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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 325 records · Page 18

Favorable Redox Thermodynamics of SrTi 0.5 Mn 0.5 O 3–δ in Solar Thermochemical Water Splitting

Two-step, solar thermochemical splitting of water using nonstoichiometric redox-active metal oxides has emerged as an intriguing approach for large-scale hydrogen production. Perovskites have been proposed as alternatives to state-of-the-art fluorite CeO 2–δ because of their potential for lowering reduction temperature while maintaining high fuel productivity. Guided by computational insights, we explore the thermodynamic properties and water splitting efficacy of the cubic perovskite SrTi 0.5 Mn 0.5 O 3–δ (STM55). Thermogravimetric analysis is performed under controlled oxygen partial pressures (pO 2 ) and temperatures up to 1500 °C, from which both the enthalpy and entropy of reduction as a function of oxygen nonstoichiometry are determined. STM55 provides an attractive combination of moderate enthalpy, 200–250 kJ (mol-O) –1 , and high entropy, with unusual δ dependence. Using a water splitting cycle in which the material is thermally reduced at 1350 °C (pO 2 , ~10 –5 atm) and subsequently exposed to steam at 1100 °C (steam partial pressure of pH 2 O = 0.4 atm), we demonstrate a hydrogen yield of 7.4 mL g –1 . Through both half-cycles, the material remains largely in quasi-equilibrium with the gas phase, as reflected in the agreement of the measured data with predicted profiles based on the thermodynamic data. This behavior indicates rapid surface and bulk diffusion kinetics. Cyclic operation showed the material to be free of degradation and always resulted in a 2:1 yield of H 2 /O 2 . Altogether, STM55 provides outstanding performance characteristics for thermochemical hydrogen production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A combined theoretical-experimental investigation of thermal transport in low-dose irradiated thorium dioxide

During reactor operation, nuclear fuels are subject to extreme temperature and irradiation conditions which can significantly degrade the fuel's thermal transport properties. The reduction in thermal conductivity of the fuel as a result of irradiation-induced lattice defects is arguably the most important fuel performance metric in regard to reactor efficiency and safety. Because thorium dioxide (ThO2) is suitable as a model system for more complex materials such as UO2 and its mixed oxides, we present a theoretical investigation of thermal conductivity reduction seen in defect-bearing thorium dioxide and compare directly to experimental measurements. Phonon-mediated thermal transport of the fuel is modeled by a solution to the Boltzmann transport equation (BTE) for phonons. A cluster dynamics (CD) model for lattice defect evolution during irradiation predicts defect densities which are used as input to the BTE for modeling phonon-defect scatterings. Phonon scatterings by lattice defects include those from point defects and vacancy clusters and interstitial clusters of various sizes. The CD model is benchmarked against structural defect characterization of irradiated thorium dioxide using electron microscopy. Thermal conductivity predicted by the BTE model is compared to measured values for irradiated thorium dioxide specimens below room temperature to isolate effects of phonon-defect scattering from intrinsic 3-phonon processes, which dominate at higher temperatures. The computed conductivity values are in partial agreement at temperatures close to room temperature while slight deviations are observed at the lowest measured temperatures, suggesting that implemented phonon-defect scattering cross-section expressions may not be adequate for low temperatures. The presented work provides a necessary investigation of the influence of irradiation induced defects on fuel performance and represents a first step toward a full characterization of phonon mediated thermal transport in irradiated materials with complex defect microstructure.

36 MATERIALS SCIENCE↗

Automated Control for Nuclear Thermal Propulsion Start-Up using MOOSE-based Applications

