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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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The optimum Mg 3 Sb 2 –Mg 3 Bi 2 alloy composition for thermoelectrics is modeled by analyzing transport properties and understanding changes in the electronic structure.
The impact of a parylene top-coating layer on the illumination and bias stress instabilities of indium-gallium-zinc oxide thin-film transistors (TFTs) is presented and discussed. The parylene coating substantially reduces the threshold voltage shift caused by continuous application of a gate bias and light exposure. The operational stability improves by 75%, and the light induced instability is reduced by 35%. The operational stability is quantified by fitting the threshold voltage shift with a stretched exponential model. Storage time as long as 7 months does not cause any measurable degradation on the electrical performance. It is proposed that parylene plays not only the role of an encapsulation layer but also of a defect passivation on the top semiconductor surface. It is also reported that depletion-mode TFTs are less sensitive to light induced instabilities. This is attributed to a defect neutralization process in the presence of free electrons.
Schottky barrier detectors (SBDs) require larger surface areas than conventional electronics to increase the detection efficiency although such SBDs manifest large diode ideality factors due to inhomogeneous areal distribution of surface barrier height (SBH). Inhomogeneous SBH distributions lead to various current flow mechanisms in SBDs, which need to be identified to optimize detector performance. In this Letter, we identify the current flow mechanism in large area Schottky barrier diodes for radiation detection fabricated on 150 μm thick n-4H–SiC epitaxial layers. The analysis of temperature-dependent forward current–voltage (I–V–T) characteristics of SBDs revealed two linear regions in current–voltage curves up to 450 K, one corresponding to the current flow through a low barrier patch, while the other corresponds to that of average barrier distribution. Applying a SBH distribution model to the reverse I–V–T characteristics, an activation energy of 0.76 eV for the current flow over the Schottky barrier was calculated. Additionally, the activation energy did not directly correspond to any of the defect levels observed from the deep level transient spectroscopy (DLTS). Above 450 K, a Schottky type barrier lowering suggested a current flow through a low barrier patch of ≈ 0.8 eV. The absence of any SBH lowering below 450 K indicated that the current corresponded to a neutrally charged trap level at ≈ 0.6 eV below the conduction band edge, which was consistent with DLTS measurements revealing the presence of an electron trap level Z1/2 at 0.59 eV below the conduction band edge.
In this work, we extend the well-known mapping between the easy-plane ferromagnet and electrostatics in d = 2 spatial dimensions to dynamical and quantum phenomena in a d = 2+1 spacetime. Ferromagnetic vortices behave like quantum particles with an electric charge equal to the vortex number and a magnetic flux equal to the transverse spin of the vortex core. Vortices with half-integer core spin exhibit fermionic statistics.
Using first-principles calculations and magnetic resonance experiments, we investigated the physical properties of the negatively charged nitrogen-vacancy (NV) center in 4H-SiC, a promising spin qubit. Our predictive theoretical model in conjunction with experimental measurements reveals a large sensitivity to strain and symmetry. The measured and computed zero-phonon lines (ZPLs) are in agreement and show a consistent trend as a function of the defect location in the crystal. The computed ZPLs are extremely sensitive to the geometrical configurations of the ground and excited states, and large supercells with more than 2 000 atoms are required to obtain accurate numerical results. We find that the computed decoherence time of the basal NV centers at zero magnetic field is substantially larger than that of the axial configurations. Furthermore, at natural nuclear spin abundance and zero field, the Hahn-echo coherence time of one of the basal configurations is similar to that of the axial divacancy in isotopically purified SiC.
