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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 1,153 records · Page 64

Effects of basal-plane thermal conductivity and interface thermal conductance on the hot spot temperature in graphene electronic devices

In this study, electrostatic force microscopy and scanning thermal microscopy are employed to investigate the electric transport and localized heating around defects introduced during transfer of graphene grown by chemical vapor deposition to an oxidized Si substrate. Numerical and analytical models are developed to explain the results based on the reported basal-plane thermal conductivity, κ, and interfacial thermal conductance, G , of graphene and to investigate their effects on the peak temperature. Irrespective of the κ values, increasing G beyond 4 × 10 7 W m –2 K –1 can reduce the peak temperature effectively for graphene devices made on sub-10 nm thick gate dielectric, but not for the measured device made on 300-nm-thick oxide dielectric, which yields a cross-plane thermal conductance ( G ox ) much smaller than the typical G of graphene. In contrast, for typical G values reported for graphene, increasing κ from 300 W m –1 K –1 toward 3000 W m –1 K –1 is effective in reducing the hot spot temperature for the 300-nm-thick oxide devices but not for the sub-10 nm gate dielectric case, because the heat spreading length (l) can be appreciably increased relative to the micron-scale localized heat generation spot size ( r 0 ) only when the oxide layer is sufficiently thick. As such, enhancement of κ increases the vertical heat transfer area above the gate dielectric only for the thick oxide case. In all cases considered, the hot spot temperature is sensitive to varying G and κ only when the G / G ox ratio and r 0 /l ratio are below about 5, respectively.

36 MATERIALS SCIENCE↗

Influence of chemical strains on the electrocaloric response, polarization morphology, tetragonality, and negative-capacitance effect of ferroelectric core-shell nanorods and nanowires

Using Landau-Ginzburg-Devonshire (LGD) approach, we proposed the analytical description of the influence of chemical strains on spontaneous polarization and the electrocaloric response in ferroelectric core-shell nanorods. We postulate that the nanorod core presents a defect-free single-crystalline ferroelectric material, and elastic defects are accumulated in the ultrathin shell, where they can induce tensile or compressive chemical strains. Finite-element modeling (FEM) based on the LGD approach reveals transitions of domain-structure morphology induced by chemical strains in the Ba Ti O 3 nanorods. Namely, tensile chemical strains induce and support the single-domain state in the central part of the nanorod, while the curled domain structures appear near the unscreened or partially screened ends of the rod. The vortexlike domains propagate toward the central part of the rod and fill it entirely, when the rod is covered by a shell with compressive chemical strains above some critical value. The critical value depends on the nanorod sizes, aspect ratio, and screening conditions at its ends. Both analytical theory and FEM predict that the tensile chemical strains in the shell increase the nanorod polarization, lattice tetragonality, and electrocaloric response well above the values corresponding to the bulk material. The physical reason for the increase is strong electrostriction coupling between the mismatch-type elastic strains induced in the core by chemical strains in the shell. Comparison with earlier XRD data confirmed an increase of the tetragonality ratio in tensile Ba Ti O 3 nanorods compared to the bulk material. Obtained analytical expressions, which are suitable for the description of strain-induced changes in a wide range of multiaxial ferroelectric core-shell nanorods and nanowires, can be useful for strain engineering of advanced ferroelectric nanomaterials for energy storage, harvesting, electrocaloric applications, and negative capacitance elements. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗

Loschmidt-amplitude wave function spectroscopy and the physics of dynamically driven phase transitions

In this work, we introduce the Loschmidt amplitude as a powerful tool to perform spectroscopy of generic many-body wave functions and use it to interrogate the wave function obtained after ramping the transverse field quantum Ising model through its quantum critical point. Previous results are confirmed and a more complete understanding of the population of defects and of the effects of magnon-magnon interaction or finite-size corrections is obtained. The influence of quantum coherence is clarified.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Assessment of thermally driven local structural phase changes in 1⁢𝑇′−MoTe 2

