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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

IImprove hydrogen sorption kinetics of MgH2 by doping carbon-encapsulated iron-nickel nanoparticles

Magnesium hydride (MgH2) with excellent hydrogen storage kinetics is important for the wide application of hydrogen energy. Herein, to accelerate the sorption kinetics of MgH2 and lower its dehydrogenation temperature, we design and prepare a carbon film coated dual transition metal alloy, the Fe0.64Ni0.36@C composite with a coreshell structure, and employ it as an additive to synthesize MgH2–Fe0.64Ni0.36@C system by ball-milling and hydriding combustion method. In contrast to pure MgH2, the initial hydrogen release temperature of the MgH2–Fe0.64Ni0.36@C composite lowers to 250°C from 480°C and the composite can absorb 5.18 wt% H2 within 20 min (150°C, 3 MPa H2). More importantly, the apparent activation energy of the dehydrogenation for decomposition of Fe0.64Ni0.36@C-doped MgH2 reduced from 162.8 ± 8.3 kJ/mol to 86.9 ± 4.6 kJ/mol. It is believed that the Fe@C and Mg2Ni/Mg2NiH4 formed on the surface of Mg/MgH2 act as intermediates of electron transfer between Mg2+ and H–, which synergistically enhanced the hydrogen absorption and desorption kinetics properties of the MgH2. Moreover, the MgH2 co-doped with the multiple in-situ formed active particles shows excellent cycling performance, indicative of potential application in practical hydrogen storage in the near future.

Ding, Zhenmin↗
DOE OSTI2022

Spark plasma sintered, MoNbTi-based multi-principal element alloys with Cr, V, and Zr

MoNbTi, MoNbTiZr, CrMoNbTiZr, and MoNbTiVZr multi-principal element alloys (MPEAs) were fabricated via spark plasma sintering (SPS) and investigated for use in high-strength applications. The fabrication method by SPS and powder metallurgy differs from those presented in the prior literature, where most MPEAs are fabricated using arc melting (AM) methods. Here cryogenic milling was used to maximize potential defect sinks (grain boundaries) for radiation resistance and to increase ultimate tensile strength through the Hall-Petch effect. SPS was chosen for consolidation in order to maintain a fine-grained structure during densification. Each alloy was characterized using x-ray diffraction and scanning electron microscopy for phase identification and compositional homogeneity. The base ternary alloy MoNbTi presented a predominantly single BCC system with minor cubic phases. The introduction of additional alloying elements—Zr, V, and Cr—heightened the phase complexity and increased the fractions of a secondary BCC phase and an HCP phase from Zr. The addition of Cr induced a larger fraction of the Laves phase to form. The addition of V caused the precipitation of small Mo inclusions. Thermodynamic analysis was performed to understand the separation of phases in each alloy. Discrepancies among the phase predictions generated by thermodynamic models, phases previously presented in the literature, and the characterization results suggest that MPEA fabrication methods, especially solid-state methods, require significant investigation to ensure that alloys can remain stable throughout their anticipated service lifetimes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thermoelectric performance in disordered Cu 2 ZnSnSe 4 nanostructures driven by ultra-low thermal conductivity

Here, high-energy reactive mechanical alloying (ball milling) was used to synthesize tetragonal and cubic polymorphs of Cu 2 ZnSnSe 4 . The ordered tetragonal (I-4) polymorph undergoes a phase transition above 400 K into a Cu-Zn disordered tetragonal (I-42 m) polymorph, while the cubic (F-43 m) polymorph with full cation disorder is stabilized at room temperature. Both polymorphs show ultra-low thermal conductivities, 0.42 W m -1 K -1 at 722 K and 0.21 W m -1 K -1 at 523 K for the disordered tetragonal and cubic phases respectively. The cubic polymorph has a higher zT in the low-temperature range, peaking at 0.26 (523 K), while the disordered tetragonal has a maximum zT of 0.46 at 712 K. The latter is the highest reported zT for stoichiometric Cu 2 ZnSnSe 4 , comparable to the best-performing doped materials in the literature. A combination of experimental results and ab-initio calculations point to a coupling between structural disorder and microstructure as the mechanism behind the reported performance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Landfilled coal ash for carbon dioxide capture and its potential as a geopolymer binder for hazardous waste remediation

