV module for nine different representative ground surface materials. Calculations are performed using simulated solar spectra together with catalogued spectral reflectivity data distributed with the SMARTS simulation software. For the specific materials considered, the results show that albedo measurement using thermopile pyranometers could over or under-estimate the ground-reflected radiation usable by a bifacial PV module by up to 10%, versus only approximately 4% total range of variation for a PV reference cell.

Albedo↗

Exascale granular microstructure reconstruction in 3D volumes of arbitrary geometries with generative learning

Reconstructing 3D granular microstructures within volumes of arbitrary geometries from limited 2D image data is crucial for predicting the material properties, as well as performances of structural components accounting for material microstructural effects. We present a novel generative learning framework that enables exascale reconstruction of granular microstructures within complex 3D geometric volumes. Building upon existing transfer learning techniques using pre-trained convolutional neural networks (CNN), we introduce several key innovations to overcome the difficulties inherent in arbitrary geometries. Our framework incorporates periodic boundary conditions using circular padding techniques, ensuring continuity and representativeness of the reconstructed microstructures. We also introduce a novel seamless transition reconstruction (STR) method that creates statistically equivalent transition zones to integrate multiple pre-existing 3D microstructure volumes. Based on STR, we propose a cost-effective strategy for reconstructing microstructures within complex geometric volumes, minimizing computational waste. Validation through numerical experiments using kinetic Monte Carlo simulations demonstrates accurate reproduction of grain statistics, including grain size distributions and morphology. A case study involving the reconstruction of a 4-blade propeller microstructure illustrates the method’s capability to efficiently handle complex geometries. In conclusion, the proposed framework significantly reduces computational demands while maintaining high reconstruction quality, paving the way for scalable microstructure reconstruction in materials design and analysis.

36 MATERIALS SCIENCE↗

Understanding Solution State Conformation and Aggregate Structure of Conjugated Polymers via Small Angle X-ray Scattering

Donor-acceptor (D-A) conjugated polymers are high-performance organic electronic materials that exhibit complex aggregation behavior. Understanding the solution state conformation and aggregation of conjugated polymers is crucial for controlling morphology during thin-film deposition and the subsequent electronic performance. However, a precise multiscale structure of solution state aggregates is lacking. Here, we present an in-depth small-angle X-ray scattering (SAXS) analysis of the solution state structure of an isoindigo-bithiophene-based D-A polymer (PII-2T) in chlorobenzene and decane as our primary system. Modeling the system as a combination of hierarchical fibrillar aggregates mixed with dispersed polymers, we extract information about conformation and multiscale aggregation and also clarify the physical origin of features often observed but unaddressed or misinterpreted in small-angle scattering patterns of conjugated polymers. The persistence length of the D-A polymer extracted from SAXS agrees well with a theoretical model based on the dihedral potentials. Additionally, we show that the broad high q structure factor peak seen in scattering profiles can be attributed to lamellar stacking occurring within the fibril aggregates and that the low q aggregate scattering is strongly influenced by the polymer molecular weight. Overall, the SAXS profiles of D-A polymers in general exhibit a sensitive dependence on the co-existence of fibrillar aggregate and dispersed polymer chain populations. We corroborate our findings from SAXS with electron microscopy of freeze-dried samples for direct imaging of fibrillar aggregates. Finally, we demonstrate the generality of our approach by fitting the scattering profiles of a variety of D-A polymers based on thieno-isoindigo (PTII-2T), diketopyrrolopyrrole (DPP2T-TT, DPP-BTZ, PDPP2FT-C- 16 ), naphthalenediimide (P(NDI2OD-T2)), and a conjugated block copolymer P3HT-b-DPPT-T. The results presented here establish a picture of the D-A polymer solution state structure and provide a general method of interpreting and analyzing their scattering profiles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of procedures for calculating stiffness and damping of elastomers in engineering applications. Part 5: Elastomer performance limits and the design and test of an elastomer damper

Tests were performed on elastomer specimens of the material polybutadiene to determine the performance limitations imposed by strain, temperature, and frequency. Three specimens were tested: a shear specimen, a compression specimen, and a second compression specimen in which thermocouples were embedded in the elastomer buttons. Stiffness and damping were determined from all tests, and internal temperatures were recorded for the instrumented compression specimen. Measured results are presented together with comparisons between predictions of a thermo-viscoelastic analysis and the measured results. Dampers of polybutadiene and Viton were designed, built, and tested. Vibration measurements were made and sensitivity of vibration to change in unbalance was also determined. Values for log decrement were extracted from the synchronous response curves. Comparisons were made between measured sensitivity to unbalance and log decrement and predicted values for these quantities.

Tecza, J. A.↗

Reduction of Ultrafine Hematite for a Spouting Bed Chemical Looping Process - Presentation

Chemical looping combustion research has been a topic of great interest since the mid-1990s, although the concept can be traced much further back. It is a combustion technology for fuel utilization that uses a two-reactor system to produce a carbon free effluent stream from the air reactor and a carbon dioxide rich stream from the fuel reactor with oxygen shuttled between the reactors with an oxygen carrier. Chemical looping combustion has been studied extensively because of this inherent separation of the carbon dioxide combustion product from the atmospheric nitrogen over that past 25 years with hundreds of research papers and tens of books. The oxygen carrier is, in general, a solid such as naturally occurring hematite or an engineered carrier like a copper and iron oxide supported on alumina. System technical and economic research activities conducted at the National Energy Technology Laboratory have shown that the costs associated with the carrier, initial and replacement, are a significant factor in the economic viability of the technology. To overcome this economic challenge, the work reported on in this paper investigates the use of a waste iron oxide as the chemical looping oxygen carrier. This waste material is quite unique as it has a particle size of 0.7 um. Given the particle size, the reactions are quite fast. However, the development of a contactor reactor to mix the fuel with the carrier is a fluidization challenge as the material is a Geldart group C material and highly cohesive. Normally, Geldart group C materials are fluidized with either a vibrating bed. This technique is acceptable for low temperature pharmaceuticals production but does not lend itself to much larger reactors used for power production or operation at temperatures in the order of 1100 to 1200 C. Therefore, a hydrodynamic solution was needed to break up the cohesive structures to replace the vibration. In this instance, it was hypothesized that a spouting bed of large Geldart group B or Geldart group D particles could provide the necessary energy to break up the cohesive structures of the Geldart group C material. This paper presents the reduction performance for this novel carrier material in a laboratory spouting bed reactor.

Breault, Ronald↗