The role of layer disorder is important in establishing the topological phases of MoTe 2 . A rich tapestry of atomic ordering influences the structural phase transitions (SPTs), but there is little understanding of the mechanistic details of the phase transition. An atomistic level study was conducted to investigate the local structure of the 1⁢𝑇′ and 𝑇 𝑑 phases of MoTe 2 by using the pair distribution function (PDF) technique. While the average structure exhibits an SPT and coexistence of phases as a function of temperature, the local structure showed the suppression of SPT. The sample retained its monoclinic structure at all temperatures in short-range order. A sharp PDF peak observed at short distances indicated a strong atom-atom correlation between the Mo and Te atoms within the Mo octahedra. In addition, a large-box modeling of the PDF data indicated a preferential motion of Te atoms towards 𝑐 axis at all temperatures. Structural defects, such as stacking faults, likely result in the coexistence of phases in the average structure and suppress the local SPT of MoTe 2 . These results are stepping stones to understand the long-debated origins of structural, vibrational, and electronic properties of MoTe 2 and similar transition metal dichalcogenides.

2-dimensional systems↗

Ballistic magnon heat conduction and possible Poiseuille flow in the helimagnetic insulator Cu 2 OSeO 3

Herein we report on the observation of magnon thermal conductivity κ m ~ 70 W/mK near 5 K in the helimagnetic insulator Cu 2 OSeO 3 , exceeding that measured in any other ferromagnet by almost two orders of magnitude. Ballistic, boundary-limited transport for both magnons and phonons is established below 1 K, and Poiseuille flow of magnons is proposed to explain a magnon mean-free path substantially exceeding the specimen width for the least defective specimens in the range 2 K < T < 10 K. These observations establish Cu 2 OSeO 3 as a model system for studying long-wavelength magnon dynamics.

36 MATERIALS SCIENCE↗

Analyzing the effect of pressure on the properties of point defects in $\gamma\mathrm{U–Mo}$ through atomistic simulations

Uranium–molybdenum (U–Mo) alloys in monolithic fuel foil are the primary candidate for the conversion of high-performance research reactors in the USA. Monolithic fuel is utilized in a plate-type design with a zirconium diffusion barrier and aluminum cladding. These fuel types are unique in that they contain no plenum for the release of fission gases, which, in conjunction with the aluminum cladding, can lead to large stress states within the fuel. The nature of how fundamental processes of radiation damage, including the evolution of point defects, under such stresses occur is unknown. In this work, we present molecular dynamics simulations of the formation energy of point defects under applied stress. We report this work will allow for the implementation of stress-dependent microstructural evolution models of nuclear fuels, including those for both fission gas bubble growth and creep, which are critical to ensure the stable and predictable behavior of research reactor fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

20-kV GaN Switch Technology Demonstrated in High-Efficiency Medium-Voltage Power Module

GaN holds significant potential as a material for vertical p-n diodes, enabling the realization of devices with reverse breakdown voltages of 5 kV or higher. Carbon serves as the primary compensating dopant in the growth process, incorporated into GaN during metalorganic chemical vapor deposition (MOCVD) growth. The level of carbon incorporation depends on several factors, including growth rate, ammonia flow, temperature, pressure, and trimethylgallium (TMGa) flow. Through guided empirical modeling, the carbon incorporation in GaN growth could be predicted using a single parameter based on the ratio of ammonia flow to the growth rate. This model accurately predicts carbon concentrations ranging from 1x10 17 to 5x10 14 cm -3 while maximizing growth rates. Other extrinsic dopants have either been reduced below the threshold of consideration or modeled using similar single-parameter relationships. By identifying the dominant extrinsic dopants and accounting for them, an intrinsic defect with a concentration of 2.2x10 15 cm -3 was identified. By combining these relationships, growth conditions for n-GaN were optimized, resulting in electron concentrations as low as 1x10 15 cm -3 . Leveraging these techniques, p-n diodes were grown, achieving a reverse breakdown voltage as high as 3.1 kV.