In this report, the legacy of global fossil fuel usage is not just the increase in global warming due to CO 2 production, but also the billions of tons of toxic coal ash disposed in landfills. This investigation evaluates the merits of using high-calcium landfilled coal fly ash of different disposal durations and granulated blast furnace (GBF) slag as primary raw materials for production of a new class of geopolymer binder. Processing of landfilled coal fly ash, GBF slag and supplementary raw materials into a geopolymer binder was accomplished by a simple, scalable milling process in the absence of heating under a carbon dioxide environment. The resultant geopolymer cement binders were tested for carbon dioxide uptake, compressive strength, and heavy metal stabilization. The geopolymer binder demonstrated a desired balance of carbon dioxide uptake, strength and safety. These results also indicate that the performance of the geopolymer binder depends on the landfill disposal age of the coal fly ash.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Synthesis, sintering, and grain growth kinetics of Hf 6 Ta 2 O 17

Here Aasystematic study of the solid-state synthesis, pressureless sintering, and grain growth kinetics of Hf 6 Ta 2 O 17 is presented. The ideal conditions for solids-state synthesis of Hf 6 Ta 2 O 17 powder with minimal particle necking was 1250 °C for 2 h in air. The resultant powder has an average particle size of 210 ± 70 nm. The combined synthesis and ball-milling procedure produces highly sinterable Hf 6 Ta 2 O 17 powder, achieving > 97 % of theoretical density after pressureless sintering at 1600 °C for 2 h in air. The grain growth mechanism was sensitive to processing conditions, appearing to be primarily driven by surface diffusion below 1600 °C and grain boundary diffusion above 1650 °C. The respective activation energies for grain growth were found to be Q S = 659 ± 79 kJ mol -1 and Q GB = 478 ± 63 kJ mol -1 .

36 MATERIALS SCIENCE↗
DOE OSTI2022

Generalizability analysis of tool condition monitoring ensemble machine learning models

Tool condition monitoring (TCM) is an essential research area for the optimization and automation of metal machining processes, and could help manufacturers reduce costs, production time, machine downtime, energy use, and part scrappage. However, TCM systems developed in prior studies have struggled to reach the high level of generalizability which is necessary for industrial applications. This study addresses TCM system generalizability to new machining conditions, how variations in machining and environmental conditions may be used to improve model generalizability, and ensemble machine learning techniques for TCM. Further, milling tool life experiments were conducted using various machining conditions, and the processes' sound, spindle power, and axial load signals were collected. Different machine learning models were evaluated for the prediction of tool wear levels, including four individual models and five ensemble models. Changes in cutting speed were found to display a large effect on model performance, while the chip load showed some effect, and the feed rate had little effect. A simulated noise data augmentation technique for model improvement is applied within TCM for the first time, and resulted in increased model generalizability and reduced overfitting. Across several performance metrics the extremely randomized trees ensemble machine learning model generally performed the best for this application, achieving a leave-one-group-out cross validation accuracy score of 92.4 %, a 10-fold cross validation score of 98.9 %, and an averaged accuracy across 11 generalizability tests of 87.3 %.

