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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Impact of Lithium‐Free Borate Additives on the Cycle Life and Calendar Aging of Silicon‐Based Lithium‐Ion Batteries

Silicon-anode lithium-ion batteries (LIBs) suffer from limited cycle life and poor calendar life, constraining their large-scale commercialization. Integrating additives into electrolytes is a simple and cost-effective strategy to improve these aspects. The effects of lithium-free boron-based additives on cycling and calendar performance of high-loading Si-anode LIBs remain largely unexplored. In this work, the influence of five Li-free borate additives, each with distinct molecular structures and elemental compositions, is systematically investigated. All additives enhance cycle life to varying extents. Notably, the addition of 1 v/v% tri(2,2,2-trifluoroethyl) borate to the baseline electrolyte nearly doubles the cycle life at 50% state of health. This enhancement is attributed to three key factors. Specifically, borate additives 1) improve electrochemical activity, 2) act as anion receptors that interact with [PF6]- anions and carbonate solvents to reduce electrolyte decomposition, and 3) promote the formation of a stable and polymeric solid electrolyte interphase layer. Furthermore, these additives exhibited negligible impact in mitigating leakage current during a 180 h voltage-hold calendar-aging test, indicating their limited effect in calendar life. These findings provide insight into the role of Li-free borate additives in improving cycle life while addressing the knowledge gap regarding their influence on calendar aging.

Li, Defu↗
DOE OSTI2023

Mycorrhizal status and host genotype interact to shape plant nutrition in field grown maize ( Zea mays ssp. mays )

Arbuscular mycorrhizal fungi (AMF) establish symbioses with the major cereal crops, providing plants with increased access to nutrients while enhancing their tolerance to toxic heavy metals. However, not all plant varieties benefit equally from this association. In this study, we used quantitative trait loci (QTL) mapping to evaluate the combined effect of host genotypic variation (G) and AMF across 141 genotypes on the concentration of 20 mineral elements in the leaves and grain of field grown maize (Zea mays spp. mays). Our mapping design included selective incorporation of a castor AMF-incompatibility mutation, allowing estimation of AMF, QTL and QTLxAMF effects by comparison of mycorrhizal and non-mycorrhizal plants. Overall, AMF compatibility was associated with higher concentrations of boron (B), copper (Cu), molybdenum (Mo), phosphorus (P), selenium (Se) and zinc (Zn) and lower concentrations of arsenic (As), iron (Fe), magnesium (Mg), manganese (Mn), potassium (K) and strontium (Sr). In addition to effects on individual elements, pairwise correlation matrices for element concentration differed between mycorrhizal and non-mycorrhizal plants. We mapped 22 element QTLs, including 18 associated with QTLxAMF effects that indicate plant genotype-specific differences in the impact of AMF on the host ionome. Although there is considerable interest in AMF as biofertilizers, it remains challenging to estimate the impact of AMF in the field. Our design illustrates an effective approach for field evaluation of AMF effects. Furthermore, we demonstrate the capacity of the ionome to reveal host genotype-specific variation in the impact of AMF on plant nutrition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Impurity Powder Injection Experiments in the Large Helical Device

The Impurity Powder Dropper (IPD) is a device capable of injecting controlled amounts of sub-millimetre powder into the plasma under the action of gravity. In 2019 the IPD was first installed on the Large Helical Device (LHD) in Japan, with the aim of improving the plasma performances through real time boronization and assessing the compatibility of this technique with steady state operation. Extensive series of experiments have been performed using the IPD, focused on the improvement of the plasma performance via low-Z powder injection and the understanding of the underlying physical phenomena. In this article, we review the experiments that took place in the period 2019-2024. The main results include the demonstration of the improvement of the wall conditions (reduction of intrinsic impurity content, wall recycling) both on a shot-to-shot basis and in real time. Furthermore, a reduced-turbulence improved confinement regime has been observed coincident with powder injection, resulting in an increase of the plasma temperature of the order of 25%, with enhancements that can reach up to 50% for ion temperature.

