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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Understanding how molecular hydrogen impacts the total dose and dose rate response of linear bipolar circuits

Recent Enhanced Low Dose Rate Sensitivity (ELDRS) investigations carried out by RLP Research, Arizona State University (ASU) and Jet Propulsion Laboratory (JPL) have shown significant differences in the degradation of bipolar micro-circuits with total dose in the presence of molecular hydrogen (H2) in packages. This has a significant impact on radiation hardness assurance and opens up opportunities to improve device performance. The general objectives of this program are to: 1. Determine the extent to which hydrogen contamination affects the total dose and dose rate response of linear bipolar circuits; 2. Develop a model that will enable the prediction of high dose rate (HDR) and low dose rate (LDR) response asymptotes and transition dose rates as a function of total dose, temperature, pressurized hydrogen, defect precursors, and other process dependent variables; 3. Explore the possibility of an accelerated hardness assurance method and possible hardening approaches; and 4. Extend the work to other technologies that have total dose response affected by hydrogen contamination.In this document, we xperimentally demonstrate with test transistors and circuits that hydrogen is correlated with ELDRS in bipolar linear circuits. We show that the amount of hydrogen determines: 1) the total dose response versus dose rate and 2) the transition dose rates between the high and low dose rate responses. The experimental results are supported with a steady state drift/diffusion analytical model as well as modeling calculations using COMSOL Multiphysics.

Pease, Ron↗
DOE OSTI2025

Machine learning-enabled multiscale modeling of mechanical deformation of aluminum and Al-SiC nanocomposites

A machine learning-enabled multiscale framework is developed for modeling the mechanical response of both pure metal and nanoparticle-reinforced metal matrix nanocomposites (MMNCs). Using aluminum–silicon carbide (Al-SiC) as an example MMNC, atomistic simulations reveal three distinct deformation mechanisms (i.e., defect-free, dislocation-based, and interface separation) governed by the interfaces between the Al matrix and SiC nanoparticles. As compared with single crystal Al, the lattice undergoes a more abrupt failure once the dislocation network becomes extensive and void nucleation initiates, whereas in Al-SiC, nanoparticle interfaces enable a more gradual progression of damage. These mechanisms are captured through a combined classification-regression neural network surrogate model that bridges atomic-scale insights with continuum-scale finite element analysis. Machine learning-enabled multiscale modeling of pure Al accurately predicted strain localization and confirmed by in-situ scanning electron microscopic tensile testing on perforated Al specimens. This study underscores the promise of integrating physics-informed machine learning with hierarchical modeling to capture the interface dominated phenomena and guide the design of advanced MMNCs.

Al-SiC↗
DOE OSTI2026

Role of Wadsley Defects and Cation Disorder to Enhance MoNb 12 O 33 Diffusion

Wadsley-Roth (WR) niobates have emerged as high-rate anode materials that can combine rapid ionic diffusion with good electronic conductivity. WR compounds have been defect-enhanced by limited annealing, however, such materials often contain multiple types of defects. In particular, both Wadsley defects (variable block size) and transition metal disorder have the potential to modify transport rates, however the corresponding effects are not well understood mechanistically. Here, MoNb 12 O 33 (MNO) was calcined at two different temperatures to compare a defect-rich condition (MNO-800) with a proximal order-rich condition (MNO-900) as assessed through XRD, XANES, EXAFS, and STEM characterizations. Galvanostatically cycled lithium half cells of MNO-800 exhibited additional capacity (307 mAhg −1 at 0.1C, 4.66% higher) and improved high-rate capacity of 200 mAhg −1 at 10C. ICI-based overpotential analysis identified solid state diffusion as the dominant rate limiting process where MNO-800 correspondingly exhibited ∼3X faster capacity-weighted diffusivity. A machine-learning interatomic potential was trained to density functional theory and then applied with molecular dynamics (MLIP-MD) to examine the possible roles of Wadsley defects and transition metal disorder. For both defect-types, Li was found to populate and activate fast diffusion paths from window sites at lower extents of lithiation as compared to the order-rich model.