This report presents a Griffin/Bison/RELAP-7 numerical model of a prototypical NTP system that features fuel assemblies arranged in rings, and which was designed to simulate rapid startup transients. The physics modeled include full-core neutronics, assembly-wise heat conduction, and conjugate heat transfer, with the balance of plant mainly imposed through boundary conditions. In addition, various forms of automated reactivity control were deployed by using the MOOSE to autonomously drive the model and simulate the reactor transitioning from assumed initial conditions to nominal power in a fraction of a minute. To generate the cross-sections of the neutronics model, and in an effort to simultaneously account for the tremendous axial temperature gradients in the reactor and to limit the number of state points required for cross-section generation, the average component temperatures and hydrogen densities in the cooling channels were correlated to the average fuel and moderator temperatures, and fixed axial profiles were derived for nominal conditions and then used during the transient. With this approximation, a tractable cross-section library tabulated with fuel/moderator temperatures and CD angles was generated using Serpent. The full-core SPH correction procedure and the CD decusping technology in Griffin, respectively, ensure preservation of the multiplication factor and reaction rates at state points, along with a reasonably accurate reactivity worth between tabulated CD angles, despite using a coarse mesh. Feedback from other physics was calculated by modeling one representative fuel assembly per ring, along with the corresponding fuel and moderator cooling channels. To limit power overshoots during startup, another layer of multiphysics coupling was added to the model in order to automatically control the drums. Two different technologies presented herein showed outstanding performance in this regard: (1) a novel hybrid PID controller based on both power and reactivity signals, and (2) a PGC that relies on kinetics parameters and reactivity coefficients to predict future behavior and adjust the desired signal accordingly. A challenging benchmark was devised, featuring a power demand curve that exponentially increases by a factor of 500 within 30 seconds, then levels out after that. Both control approaches create a simulated power curve that closely follows the power demand curve and limits power overshoots to 1% or less. While the former approach requires more tuning of the internal parameters, the latter requires additional knowledge of the reactivity feedback coefficients and rates of change of the corresponding variables, including fuel and moderator temperature, which could be difficult to dynamically measure for a real NTP system. Fortunately, some inaccuracy in these quantities will not drastically degrade the PGC performance. Subsequently, a more realistic startup sequence was considered, in which the mass flow rate and outlet pressures are ramped up to model bootstrap and thrust build-up phases prior to reaching steady-state conditions, demonstrating the ability of the hybrid PID and PGCs to handle such transients, with both types of controllers exhibiting very similar behavior. Nevertheless, a significant chamber temperature overshoot was observed, caused by the demanded power signal and assumed mass flow rate. This issue could be mitigated by deploying a reactor controller that follows the chamber temperature signal and actuates both the control valves and drums (rather than using a power signal based solely on the drums to control reactivity). Enhancement of the hydrogen fluid properties available in MOOSE, as well as a better understanding of prototypical initial conditions, are also needed to further enhance this startup model. Finally, a study was performed to model decay heat post-shutdown, and to prepare for extending this model to predict shutdown behavior and post-shutdown pulsed cooling requirements.

33 ADVANCED PROPULSION SYSTEMS↗

Methods development towards automated, physics-informed, quantitative quality control of TRISO-SiC

Tristructural-isotropic (TRISO) fuel particles have been developed as a high-performance fuel for use in high-temperature gas-cooled reactor (HTGR) systems due to their high efficiency and stability under both normal and off-normal conditions. Broader deployment of this technology in advanced nuclear applications may benefit from quantitative quality assurance and quality control (QA/QC) methods that directly link TRISO properties to downstream performance. A key TRISO property is the SiC layer microstructure, which influences fission product retention during irradiation. However, existing QA/QC for the TRISO-SiC microstructure comprises only a qualitative visual inspection; therefore, there is a clear opportunity for the development of quantitative methods for TRISO QA/QC. Here, to this end, previous work has demonstrated an image processing approach to grain boundary (GB) identification and subsequent extraction of microstructural metrics; however, extensive twinning within the SiC layer complicates such analyses because twin GBs significantly influence microstructural metrics but are not expected to contribute to fission product transport. This study presents the initial development, training, and testing of an ML-based image segmentation algorithm designed to identify and remove twin GBs from standard backscattered electron micrographs, providing an industrially applicable, quantitative, and physically meaningful QA/QC approach for the TRISO-SiC microstructure. Although pixel-wise performance metrics for the twin predictions are low, the change in grain area and the number of GB pixels after twin removal predicted by the ML workflow are within 1% of the true values calculated using crystallographic data. This suggests that the model is well capable of predicting overall twin boundary structures and grain morphology, and continued advancement of this approach could enable automated, scalable, and physics-informed QA/QC for TRISO-SiC microstructures, supporting the reliable qualification of coated particle fuels for next-generation reactor systems.