Nespoli, F. [Princeton Plasma Physics Laboratory (↗
DOE OSTI2024

Monte Carlo Simulations of 347H Stainless Steel Aging for the Synthetic Generation of Microstructures Under Creep Conditions

Here, a Monte Carlo simulation method capable of replicating the kinetics of M 23 C 6 precipitation in 347H stainless steels was developed for the purpose of producing synthetic microstructures that approximate its microstructural evolution under aging periods of up to 10,000 hours at temperatures between 600 °C and 750 °C. To accomplish this, experimental data from the literature was used to parameterize simulations and replicate the nucleation and growth kinetics of M 23 C 6 particles within 347H and similar austenitic stainless steel alloys. These simulations were found to have considerable fidelity to previous efforts to study the precipitation of M 23 C 6 in other 300 series stainless steel alloys. Synthetic 347H microstructures were then generated that accounted the effects of aging temperature, duration, dislocation density, and the presence of boron within the microstructure. These simulations predict several key trends, those being that (1) the size of M 23 C 6 precipitates decreased with aging temperature and (2) the growth rate of M 23 C 6 particles decreased with aging temperature. Further, while (3) the addition of dislocation density due to creep conditions resulted in increasing intragranular nucleation of M 23 C 6 precipitates with increasing dislocation density and (4) B additions within the microstructure led to modest increases in precipitate size above 700 °C, which indicates that more complex physics are necessary to account for the presence of B.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Room Temperature Stamping of High-Strength Aluminum for Lightweight Structural Automotive Components

The use of aluminum (Al) 7xxx series in automobile structural applications is limited by factors such as its low room-temperature formability in T6 temper and the need for off-line artificial aging to regain high strength if it is formed in soft temper. In this study, two tempers were established that enable Al 7075 blanks to be room temperature stamped to create side impact beams that achieve near-T6 strength without post-forming artificial aging. It is shown that natural aging at room temperature, after solution treatment and before stamping, provides an alternative to high temperature pre-aging and hot stamping techniques in 7xxx alloys. Both tempers enabled room temperature stamping of the beams without cracking, indicating good formability. The Al beams were ~38% lighter than the benchmark boron steel beam. Further, the hardness in the low-deformation regions of the stamped Al beams were within 88% of a conventional 7075-T6 sheet. Paint-bake treatment of the beams appeared to cause over aging, lowering the ultimate tensile strength and ductility. Finite element three point bending simulations of the beams showed higher bending force and energy absorption before failure for the Al 7075 showing good promise for 7xxx series Al as a light-weight alternative to steel beams.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Effect of thermal aging on corrosion behavior of duplex stainless steels

Abstract Despite their exceptional mechanical and corrosion properties, duplex stainless steels (DSS) have not found widespread use in high-temperature applications due to concerns over thermal aging and embrittlement at elevated operational temperatures (> 300 °C). The present study investigated the effect of thermal aging time on the electrochemical properties of lean and standard grade DSS that are exposed to a range of pressurized water reactors containing LiOH and H 3 BO 3 . The results indicated that the electrolyte chemistry plays a significant role in the corrosion behavior of the DSS alloys. Corrosion resistance decreased with thermal aging time for all DSS alloys; however, standard grade DSS (2205 and 2209-w) alloys showed better corrosion resistance than lean grades (2003, 2101, 2101-w). The presence of dissolved oxygen in the electrolytes resulted in a significant increase in corrosion rate for the DSS alloys, but it did not affect the general trend of corrosion rates with aging time. All DSS alloys became vulnerable to pitting corrosion due to chloride addition, but the pitting resistance decreased with increasing thermal aging time. Increased boron B content resulted in degradation of corrosion resistance of the DSS alloys, while minor changes in pH did not show a significant change in corrosion resistance. Mechanical and metallurgical characterization coupled with electrochemical characterization of the DSS alloys gave a comprehensive insight into the effects of thermal aging on the electrochemical response of the DSS. Graphical abstract

