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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

The utility of ultrasound guidance in transjugular liver biopsy: our experience

Purpose: To demonstrate the utility of ultrasound (US) guidance in improving the safety and efficacy of transjugular liver biopsy (TJLB) by analyzing all the TJLBs performed by us in the last 4 years. Materials and methods: Forty-seven patients who underwent TJLB in the last 4 years in our two centers were retrospectively analyzed. US guidance was used for all but for one patient during the two crucial steps of the procedure—for internal jugular vein (IJV) access and during the parenchymal biopsy. Biopsies were obtained under real-time sonographic guidance from the right lobe after confirming an adequate room for needle throw without breaching the liver capsule or any major hilar structures. Post-procedure complications, tissue yield, and histopathological adequacy of samples were analyzed. Results: Overall technical success rate was 100%. No major complications were found where ultrasound-assisted TJLB (uTJLB) was performed. One patient who underwent non-US guided TJLB had an event of a capsular breach and intra-peritoneal hemorrhage requiring coil embolization. Samples were of adequate dimension. Histopathological positivity was 100%. The overall complication rate for uTJLB was 4.7% which was due to minor complications in two patients. Conclusions: Addition of US unit to the angiographic suite is effortless and Interventional Radiologists being already skilled in US can easily implement this simple yet valuable modification to conventional TJLB procedures. Our experience on uTJLB further emphasizes the role of US guidance in improving the procedural success rate, safety profile, and efficacy in the histopathological outcome of TJLB in all patients irrespective of age and disease burden.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

WE-DE-201-03: Combined Use of 192Ir, 60Co, and 169Yb Sources with the Novel Direction Modulated Brachytherapy Tandem Applicator for High Dose Rate Brachytherapy Planning of Cervical Cancer

Purpose: To evaluate the improvement in plan quality when various combinations of 192Ir, 60Co, and 169Yb sources are used in combination with a novel direction modulated brachytherapy (DMBT) tandem applicator for high dose rate brachytherapy of cervical cancer. Methods: The proposed DMBT tandem applicator is designed for image-guided adaptive brachytherapy (IGABT), especially MRI, of cervical cancer. It has 6 peripheral holes of 1.3-mm width, grooved along a 5.4-mm diameter nonmagnetic tungsten alloy rod of density 18.0 g/cc, capable of generating directional dose profiles - leading to enhanced dose sculpting capacity through inverse planning. Monte Carlo simulations of the three HDR sources individually inside the DMBT applicator were performed and imported into an in-house developed inverse optimization code. We then performed inverse planning with 14 cervical cancer patients enrolled in EMBRACE study. In all patients, 3D MRI-based planning was performed while utilizing 1) tandem-ring and needles attached-to-ring (7 patients) and 2) tandem-ring and needles both attached-to-ring and free-hand-loaded (7 patients), in accordance with the GEC-ESTRO recommendations. All plans were normalized to receive the same HRCTV D90 and DVH parameters were evaluated. Results: The DMBT tandem was used in all cases. Overall, the combined use of two sources (192Ir-60Co and 192Ir-169Yb, but not 60Co-169Yb) generally produced better quality plans than with the 192Ir source alone in terms of sparing OARs. For example, up to 3.5, 4.4, and 3.9% individual reductions in D2cc were observed for the bladder, rectum, and sigmoid, respectively, between 192Ir-60Co and 192Ir-only plans for patient cases in #1. While up to 5.5, 2.0, and 5.7% individual reductions were observed for patient cases in #2. Conclusion: We have demonstrated that, in addition to “directional modulation” of DMBT, use of multiple sources with sufficient differences in energy can be utilized to achieve additional improvement in plan quality for IGABT of cervical cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Techno-Economic Evaluation of Electrified Vehicle Options in Drayage Fleets