defect↗
DOE OSTI2020

Schizophrenia-related microdeletion causes defective ciliary motility and brain ventricle enlargement via microRNA-dependent mechanisms in mice

Progressive ventricular enlargement, a key feature of several neurologic and psychiatric diseases, is mediated by unknown mechanisms. Here, using murine models of 22q11-deletion syndrome (22q11DS), which is associated with schizophrenia in humans, we found progressive enlargement of lateral and third ventricles and deceleration of ciliary beating on ependymal cells lining the ventricular walls. The cilia-beating deficit observed in brain slices and in vivo is caused by elevated levels of dopamine receptors (Drd1), which are expressed in motile cilia. Haploinsufficiency of the microRNA-processing gene Dgcr8 results in Drd1 elevation, which is brought about by a reduction in Drd1-targeting microRNAs miR-382-3p and miR-674-3p. Replenishing either microRNA in 22q11DS mice normalizes ciliary beating and ventricular size. Knocking down the microRNAs or deleting their seed sites on Drd1 mimicked the cilia-beating and ventricular deficits. These results suggest that the Dgcr8–miR-382-3p/miR-674-3p–Drd1 mechanism contributes to deceleration of ciliary motility and age-dependent ventricular enlargement in 22q11DS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Electronic conductivity in metal-graphene composites: the role of disordered carbon structures, defects, and impurities

Abstract This paper explores the transport properties of aluminum-carbon composite material via ab initio methods. Interfacial and electronic dynamics of the aluminum-graphene interface structure were investigated using models of amorphous graphene added to an aluminum matrix. We examine the impact on electronic conduction caused by the presence of nitrogen impurities within the interfacial amorphous graphene layer. We elucidate the conduction mechanisms by using a projection of the electronic conductivity into space.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Small uranium and oxygen interstitial clusters in UO 2 : An empirical potential study

The aggregation of defect clusters in UO 2 under irradiations creates dislocation loops and cavities, which in turn contribute to swelling of the fuels, leading to detrimental pellet-clad mechanical interactions. The kinetics of the defect clusters, however, have received less attention and are not well understood. As such, using two interatomic potentials, the Morelon potential and a many-body model by Cooper, Rushton, and Grimes (CRG), the energetics and kinetics of small uranium interstitial clusters, with and without bound oxygen interstitials, are investigated with molecular dynamics and accelerated molecular dynamics simulations. For the single bound anti-Schottky interstitial cluster (U i 2O i ), both potentials find the interstitialcy migration mechanism to be a low barrier migration mechanism. However, for the CRG potential, an oxygen Frenkel pair assisted interstitial cluster migration mechanism with a lower migration barrier is identified during accelerated molecular dynamics simulations. For the Morelon potential, the interstitial clusters have geometrically compact structures, and small interstitial clusters (two and three anti-Schottky clusters) are more mobile than the single bound anti-Schottky interstitial cluster; for the CRG potential, the interstitial clusters have geometrically non-compact structures, yielding a more complex energy landscape. The rapid migration of interstitials and interstitial clusters are important for the irradiation response of UO 2 and correlates well with the very low barriers reported in a few historic experimental studies.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