Murkute, Pratik (ORCID:0000000278636346)↗
DOE OSTI2021

Synthesis and ion-irradiation tolerance of the Dy2TiO5 polymorphs

In developing improvements in nuclear fuels, work has been conducted in replacing boron with lanthanides to act as neutron absorbent materials. To further this development for the first time the three major polymorphs of Dy2TiO5 have been fabricated as bulk, single-phase materials in a systematic study. Crystal structure refinement has been carried out from powder x-ray diffraction data, with further structural detail attained via electron diffraction. A cubic phase, defect-pyrochlore, Fd-3m space group, was found with cell parameter a = 10.2996 (1) angstrom and oxygen x48f positional parameter = 0.331 (1). Dy2TiO5 was also fabricated as a bulk, single-phase compound with hexagonal symmetry, P6(3)/mmc space group, with cell parameters a = b = 3.6307(2), c = 11.8963(8) angstrom. The radiation response for each of the polymorphs has been investigated in-situ via 1 MeV Kr - ion-irradiation and transmission electron microscopy characterisation at the IVEM-TANDEM facility, Argonne National Laboratory. Critical temperatures, T-c, for maintaining crystallinity during irradiation were determined and showed Dy2TiO5 with either orthorhombic or cubic symmetry to perform the best, with the lowest T-c values of 711 and 761 K respectively when compared with the hexagonal form. These relatively low T-c values may be attributed to different characteristics for each phase; high anti-site defect formation energy for the orthorhombic symmetry, and the ability to accommodate disorder for the cubic symmetry.

Burnable poison↗
DOE OSTI2023

Data-driven discovery of a formation prediction rule on high-entropy ceramics

The interest in high entropy ceramics (HECs) has increased steadily due to their superior properties. However, the prediction of their formation still poses challenges for the discovery of new systems. Here, we discover a rational rule for designing single-phase high entropy metal diborides (HEBs) using data-driven approach. The machine learning (ML) model is trained on data collected via high-throughput experiments (HTEs). K nearest neighbor (KNN) model shows an experimental validation accuracy of 93.75%. By implementing interpretable ML method, we demonstrate that a mismatch of the bonds between boron and transition metals (δ B-TM ) dominates the formation of HEBs. We propose an empirical rule that HEBs favor forming a single phase when δ B-TM < 3.66; otherwise, multiphase. The rule has a high accuracy of 93.33% for new HEBs predictions. In addition, we contribute 165 high quality HEBs data in total, which can promote the development of materials informatics in HEBs. Furthermore, this data-driven strategy can be expanded to accelerate the search for new HECs, paving a pathway to design novel HECs with superior properties rapidly.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Material extrusion with integrated compression molding of NdFeB/SmFeN nylon bonded magnets using small- and large-scale pellet-based 3D-printers

High-density bonded rare-earth magnets are manufactured using pellet-fed additive manufacturing (AM)/material extrusion and an integrated additive manufacturing-compression molding (AM-CM) process. Neodymium iron boron – samarium iron nitride in polyamide 12 (NdFeB-SmFeN/PA12) of 93 % weight fraction (65 % volume fraction) are used for the study. The mechanical properties (tensile strength and modulus), magnetic properties (maximum energy density, coercivity, remanence) are reported. Manufacturing parameters such as layer height, barrel temperatures, screw speed and gantry feed rate are optimized to obtain the highest possible density of the magnets using a small-scale desktop material extrusion printer. Large scale integrated additive manufacturing-compression molding (AM-CM) is then utilized to increase the density of the magnets by reducing porosity defects common in the material extrusion process. The density of as-printed magnets was 5.2 g/cm 3 with a BH max value of 124.14 kJ/m 3 , tensile strength of 20 MPa and a modulus of 2 GPa. AM-CM increased the density of the compound by 5.5 % (5.49 g/cm 3 ). The reduction in porosity was confirmed using X-ray tomography (XCT). Improvement in mechanical strength of the material was also observed, with an increase in tensile strength of 25 % (25.09 MPa) and increase in tensile modulus of 275 % (5.49 GPa). Scanning electron microscopy showed increased particle-matrix adhesion with the integrated AM-CM process.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Lead tolerance and bioremoval by four strains of green algae from Nigerian fish ponds