36 MATERIALS SCIENCE↗

Power Electronics Materials and Bonded Interfaces - Reliability and Lifetime

High temperature operation of wide bandgap devices continue to be a challenge for the power electronics packages. Thermal performance and reliability are important factors that determine the viability of a bonded interface for operation at high temperatures. In this presentation, we present the technical approach and key results from the research on sintered silver, transient liquid phase alloy, and polymeric materials. A lifetime prediction model that incorporates the thermomechanical behavior of sintered silver at 200C was developed. The copper-aluminum transient alloy completed 350 thermal cycles from -40C to 200C and little increase in the defect level was observed. In addition to material research, we initiated a time-series analysis on the scanning acoustic microscope images of eutectic solder to explore statistical forecasting methods and machine learning techniques. Initial results that report the accuracy of a few different statistical models are presented.

ADVANCED PROPULSION SYSTEMS↗

In-Situ Calibrated Digital Process Twin Models for Resource Efficient Manufacturing

The chief objective of manufacturing process improvement efforts is to significantly minimize process resources such as time, cost, waste, and consumed energy while improving product quality and process productivity. This paper presents a novel physics-informed optimization approach based on artificial intelligence (AI) to generate digital process twins (DPTs). The utility of the DPT approach is demonstrated in the case of finish machining of aerospace components made from gamma titanium aluminide alloy (γ-TiAl). This particular component has been plagued with persistent quality defects, including surface and sub-surface cracks, which adversely affect resource efficiency. Previous process improvement efforts have been restricted to anecdotal post-mortem investigation and empirical modeling, which fail to address the fundamental issue of how and when cracks occur during cutting. In this work, the integration of in-situ process characterization with modular physics-based models is presented, and machine learning algorithms are used to create a DPT capable of reducing environmental and energy impacts while significantly increasing yield and profitability. Based on the preliminary results presented here, we report an improvement in the overall embodied energy efficiency of over 84%, 93% in process queuing time, 2% in scrap cost, and 93% in queuing cost has been realized for γ-TiAl machining using our novel approach.

42 ENGINEERING↗

A one-dimensional time-dependent model for studying oxide film growth on metallic surfaces

Corrosion resistance of industrial metals and alloys is largely imparted by the formation of a stable oxide film on the surface that kinetically limits the process of corrosion. Developing a fundamental knowledge of the processes involved in the oxide layer formation and growth is thus important for designing corrosion-resistant alloys. In this work, a model for oxide growth tracking two species (the oxygen and metal vacancies) was presented. The model accounted for species transport and interfacial chemistry. The potential profile was obtained by solving the Poisson equation without needing to invoke the typical linear assumption. Moreover, the fully time-dependent concentration and potential profiles were obtained and the oxide thickness was allowed to evolve by allowing the movement of the domain boundaries at either end. The results were analyzed and the effects of different parameters on the model were discussed.

36 MATERIALS SCIENCE↗

Massive all-atom analysis of 2D materials with quantum properties (Final report)

Improvements in microscopy have enabled the acquisition of data at a scale that is difficult to process manually, making automated machine learning approaches to analyzing experimental images essential. In this project, we developed and applied machine learning (ML) workflows for atomic resolution scanning transmission electron microscopy (STEM) images. This development included improving both methodology as well as generating user-friendly codes. We developed machine learning architectures which, after training, automatically identify the location and types of defects throughout a material. We used these data to produce class-averaged images of 2D atomic coordinates with up to 0.3 pm precision, uncovering the structure and oscillations of long-range strain fields around point defects in WSe 2-2x Te 2x . We also resolved a long-standing problem in this field in the training of ML models, a lack of labeled experimental data, by developing a cycle-GAN that transformed simulated-generated labeled data into labeled data indistinguishable from experiment and therefore suitable for training. This removed the remaining parts of the ML data processing workflow where human intervention was still critical and therefore a bottleneck to working at scale. Codes have been developed and released for this full machine learning workflow. ML approaches to partially automate STEM acquisition were also developed. Finally we applied ML and other advanced data processing methods to several materials science problems in two-dimensional materials, including studying the evolution of hyperuniformity with defect concentration in WSe2, understanding phase transformations in transition metal dichalcogenides during in-situ heating in the STEM, and exploring how 2D interfaces transform from twisted into aligned structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Antimony diffusion in CdTe

Group V dopants may be used for next-generation high-voltage cadmium telluride (CdTe) solar photovoltaics, but fundamental defect energetics and kinetics need to be understood. Here, antimony (Sb) diffusion is studied in single-crystal and polycrystalline CdTe under Cd-rich conditions. Diffusion profiles are determined by dynamic secondary ion mass spectroscopy and analyzed with analytical bulk and grain-boundary diffusion models. Slow bulk and fast grain-boundary diffusion are found. Density functional theory is used to understand formation energy and mechanisms. Lastly, the theory and experimental results create new understanding of group V defect kinetics in CdTe.