The electrification of drayage fleets offers potential economic and operational benefits, but the financial viability of electrified vehicles remains sensitive to battery cost, energy price, and fleet usage patterns. While total cost of ownership (TCO) is a useful benchmark, fleet operators and investors are equally concerned with investment performance metrics such as payback period (PB) and Internal Rate of Return (IRR), which better reflect financial risks and investment return timelines. This study develops a unified techno-economic framework that jointly evaluates TCO, PB, and IRR to determine when electrified trucks become cost-effective alternatives to diesel trucks. Building on a previously developed cost modeling tool and using real-world telematics data from a Class 8 drayage fleet at the Port of Savannah, the analysis incorporates projected battery cost trajectories, electricity and diesel price trends, vehicle efficiency improvements, and multiple battery capacities. Parameter ranges reflect widely cited projections and observed drayage-duty-cycle variability. A surrogate-modeling method approximates economic performance across thousands of battery cost–electricity price combinations, enabling high-resolution identification of conditions that achieve TCO parity, acceptable PB thresholds, and target IRR levels. Additionally, the study estimates the evolving share of the fleet that can feasibly electrify over time under multiple economic metrics. This integrated framework offers a novel, data-driven approach to inform risk-aware decision-making for fleet electrification and supports investment planning under evolving cost and operational conditions.

Sun, Ruixiao [ORNL] (ORCID:0000000341768676)↗
DOE OSTI2022

Developing the S 32 ( p , d ) S * 31 ( p ) ( γ ) reaction to probe the P 30 ( p , γ ) S 31 reaction rate in classical novae

Background: The 30 P(p,γ) 31 S reaction rate is one of the largest remaining sources of uncertainty in the final abundances of nuclei created in a classical nova involving a ONe white dwarf. The reaction rate directly influences silicon isotopic ratios, which are used as identifiers of presolar grains with nova origins. Additionally, the uncertainty in the 30 P(p,γ) 31 S reaction rate has been found to limit the use of nova nuclear thermometers based on observations of elemental ratios in nova ejecta. Purpose: Reduce uncertainties in the nuclear data for proton-unbound states in 31 S, which act as resonances for the 30 P(p,γ) 31 S reaction at classical nova temperatures, and develop a technique for high efficiency, high-resolution reaction-decay coincidence measurements. Methods: Here, the 32 S(p,d) 31 S reaction was used to populate the states of interest in 31 S. The experiment was performed at the Texas A&M Cyclotron Institute using the LLNL Hyperion array for the detection of charged particles and γ rays. A downstream silicon telescope was used to select reaction deuterons, and a single upstream silicon detector was used to measure protons emitted in the decay of unbound 31 S levels. Results: Several states in 31 S above the proton separation energy were observed to have been populated. Decay protons from the resonant states in 31 S were identified as events in the upstream silicon detectors that came in coincidence with deuterons in the downstream telescope. Protons emitted from these states were measured and branching ratios extracted. Conclusions: While no new reaction rate is derived, spin-parity assignments for several higher-lying proton unbound states have been confirmed. Measured p 0 branching ratios for these levels have been compared to previous measurements with good agreement, and in some cases provided a reduction in uncertainty. The previously identified T = 3/2 state may have been incorrectly assigned a large p 0 branching ratio in a previous measurement. The technique of measuring reaction-decay coincidences with a particle-gamma setup appears promising.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Machine learning-based optimization of air-cooled heat sinks

Machine learning-based models using Artificial Neural Network (ANN) and greedy search algorithm are used to optimize air-cooled parallel plate-finned heat sinks (PPFHSs) subjected to laminar flow over an extensive range of design parameters. Here, the thermal and hydraulic performances of PPFHSs are represented by heat transfer coefficient (h) and pressure drop (ΔP), respectively. Optimization objectives for PPFHS designs can vary from industry to industry depending on their design priorities. The present study proposes a novel and generalized optimization method that defines practical optimization objectives and provides an accurate optimization process to design effective PPFHSs for a wide range of industrial applications with different design requirements. Three optimization objectives are presented in this study: (i) the largest h PΔ, (ii) the largest h within a specified maximum allowed flow rate, and (iii) the lowest weight that maximizes h for operation within the maximum allowed flow rate. While the shortcoming of the first objective is demonstrated, the other two objectives are found to be suitable for designing effective heat sinks (HSs) across different applications. Results suggest a promising trend from the third objective to develop HSs with ~ 37-68% lower weight, 80-85% reduced ΔP, and negligible penalty in h compared with optimized HSs obtained from the second objective. However, since the third objective leads to HSs with thinner fins, structural analysis should be performed to ensure reliable operation of the HSs.