42 ENGINEERING↗
DOE OSTI2023

Influence of topology optimization parameters on the mechanical response of an additively manufactured test structure

Topology Optimization (TO) determines a material distribution within a domain under given conditions and design constraints, and generally generates complex geometries as a result. Complementary to TO, Additive Manufacturing (AM) offers the ability to fabricate complex geometries which may be difficult to manufacture using traditional techniques such as milling. AM has been used in multiple industries including the medical devices area. Hence, TO may be used to create patient-matched devices where the mechanical response is catered to a particular patient. Furthermore, during a medical device regulatory 510(k) pathway, demonstrating that worst-cases are known and tested is critical to the review process. Using TO and AM to predict worst-case designs for subsequent performance testing may be challenging and does not appear to have been thoroughly explored. Investigating the effects of TO input parameters when AM is employed may be the first step in determining the feasibility of predicting these worst-cases.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Semihard magnetic properties of TiFe 2.5 iron-rich Laves phase and the effect of 4d- and 5d-element-substitutions for Ti

Rare-earth-free compounds exhibiting modest intrinsic hard magnetic properties may still yield viable permanent magnets if their constituent elements are abundant and inexpensive, and the properties are at least comparable to those of the hard ferrites. In this study, one such compound, the off-stoichiometric TiFe 2.5 Laves phase with the hexagonal C14 crystal structure, was found to exhibit – in addition to the already known room-temperature ferromagnetism – a uniaxial, albeit weak, magnetic anisotropy. With a Curie temperature of 422 K, saturation magnetization of 55.3 Am 2 /kg and magnetic hardness parameter of 0.97 this semihard compound is just below the threshold for being of interest for the development into permanent magnets. Replacing a small fraction of Ti with the 4d Nb and Mo or with the 5d Ta or W increases the anisotropy field, but only below room temperature. Replacing Ti with Zr or Hf increases the Curie temperature and leads to a spin reorientation below 200 K. All these substitutions, as well as combined (Zr,W) and (Nb,W) substitutions, fail to improve the room-temperature intrinsic hard magnetic properties of the Fe-rich Laves phase. Furthermore, an attempt to develop a room-temperature coercivity through high-energy ball-milling yielded a value of 0.026 T, an unusually small 2.9% fraction of the anisotropy field. Here, defects inherent in the C14 crystal lattice may be responsible for the underperformance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Micro-mechanical investigation of the thermo-mechanical properties of micro-architectured tungsten coatings

The thermo-mechanical response of micro-architectured tungsten coatings is characterized in the temperature range of 293 to 673 K using both in situ micro-compression experiments inside a scanning electron microscope (SEM) as well as image-based crystal plasticity finite element method (CPFEM) simulations. The experiments were conducted on micropillar-like specimens that were focus ion beam milled into the coatings, while the simulations were conducted on columnar-grained micropillar simulation cells constructed based on the statistics of the coating’s microstructure. The experimental results show that the stress–strain response and deformation mode exhibit a strong temperature-dependence. At room temperature, catastrophic failure is observed shortly after yield and is manifested in the form of intergranular fracture and buckling of individual columnar grains. With increasing temperature, this catastrophic failure is gradually suppressed and the material exhibits a steadier strain hardening response at 693 K. The CPFEM simulations are also shown to be in good agreement with the experimental results, and these simulations indicate that the material response is strongly influenced by the local crystallographic anisotropy and microstructure inhomogeneity. Furthermore, the simulations capture the underlying mechanisms that control the temperature-dependent transition in deformation mode. The current results highlight that the micro-architectured microstructure offers a great combination of excellent mechanical strength and structural integrity at elevated temperatures, which is of importance for high temperature applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Physics-guided logistic classification for tool life modeling and process parameter optimization in machining

This paper describes a physics-guided logistic classification method for tool life modeling and process parameter optimization in machining. Tool life is modeled using a classification method since the exact tool life cannot be measured in a typical production environment where tool wear can only be directly measured when the tool is replaced. Here, in this study, laboratory tool wear experiments are used to simulate tool wear data normally collected during part production. Two states are defined: tool not worn (class 0) and tool worn (class 1). The non-linear reduction in tool life with cutting speed is modeled by applying a logarithmic transformation to the inputs for the logistic classification model. A method for interpretability of the logistic model coefficients is provided by comparison with the empirical Taylor tool life model. The method is validated using tool wear experiments for milling. Results show that the physics-guided logistic classification method can predict tool life using limited datasets. A method for pre-process optimization of machining parameters using a probabilistic machining cost model is presented. The proposed method offers a robust and practical approach to tool life modeling and process parameter optimization in a production environment.