14 SOLAR ENERGY↗

Microstructural evolution of 3C-SiC exposed to simultaneous neutron irradiation and helium implantation

The synergism of transmutant helium and irradiation defects is critically important to understand the performance of SiC when in service in nuclear environments. In this study, we exposed 3C-SiC in contact with a 2 μm Ni foil to neutron irradiation at 500 °C to 29 dpa in the high flux isotope reactor to simulate the simultaneous introduction of helium and irradiation defects into SiC. The combination of TEM observations and thermal desorption measurements helps to elucidate the impact of helium on the microstructural evolution in 3C-SiC. Thermal helium desorption spectra from ion-implanted and neutron-irradiated SiC showed a completely different desorption behavior in terms of the peak position and helium desorption flux. The identification of possible helium trapping sites was attempted by applying the first order dissociation model to the measured thermal helium desorption spectra. TEM observations of the neutron-irradiated samples showed that the presence of helium facilitated the stabilization of the defect clusters and promoted the formation of visible helium bubbles in SiC subject to simultaneous neutron irradiation and in-situ He implantation. Following the subsequent heat treatment during the thermal desorption measurements, large faceted helium bubbles were found along grain boundaries in the neutron-irradiated SiC with in-situ He implantation, while the helium bubbles in the grain interior were relatively smaller than those found in the neutron-irradiated sample without in-situ He implantation due to the reduced mobility of He-defect clusters. In conclusion, the He contents contained in the neutron-irradiated samples were quantified based on the experimental data from TEM and thermal desorption measurements.

36 MATERIALS SCIENCE↗

Predicting Thermochemical Equilibria with Interacting Defects: Sr 1 − x Ce x Mn O 3 − δ Alloys for Water Splitting

Solar thermochemical hydrogen is one of the few potential routes towards direct fuel production from renewable energy sources, but the thermodynamic boundary conditions for efficient and economic energy conversion are challenging. Success or failure of a given oxide working material depends on the subtle balance between enthalpy and entropy contributions in the redox processes. Developing a mechanistic understanding of the behavior of materials on the basis of atomistic models and first-principles calculations is an important part of advancing the technology. One challenge is to quantitatively predict thermochemical equilibria at high concentrations when the redox-active defects start to interact with each other, thereby impeding the formation of additional defects. This problem is of more general importance to applications that rely on high levels of off-stoichiometry or doping, including, for example, batteries, thermoelectrics, and ceramic fuel cells. To account for such repulsive defect interactions, we introduce a statistical mechanics approach, defining an expression for the free energy of defect interaction based on limited sampling of defect configurations in density functional theory supercell calculations. The parameterization of this energy contribution as a function of defect concentration and temperature allows on-the-fly simulation of thermochemical equilibria. The approach consistently incorporates finite temperature effects by including the leading contributions to the temperature-dependent free energy for the case at hand, i.e., the ideal gas and configurational enthalpies and entropies. We demonstrate the capability and utility of the approach by simulating the water splitting redox processes for Sr 1 − x Ce x Mn O 3 − δ alloys. Published by the American Physical Society 2024