Computer vision↗

Accelerating the discovery of battery electrode materials through data mining and deep learning models

The availability of crystalline materials databases allows for building accurate machine learning (ML) models that can accelerate the exploration of materials chemical space for energy storage applications. In this work, we screen all inorganic materials included in the Materials Project and AFLOW databases as potential metal-ion battery electrodes. We develop an efficient protocol to mine and screen raw data in current databases and provide a new database of electrode materials by considering pairs of charged and discharged electrodes. This effort leads to a new database with over 190,000 instances, in contrast to the original battery database which contains about 5000. The expanded battery data set is then used to build regression-based deep neural network models for predicting average voltages and percentage volume changes upon charging and discharging, which present improvements of at least 28% for target properties with respect to previous models, and are now able to predict anode electrodes (low voltage region) as well as electrodes that will not work in electrochemical cells (negative voltages), overcoming the challenges identified in previous ML models for battery electrodes. Additionally, a further screening of the expanded database itself allowed us to identify 35 novel electrode candidates with excellent battery performance metrics.

25 ENERGY STORAGE↗

An integrated approach to examine fuel-cladding chemical interaction in HT9/U-10Zr metallic fast reactor fuels: Coupling machine learning with electron microscopy and local mechanical properties analysis

The metallic U-Zr nuclear fuel alloy has garnered renewed interest as a promising candidate for next-generation sodium-cooled fast reactors. Recent studies and technology assessments have identified several areas requiring improvements, enhanced knowledge, and reliable data to strengthen the U-Zr fuel design basis for qualification and commercial applications. One of the most challenging phenomena impacting this fuel system’s performance is fuel-cladding chemical interaction (FCCI). This work aimed to harvest FCCI data by examining selected HT9/U-10Zr (wt. %) fuel samples of prototypic full-length fuel pins through an integrated approach. This approach integrated scanning electron microscopy (SEM) microstructure characterization with localized mechanical properties examination to deepen understanding of FCCI phenomenon in HT9/U-10Zr fuel system. Particularly, this study focused on MFF fuel pins irradiated at Fast Flux Test Facility (FFTF), which aimed to qualify metallic fuel as a driver fuel for FFTF and to assess its viability for larger-scale fast reactors. Electron microscopy provided high confidence in detecting and distinguishing the different FCCI layers, while small-scale mechanical testing (SSMT) probed the mechanical properties of these layers. SEM examination of a MFF-2 pin 192167, with a time averaged inner cladding temperature (TICT) slightly over 500°C, revealed minimal cladding-side FCCI (cladding wastage). In contrast, significantly thicker cladding wastage comprising two distinct sublayers was observed in samples from the thermally hot MFF-3 pin 193045 and MFF-5 pin 195011 where the TICT ranged from 610-635°C. SSMT indicated complete embrittlement in the sublayer adjacent to the fuel and a tendency toward embrittlement in the other sublayer. Additionally, a new machine learning method was developed, validated, and used to quantify cladding wastage thickness. The machine learning method reliably predicted the wastage thickness across various fuel pins and sample cross-sections. Furthermore, the available cladding wastage data from HT9/U-10Zr fuel system demonstrated a strong temperature dependency. However, the dataset remains small, and ongoing research activities are essential to further understand the FCCI phenomenon and develop a reliable FCCI model for enhanced fuel performance simulation under various conditions.

36 - MATERIALS SCIENCE↗

Sustainable energy and fuels from biomass: a review focusing on hydrothermal biomass processing

Fossil fuels are being replaced with renewable energy resources (biomass and biomass waste, solar, geothermal, wind, etc.) to ensure sustainable development, reduce the dependence on fossil fuels, address environmental challenges including climate change. Today, biomass produces 5 × 10 19 kJ of energy/year, which corresponds to 10% of the annual global energy consumption. Considering the variety of biomass resources, this value is predicted to reach 150 × 10 19 kJ by 2050. Biomass may become even more important for use as an energy resource and chemical raw material in the 21st century. Hydrothermal biomass conversion stands out as a promising and alternative technology. Methods such as traditional gasification and pyrolysis require dry biomass. Hydrothermal techniques have been developed to eliminate the cost and time required for drying biomass. The purpose of this process is to decompose biomass with a high moisture content into small molecules and reduce its oxygen content to obtain liquid fuels or valuable chemicals. Finally, this review presents the current and future state of energy, energy sources, biomass properties and biomass conversion technologies with a focus on hydrothermal technologies.