Machine learning↗
DOE OSTI2021

Enhancing thermal conductivity of UO 2 with the addition of UB 2 via conventional sintering techniques

We report that uranium dioxide has been the primary fuel type used in light water reactors for more than 40 years and proven to be reliable and robust. However, the Fukushima-Daiichi nuclear accident has motivated new work evaluating fuels with characteristics promoting accident tolerance, including enhanced thermal conductivity. Recently, additives have been investigated to increase thermal conductivity, but research has been largely focused on non-fissile additions. This study investigated the use of fissile additives to not only increase the thermal conductivity but also increase the uranium loading. Uranium diboride was chosen as the additive for this study due to its promising corrosion behavior as well as its significantly higher thermal conductivity at 573 K (25 Wm -1 K -1 ) when compared to UO 2 (7 Wm -1 K -1 ). Uranium diboride powder was fabricated via the arc melting technique and a ball milling process prior to mixing with UO 2 in a 90/10 wt% UO 2 /UB 2 ratio. Green bodies were made using a uniaxial die and subjected to a traditional pressureless sintering technique at 2073 K in argon. Sintered samples were analyzed via laser flash analysis for thermal diffusivity and differential scanning calorimetry for specific heat capacity in order to calculate thermal conductivity. The samples displayed an increase of 36-55% in thermal conductivity between 323 K and 1273 K when compared to the benchmark samples (pure UO 2 ) as reported in open literature.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Europium diffusion in IG-110 nuclear graphite

Europium diffusion in graphite has been recognized to be of interest in high-temperature gas reactor safety analysis, particularly as an indicator of strontium diffusion. However, no measurements of europium diffusion coefficients have been reported in the literature. In this work, the effective diffusion coefficient of europium was measured using a time-release method. Natural europium was loaded into pre-milled unirradiated IG-110 graphite spheres using a pressurized acid digestion vessel. The time-release experiments were performed in the temperature range 1823 K – 1973 K using a SiC diffusion cell connected to an inductively-coupled plasma mass spectrometer (ICP-MS) via a He gas line. Finally, the results of this work are: D Eu, IG-110 = (1.5 x 10 -3 m 2 /s) exp $(\frac{-2.87\mathrm{x}10^{5} J/mol}{RT})$ This effective diffusion coefficient can be used to aid in predictive modelling of europium transport in HTGRs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Grain growth kinetics of the gamma phase metallic uranium

We report metallic uranium is a leading fuel form for sodium cooled fast reactors as an enabling technology of future nuclear energy systems. Mechanistic understanding of fuel behaviors and kinetics under thermodynamic equilibrium and highly non-equilibrium conditions are essential for evaluating fuel performance. It is important to understand and predict the grain and pore evolutions of metallic fuels under thermal and irradiation conditions. However, very limited data are available on the grain growth kinetics and mechanisms of pure gamma phase uranium. In this paper, the pure gamma uranium pellets with different grain structures were fabricated by combining high-energy ball milling and spark plasma sintering. Isothermal annealing tests were performed to investigate the grain growth behavior of the pure gamma phase uranium with different initial grain sizes. A parabolic relationship in grain growth with time was identified for the submicron-sized (374 nm) sample. In contrast, for the nano-sized (137 nm) sample, the grain growth shows a linear relationship with time. The activation energies of grain growth were determined as 199.5 KJ/mol and 80.6 KJ/mol for nano-sized and submicron-sized grain structures, respectively. For the nano-sized sample, the rate-control step of grain growth is dominated by the triple-junction migration, in which the grain boundary triple junction drags the grain growth, leading to a higher activation energy than the bulk diffusion. The dominating mechanism for the submicron-sized sample is grain boundary diffusion. The mechanistic understanding and critical data obtained on the kinetics of pure uranium phases will be useful to evaluate fuel behavior under thermodynamic equilibrium conditions and develop a high fidelity model to predict fuel performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Manufacturing porous U10Zr fuels with controlled porosities by SPS and thermal properties

