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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Energetics of the nucleation and glide of disconnection modes in symmetric tilt grain boundaries

Grain boundaries (GBs) evolve by the nucleation and glide of disconnections, which are dislocations with a step character. In this work, motivated by recent success in predicting GB properties such as the shear coupling factor and mobility from the intrinsic properties of disconnections, we develop a systematic method to calculate the energy barriers for the nucleation and glide of individual disconnection modes under arbitrary driving forces and a quasi-2D setting. This method combines tools from bicrystallography to enumerate disconnection modes and the Nudged elastic band (NEB) method to calculate their energetics, yielding minimum energy paths and atomistic mechanisms for the nucleation and glide of each disconnection mode. We apply the method to accurately predict shear coupling factors of $[001]$ symmetric tilt grain boundaries in Cu. Particular attention is paid to the boundaries where the dislocation-based disconnection nucleation model produces incorrect nucleation barriers. We demonstrate that the method can accurately compute energy barriers and predict shear-coupling factors in the low-temperature regime. For certain disconnection modes in which the assumptions underlying our method do not hold, we report upper bounds on the energy barriers for disconnection nucleation and glide. In addition, the NEB trajectories reveal interesting phenomena such as the dissociation of a higher energy mode into lower energy modes, and in some cases, shear coupling being mediated by partial disconnections, wherein the GB structure temporarily changes to a metastable state before reverting back to its original structure. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2021

Accumulation-Type Ohmic van der Waals Contacts to Nearly Intrinsic WSe 2 Nanosheet-Based Channels: Implications for Field-Effect Transistors

We report the fabrication of ohmic van der Waals (vdW) contacts to nearly intrinsic WSe 2 nanosheet-based channels in field-effect transistors (FETs) using degenerately p-doped MoS2 (p + -MoS2) as a contact metal. We demonstrate that accumulation-type ohmic contacts and the high device performance are achievable without electrostatically gating the drain/source contact regions despite the nearly intrinsic nature of WSe 2 . Back-gated WSe 2 FETs with p + -MoS 2 bottom contacts (which screen the back-gate electric field in the drain/source regions) exhibit linear output characteristics, a high on/off ratio of 10 8 , and a high two-terminal field-effect mobility up to ~200 cm2 V –1 s –1 at room temperature. Our theoretical modeling reveals that the p + -MoS 2 /WSe 2 vdW junction behaves like a metal/semiconductor ohmic contact signified by a vanishingly thin space-charge region of ~1 nm on the p + -MoS 2 side and a substantial accumulation layer of free holes on the WSe 2 side, which is further verified by additional temperature-dependent and dual-gated measurements of WSe 2 FETs. We attribute the formation of accumulation-type ohmic contacts free of a Schottky barrier to the near absence of Fermi-level pinning at the vdW interface and the work function of p + -MoS 2 being larger than the ionization energy of WSe 2 . This study represents an important step toward achieving low-resistance ohmic contacts to two-dimensional (2D) semiconductors by eliminating the Fermi-level pinning effects, which is expected to have significant implications for next-generation 2D semiconductor-based nanoelectronics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Near-edge beta induced Alfven eigenmode in DIII-D high bootstrap current fraction plasmas

In DIII-D high bootstrap current fraction plasmas heated solely by neutral beam injection, a fast ion-driven Beta-Induced Alfven Eigenmode (BAE) is frequently observed. The BAE peaks near the edge, suggesting the possibility of enhanced fast ion transport there and raising a potential concern for the first wall. Theoretical analysis and simulations show that the mode location is not fully determined by the fast-ion drive intensity, i.e. fast ion pressure gradient but is strongly related to the background unfavorable magnetic curvature drive near the edge, which is an intrinsic property of advanced scenarios that rely on a large radius internal transport barrier that exists for all the kinetic channels for performance improvement.

beta induced Alfven eigenmode↗
DOE OSTI2024

Bottom-up design of actinide materials from molecular clusters: Demonstration of a general-purpose simulation capability leveraging machine-learned atomic potentials