09 BIOMASS FUELS↗

Scaling for Nuclear Reactor System: Overview

A scaling analysis is essential for predicting the behavior of a reactor system under various operating conditions, as well as for ensuring safe and reliable experimentation and adequate dataset generation for supporting the system code model development and assessment in accordance with USNRC guidelines 1.203. Testing and modeling can be carried out at various scales, from small test units to full-scale reactors, to validate the predictions produced by the analysis. However, due to the cost and challenges associated with full-scale testing, the nuclear industry uses scaled test facilities—integral effect test (IET) and separate effect test (SET)—to identify potential design issues and optimize the design to ensure regulatory compliance for safer operation and anticipated accident management. In general, IET facilities are non-nuclear thermal hydraulics test facilities. In contrast, SET facilities can be non-nuclear testing (e.g., steam generator, containment, pump system SETs) and nuclear testing (mostly fuel-material irradiation testing). IETs are used to study the system-level thermal-hydraulic behavior of the reactor coolant system (RCS) under different anticipated operational occurrences (AOOs) and design basis accidents (DBAs) such as loss-of-coolant-accident (LOCA) and loss-of-power (i.e., station blackout) and loss-of-flow (i.e., failure of RCS pump). Several LOCA scenarios could happen in reactor DBAs, such as main steam line break (MSLB), SG tube rapture (SGTR), break in direct vessel injection (DVI), and other small breaks LOCA. Scaling analysis determines the appropriate size and operating conditions for the test facility. This involves analyzing the system's thermal-hydraulic behavior at different scales and identifying the key parameters that affect the thermal-hydraulic behavior of the reactor. These key parameters can be identified so that the scaled facility can replicate the expected conditions in a prototypical setting. The scaled facility can simulate the same flow rates, pressure gradients, heat transfer coefficients, and fluid properties as the prototype. Scaling analysis is used to ensure that the results from these tests can be scaled up to predict the behavior of a full-scale prototype with an acceptable range of scaling distortions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Transport of Highly Volatile Gases Related to Noble Gases and Tritium in the MSRE

This study aims to comprehend mass transfer in the closed-loop circulation of highly volatile gases, including noble gases and tritium. We explore the impact of steady-state xenon-135 and tritium on the MSRE and reveal their isotopic distributions using online noble gas stripping of fuel salts. The MSRE was engineered to extract fission product gases from fuel salts and efficiently eliminate inert gases with the help of helium bubbles within a circulating fuel pump. These reactors introduce significant theoretical challenges in estimating interfacial area and mass transfer coefficients, crucial for modeling mass transfer processes. An essential component of our analysis is the mass transfer coefficient. These coefficients are important for understanding how radionuclides move during various phase transitions within a nuclear reactor. Xenon-135 and tritium are found in both liquid and gas phases within the reactor system. In the liquid phase, they dissolve in molten salts, while in the gas phase, they manifest as bubbles. These elements have significant adverse effects on reactor operation due to their strong neutron absorption properties, influencing both safety and performance. The Mole code, which predicts the behavior of chemical species under steady-state conditions, facilitates multiphysics coupling with Griffin to update species distributions and address inherent MSR safety.