Anoxygenic purple phototrophic bacteria have served as important models for studies of photophosphorylation. The pigment-protein complexes responsible for converting light energy to ATP are relatively simple and these bacteria can grow heterotrophically under aerobic conditions, thus allowing for the study of mutants defective in photophosphorylation. In the past, genes responsible for anoxygenic phototrophic growth have been identified in a number of different bacterial species. Here we systematically studied the genetic basis for this metabolism by using Tn-seq to identify genes essential for the anaerobic growth of the purple bacterium Rhodopseudomonas palustris on acetate in light. We identified 171 genes required for growth in this condition, 35 of which are annotated as photosynthesis genes. Among these are a few new genes not previously shown to be essential for phototrophic growth. We verified the essentiality of many of the genes we identified by analyzing the phenotypes of mutants we generated by Tn mutagenesis that had altered pigmentation. We used directed mutagenesis to verify that the R. palustris NADH:quinone oxidoreductase complex IE is essential for phototrophic growth. As a complement to the genetic data, we carried out proteomics experiments in which we found that 429 proteins were present in significantly higher amounts in cells grown anaerobically in light compared to aerobically. Among these were proteins encoded by subset of the phototrophic growth-essential genes.
The Materials Dynamics area of leadership focuses on understanding process-structure-properties-performance (PSPP) relationships for the extreme conditions of dynamic loading. This research encompasses controlled synthesis of materials to meet dynamic performance requirements and entails computational coupling across length and time scales for three-dimensional microstructure modeling. For this leadership area, we define dynamic loading as strain rates ≥ 10 3 /s and often, high pressures. A key grand challenge of this area is to predict and measure the evolution of microstructural phases, defect structures, and electronic structure under dynamic conditions while also measuring local temperature to understand transition states. Solving this challenge will require agile, multi-dimensional data analysis and interpretation capability.
Here, we investigate the heterogeneity of the stress state driven by anisotropic deformation response at the single crystal level through five statistical volume element (SVE) calculations of polycrystalline BCC tantalum. This work focuses on grain boundaries as a prominent material defect type prone to void nucleation based upon experimental observations of predominantly intergranular void nucleation in this material. The SVEs are constructed to be statistically representative of larger volumes of material and are meshed such that mean and standard deviation of grain size and orientation information is reconstructed. The computational meshes feature hexahedral (brick) elements and smooth conformal grain boundaries where significant stress concentration is known to occur, a tail effect of interest in the extreme events process of dynamic ductile damage. An existing micromechanical crystallographic plasticity model shown to capture the single crystal behavior of BCC tantalum well is used to perform the polycrystal calculations. The model includes representation of the non-Schmid effect of non-planar screw dislocation kinetics in tantalum. A three-dimensional stress state time profile predicted by damage modeling of a flyer plate impact experiment is applied as boundary conditions to each SVE. Resulting grain boundary stress state statistics are strongly non-Gaussian. Significant structural evolution is observed within the compressive hold before unloading into tension in the stress profile. Strong angular dependence of grain boundary traction magnitude with shock direction is observed. Non-Schmid effects continue to suggest their influence on propensity of microstructural defect types to nucleate voids. A general void nucleation criterion is proposed using probability theory. The general framework is specified to polycrystalline BCC tantalum in the weak shock regime to include the SVE calculations and literature molecular dynamics calculations of grain boundary void nucleation strength. Probability density functions (PDFs) are used to describe the interaction between the local stress state heterogeneity and the distributed grain boundary void nucleation strength state. A causation entropy maximization procedure removes the requirement for ad hoc selection of a PDF functional form and provides a rigorous procedure for data-based PDF determination. The resulting physically informed PDF describes the spatial appearance frequency of nucleated voids as a function of applied macroscale pressure. Lower length scale physics are thus packaged in a precise and computationally efficient way to provide computational plasticity insight to macroscale dynamic ductile damage models.