08 HYDROGEN↗

High fidelity ultrasound imaging of concrete structures

As plans are made to extend licenses for the aging fleet of commercial nuclear power plants for periods of sixty years and beyond, research into the long-term integrity of their concrete structures has increased. Ultrasound tomography is a useful tool for nondestructive evaluation of these concrete structures. Typically, pulse-echo measurements are made over a large surface and are processed using a reconstruction algorithm, producing a 3D image of the structure that highlights embedded defects. These measurements are processed using a delay-and-sum algorithm such as the synthetic aperture focusing technique (SAFT). Oak Ridge National Laboratory is developing novel ultrasound model-based image reconstruction (U-MBIR) algorithms to improve the imaging capability of pulse-echo ultrasound array imagers. U-MBIR is an inversion technique that reconstructs the sample under test from the ultrasound measurements by formulating and solving a mathematical optimization problem using two sets of terms: one set ensures that the reconstruction matches measured data based on a model for the physics of beam propagation with the noise in the detector, and another set ensures that the reconstruction has certain properties based on a model for the object being scanned. This paper compares three techniques: SAFT, frequency-banded SAFT (FB-SAFT), and U-MBIR. The U-MBIR method produces higher quality images of the underlying concrete structures compared to the images produced using SAFT and FB-SAFT from the same set of measurements. This paper also illustrates the detection of various defects with higher confidence due to the lower noise and artifact-free U-MBIR images.

Ezell, N Dianne↗

Generalizable machine learning potentials for quantum-accurate predictions of non-equilibrium behavior in 2D materials

Machine learning interatomic potentials (ML-IAPs) are emerging as transformative tools in materials modeling, promising quantum-level accuracy at a fraction of the computational cost. However, their ability to generalize beyond equilibrium configurations and to reliably capture defect- and temperature-driven behavior remains underexplored. Here, we develop and benchmark two state-of-the-art ML-IAPs, Spectral Neighbor Analysis Potential (SNAP) and Allegro, on a comprehensive dataset for monolayer MoSe₂. Using density functional theory (DFT) as the reference, we evaluate their performance in capturing stress–strain behavior, phase transition energetics, defect evolution, edge stability, and fracture toughness. Allegro, a deep equivariant neural network potential, surpasses both SNAP and the classical Tersoff potential in accuracy, efficiency, and transferability. Importantly, both ML potentials accurately reproduce experimental fracture measurements and ab initio predictions of inversion domain formation—phenomena well beyond their training sets. Our findings establish ML-IAPs as viable replacements for traditional force fields in the study of non-equilibrium mechanical phenomena, enabling large-scale, high-fidelity simulations in 2D materials and beyond. In conclusion, this work provides a broadly applicable framework for data-driven modeling of structural and functional transformations under extreme conditions.

2D materials↗

Dissociated vacancies and screw dislocations in MgO and UO 2 : atomistic modeling and linear elasticity analysis

Understanding the effect of dislocations on the mass transport in ionic ceramics is important for understanding the behavior of these materials in a variety of contexts. In particular, the dissociated nature of vacancies at screw dislocations, or more generally, at a wide range of low-angle twist grain-boundaries, has ramifications for the mechanism of defect migration and thus mass transport at these microstructural features. In this paper, a systematic study of the dissociated vacancies at screw dislocations in MgO is carried out. The important role of stress migration in the atomistic modeling study is identified. Another aspect of the current work is a rigorous treatment of the linear elasticity model. As a result, good agreement between the atomistic modeling results and the linear elasticity model is obtained. Furthermore, we demonstrate that the proposed vacancy dissociation mechanism can also be extended to more complicated ionic ceramics such as UO 2 , highlighting the generality of the mechanism.

36 MATERIALS SCIENCE↗

Holographic BCFT with a Defect on the End-of-the-World brane

In this paper, we propose a new gravity dual for a 2d BCFT with two conformal boundaries by introducing a defect that connects the two End-of-the-World branes. We demonstrate that the BCFT dual to this bulk model exhibits a richer lowest spectrum. The corresponding lowest energy eigenvalue can continuously interpolate between - πc 24 Δ x and 0 where Δ x is the distance between the boundaries. This range was inaccessible to the conventional AdS/BCFT model with distinct boundary conditions. We compute the holographic entanglement entropy and find that it exhibits three different phases, one of which breaks the time reflection symmetry. We also construct a wormhole saddle, analogous to a 3d replica wormhole, which connects different boundaries through the AdS bulk. This saddle is present only if the BCFT is non-unitary and is always subdominant compared to the disconnected saddle.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