To accommodate the swelling of metallic fuels induced by the fission gas release during burnup in sodium fast reactor for a sodium-free fuel option, advanced U-10Zr fuels with controlled porosity were designed and demonstrated by spark plasma sintering. U-10Zr fuel pellets with manufactured porosities varying from 35% up to fully dense fuel pellets have been fabricated by controlling ball milling times of the starting uranium powders, sintering temperature, pressure, and duration, and the correlation among the microstructure control – porosity – sintering conditions has been established. To further mimick the pore structure in irradiated fuels, different pore formers (NaCl and NH4HCO3) have been used to control the pore size and distribution. Microstructure characterization indicates a lamellar reaction zone of U and Zr, differing from the arc-melted U-10Zr as a result of rapid consolidation of SPS at lower temperature and short durations. The thermal conductivity of U10Zr with different porosities are also measured. Here this work demonstrates the success in manufacturing new metallic fuel forms with controlled porosities and pore distribution, which can be used as model systems to investigate the thermal transfer behavior of metallic fuels in the reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Investigating microstructural evolution in SolidStir™ extruded oxide dispersion strengthened 14YWT alloy fuel cladding tube

Structural components for extreme environments require advanced materials and manufacturing processes. One such advanced material is oxide dispersion strengthened (ODS) Fe–14 wt.%Cr–3W–0.4Ti–0.3Y 2 O 3 (14YWT), which is developed for components to be used in Gen IV and fusion nuclear reactors. However, the conventional manufacturing processes to produce components, such as fuel cladding tubes, either do not retain the desired microstructural attributes or are costly and less efficient. As a result, a more attractive option is a novel manufacturing process developed on the principle of friction stir welding or processing (FSW/P) and commercially referred to as SolidStir™ Extrusion (SSE). Here this study used the SSE technique to study the manufacturing and microstructural evolution of a fuel cladding tube made of ODS 14YWT alloy. The cladding extrusion by the SSE technique involved the use of ball-milled 14YWT powders with Y, Ti, and O in the solid solution and the use of a specially designed W-25Re-Hf tool for consolidation and extrusion of the powders. A scanning electron microscope (SEM), electron backscattered diffraction (EBSD), and transmission electron microscope (TEM) were utilized for microstructural characterization. A Keyence microscope captured macrostructural photographs of the extruded tube. EBSD examination of the extruded tube on both transverse and longitudinal cross-sections showed the presence of dynamically recrystallized grains and revealed that the average grain size of the transverse cross-section was smaller than that of the longitudinal cross-section. The texture was weak and consisted of some amount of shear texture. The presence of nano-oxide clusters or precipitates of Y, Ti, and O (pyrochlores) in the extruded tube was determined by TEM. Aging heat treatment caused the average precipitate size to decrease and the density to increase compared to the as-processed condition. The results indicated that SSE is a viable tool for manufacturing fuel cladding tubes with the desired microstructural attributes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Manufacturing Oxide Dispersion Strengthened (ODS) steel plate via cold spray and friction stir processing

Oxide dispersion strengthened (ODS) steels, traditionally fabricated by ball milling and conventional powder metallurgy techniques to achieve bulk form, followed by intricate rolling and thermal treatment steps to achieve plate or sheet form. Here, we present a novel processing route that combines cold spray (CS) with friction stir processing (FSP) to manufacture ODS steel plate directly from gas atomization reaction synthesis (GARS)-prepared powder, thus no rolling steps involved. Microstructural and mechanical characterizations were performed to assess the quality and properties of the resulting ODS steel plate. Our findings demonstrate that the slightly porous CS deposited layer was fully consolidated after FSP, yielding a fully dense ODS steel plate that exhibited a favorable tradeoff between strength and ductility upon extraction from the substrate. Furthermore, through microstructural analysis, we revealed the presence of an appreciable density (∼10 22 /m 3 ) of nano-sized oxide particles, with the majority being smaller than 5 nm via the combined CS + FSP fabrication route. This work serves as a first proof-of-concept demonstration of the manufacturing approach described herein, offering a possible alternative route for producing ODS steel plates.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optimization of catholyte for halide-based all-solid-state batteries