42 ENGINEERING↗
DOE OSTI2020

Real Time Data Analysis With the ATLAS Trigger at the LHC in Run-2

The trigger selection capabilities of the ATLAS detector have been significantly enhanced for the LHC Run- 2 in order to cope with the higher event rates and with the large number of simultaneous interactions (pile-up) per protonproton bunch crossing. A new hardware system, designed to analyse real time event-topologies at Level-1 came to full use in 2017. A hardware-based track reconstruction system, expected to be used real-time in 2018, is designed to provide track information to the high-level software trigger at its full input rate. The high-level trigger selections are largely relying on offline-like reconstruction techniques, and in some cases multivariate analysis methods. Despite the sudden change in LHC operations during the second half of 2017, which caused an increase in pile-up and therefore also in CPU usage of the trigger algorithms, the set of triggers (so called trigger menu) running online has undergone only minor modifications thanks to the robustness and redundancy of the trigger system, and the use of a levelling luminosity scheme in agreement with LHC and other experiments. Here, this presentation gives a brief yet comprehensive review of the real-time performance of the ATLAS trigger system in 2017. Considerations will be presented on the most relevant parameters of the trigger (efficiency to collect signal and output data rate) as well as details on some aspects of the algorithms which are run real-time on the High Level Trigger CPU farm.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Impact of installation faults in air conditioners and heat pumps in single-family homes on U.S. energy usage

To ensure that new residential air conditioners and heat pumps operate optimally, care must be taken during the initial system design and installation to avoid missteps that immediately degrade a system’s performance. Laboratory and simulation studies have quantified the impact that faults can have on capacity and efficiency. Field studies have demonstrated that installation-related faults are commonplace. However, the national impact of installation-related faults cannot be accurately estimated by only simulating a limited number of homes at several fault levels because of the variety of home characteristics and climates involved. In our analysis, we use an improved residential building stock simulation tool to predict the annual energy increase and additional utility costs resulting from two common installation faults: indoor airflow rate and refrigerant charge level. Our method considers the wide range of building characteristics and climate zones of the U.S. housing stock. We use existing field data to develop fault intensity probability distributions to inform our analysis. The study shows that these two faults result in approximately 20.7 TWh/y of additional energy use for central air conditioners and air-source heat pumps in U.S. single-family detached homes, which is a 9% increase over baseline (no-fault) usage, costing homeowners approximately $2.5 billion annually on utility bills. Air-source heat pumps are responsible for a disproportionate fraction of this energy use increase because of the larger number of operating hours compared to central air conditioners and the sensitivity of heating mode performance to the faults analyzed compared to cooling mode.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Early therapeutic effects of adaptive servo-ventilation on cardiac sympathetic nervous function in patients with heart failure evaluated using a combination of {sup 11}C-HED PET and {sup 123}I-MIBG SPECT