Actinide thin-film coatings such as uranium dioxide (UO 2 ) play an important role in nuclear reactors and other mission-relevant applications, but realization of their potential requires a deep fundamental understanding of the chemical vapor deposition (CVD) processes used for their growth. The slow experimental progress can be attributed, in part, to the standard safety guidelines associated with handling uranium byproducts, which are often corrosive, toxic, and radioactive. Accurate simulation techniques, when used in concert with experiment, can improve laboratory safety, material durability, and deliverable timeframes. However, state-of-the-art computational methods are either insufficiently accurate or intractably expensive. To remedy this situation, in this project we suggested a machine-learning (ML) accelerated workflow for simulating molecular clustering toward deposition. As a benchmark test case, we considered molecular clustering in steam and assessed independent components of our workflow by comparing with measured thermodynamic properties of water. After analyzing each component individually and finding no fundamental barrier to realization of the workflow, we attempted to integrate the ML component, a Sandia-developed tool called FitSNAP. As this was the first application of FitSNAP to atoms and molecules in the gas phase at Sandia, the method required more fitting data than was originally anticipated. Systematic improvements were made by including in the fit data diatomic potentials, molecular single-bond-breaking curves, and symmetry-constrained intermolecular potentials. We concluded that our strategy provides a feasible pathway toward modeling CVD and related processes, but that extensive training data must be generated before it can be of practical use.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Lignin with controlled structural properties by N-heterocycle-based deep eutectic solvent extraction

The complex and heterogeneous nature of the lignin macromolecule has presented a lasting barrier to its utilization. To achieve high lignin yield, the technical lignin extraction process usually severely modifies and condenses the native structure of lignin, which is a critical drawback for its utilization in conversion processes. In addition, there is no method capable of separating lignin from plant biomass with controlled structural properties. Here, we developed an N-heterocycle-based deep eutectic solvent formed between lactic acid and pyrazole (La–Py DES) with a binary hydrogen bonding functionality resulting in a high affinity toward lignin. In this study, up to 93.7% of lignin was extracted from wheat straw biomass at varying conditions from 90 °C to 145 °C. Through careful selection of treatment conditions as well as lactic acid to pyrazole ratios, lignin with controlled levels of ether linkage content, hydroxyl group content, and average molecular weight can be generated. Under mild extraction conditions (90 °C to 120 °C), light-colored native-like lignin can be produced with up to 80% yield, whereas ether linkage–free lignin with low polydispersity can be obtained at 145 °C. Overall, this study offers a new strategy for native lignin extraction and generating lignin with controlled structural properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Fuel Property Effects on Knock Propensity and Thermal Efficiency in a Direct-Injection Spark-Ignition Engine

Engine knock remains one of the major barriers to further improvement in thermal efficiency of Direct-Injection Spark-Ignition (DISI) engines. While Research Octane Number and Motor Octane Number are often used as standard rating methods for knock resistance of fuels, the impacts of other fuel properties on knock propensity in modern engines such as heat of vaporization (HoV) and laminar flame speed (LFS) require better understanding in order to co-optimize fuels and engine designs to achieve higher thermal efficiency and lower CO2 emission. In the present study, computational fluid dynamics (CFD) is used to model a boosted DISI engine with a focus on knock prediction and fuel property effects. A level-set G-equation model is employed to capture turbulent premixed combustion, and is coupled with a transported Livengood-Wu (L-W) integral approach to predict autoignition in the unburnt region. A criterion associated with the L-W integral is developed to accurately predict knock onset and knock-limited spark-advance. This model is then applied to a sensitivity analysis of HoV and LFS on knock tendency and thermal efficiency. The pressure-temperature trajectory framework is applied and extended to study the fuel effects on auto-ignition process in the engine. An existing efficiency-based merit function, which is derived from experiments for boosted SI engines, is evaluated and improved based on the current CFD results.