This report summarizes the mesoscale modeling work performed in fiscal year 2024 under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to capture the microstructural evolution and restructuring observed in the dark regions of high burnup UO 2 nuclear fuel. This is the first attempt to realistically simulate the restructuring behavior observed in different region of a high burnup fuel. We employ a grand-potential based phase-field model to concurrently evaluate the formation of subgrains and growth of fission bubbles within the fuel. A energy-based subgrain formation criteria is introduced to simulate the restructuring process. Effect of different initial conditions and different modeling parameters are studies systematically to capture how each of these parameters influence the characteristics of the restructured fuel. It is observed that the subgrain formation begins around existing fission gas bubbles and then proceeds towards triple junctions, grain boundaries and grain interiors. It is demonstrated that restructuring is influenced by a combination of initial dislocation densities, subgrain formation rate, and temperature. Rate of restructuring increases with increase in fuel temperature. A restructuring bias is observed within the microstructure due to variation in defect accumulation among different grains. Furthermore, bubble sizes and distribution does not have a significant effect on rate of restructuring. The predicted microstructures resembles the characteristics of the restructured regions as observed in experiments. Finally, a correlation is presented that demonstrates the evolution of the restructuring volume fraction as a function of local effective burnup. This work provides a first of its kind restructuring model for darkzone that can be used by BISON for performance prediction of high burnup UO 2 fuel.
In this work, we have utilized photoluminescence spectroscopy and optical ellipsometry to characterize the dose-dependence of the photoluminescence emission intensity and changes in optical absorption of thoria single crystals subject to irradiation with energetic protons at room- and elevated-temperatures. The photoluminescence peaks and the optical absorption bands are attributed to creation of new electronic states emerging from defects resulting from displacement damage. These bands are most likely associated with electrons trapped at the oxygen vacancy sites similar to color centers formed in other irradiated oxides and halides. Our experimental observations are supported by a standard density functional theory calculation of the electronic structure in pristine and oxygen vacancy-bearing thoria crystals. The dose-dependence of the intensity of the photoluminescence peaks is used to parameterize a rate theory model that estimates the concentration of color centers in the irradiated crystals. This parameterization provides optimized migration barrier parameters for oxygen interstitials and vacancies that simultaneously capture the optical response of the crystals irradiated at room- and elevated-temperature. These optical spectroscopy techniques offer a promising pathway to characterize the population of color centers formed at the sites of oxygen anion vacancies, particularly in irradiated nuclear fuels, where atomic-level defects cannot be readily imaged using electron microscopy. When combined with other direct and indirect characterization tools, our approach can provide new insight into defect formation and accumulation in energy materials over single atomic to extended length scales.
Temperature-dependent measurements of carrier recombination rates using a time-resolved optical pump-probe technique are reported for mid-wave infrared InAs/InAs{sub 1−x}Sb{sub x} type-2 superlattices (T2SLs). By engineering the layer widths and alloy compositions, a 16 K band-gap of ∼235 ± 10 meV was achieved for five unintentionally and four intentionally doped T2SLs. Carrier lifetimes were determined by fitting lifetime models based on Shockley-Read-Hall (SRH), radiative, and Auger recombination processes to the temperature and excess carrier density dependent data. The minority carrier (MC), radiative, and Auger lifetimes were observed to generally increase with increasing antimony content and decreasing layer thickness for the unintentionally doped T2SLs. The MC lifetime is limited by SRH processes at temperatures below 200 K in the unintentionally doped T2SLs. The extracted SRH defect energy levels were found to be near mid-bandgap. Also, it is observed that the MC lifetime is limited by Auger recombination in the intentionally doped T2SLs with doping levels greater than n ∼ 10{sup 16} cm{sup −3}.
The impact of annealing of proton irradiation-induced defects in n-type GaN devices has been systematically investigated using deep level transient and optical spectroscopies. Moderate temperature annealing (>200–250 °C) causes significant reduction in the concentration of nearly all irradiation-induced traps. While the decreased concentration of previously identified N and Ga vacancy related levels at E{sub C} − 0.13 eV, 0.16 eV, and 2.50 eV generally followed a first-order reaction model with activation energies matching theoretical values for N{sub I} and V{sub Ga} diffusion, irradiation-induced traps at E{sub C} − 0.72 eV, 1.25 eV, and 3.28 eV all decrease in concentration in a gradual manner, suggesting a more complex reduction mechanism. Slight increases in concentration are observed for the N-vacancy related levels at E{sub C} − 0.20 eV and 0.25 eV, which may be due to the reconfiguration of other N-vacancy related defects. Finally, the observed reduction in concentrations of the states at E{sub C} − 1.25 and E{sub C} − 3.28 eV as a function of annealing temperature closely tracks the detailed recovery behavior of the background carrier concentration as a function of annealing temperature. As a result, it is suggested that these two levels are likely to be responsible for the underlying carrier compensation effect that causes the observation of carrier removal in proton-irradiated n-GaN.