Rationale: Adaptive servo-ventilation (ASV), a novel respiratory support therapy for sleep disorders, may improve cardiac function in heart failure (HF). However, the reasons that ASV improves cardiac function have not been fully studied especially in sympathetic nervous function (SNF). The purpose of the present study was to investigate the effects of ASV therapy on cardiac SNF in patients with HF. Methods: We evaluated ASV therapeutic effects before and 6 months after ASV therapy in 9 HF patients [57.3 ± 17.3 years old, left ventricular ejection fraction (LVEF) 36.1 ± 16.7%]. We performed echocardiography, polysomnography, biomarkers, {sup 11}C-hydroxyephedrine (HED) PET as a presynaptic function marker and planar {sup 123}I-metaiodobenzylguanidine (MIBG) to evaluate washout rate. Results: ASV therapy reduced apnea-hypopnea index (AHI) and improved plasma brain natriuretic peptide (BNP) concentration. In {sup 123}I-MIBG imaging, the early heart/mediastinum (H/M) ratio increased after ASV therapy (2.19 ± 0.58 to 2.40 ± 0.67; P = 0.045). Washout rate did not change (23.8 ± 7.3% to 23.8 ± 8.8%; P = 0.122). Global {sup 11}C-HED retention index (RI) improved from 0.068 ± 0.033/s to 0.075 ± 0.034/s (P = 0.029). Conclusions: ASV reduced AHI and improved BNP. ASV might initially improve presynaptic cardiac sympathetic nervous function in HF patients after 6 months of treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Efficient data-driven models for prediction and optimization of geothermal power plant operations

Increasing the capacity of geothermal energy as a renewable resource calls for development and deployment of efficient control and optimization technologies for geothermal power plants. A data-driven prediction and optimization model is presented as a cost-effective and efficient alternative to physics-based approach. The model predicts power output and operational cost by propagating the influence of control and disturbance variables within an artificial neural network (ANN). Numerical experiments with simulated and field data from a real geothermal power plant are first used to demonstrate the prediction performance of the ANN model. The model is then adopted to maximize the net predicted power production by automatically adjusting the working fluid circulation rate. The optimization performance of the model in evaluated using a thermodynamic flowsheet simulation model. The workflow is applied to model and control the effect of ambient temperature on an air-cooled binary cycle power plant, which is complex and costly to perform using a physics-based predictive model. As a result, the performance of the method is demonstrated by applying it to both simulated and field datasets from a binary cycle geothermal power plant.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Improved Li storage performance in SnO 2 nanocrystals by a synergetic doping

Tin dioxide (SnO 2 ) is a widely investigated lithium (Li) storage material because of its easy preparation, two-step storage mechanism and high specific capacity for lithium-ion batteries (LIBs). In this contribution, a phase-pure cobalt-doped SnO 2 (Co/SnO 2 ) and a cobalt and nitrogen co-doped SnO 2 (Co-N/SnO 2 ) nanocrystals are prepared to explore their Li storage behaviors. It is found that the morphology, specific surface area, and electrochemical properties could be largely modulated in the doped and co-doped SnO 2 nanocrystals. Gavalnostatic cycling results indicate that the Co-N/SnO 2 electrode delivers a specific capacity as high as 716 mAh g –1 after 50 cycles, and the same outstanding rate performance can be observed in subsequent cycles due to the ionic/electronic conductivity enhancement by co-doping effect. Further, microstructure observation indicates the existence of intermediate phase of Li 3 N with high ionic conductivity upon cycling, which probably accounts for the improvements of Co-N/SnO 2 electrodes. Furthermore, we find that the method of synergetic doping into SnO 2 with Co and N, with which the electrochemical performances is enhanced remarkably, undoubtedly, will have an important influence on the material itself and community of LIBs as well.

25 ENERGY STORAGE↗
DOE OSTI2024

First application of a liquid argon time projection chamber for the search for intranuclear neutron-antineutron transitions and annihilation in 40 Ar using the MicroBooNE detector

We present a novel methodology to search for intranuclear neutron-antineutron transition (n→n̅) followed by n̅-nucleon annihilation within an 40 Ar nucleus, using the MicroBooNE liquid argon time projection chamber (LArTPC) detector. A discovery of n→n̅ transition or a new best limit on the lifetime of this process would either constitute physics beyond the Standard Model or greatly constrain theories of baryogenesis, respectively. The approach presented in this paper makes use of deep learning methods to select n→n̅ events based on their unique features and differentiate them from cosmogenic backgrounds. The achieved signal and background efficiencies are (70.22 ± 6.04)% and (0.0020 ± 0.0003)%, respectively. A demonstration of a search is performed with a data set corresponding to an exposure of 3.32 ×10 26 neutron-years, and where the background rate is constrained through direct measurement, assuming the presence of a negligible signal. With this approach, no excess of events over the background prediction is observed, setting a demonstrative lower bound on the n→n̅ lifetime in 40 Ar of τ m ≳ 1.1×10 26 years, and on the free n→n̅ transition time of τ n→n̅ ≳ 2.6×10 5 s, each at the 90% confidence level. This analysis represents a first-ever proof-of-principle demonstration of the ability to search for this rare process in LArTPCs with high efficiency and low background.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Younger facial looks are associate with a lower likelihood of several age-related morbidities in the middle-aged to elderly