Development of neural network force fields for corrosion studies

To fully understand the chemistry and physics of corrosion, novel methods of simulation must be developed. One approach is designing machine learning (ML) algorithms integrated with density functional theory to develop adaptive force fields to gain insight into corrosion behavior namely at the surface of metal oxides. Current methods of modeling corrosion are slow due to the computational cost of resolving both reaction mechanics and mass transport processes. Machine learning methods can be implemented to obtain structure-activity relationships at both the molecular and bulk scale while still retaining the accuracy of density functional theory (DFT) and significantly decreasing the time needed for simulations of complex chemical processes in the various environments of corrosion. Multiscale models are needed for corrosion studies to fully understand its processes not only at the atomic length scale (chemical bonding, energies, and forces), but also at the nano and meso length scales (solid-state physics and material science processes). Current methods of study include DFT, molecular dynamics, and Monte Carlo. The limitation of DFT is that only a small number of atoms or molecules can be simulated at that level of theory. Density functional theory is used to study the electronic structure of atoms and molecules, and calculate the force component of each atom. However, these calculations are limited to about 1000 atoms. Custom periodic boundary conditions (PBC) can be used to describe the various environments and defects that affect the atomic forces to produce a large data set from which a training set can be derived. Machine learning can be utilized to overcome the barrier of modeling macroscopic and multi-scale processes from ab initio calculations through the development of adaptive force fields. Local environments determine the atomic forces of a given system, therefore adaptive force fields must be created to produce reliable quantum mechanical calculations. This can be achieved by developing a learning algorithm that uses the mapped atomic forces or fingerprint as an input to produce energies and magnetic moments as output. A systematic approach was used to begin to build a data set in order to accurately describe the atomic forces in various environments. In Figure 4 below, a simple PBC cell of Fe{sub 2}O{sub 3} was first optimized. A surface optimization was performed next, followed by a hydroxylated surface optimization. Once this calculation has converged, the adsorption of halide species to the hydroxylated surface will be investigated. TensorFlow is an open source platform for machine learning developed by Google. Using a high level application program interface (API) such as Keras allows for building and training ML models easily in a number of different environments and languages. For this project, a neural network was developed within Anaconda in Python. Future Work: Further development of reference data set; Refining neural network and learning algorithm; Fingerprinting atomic environment to enable mapping of atomic force components; Choosing appropriate training set from reference data; Learning from training set and enabling non-linear mapping of training set fingerprints and the atomic forces; Estimation of uncertainty to identify ranges of outside applicability; Testing and analysis of molecular dynamic simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Radiation-Enhanced Anion Transport in Hematite

The influence of radiation-induced (1 MeV energy H+ to ~0.1 dpa at 450°C), non-equilibrium point defect populations on mass transport is studied with an integrated campaign of experimental and theoretical methods. Using epitaxial thin films of hematite with embedded 18O tracer layers and nanoscale atom probe tomography measurements, it is shown that anion self-diffusion is enhanced by at least 2 orders of magnitude under irradiation compared to thermal diffusion alone. Complementary scanning transmission electron microscopy of vacuum annealed specimens, reveals associated microstructural changes in the oxide films, including local phase transformation to Fe3O4 and the development of nanoscale voids from vacancy coalescence. Point defect formation and migration energies were computed from density functional theory and applied within the context of chemical rate theory to analyze contributions from both interstitial and vacancy mechanisms to self-diffusion in thermal and irradiation conditions. Comparisons are made between calculated, literature and newly measured self-diffusion values, revealing good agreement on the magnitude of radiation-enhanced anion diffusion. Further, the model suggests a transition from vacancy to interstitialcy mechanisms at low temperatures and high oxygen activity, consistent with the varied activation energies reported from prior studies.

iron oxides, isotopic tracers, atom probe tomograp↗
DOE OSTI2022

Origin, parameters, and underlying deformation mechanisms of propagating deformation bands in irradiated 316L stainless steel

Lüders-type propagating deformation bands were observed in specimens of irradiated 316L stainless steel samples removed from Spallation Neutron Source target vessels after service. Mechanical testing with digital image correlation (DIC) and in-situ tensile testing with scanning electron microscopy electron backscatter diffraction showed that the observed Lüders-type behavior was not related to the known transformation-induced plasticity or twinning-induced plasticity behavior. Instead, the phenomenon occurs at small local strain values before a significant amount of martensite or deformation twins appear in the microstructure. Microstructural analysis and in-situ mechanical test results suggest Lüders-type band formation and propagation were related to the appearance and evolution of defect-free channels—analogous to slip bands. A modified Swift equation with a Ludwigson-like component was offered to rationalize the phenomenon and model the strain-softening processes at small strain values. Finally, the results indicate complex microstructural processes and deformation mechanisms were active at small strain values and underline the benefits of advanced mechanical test approaches such as DIC.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Influence of carrier trapping on radiation detection properties in $\mathrm{CVD}$ grown 4H-SiC epitaxial layers with varying thickness up to 250 µm