Halide solid electrolytes gain significant attention due to their high ionic conductivity, low processing temperature, dry air compatibility, and high-voltage stability. However, low cathode active material (CAM) loading in the composite cathode constrains the realization of high energy density for halide-based all-solid-state batteries. In this study, three halide materials, raw Li 3 YBrCl 5 (LYBC-R, <30μm), milled LYBC (LYBC-M, <5 μm) and freeze-dried Li 3 InCl 6 (LIC, <500 nm), were used as catholytes, combined with LYBC-M as the electrolyte and LiIn alloy as the anode. The CAM:catholyte ratio was investigated as well as stack pressure and operating temperature. Our study demonstrates that particle size of the catholyte plays an important role only for high CAM loading or high C-rate cycling. At moderate CAM loading (65 and 70wt% LiNi 0.83 Mn 0.06 Co 0.11 O 2 ) and 0.1 C-rate, all the three catholytes perform well, providing initial discharge capacities >177 mAh/g. At high CAM loading (85wt%) and 0.1 C-rate, a cathode with the nano-scale LIC catholyte provides discharge capacity of 175 mAh/g, while the larger particle size catholytes suffer significantly reduced capacity. Both LYBC and LIC catholytes provided capacity retention >80% after 200 cycles at 0.5C. These results imply that cathode particle size is critically important for performance at high CAM loading. Furthermore, both electrolyte and cathode were tape cast to scale up size and prepare realistic layer thicknesses. A small amount of binder was used in both layers, to balance the electrochemical performance and mechanical properties. Further, the discharge capacity of a tape cell was 152mA h/g at 0.1C with a capacity retention of 81.8% after 20 cycles at 0.5C. The results demonstrate the excellent performance of LYBC as an electrolyte, and provide guidance for halide-based cathode design.

25 ENERGY STORAGE↗
DOE OSTI2023

Identifying common stored product insects using automated deep learning methods

Monitoring stored product insect pests is a common practice for post-harvest management of stored grain and grain-based commodities, which helps ensure product quality from harvest to final consumer. Current methods of sampling and monitoring can be time-consuming, labor-intensive, expensive and require expertise in insect identification. Therefore, this study aims to develop an image-based automated identification system for common stored product insect species using deep-learning methods. Top-down images of the common stored product adult insect species of Rhyzopertha dominica, Cryptolestes ferrugineus, Tribolium castaneum, Sitophilus oryzae, and Oryzaephilus surinamensis were acquired and analyzed. Deep learning-based, state-of-the-art Convolutional Neural Networks (CNN) models (ResNet-50, MobileNet-v2, DarkNet-53, and EfficientNet-b0) were fine-tuned with a transfer learning approach to classify the insect species. All models were able to correctly identify the insect species with at least 96% accuracy and with few misclassifications. One issue with trained CNNs is that they do not explain the reasoning for the classification and are often called a “black box”. Therefore, visualization methods called Gradient-weighted Class Activation Mapping (Grad-CAM) were implemented to explore the black box network. The Grad-CAM uses heat maps to highlight the major image features that the network focused on to make insect species predictions. The Grad-CAM verifies the network's prediction and also helps improve network performance. This study contributes to the overall goal of developing a camera-based system for monitoring stored grain insects. As a result, the developed system would empower warehouse, flour mills, and other food facilities with a tool to quickly and accurately identify insect species in stored product environments and could be implemented as part of a close to real-time monitoring system.

60 APPLIED LIFE SCIENCES↗