Abstract Background Looking older for one’s chronological age is associated with a higher mortality rate. Yet it remains unclear how perceived facial age relates to morbidity and the degree to which facial ageing reflects systemic ageing of the human body. Objectives To investigate the association between ΔPA and age-related morbidities of different organ systems, where ΔPA represents the difference between perceived age (PA) and chronological age. Methods We performed a cross-sectional analysis on data from the Rotterdam Study, a population-based cohort study in the Netherlands. High-resolution facial photographs of 2679 men and women aged 51.5–87.8 years of European descent were used to assess PA. PA was estimated and scored in 5-year categories using these photographs by a panel of men and women who were blinded for chronological age and medical history. A linear mixed model was used to generate the mean PAs. The difference between the mean PA and chronological age was calculated (ΔPA), where a higher (positive) ΔPA means that the person looks younger for their age and a lower (negative) ΔPA that the person looks older. ΔPA was tested as a continuous variable for association with ageing-related morbidities including cardiovascular, pulmonary, ophthalmological, neurocognitive, renal, skeletal and auditory morbidities in separate regression analyses, adjusted for age and sex (model 1) and additionally for body mass index, smoking and sun exposure (model 2). Results We observed 5-year higher ΔPA (i.e. looking younger by 5 years for one’s age) to be associated with less osteoporosis [odds ratio (OR) 0.76, 95% confidence interval (CI) 0.62–0.93], less chronic obstructive pulmonary disease (OR 0.85, 95% CI 0.77–0.95), less age-related hearing loss (model 2; B = −0.76, 95% CI −1.35 to −0.17) and fewer cataracts (OR 0.84, 95% CI 0.73–0.97), but with better global cognitive functioning (g-factor; model 2; B = 0.07, 95% CI 0.04–0.10). Conclusions PA is associated with multiple morbidities and better cognitive function, suggesting that systemic ageing and cognitive ageing are, to an extent, externally visible in the human face.

Mekić, Selma↗
DOE OSTI2024

A Novel Spinel High-Entropy Oxide (Cr0.2Mn0.2Co0.2Ni0.2Zn0.2)3O4 as Anode Material for Lithium-Ion Batteries

In this study, we synthesized spinel high-entropy oxide (HEO) (Cr0.2Mn0.2Co0.2Ni0.2Zn0.2)3O4 nanoparticles by a simple solution combustion method. These particles were investigated for their performance as anodes in lithium-ion batteries. The reversible capacity is 132 mAh·g−1 after 100 cycles at a current density of 100 mA·g−1, 107 mAh·g−1 after 1000 cycles at a current density of 1 A g−1, and 96 mAh·g−1 rate capacity at a high current density of 2 A g−1. The outstanding cycle stability under high current densities and remarkable rate performance can be attributed to the stable structure originating from the high entropy of the material.

25 ENERGY STORAGE↗
DOE OSTI2024

Efficient Anomaly Detection Driven By Different Machine Learning Architectures And Models