The results of experimental studies of processes of the radiation defect formation under ion implantation of narrow-gap Cd{sub x}Hg{sub 1-x}Te solid solutions (MCT) are presented. The processes of formation of structural damages of the crystal and their effect on the electrophysical properties of ion-implanted bulk crystals and ptype heteroepitaxial structures grown by liquid-phase and molecular-beam epitaxy are considered. The results on the spatial distribution of implanted boron atoms and radiation donor centers in these materials are presented as a function of the mass, dose, and energy of ions being implanted and the implantation temperature. The processes and models of the formation of n{sup +}–n{sup -}–p-structures during boron ion implantation in p-type MCT and their experimental proof are considered.
To expand the capabilities of safeguards authorities to verify the integrity of fresh fuel assemblies, Oak Ridge National Laboratory has retrofit the existing electronics of the JCC-71 uranium neutron coincidence collar, which contains 18 3 He neutron detectors and an external 241 AmLi(α, n) neutron interrogation source arranged to surround a fresh nuclear fuel assembly. The new electronics system allows analysts to record list-mode neutron multiplicity data in addition to the singles and doubles rates that are currently measured. Based on previous proof-of-concept research, analysis of these new data will identify off-normal fuel configurations in an assembly and characterize or localize the specific partial fuel defects. The purpose of this report it to document the analysis algorithm development and then to demonstrate its capability for the safeguards verification of fresh fuel assemblies using list mode neutron collar data. To analyze the complex list-mode data collected with the upgraded uranium neutron collar, multivariate classification algorithms are being developed using a novel classification method, the relevance vector machine. This approach may be applied to multiclass problems to estimate the probability that test data belongs to one of many possible classes of data. In addition, our method identifies the most useful variables/channels for making predictions, which illuminates the basis for the model’s predictions, and this interpretability is largely unique among data analytics methods. Variable selection occurs during model training and parameter tuning and does not need any external hyperparameter tuning routines. Finally, we apply the modified relevance vector machine to a simulated dataset of list-mode neutron collar data generated with the radiation transport code MCNP. The method can correctly identify off-normal fuel configurations, categorize the data according to four fuel defect scenarios, and rank the channels in the data according to prediction utility. For nuclear safeguards applications, it is concluded that this method has the potential to increase the sensitivity and reliability to detect missing fuel rods from a standard 17 x 17 Pressurized Water Reactor (PWR) fresh fuel assembly. Within this analysis, “off-normal” (i.e., missing fuel rods) were correctly classified in 17 simulated test scenarios with one quarter (25%) of the fresh fuel rods missing using a training data set of 58 simulated measurements.
Transition metal dichalcogenides (TMDs) are well known catalysts as both bulk and nanoscale materials. Two-dimensional (2-D) TMDs, which contain single- and few-layer nanosheets, are increasingly studied as catalytic materials because of their unique thickness-dependent properties and high surface areas. Here, colloidal 2H-WS 2 nanostructures are used as a model 2-D TMD system to understand how high catalytic activity and selectivity can be achieved for useful organic transformations. Free-standing, colloidal 2H-WS 2 nanostructures containing few-layer nanosheets are shown to catalyze the selective hydrogenation of a broad scope of substituted nitroarenes to their corresponding aniline derivatives in the presence of other reducible functional groups. Microscopic and computational studies reveal the important roles of sulfur vacancy-rich basal planes and tungsten-terminated edges, which are more abundant in nanostructured 2-D materials than in their bulk counterparts, in enabling the functional group selectivity. At tungsten-terminated edges and on regions of the basal planes having high concentrations of sulfur vacancies, vertical adsorption of the nitroarene is favored, thus facilitating hydrogen transfer exclusively to the nitro group due to geometric effects. At lower sulfur vacancy concentrations on the basal planes, parallel adsorption of the nitroarene is favored, and the nitro group is selectively hydrogenated due to a lower kinetic barrier. These mechanistic insights reveal how the various defect structures and configurations on 2-D TMD nanostructures facilitate functional group selectivity through distinct mechanisms that depend upon the adsorption geometry, which may have important implications for the design of new and enhanced 2-D catalytic materials across a potentially broad scope of reactions.