DISI↗
DOE OSTI2024

Vacancy diffusion barrier spectrum and diffusion correlation in multicomponent alloys

Vacancy diffusion serves a crucial role in many important kinetic behaviors and properties of multicomponent alloys. Essential questions, however, persist regarding how chemical complexity affects diffusion and what unique characteristics, if any, set these alloys apart from traditional metals. Using neural network kinetics model, we study vacancy diffusion in NbMoTa alloy across a broad temperature range (2600 to 800 K). Unlike pure metals, the two key diffusion parameters—diffusion correlation factor f and activation energy ΔG m —are not constant in alloys, but instead substantially decrease with decreasing temperature. This temperature dependence arises from a reduced number of active vacancy jump pathways at lower temperatures, leading to more correlated diffusion. Upon examining vacancy diffusion throughout the entire compositional space of the Nb-Mo-Ta system, we discover that the slowest vacancy diffusion surprisingly occurs in the non-equimolar region, rather than the equimolar concentration where the configurational entropy is highest. The diffusion barrier spectrum, characterizing the diffusion energy landscape, is an intrinsic material characteristic, which controls both f and ΔG m and, thereby, the diffusivity. Lastly, we find that the vacancy diffusion rate drops noticeably in the presence of local chemical order in the NbMoTa system, particularly for MoTa alloys with long-range B2 order.

Defects↗
DOE OSTI2021

Deep learning of accurate force field of ferroelectric HfO 2

The discovery of ferroelectricity in HfO 2 -based thin films opens up new opportunities for using this silicon-compatible ferroelectric to realize low-power logic circuits and high-density nonvolatile memories. The functional performances of ferroelectrics are intimately related to their dynamic responses to external stimuli such as electric fields at finite temperatures. Molecular dynamics is an ideal technique for investigating dynamical processes on large length and time scales, though its applications to new materials are often hindered by the limited availability and accuracy of classical force fields. Here we present a deep neural network–based interatomic force field of HfO 2 learned from ab initio data using a concurrent learning procedure. The model potential is able to predict structural properties such as elastic constants, equation of states, phonon dispersion relationships, and phase transition barriers of various hafnia polymorphs with accuracy comparable with density functional theory calculations. Here, the validity of this model potential is further confirmed by the reproduction of experimental sequences of temperature-driven ferroelectric-paraelectric phase transitions of HfO 2 with isobaric-isothermal ensemble molecular dynamics simulations. We suggest a general approach to extend the model potential of HfO 2 to related material systems including dopants and defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Isospin composition of fission barriers

We employ a microscopic method to study how isospin affects the fission potential of 240 Pu. Our approach uses constrained Hartree-Fock theory (CHF) which allows us to separately investigate the isoscalar and isovector properties of the nuclear energy density functional (EDF). By analyzing the isoscalar and isovector components of the EDF along the fission path we can assess the isovector contribution to fission barriers. Here, we study this effect for the fully adiabatic path to scission. The isovector component of the fission potential is found to increase in magnitude as the nucleus evolves towards scission, exemplifying the importance of stringent constraints on the isovector sector of the nuclear EDF for reliable predictions of fission properties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Effect of pore fluid chemistry on the mechanical behavior of a divalent compacted bentonite, an experimental and constitutive study