The rapid growth and ubiquitous adoption of the internet and cyber-physical systems (CPS) have fundamentally transformed modern communication, work, and human-system interactions. While networks now form the backbone of critical digital ecosystems, enabling seamless data transmission across diverse, interconnected systems, this increased connectivity also expands the attack surface, making real-time detection of network intrusions and anomalies a pressing challenge. Detecting unusual activities within network infrastructure requires advanced data traffic analysis to differentiate between legitimate and malicious interactions. Traditional approaches to network anomaly detectionâ??such as rule-based and signature-based systemsâ??often depend on predefined patterns to identify known anomalies, limiting their effectiveness against emerging, stealthy, or previously unseen threats. These conventional methods suffer from high false alarm rates and fail to adapt to the ever-evolving nature of network traffic, particularly in large-scale, decentralized environments where data volume, velocity, and variety are constantly increasing. This dissertation presents artificial intelligence (AI)-driven approaches to anomaly detection that leverage graphics processing unit (GPU)-enabled high-performance computing (HPC) platforms for processing massive network traffic data and monitoring the components of cyber-physical systems (CPS) for potentially hazardous conditions. The research advances several key contributions: (1) Designing efficient machine learning techniques for CPS condition monitoring and anomaly detection; (2) enabling federated learning (FL) frameworks that enable distributed detection while preserving data privacy and system resilience; (3) exploring graph-based methodologies combining graph neural networks (GNN) and graph machine learning (ML) approaches for the Internet of Things (IoT) and automotive network security, and (4) performing distributed edge computing optimizations that integrate FL with scalable technologies for reduced communication overhead. Through extensive experiments, these methodologies demonstrate that complex anomaly detection and condition monitoring tasks can be achieved while balancing computational efficiency and detection accuracy through fine-grained network information processing. The frameworks developed in this research establish a robust foundation for network anomaly detection, providing scalable, adaptive, and privacy-preserving solutions for safeguarding CPS and IoT networks in an increasingly interconnected digital landscape. The practical implications of these research findings are significant, as they can inform the development of next-generation network security systems and contribute to the protection of critical infrastructure against sophisticated cyber attacks.

Marfo, William↗
DOE OSTI2024

An Na/TM-site Mg substituted P2-Na 2/3 [Fe 1/3 Mg 1/12 Mn 7/12 ]O 2 cathode with extremely high capacity for sodium-ion batteries

The anionic redox reaction (ARR) has become a hot topic in battery research due to its ability to provide high energy density. Nevertheless, there are still many issues in Na-based layered oxides with the ARR, such as large voltage hysteresis, lattice oxygen loss, irreversible structural changes, and cation migration in the TM layer, resulting in structural collapse and poor electrochemical performance. Herein, a series of Na 2/3 [Fe 1/3 Mg x Mn 2/3–x ]O 2 cathodes are synthesized using a traditional solid-state reaction method. The effectiveness of Mg substitution amounts and site occupancy in regulating the reversibility of the ARR has been explored using various experimental techniques. Surprisingly, the well-designed Na/TM-site Mg substituted P2-Na 2/3 [Fe 1/3 Mg 1/12 Mn 7/12 ]O 2 exhibits an extremely high initial reversible capacity of ~253.21 mA h g –1 , equivalent to ~0.94 e – transfer, which is contributed by both cationic and anionic redox reactions as confirmed by hard X-ray absorption spectroscopy (hXAS) and soft X-ray absorption spectroscopy (sXAS) analyses. In addition, the improved cycling and high-rate performance of the P2-Na 2/3 [Fe 1/3 Mg 1/12 Mn 7/12 ]O 2 are achieved by a well-maintained crystal structure and the highly reversible anionic redox reaction of O 2– /O n– . Finally, these in-depth studies provide crucial knowledge for the development and understanding of cathode materials with a highly reversible ARR for low-cost and high-energy sodium-ion batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling Isothermal Reduction of Iron Ore Pellet Using Finite Element Analysis Method: Experiments & Validation