Lee, Kyoung↗

Cryogenic Vibrational Spectroscopy of the Deprotonated Dimer of Phosphoric Acid

Phosphate-containing molecules are ubiquitous in nature, where they play crucial roles in biochemical processes. Further, they are of technical importance, for example, in certain batteries and in fuel cells, where a unique property of phosphoric acid is exploited its exceptionally high proton conductivity. Proton transport in phosphoric acid is known to involve proton shuttling; however, the elementary steps involved are not clear. To elucidate the hydrogen bonding preferences of phosphoric acid, we investigate the dihydrogen phosphate anion as well as the deprotonated dimer of phosphoric acid (H 3 PO 4 ·H 2 PO 4 − ) in the gas phase using infrared action spectroscopy in helium nanodroplets and infrared D 2 -tagging photodissociation spectroscopy, and the experimental spectra are compared to theoretical ones. Theory finds for H 3 PO 4 ·H 2 PO 4 − two different structures that are predicted to be nearly isoenergetic. The comparison to the experimental spectra, however, allows for a clear assignment and structure identification. The resulting structure has an interesting binding motif, which might be of relevance to interactions of phosphoric acid in the condensed phase and which can serve as a benchmark for quantum chemical calculations.

Chemical structure↗

Fundamental study of gas species transport in the oxygen electrode of solid oxide fuel and electrolysis cells

A fundamental analysis of multicomponent gas transport models was performed in application to the oxygen electrodes of solid oxide cells. It is common practice to neglect the effect of pressure gradients within oxygen electrodes, even though a net molar flux at the electrolyte surface implies that a pressure gradient must exist. The influence of both Darcy velocity and Knudsen flux are considered in the context of ordinary (Fickian) diffusion, the dusty gas model, and the binary friction model. Comparisons between the models and different sets of assumptions are made via parametric studies on operating load, oxygen partial pressure, microstructural properties, and electrode thickness. Results show that the pressure gradient will have a significant impact on the oxygen concentration distribution and therefore the concentration overpotential. In electrolysis mode, pressure increases up to 1 atm are predicted, indicating that pressure at the electrode/electrolyte interface could contribute to electrode delamination. Additionally, it is found that Darcy's law is insufficient for calculating the pressure distribution without accounting for the flux due to Knudsen diffusion. Additionally, it is found that for the range of properties typical of oxygen electrodes, there is a negligibly small difference between the dusty gas model and binary friction model from a practical standpoint.

08 HYDROGEN↗

Pilot-Scale Pelleting Tests on High-Moisture Pine, Switchgrass, and Their Blends: Impact on Pellet Physical Properties, Chemical Composition, and Heating Values

In this study, we evaluated the pelleting characteristics of southern yellow pine (SYP), switchgrass (SG), and their blends for thermochemical conversion processes, such as pyrolysis and gasification. Using a pilot-scale ring-die pellet mill, we specifically assessed the impact of blend moisture, length-to-diameter (L/D) ratio in the pellet die, and ratio of pine to SG on the physico-chemical properties of the resulting pellets. We found that an increase in pine content by 25–50% marginally affected the bulk density; however, it also led to an increase in calorific value by 7% and a decrease in ash content by 72%. A moisture content of 25% (wet basis) and an L/D ratio of 5 resulted in poor pellet durability at <90% and bulk density values of <500 kg/m 3 , but increasing the L/D ratio to 9 and lowering the moisture content to 20% (w.b.) improved the pellet durability to >90% and the bulk density to >500 kg/m 3 . Blends with ≥50% pine content resulted in lower energy consumption, while a lower L/D ratio resulted in higher pelleting energy. Based on these findings, we successfully demonstrated the high-moisture pelleting of 2.5 ton of pine top residues blended with SG at 60:40 and 50:50 ratios. The quality of the pellets was monitored off-line and at-line by near infrared (NIR) spectroscopy. Multivariate models constructed by combining the NIR data and the pelleting process variables could successfully predict the pine content (R 2 = 0.99), higher heating value (R 2 = 0.98), ash (R 2 = 0.95), durability (R 2 = 0.94), and bulk density (R 2 = 0.86) of the pellets. Thus, we established how blending and densification of SYP and SG biomass could improve feedstock specifications and that NIR spectroscopy can effectively monitor the pellet properties during the high-moisture pelleting process.