Heavy metals from industry pose threats to human and environmental health. Microalgae are prime candidates to remove heavy metals from water and soil due to their metal-binding affinities, high growth rates, and contamination tolerance. Strain selection and composition of resulting contaminated biomass must be considered for downstream processing. In this study, we assessed the ability of four microalgae strains (Chlorophyceae) that were isolated from contaminated Nigerian fish ponds to take up dissolved lead at environmentally relevant concentrations (<0.05 mg L -1 – WHO standard). In a microplate assay, all strains grew in the presence of lead, tolerating concentrations up to 60 ppm, though the addition of dissolved lead affected the growth of the four strains. In a photobioreactor assay, all strains demonstrated the ability to take up dissolved lead, with removal efficiencies ranging from 86 to 93%. The concentrations of lead in contaminated biomass, removal efficiencies, and bioconcentration factors were greatest in one of the isolates Chlorella sp. MOW 12. Our results reinforce the fact that live microalgae have a greater biosorption capacity. Lead recovery from freeze-dried biomass using five different reagents showed that a 0.1 M hydrochloric acid solution was the most effective, with 83.4% recovery. We also showed that presence of lead in the culture medium resulted in an increase in the quantity of protein in the biomass. Elemental analysis of lead-bound biomass showed an increase in elements including boron and copper and a decrease in cobalt and sodium. Synergystic and antagonystic effect in uptake of other elements was strain specific, suggesting the possibility of tailored wastewater treatments depending on specific requirements.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Reactor and fuel cycle performance of light water reactor fuel with 235 U enrichments above 5%

Recent advances in nuclear fuel materials research, particularly on the topic of accident-tolerant fuels, have brought up potential opportunities for expanding the operating envelope of existing light water reactors. As many of the performance improvements offered by these technologies may be most fully realized by increasing fuel enrichment beyond the standard 5% limit, this paper examines the potential reactor performance and fuel cycle performance of low-enriched uranium oxide fueled light water reactors by generically considering pressurized water reactors with 235 U enrichment from 5 to 7%. Advanced cladding, including accident-tolerant cladding, has the potential to increase fuel burnup limits related to hydrogen in the cladding that coincide with those limits associated with end-of-life reactivity. Therefore, higher enrichment will be necessary in order to realize the higher fuel burnups. This work includes evaluation of the fuel cycle length, discharge burnup, reactivity coefficients, and fuel cycle performance, including radioactive waste and environmental impact metrics per unit energy generated. The analysis was performed using the evaluation metrics from the US Department of Energy Office of Nuclear Energy Fuel Cycle Evaluation and Screening Study. The reactor performance and safety analysis show that enrichments between 5 and 7% would have similar fuel temperature and moderator temperature coefficients. However, the soluble boron coefficient would decrease in magnitude, requiring more corrosive boric acid in the coolant or other methods of reactivity control during the fuel cycle. At these higher enrichments the maximum burnup at the rim of the fuel pellet would increase by almost a factor of two, which is expected to impact the formation of high-burnup structure in the fuel and the corresponding thermo-mechanical fuel properties. The fuel cycle performance assessment shows that increasing enrichment reduces the quantity of high-level waste disposed per unit energy generated, but it increases the natural resource requirements normalized to a gigawatt-electricity-per-year basis. Another impact is the slightly higher discharge burnup, resulting in somewhat different activity levels of the spent nuclear fuel and high-level waste radioactivity at 100 and 100,000 years after fuel discharge. The environmental impacts—including land use, water use, carbon emission, and radiological exposure—are of the same magnitude per unit energy generated. Finally, however, the impacts are distributed differently. Less than 5% enrichment has marginally more impact on the back-end of the fuel cycle, and greater than 5% enrichment has marginally more impact on the front-end of the fuel cycle. Ultimately, no neutronic or reactor safety hindrances to employing light water reactor fuel with enrichments greater than 5% are identified; given the achievable reactor performance benefits with advanced fuels, further practical exploration of increased enrichment fuel is recommended.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Simulation of the BEAVRS benchmark using VERA