Ongoing research in isolating high-level nuclear waste and spent fuel has highlighted compacted bentonite as a suitable material for engineered barrier systems in deep geological repositories due to its extraordinary swelling and retention properties. This research focuses on the chemo-mechanical behavior of compacted bentonite exposed to different pore fluids with different concentrations and loading conditions. The study involves swelling pressure and compressibility experiments along with mineralogy analysis employing X-ray diffraction (XRD) and Cation exchange. The tests were conducted on BCV (a Mg/Ca- bentonite) compacted at a dry density of 1.48 ± .02 Mg/m 3 . An advanced chemical-mechanical constitutive model for unsaturated highly expansive clays was adopted to simulate the material response and better understand its behavior. The model is able to account for the main phenomena at both macro and microstructural levels and the interactions between them. The model successfully replicated experimental observations. The XRD analyses support the macroscopic observation, indicating that salinity impacts crystalline swelling as demonstrated by the reduction of basal spacing from 19.27 Å to 15.68 Å when the osmotic suction increases from 0 MPa to 33 MPa. The results suggested that the osmotic pressure generated by the concentration in the pore fluids promotes a reduction in swelling pressures, swelling strains, and crystalline swelling of clay minerals. Also, it affects the pre-consolidation stress and the compressibility of the compacted samples. In conclusion, it was also observed that both solution type and solution concentration impact the clay swelling pressure.

Chemo-mechanical constitutive model↗
DOE OSTI2022

Hydrogen Storage Performance of Preferentially Oriented Mg/rGO Hybrids

Chemical interactions on the surface of a functional nanoparticle are closely related to its crystal facets, which can regulate the corresponding energy storage properties like hydrogen absorption. In this study, we reported a one-step growth of magnesium (Mg) particles with both close- and nonclose-packed facets, that is, {0001} and {$2\overline{116}$} planes, on atomically thin reduced graphene oxide (rGO). The detailed microstructures of Mg/rGO hybrids were revealed by X-ray diffraction, selected-area electron diffraction, high-resolution transmission electron microscopy, and fast Fourier transform analysis. Hydrogen storage performance of Mg/rGO hybrids with different orientations varies: Mg with preferential high-index {$2\overline{116}$} crystal surface shows remarkably increased hydrogen absorption up to 6.2 wt % compared with the system exposing no preferentially oriented crystal surfaces showing inferior performance of 5.1 wt % within the first 2 h. First-principles calculations revealed improved hydrogen sorption properties on the {$2\overline{116}$} surface with a lower hydrogen dissociation energy barrier and higher stability of hydrogen atoms than those on the {0001} basal plane, supporting the hydrogen uptake experiment. In addition, the hydrogen penetration energy barrier is found to be much lower than that of {0001} because of low surface atom packing density, which might be the most critical process to the hydrogenation kinetics. Here, the experimental and calculation results present a new handle for regulating the hydrogen storage of metal hydrides by controlled Mg facets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The Effects of Phosphate Impurity on Recovered LiNi 0.6 Co 0.2 Mn 0.2 O 2 Cathode Material via a Hydrometallurgy Method

From portable electronics to electric vehicles, lithium-ion batteries have been deeply integrated into our daily life and industrial fields for a few decades. The booming field of battery manufacturing could lead to shortages in resources and massive accumulation of battery waste, hindering sustainable development. Therefore, hydrometallurgy-based approaches have been widely used in industrial recycling to recover cathode materials due to their high efficiency and throughput. Further, impurities have always been a great challenge for hydrometallurgical recycling, introducing challenges to maintain the consistency of product quality because of potential unintended effects caused by impurities. Herein, after comprehensive investigation, we first report the impacts of phosphate impurity on a recycled LiNi 0.6 Co 0.2 Mn 0.2 O 2 ("NCM622") cathode via a hydrometallurgy method. We demonstrate that a passivation layer of Li 3 PO 4 is formed at grain boundaries during sintering, which significantly raises the activation barrier and hinders lithium diffusion. In addition, the distinct degradation of cathode electrochemical properties is observed from poor particle morphology and high cation mixing as a result of phosphate impurity. Cathode powders with 1 at. % phosphate impurity retain a capacity of 146 mAh/g after 100 cycles at 0.33C, 6% less than that of a virgin cathode. Furthermore, cathodes with higher phosphate concentrations perform even worse in electrochemical tests. Therefore, phosphate impurities are detrimental to the hydrometallurgical recycling of NCM cathode materials and need to be excluded from the recycling process.