09 BIOMASS FUELS↗

First-principles study of surface properties of crystalline and amorphous uranium aluminides

Surface energy is a crucial material property required for the modeling of fission gas bubble behavior in nuclear materials. However, there is no information available regarding the surface properties of uranium aluminides. In this work we systematically investigate the surface properties of uranium aluminides (UAl 3 and UAl 4 ) by first-principles density functional theory (DFT) calculations. Specifically, a total of 13 surface orientations with a maximum Miller index (MMI) up to 3 are studied for cubic UAl 3 , while 19 surfaces with a MMI of 2 for orthorhombic UAl 4 . Using the surface energies predicted by DFT, the surface properties of equilibrium single crystal UAl 3 and UAl 4 , including surface area weighted surface energy, dominant surface orientations and surface anisotropy, are obtained from Wulff construction. To understand gas bubble behaviors in amorphous uranium aluminides under irradiation, we study the surface properties of amorphous UAl 3 and UAl 4 . Compared to the crystalline phases, the amorphous phases are found to have lower surface energies due to the reduced number of breaking U-Al bonds close to the surface. The currently obtained surface properties of UAl 3 and UAl 4 can be used for the future modeling of gas bubble behaviors in both crystalline and amorphous uranium aluminide fuels.

36 MATERIALS SCIENCE↗

Combustion characteristics and detailed simulations of surrogates for a Tier II gasoline certification fuel

An experimental and numerical study of combustion of a gasoline certification fuel (‘indolene’), and four (S4) and five (S5) component surrogates for it, is reported for the configurations of an isolated droplet burning with near spherical symmetry in the standard atmosphere, and a single cylinder engine designed for advanced compression ignition of pre-vaporized fuel. The intent was to compare performance of the surrogate for these different combustion configurations and to assess the broader applicability of the kinetic mechanism and property database for the simulations. A kinetic mechanism comprised of 297 species and 16797 reactions was used in the simulations that included soot chemistry and accounted for unsteady transport, liquid diffusion inside the droplet, radiative heat transfer, and variable properties. The droplet data showed a clear preference for the S5 surrogate in terms of burning rate. The simulations showed generally very good agreement with measured droplet, flame, and soot shell diameters. Measurements of combustion timing, in-cylinder pressure, and mass-averaged gas temperature were also well predicted with a slight preference for the S5 surrogate. Preferential vaporization was not evidenced from the evolution of droplet diameter but was clearly revealed in simulations of the evolution of mixture fractions inside the droplets. The influence of initial droplet diameter (Do) on droplet burning was strong, with S5 burning rates decreasing with increasing Do due to increasing radiation losses from the flame. Flame extinction was predicted for Do =3.0 mm as a radiative loss mechanism but not predicted for smaller Do for the conditions of the simulations.

Guo, Songtao↗

Mobility assessment of the BCC and carbide phases in the C-Nb, C-U and Nb-U systems

Uranium carbides with refractory metal additions are considered for Gen IV nuclear reactors and nuclear thermal propulsion as fuels for their high-temperature and corrosion resistant properties. Understanding kinetic effects that dictate microstructural evolution during fabrication and operating conditions is essential to advance technological development of these fuels. This work presents the development of an atomic mobility database for C-Nb-U systems based off available experimental data supported with ab-initio methods. The mobility assessments and uncertainty quantification (using Markov chain Monte Carlo) were conducted in the Kawin software. Carbon diffusion is considered dominant, as metal diffusion is much slower, with niobium diffusion being even slower and rate limiting than uranium metal. We provide a comprehensive and self-consistent thermo-kinetic database that is validated by diffusion couple simulations through Kawin. In conclusion, this enables prediction of microstructural and phase evolution critical for the development and lifetime assessment of next generation nuclear fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Adsorption of molecular iodine and alkyl iodides from spent-nuclear-fuel-reprocessing off-gas using reduced silver mordenite