The Virtual Environment for Reactor Applications (VERA) is being developed by the Consortium for the Advanced Simulation of Light Water Reactors (CASL). Here, VERA is used to perform the Benchmark for Evaluation and Validation of Reactor Simulations (BEAVRS), which provides two cycles’ worth of operating power history, along with a full, detailed description of the geometry, and measured data. Cycle 1 and 2 are simulated with VERA and the results are compared to the measured zero power physics tests, critical boron concentration, and flux maps.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Genetic algorithm optimization of nuclear criticality experiment for reduction of intermediate-energy 239 Pu nuclear data uncertainties

Nuclear criticality experiments are conducted to investigate specific nuclear data important for safe handling and storage of fissile materials, reactor design and operation, and the validation of radiation transport codes. Incorrect or uncertain nuclear data can prohibitively impact operational safety limits, reactor licensing, and predictive simulation capability; therefore, integral measurements from criticality experiments are necessary and should be performed frequently. To maximize the impact of the integral measurements, it is important to consider experiment geometry, material selection, and component dimensions. When taking these considerations into account, the experiment design process becomes iterative and very time intensive. This work utilizes a genetic algorithm to efficiently explore potential nuclear criticality experiment designs for the Laboratory Directed Research & Development project PARADIGM (PARallel Approach of Differential and InteGral Measurements) at Los Alamos National Laboratory. In this paper, the building blocks of the genetic algorithm are discussed in detail, the genetic algorithm methodology is verified, and the genetic algorithm is used to produce three candidate experiment models for the final PARADIGM design. The three candidate models produced by the genetic algorithm consist of copper-reflected assemblies containing 14 repeating units of alumina, graphite, boron, and plutonium plates. Furthermore, in addition to the optimization results, final design considerations are also discussed for designs with a height and/or weight very close to or slightly above assembly machine operational limits.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Design and synthesis of astatinated benzothiazole compounds for their potential use in Targeted Alpha Therapy (TAT) strategies to treat Alzheimer's disease-associated amyloid plaques

Alzheimer's disease (AD) is a terminal neurodegenerative disease characterized by the buildup of amyloid fibrils, amorphous aggregates and tauopathies. Several treatment modalities, which rely on various biological processes to reduce disease burden, have been largely ineffective at treating Alzheimer's disease. Targeted alpha therapy (TAT) has demonstrated positive results in the treatment of cancer. Benzothiazole derivatives have been successfully shown to target these plaques and are used in several imaging applications. One such derivative, Flutemetamol (Vizamyl TM ) is an FDA approved diagnostic tool for PET imaging of AD-associated plaques. We report the radiolabeling of benzothiazole derivatives with 211 At, a 7.2 h alpha emitting radionuclide, using a copper catalyzed reaction with a boronic acid precursor molecule. In conclusion, our final compound [ 211 At]3'-At-PIB-OMe had a radiochemical yield of 55% and was found to be stable for at least 3 h in phosphate buffered saline.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Accurate activity determination of a californium neutron source

Accurately counting analog events requires constructing an electronics chain that produces one count for each input pulse. Here, in this work, we review the use of Nuclear Instrumentation Module electronic units for counting neutron capture events in a 3He tube. We identify two unique types of false trigger events in a leading-edge discriminator and show how a dual timer module can be used to produce a veto window to exclude these events. We use the constructed electronics chain to build an apparatus to measure neutron pulses from a 252 Cf neutron source. We compare the measurements with a Monte Carlo N-Particle (MCNP) model to determine the activity of the neutron source. Furthermore, by making additional measurements with borated polyethylene attenuators between the source and detector, we are able to determine the boron concentration of the polyethylene. This technique provides accurate determination of the source activity to a precision of 2.8% at the k=1 level. The method used is simple, inexpensive, and requires no additional calibrated instruments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Reaction of BCl 3 with H- and Cl-terminated Si(100) as a pathway for selective, monolayer doping through wet chemistry