25 ENERGY STORAGE↗
DOE OSTI2024

Chain-End Controlled Depolymerization Selectivity in α,α-Disubstituted Propionate PHAs with Dual Closed-Loop Recycling and Record-High Melting Temperature

In this article, within the large poly(3-hydroxyalkanoate) (PHA) family, C3 propionates are much less studied than C4 butyrates, with the exception of α,α-disubstituted propionate PHAs, particularly poly(3-hydroxy-2,2-dimethylpropionate), P3H(Me) 2 P, due to its high melting temperature (T m ~ 230 °C) and crystallinity (~76%). However, inefficient synthetic routes to its monomer 2,2-dimethylpropiolactone [(Me) 2 PL] and extreme brittleness of P3H(Me) 2 P largely hinder its broad applications. Here, we introduce simple, efficient step-growth polycondensation (SGP) of a hydroxyacid or methyl ester to afford P3H(Me) 2 P with low to medium molar mass, which is then utilized to produce lactones through base-catalyzed depolymerization. The ring-opening polymerization (ROP) of the 4-membered lactone leads to high-molar-mass P3H(Me) 2 P, which can be depolymerized by hydrolysis to the hydroxyacid in 99% yield or methanolysis to the hydroxyester in 91% yield, achieving closed-loop recycling via both SGP and ROP routes. Intriguingly, the chain end of the SGP-P3H(Me) 2 P determines the depolymerization selectivity toward 4- or 12-membered lactone formation, while both can be repolymerized back to P3H(Me) 2 P. Through the formation of copolymers P3H(Me/R) 2 P (R = Et, n Pr), PHAs with high tensile strength and ductility, coupled with high barriers to water vapor and oxygen, have been created. Notably, the PHA structure–property study led to P3H( n Pr) 2 P with a record-high T m of 266 °C within the PHA family.

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

Vibrational relaxation dynamics in layered perovskite quantum wells

Significance Halide perovskites, especially layered perovskites, offer a number of advantages to creating bright and efficient light-emitting devices and other optoelectronic applications. The organic–inorganic hybrid layered perovskite features complex lattice dynamics due to the ionic character of the crystal and the softness arising from noncovalent bonds between molecular moieties and the inorganic network. Especially, the packing geometry of the organic barriers leads to a structural deformation of inorganic octahedral, which strongly affects the properties that are crucial for device applications. In this work, we use high-resolution resonant impulsive stimulated Raman spectroscopy of a variety of ligand substitutions in layered perovskites. We find the composition of organic ligands can substantially change the dephasing rate of optical phonons and their temperature dependence, due to varying degrees of anharmonicity in the lattice and dynamic structural disorder.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Atomic-Layer Engineering of La 2-x Sr x CuO 4 —La 2-x Sr x ZnO 4 Heterostructures

The fabrication of trilayer superconductor-insulator-superconductor (SIS) Josephson junctions with high-temperature superconductor (HTS) electrodes requires atomically perfect interfaces. Therefore, despite great interest and efforts, this remained a challenge for over three decades. Here, we report the discovery of a new family of metastable materials, La 2-x Sr x ZnO 4 (LSZO), synthesized by atomic-layer-by-layer molecular beam epitaxy (ALL-MBE). We show that LSZO is insulating and epitaxially compatible with an HTS compound, La 2-x Sr x CuO 4 (LSCO). Since the “parent” compound La 2-x Sr x ZnO 4 (LZO) is easier to grow, here we focus on this material as our insulating layer. Growing LZO at very low temperatures to reduce cation interdiffusion makes LSCO/LZO interfaces atomically sharp. We show that in LSCO/LZO/LSCO trilayers, the superconducting properties of the LSCO electrodes remain undiminished, unlike in previous attempts with insulator barriers made of other materials. This opens prospects to produce high-quality HTS tunnel junctions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Selective thermal neutron transmutation doping with Gd masks in GaN semiconductors