We report low doped n-type 4H-SiC epitaxial layers of thickness 50, 150, and 250 µm grown by hot wall chemical vapor deposition were used to fabricate Ni/4H-SiC Schottky radiation detectors. The epitaxial layers were grown on the (0001) face of highly conductive bulk 4H-SiC substrates 8° offcut towards the $\langle 11\bar{2}1\rangle$ direction. The 50, 150, and 250 µm thick epilayer detectors, under optimized settings, showed energy resolutions of 2.0%, 0.78%, and 0.63%, respectively for 5.48 MeV alpha particles. Deep level transient spectroscopy studies showed that the observed variation in the detector resolution is linked to the defect parameters in the devices. Least-squares fitting of the bias dependence of the charge collection efficiency according to a drift-diffusion model, revealed minority carrier diffusion lengths of 16, 10, and 9.2 µm, respectively, implying that the detectors are not limited by minority carrier trapping. The detector performance was observed to be primarily dependent on the concentration and capture cross-sections of the lifetime killing electron traps Z 1/2 and EH 6/7 .

36 MATERIALS SCIENCE↗
DOE OSTI2020

Revealing the synergistic effects of sequential and simultaneous dual beam irradiations in tungsten via in-situ TEM

Elucidating the synergistic effects of different energetic beams on the radiation response of nuclear materials is critical for developing an improved methodology for their evaluation when exposed to extreme environments. This article describes in-situ sequential (He implantation followed by Kr irradiation and vice-versa) and simultaneous (heavy ion Kr irradiation and He implantation) dual beam irradiations performed on tungsten at 1223 K. Dislocation loop density, average area, and total loop damage as a function of irradiation history and dose/fluence are quantified. The loop Burgers vectors and cavity damage (cavity density, size and total change in volume) are also determined at the final maximum dose for each condition. The loop damage evolution was different in all cases, with the smallest loop damage observed in the simultaneous experiment. Annihilation of Kr generated dislocation loops during He implantation in the Kr + He experiment was an unanticipated observation that may be explained by the dynamic evolution of dislocation loop sink strengths and time-dependent defect fluxes. Dislocation loop raft formation, denuded zones near extended defects, and cavity damage are compared across the different conditions. The phenomena observed and discussed in this work will stimulate further experimental and computational modeling activities leading to improved fundamental understanding of the irradiation response of nuclear materials under reactor-similar environments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Parameterization of vacancy production rate in phase-field models of fission gas bubble evolution in nuclear fuel

Phase-field modeling has increasingly been used to study microstructural evolution in fission gas bubbles in nuclear fuel to improve understanding of fission gas release. To improve computational efficiency, often only vacancies and gas atoms are included as defect species. In this case, the net effects of vacancy and interstitial production, recombination, and biased sink absorption are included as a net vacancy source, or net vacancy source combined with an effective sink. However, there has been a lack of clarity on what parameter values should be used for these approaches to best match the more complete physical picture that includes interstitials and vacancies. Here, we compare a phase-field model of void growth to analytical models for the source-only and source plus sink approach to gain insight into how the phase-field models can be parameterized effectively. The source-only approach provides greater flexibility to match growth rates determined from the full vacancy-interstitial picture. A strategy was developed for determining the value of the net vacancy source term by comparing to an analytical model that includes vacancy and interstitial production, recombination, and biased sink absorption. Finally, this strategy can be used to parameterize phase-field models of fission gas bubble growth.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Graphene-Supported Monometallic and Bimetallic Dimers for Electrochemical CO 2 Reduction

Bimetallic catalysts are attractive alternatives to extend the parameter space that can be tuned for support interactions and catalytic performance. In this study, we have investigated the smallest bimetallic catalysts dimers supported on defective graphene for the electrochemical reduction of CO 2 to CH 4 based on a first-principles approach and the computational hydrogen electrode model. The monometallic and bimetallic dimers formed from Group 10 (Ni, Pd, Pt) and group 11 (Cu, Ag, Au) elements are characterized by a positively charged anchoring atom occupying the vacancy site of graphene and a neutral or slightly negatively charged antenna atom sticking out from the graphene surface. The strong selective binding of these dimers ensures their high stability. Possible rate-limiting steps are identified from the full reaction pathways to generate CH4. Overall, Pt-2, AgNi, Pd-2, and AgPt are the best candidates with the lowest overpotential values of 0.37, 0.69, 0.69, and 0.76 V, respectively. It is found that the alloy effect and the interaction with support help to optimize the property. These metallic dimers, however, retain nonmonotonous property relationships that give opportunity to go beyond scaling behavior and look for a few atom catalysts that have unique properties to reduce rate-limiting potentials and improve the catalytic performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Origins of Acid-Gas Stability Behavior in Zeolitic Imidazolate Frameworks: The Unique High Stability of ZIF-71