The pressing need for novel materials that can serve rising demands in solar cell and optoelectronic technologies makes the nexus of halide perovskites, high-throughput computations, and machine learning, very promising. Ever increasing amounts of data on the structure, fundamental properties, and device performance of halide perovskites provide opportunities for learning chemical rules and design principles that make these materials attractive, and applying them across wide chemical spaces. In this work, we show that impurity properties of halide perovskites computed using density functional theory (DFT) can be combined with machine learning (ML) to deliver predictive models and quick identification of optoelectronically active impurity atoms. Our computation lead to the largest reported dataset of the formation energies and charge transition levels of Pb-site impurities in methylammonium lead halide (MAPbX 3 ) perovskites. Descriptors are defined to uniquely represent any impurity atom in any MAPbX 3 compound and mapped to the computed impurity properties using regression techniques such as Gaussian process regression, neural networks, and random forests. We use the best optimized predictive models to make predictions for hundreds of impurities across 9 MAPbX 3 compounds and create lists of dominating impurities, that is, impurities that can shift the equilibrium Fermi level in the perovskite as determined by native point defects. Finally, this accelerated screening powered by computations and machine learning can guide the identification of problematic impurities that may cause undesired recombination of charge carriers, as well as impurities that can be deliberately introduced to tune the perovskite conductivity and resulting photovoltaic absorption.
A hybrid atomic-scale and continuum modeling framework is used to study the microstructural evolution during the laser-induced shock deformation and failure (spallation) of copper microstructures. A continuum two-temperature model (TTM) is used to account for the interaction of Cu atoms with a laser in molecular dynamics (MD) simulations. The MD-TTM simulations study the effect of laser loading conditions (laser fluence) on the microstructure (defects) evolution during various stages of shock wave propagation, reflection, and interaction in single-crystal (sc) Cu systems. In addition, the role of the microstructure is investigated by comparing the defect evolution and spall response of sc-Cu and nanocrystalline (nc) Cu systems. The defect (stacking faults and twin faults) evolution behavior in the metal at various times is further characterized using virtual in situ selected area electron diffraction and x-ray diffraction during various stages of evolution of microstructure. Here, the simulations elucidate the uncertain relation between spall strength and strain-rate and the much stronger relation between the spall strength and the temperatures generated due to laser shock loading for the small Cu sample dimensions considered here.
In this work, we employed a combined density functional theory and kinetic Monte Carlo approach in order to investigate the nanoscale behavior of lithium stripping and plating on lithium-copper nanoalloys. Density functional theory calculations were used to develop an atom-by-atom understanding of the nucleation behavior of lithium on copper surfaces with different surface morphologies. We found that nanometric pits resulted in significantly more favorable lithium deposition when compared to pristine or lightly-defective Cu surfaces, which is in agreement with previous experimental studies. We then used density functional theory and constrained ab initio molecular dynamics to develop interaction and reaction parameters for a larger-scale kinetic Monte Carlo model in order to provide insight into the stripping and plating behavior of nanostructured Li-Cu nanoalloy anodes. Substantial losses in capacity and strong indications of morphological change were observed for a wide range of Cu:Li ratios over 100 cycles. We observed a complex relationship between the nanoparticle composition and the properties of the formed solid-electrolyte interphase.