Radioactive iodine is a hazardous byproduct of spent-nuclear-fuel reprocessing that must be removed from the off-gas stream before it can be discharged. Reduced silver mordenite (Ag 0 Z) is currently the baseline material for iodine capture in the U.S. Although the performance characteristics and capture mechanisms of I 2 and CH 3 I have been established, similar investigations into long-chain organic iodides have yet to be performed. In this study, thin beds of Ag 0 Z were loaded with I 2 , CH 3 I, C 4 H 9 I, and C 12 H 25 I (5 ppm to 50 ppm) carried in a dry air stream at 150°C. The maximum iodine capacity was 105 ± 5 mg I/g Ag 0 Z for all species. Saturated Ag 0 Z samples were characterized using scanning electron microscopy, X-ray fluorescence, X-ray photoelectron spectroscopy, diffuse reflectance UV–visible spectroscopy, pair distribution function analysis, and thermogravimetric analysis. Further, near-complete Ag utilization and similar physical/chemical properties were observed for all samples. Through a comparison with previous studies and an investigation of aged Ag 0 Z, we propose that iodine species react with Ag + at exchange sites, forming α-AgI within the mordenite channels, and with surface Ag 0 nanoparticles, yielding β-/γ-AgI. The available Ag sites in the interior (Ag + ) and exterior (Ag 0 ) of mordenite determine the adsorption capacity since α-AgI formation is limited by the total pore volume. Potential iodine uptake routes were summarized for aging and non-aging environments. A scalable predictive model was implemented for deep-bed iodine removal, and predictions were in good agreement with experimental data. Sensitivity analysis suggests that iodine uptake kinetics is governed by pore diffusion.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Exploring biofiber properties and their influence on biocomposite tensile properties

Biofibers serve as effective reinforcements for neat polylactic acid (PLA) in biocomposites, offering an attractive opportunity to decarbonize the manufacturing sector of the United States by displacing fossil-based reinforcement fibers such as carbon fibers. Also, biofiber production can stimulate economic growth in rural economies, fueling sustainable development. PLA resins are commonly compounded with biofibers to create biocomposites suitable for additive manufacturing. PLA-biofiber composites often exhibit better overall material properties than neat (pure) PLA, but the associations between biofiber properties and the material properties of their biocomposites remain largely unexplored. Hence, this research delves into a comprehensive exploration of diverse biofibers, scrutinizing their physical and chemical attributes, including size, shape, ash content and biochemical composition. The study meticulously analyzes the flow properties of each biofiber and elucidates the ultimate tensile strengths and Young's modulus of corresponding biocomposite samples. Noteworthy correlations between biofiber and biocomposite tensile properties are uncovered, shedding light on critical interrelationships. The study introduces an approach employing regression models to predict the ultimate tensile strength and Young's modulus of biocomposites. These models, validated with a cross-validation technique, exhibit remarkable predictive accuracy, particularly in estimating ultimate tensile strength. © 2024 Oak Ridge National Laboratory managed by UT-Battelle, LLC and The Author(s). Polymer International published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

36 MATERIALS SCIENCE↗

Combustion characteristics and detailed simulations of surrogates for a Tier II gasoline certification fuel

An experimental and numerical study of combustion of a gasoline certification fuel (‘indolene’), and four (S4) and five (S5) component surrogates for it, is reported for the configurations of an isolated droplet burning with near spherical symmetry in the standard atmosphere, and a single cylinder engine designed for advanced compression ignition of pre-vaporized fuel. The intent was to compare performance of the surrogate for these different combustion configurations and to assess the broader applicability of the kinetic mechanism and property database for the simulations. A kinetic mechanism comprised of 297 species and 16,797 reactions was used in the simulations that included soot formation and evolution, and accounted for unsteady transport, liquid diffusion inside the droplet, radiative heat transfer, and variable properties. The droplet data showed a clear preference for the S5 surrogate in terms of burning rate. The simulations showed generally very good agreement with measured droplet, flame, and soot shell diameters. Measurements of combustion timing, in-cylinder pressure, and mass-averaged gas temperature were also well predicted with a slight preference for the S5 surrogate. Preferential vaporization was not evidenced from the evolution of droplet diameter but was clearly revealed in simulations of the evolution of mixture fractions inside the droplets. Here, the influence of initial droplet diameter (D o ) on droplet burning was strong, with S5 burning rates decreasing with increasing D o due to increasing radiation losses from the flame. Flame extinction was predicted for D o =3.0 mm as a radiative loss mechanism but not predicted for smaller D o for the conditions of the simulations.

42 ENGINEERING↗