For the first time, selective neutron transmutation doping was successfully performed on GaN through Gd masks, showing the feasibility of patternable doping through neutron irradiations. In collaborating with Oak Ridge National Laboratory, GaN with Gd masks was irradiated by directional neutrons. By using the Gd properties with high neutron absorption cross-sections, it was confirmed that the area covered by Gd masks on GaN was completely shielded from neutrons, and the uncovered area was doped with the generated Ge and 14 C. Property differences were clearly identified in various ways when comparing the area exposed by neutrons and the area unexposed by neutrons. The discoloration by the ejected protons and elastic scattering of neutrons appeared only in the exposed area while the unexposed area remained the same as before irradiation. The aspect ratio of the patterned profile of GaN was estimated by comparing patterns on the front and backside. From energy dispersive X-ray spectroscopy spectra and secondary ion mass spectrometry measurement, the concentration difference between Ge and 14 C as well as the exact concentration of produced 14 C was also checked. Further, Schottky barrier diodes on the selectively doped GaN were fabricated and investigated to study the electrical properties.

42 ENGINEERING↗
DOE OSTI2022

Blended fuel property analysis of butyl-exchanged polyoxymethylene ethers as renewable diesel blendstocks

Methyl-terminated polyoxymethylene ethers (MM-POMEs), having the formula CH 3 O-(CH 2 O)n-CH 3 (n = 3-6), are a class of oxygenates with desirable diesel-like fuel properties including high cetane number and low soot formation. However, their low energy density and high water-solubility present barriers to their adoption. Both concerns were recently addressed by our research group by synthesizing a mixture of POME structures having butyl end-groups and n = 1-6, termed B*POME1-6. B*POME1-6 maintained the advantageous properties of the parent MM-POMEs, and exhibited improved energy density and most notably, dramatically decreased water solubility. For evaluation against a set of criteria for a blended diesel blendstock, a 20 vol% blend of B*POME1-6 with a base diesel fuel was investigated here. Oxidation stability, cetane number, sooting tendency, lubricity and conductivity were improved in the B*POME1-6 blend compared with the base diesel, while also maintaining the flash point, cloud point, energy density, viscosity, and boiling point requirements. The B*POME1-6 product demonstrated a synergistic blending behavior at 10 vol% and a linear blending behavior at 20-30 vol% blends, in agreement with similar POME blends at comparable blend levels. Finally, common environmental and toxicity models performed on B*POME1-6 component molecules suggested they have a greater propensity to partition into the water compartment compared to a common diesel surrogate, but with a lower tendency to bioaccumulate.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Machine learning reveals factors that control ion mobility in anti-perovskite solid electrolytes

Solid-state batteries are projected to exhibit improved energy densities and safety compared to liquid-electrolyte-based systems. Consequently, the development of solid electrolytes that can conduct cations at rates comparable to that of liquid electrolytes is an active area of research. To facilitate this search it is desirable to understand the chemical and structural features that control ion transport through a crystalline lattice. Here, machine learning (ML) is used to identify features that influence ion mobility in solids, quantify the relative importance of those features, and demonstrate how the variation of individual features alters ion mobility. Adopting the anti-perovskite lattice as a model system, ML algorithms were trained to predict migration barriers from a data set containing hundreds of barriers calculated using density functional theory. In this study, more than 10 6 feature sets of non-redundant descriptors were evaluated for their ability to predict migration barriers. The present analysis correctly reiterates the importance of several features that are known to influence mobility – for example, anion polarizability – but also identifies others whose importance is not widely recognized. Lattice properties such as hopping distance and channel width exhibit the greatest influence on cation mobility. Individual conditional expectation analyses performed on these features shows that barriers decrease as hopping distance decreases and as channel width increases. The defect formation energy – which is commonly associated with the concentration of defects, but not with their mobility – is identified as an important feature for interstitial migration. In sum, this analysis aids in the design of optimal solid electrolytes by simplifying the multi-dimensional design space to a sub-set of properties that are the most important.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