Iron ore pellet reduction experiments were performed with pure hydrogen (H2) and mixtures with carbon monoxide (CO) at different ratios. For direct reduction processes that switch dynamically between reformed natural gas and hydrogen as the reductant, it is important to understand the effects of the transition on the oxide reduction kinetics to optimize the residence time of iron ore pellets in a shaft reactor. Hence, the reduction rates were studied by varying experimental parameters such as the temperature (800, 850 & 900 °C), reactant gas flow rate (100, 150 & 200 cm3/min), pellet size and composition of the reactant gas mixture. The rate of reduction was observed to increase with an increase in temperature and reactant gas flow rate, but it decreased with an increase in pellet size. SEM greyscale analysis was performed to analyze the porosity and phase composition of partially reduced pellets. The porosity of the pellets was observed to increase from 0.3 for unreacted pellet to 0.42 for a completely reduced pellet. Energy-dispersive X-ray spectroscopy (EDAX) analysis was performed to identify the phases observed in the SEM images. The fraction of iron phase was observed to increase from the shell region of the pellet to the core region with an increase in the degree of reduction. A 2D-axisymmetric numerical model was developed on COMSOL Multiphysics, and it was validated using the conversion (X) vs. time curves obtained from each experiment. The model was able to accurately predict the total time needed for the complete conversion of a single iron ore pellet for multiple experiments. Effects of changes in the porosity and tortuosity of the pellet on the model were also studied and the rate of reduction was observed to be sensitive to changes in both porosity and tortuosity. The SEM analysis and the model results show that tortuosity is higher for pellets reduced with H2 than for pellets reduced with H2-CO gas mixtures.

08 HYDROGEN↗
DOE OSTI2016

Impact of axial velocity and transmembrane pressure (TMP) on ARP filter performance

The Savannah River Site (SRS) is currently treating radioactive liquid waste with the Actinide Removal Process (ARP) and the Modular Caustic Side Solvent Extraction Unit (MCU). Recently, the low filter flux through the ARP of approximately 5 gallons per minute has limited the rate at which radioactive liquid waste can be treated. Salt Batch 6 had a lower processing rate and required frequent filter cleaning. Savannah River Remediation (SRR) has a desire to understand the causes of the low filter flux and to increase ARP/MCU throughput. One potential method for increasing filter flux is to adjust the axial velocity and transmembrane pressure (TMP). SRR requested SRNL to conduct bench-scale filter tests to evaluate the effects of axial velocity and transmembrane pressure on crossflow filter flux. The objective of the testing was to determine whether increasing the axial velocity at the ARP could produce a significant increase in filter flux. The authors conducted the tests by preparing slurries containing 6.6 M sodium Salt Batch 6 supernate and 2.5 g MST/L, processing the slurry through a bench-scale crossflow filter unit at varying axial velocity and TMP, and measuring filter flux as a function of time.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

High-temperature electrochemical performance of low-cost La–Ni–Fe based hydrogen storage alloys with different preparation methods

Highlights: • Effects of four different preparation processes were studied at 20/60 °C. • All NS + HT, RS and RS + HT processes can optimize the thermodynamic performance. • The HT process can provoke the precipitation of A{sub 2}B{sub 7} and leads to a poor cycling life. • Al exhibits the most remarkable dissolution for all the alloys, especially at 60 °C. - Abstract: In order to optimize the microstructure and high temperature electrochemical performances of low-cost AB{sub 5}-type Ml(NiMnAl){sub 4.2}Co{sub 0.3}Fe{sub 0.5} hydrogen storage electrode alloys, four different preparation methods including normal solidification (NS), normal solidification and 900 °C heat treatment (NS + HT), rapid solidification (RS), rapid solidification and 900 °C heat treatment (RS + HT) were adopted in this work. All alloys exhibit CaCu{sub 5} type hexagonal structure and there is a small amount of A{sub 2}B{sub 7} phase in NS + HT and RS + HT alloys. It is found the using of HT process can decrease the hydrogen equilibrium plateau pressure, the plateau slope and hysteresis at 40, 60 and 80 °C. The NS + HT and RS + HT alloys also possess better activation, high rate discharge performance, larger discharge capacity, but poor cycling performance due to the existence of A{sub 2}B{sub 7} phase which can accelerate dissolution of Ni, Mn and Fe elements in KOH alkaline electrolyte. The RS process can make alloy exhibit the best cycling performance especially at 60 °C.

36 MATERIALS SCIENCE↗