Zeolitic imidazolate frameworks (ZIFs) are promising materials for industrial process separations, but recent literature reports have highlighted their vulnerability to acid gases (e.g., SO 2 , CO 2 , NO 2 , H 2 S), often present in practical applications. While previous work has documented the widely varying stability behavior of many ZIFs under varying (humid and dry) acid gas environments, efforts to explain or correlate these experimental observations via empirical descriptors have not succeeded. A key observation is that ZIF-71 (RHO topology) is an extraordinarily stable ZIF material, retaining both structure and porosity under prolonged humid SO 2 exposure whereas many other well-known ZIFs with different linkers and topologies (such as ZIF-8) were shown to degrade. Through a combination of hybrid quantum mechanics/molecular mechanics (QM/MM) based methods and statistical mechanical models, we successfully explain this important experimental observation via atomistic investigations of the reaction mechanism. Our holistic approach reveals an ~9 times lower average defect formation rate in ZIF-71 RHO compared to ZIF-8 SOD, leading to the conclusion that the observed experimental stability of this material rises from kinetic effects. Moreover, our analysis reveals that differing stability of the two materials is determined by the distributions of acid gas molecules, which is difficult to capture using empirical descriptors. Furthermore, our results suggest wider applicability of the present approach, toward identifying tuned functional groups and topologies that move the acid gas distributions away from more reactive sites and thus allow enhanced kinetic stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Stress-induced hydrogen self-trapping in tungsten

The molecular dynamics simulations of trapping of hydrogen atoms in tungsten are presented. The simulations reveal formation of platelet-like structures of self-trapped hydrogen induced by stresses in tungsten, in particular, those produced by dislocations, at the interstitial hydrogen concentrations ~0.3-1 at.%. The spontaneous hydrogen platelet formation in absence of dislocations and external stresses has been also observed at the higher hydrogen concentrations ~10 at.%. It is shown that the platelets can retain substantial quantities of hydrogen, exceeding trapping capacity of other non-cavity defects in tungsten. The properties of the hydrogen latelets formed in tungsten under various conditions are assessed and a formation mechanism is proposed. A model of hydrogen retention by the dislocation-induced structures is also presented, which describes retained quantities and outgassing dynamics of hydrogen in plasma exposed tungsten samples.

08 HYDROGEN↗
DOE OSTI2019

Consideration of thermal Hall effect in undoped cuprates

A recent observation of the thermal Hall effect of magnetic origin in underdoped cuprates calls for critical reexamination of low-energy magnetic dynamics in an undoped antiferromagnetic compound on square lattice, where traditional, renormalized spin-wave theory was believed to work well. Using the Holstein-Primakoff boson formalism,in this work we find that magnon-based theories can lead to finite Berry curvature in the magnon band once the Dzyaloshinskii-Moriya spin interaction is taken into account explicitly, but fail to produce nonzero thermal Hall conductivity. Assuming accidental doping by impurities and magnon scattering off of such impurity sites fails to predict skew scattering at the level of the Born approximation. Local formation of skyrmion defects is also found incapable of generating the magnon thermal Hall effect. Turning to a spinon-based scenario, we write down a simple model by adding spin-dependent diagonal hopping to the well-known π-flux model of spinons. The resulting two-band model has a Chern number in the band structure, and generates thermal Hall conductivity whose magnetic field and temperature dependencies mimic closely the observed thermal Hall signals. In disclaimer, there is no firm microscopic basis of this model and we do not claim to have found an explanation of the data, but given the unexpected nature of the experimental observation, it is hoped this work could serve as a step towards reaching some level of understanding.

36 MATERIALS SCIENCE↗