The reaction of boron trichloride with the H and Cl-terminated Si(100) surfaces was investigated to understand the interaction of this molecule with the surface for designing wet-chemistry based silicon surface doping processes using a carbon- and oxygen-free precursor. The process was followed with X-ray photoelectron spectroscopy (XPS). Within the reaction conditions investigated, the reaction is highly effective on Cl-Si(100) for temperatures below 70°C, at which point both surfaces react with BCl$_3$. The XPS investigation followed the formation of a B 1s peak at 193.5 eV corresponding to (B-O)$_x$ species. Even the briefest exposure to ambient conditions lead to hydroxylation of surface borochloride species. However, the Si 2p signature at 102 eV allowed for a confirmation of the formation of a direct Si-B bond. Density functional theory was utilized to supplement the analysis and identify possible major surface species resulting from these reactions. This work provides a new pathway to obtain a functionalized silicon surface with a direct Si-B bond that can potentially be exploited as a means of selective, ultra-shallow, and supersaturated doping.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2027

Low thermal budget dopant activation in shallow junctions of implanted Si via Tunable plasma enhanced annealing

Low thermal budget (LTB) annealing has become increasingly critical for shallow junctions as semiconductor devices are scaled down. Plasma Enhanced Annealing (PEA) has emerged as a promising LTB annealing process, however its mechanisms remain unclear. In this study, arsenic and boron implanted silicon wafers were subjected to helium or argon ion bombardment generated by annealing plasmas under controlled ion energies and doses in a home-built annealing reactor. The structural and electrical changes were characterized by four-point probe measurements, secondary ion mass spectrometry, Raman spectroscopy and spectroscopic ellipsometry. A pronounced reduction in sheet resistance, accompanied by a decrease in the damage layer thickness demonstrates the surface selective annealing capability of PEA process. Comparative studies using He and Ar plasmas and related ion bombardment reveal a dependence of activation efficacy on both ion species and the dopant implantation profile. Furthermore, a multi-step annealing mechanism is proposed, consisting of an initial (low dose) structural recovery stage followed by the generation of “extended” defects and concluded at large doses by an enhanced dopant activation. The proposed annealing kinetics are thought to be controlled by ion flux, dose and energy. Finally, these results highlight PEA as an effective, surface-selective, LTB approach for shallow-dopant activation and near surface annealing, and provide mechanistic insights into PEA processes.

dopant activation↗
DOE OSTI2020

Inverse design of two-dimensional graphene/h-BN hybrids by a regressional and conditional GAN

Design of materials with desired properties is currently laborious and heavily relies on intuition of researchers through a trial-and-error process. To tackle this challenge, in this work we propose a novel regressional and conditional generative adversarial network (RCGAN) for inverse design of representative two-dimensional materials, the graphene and boron-nitride (BN) hybrids. RCGAN incorporates a supervised regressor network, thus overcoming the common technical barrier in the traditional unsupervised GANs, which cannot generate data when fed with continuous and quantitative labels. RCGAN can autonomously generate graphene/BN hybrids given any target bandgap values. These structures are distinguished from the ones used for training and exhibit high diversity for a given bandgap. Moreover, they exhibit high fidelity, yielding bandgaps within ~10% MAE F of the desired bandgaps as validated by density functional theory (DFT) calculations. Analysis by the principle component analysis (PCA) and modified locally linear embedding (MLLE) reveals that the generator has successfully generated structures following the statistical distribution of the real structures. It implies the possibility of the RCGAN in recognizing physical rules hidden in the high-dimensional data. The novel strategy for designing regressional GAN architecture together with the successful application to inverse design of materials would inspire further exploration in research fields beyond materials.

36 MATERIALS SCIENCE↗