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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Formation mechanism of two-dimensional hexagonal silica on SiO 2 /Si substrate

In this study, owing to their remarkable electronic properties, silica ultrathin films have been utilized as an insulating layer in nanoelectronics systems. Silica films have been epitaxially grown on different substrates using various synthesis methods. Among all fabrication approaches, chemical vapor deposition has long been an advanced method for synthesizing two-dimensional (2D) materials due to its ability to ensure precise stacking control and minimize contamination between layers. This study harnessed the potential of CVD to atomically fabricate thin layered 2D silica on a SiO 2 /Si substrate. Significantly, a unique combination of multiple transition metals and salt as the catalysts aided the formation of 2D silica for the first time. Salt is a crucial catalyst in promoting the evaporation of high-melting-point metal catalysts, resulting in hexagonal nucleation sites on the SiO 2 /Si wafer. By meticulously controlling growth parameters, a distinctive hexagonal structure was obtained. Correspondingly, this work delves into the growth mechanism of 2D silica, as evidenced by experiments involving salt alone and individual transition metals. Group VB transition metals played a prominent role in achieving the hexagonal structure compared to their group IVB counterparts. This research offers insight into the formation and growth mechanism of 2D silica, expanding the understanding of silica nanostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Fast uncertainty estimates in deep learning interatomic potentials

Deep learning has emerged as a promising paradigm to give access to highly accurate predictions of molecular and material properties. A common short-coming shared by current approaches, however, is that neural networks only give point estimates of their predictions and do not come with predictive uncertainties associated with these estimates. Existing uncertainty quantification efforts have primarily leveraged the standard deviation of predictions across an ensemble of independently trained neural networks. This incurs a large computational overhead in both training and prediction, resulting in order-of-magnitude more expensive predictions. Here, we propose a method to estimate the predictive uncertainty based on a single neural network without the need for an ensemble. This allows us to obtain uncertainty estimates with virtually no additional computational overhead over standard training and inference. We demonstrate that the quality of the uncertainty estimates matches those obtained from deep ensembles. We further examine the uncertainty estimates of our methods and deep ensembles across the configuration space of our test system and compare the uncertainties to the potential energy surface. Finally, we study the efficacy of the method in an active learning setting and find the results to match an ensemble-based strategy at order-of-magnitude reduced computational cost.

Chemistry↗
DOE OSTI2020

Pool boiling critical heat flux studies of accident tolerant fuel cladding materials

Pool boiling experiments have been performed at atmospheric pressure on potential accident tolerant fuel (ATF) cladding materials (Zirlo®, Cr coated Zirlo®, FeCrAl coated Zirlo®, and monolithic SiC) to evaluate the Critical Heat Flux (CHF) points. Corrosion resistant coatings of Cr and FeCrAl alloy were deposited on flat Zirlo® samples using cold spray technology. The as-prepared samples after uniform surface polishing were subjected to autoclave tests at 360 °C water and 18.6 MPa for 360 h to simulate prototypic corrosion of the ATF cladding materials in LWR normal operation. Surface characteristics potentially influencing CHF such as surface morphology, roughness, static contact angle, and surface chemistry were characterized using a suite of characterization methods including scanning electron microscopy, 3D optical profilometry, optical contact angle measurements, and x-ray photoelectron spectroscopy (XPS). Thermo-physical properties of the samples such as density, thermal conductivity, and heat capacity were measured by differential scanning calorimetry and laser flash thermal diffusivity measurement. FeCrAl coatings showed CHF values comparable to bare Zirlo® samples, while slightly lower CHF values were observed for Cr coated samples and bulk SiC flats (produced by chemical vapor deposition, CVD). As-deposited Cr coatings showed 67% higher CHF than the as-polished Cr coatings due to its higher surface roughness level. The autoclave testing for the prepared samples generally increased the CHF except for the surface polished Cr coatings. Similar CHF values of bare Zirlo®, FeCrAl coating, and CVD SiC samples were observed after autoclave test but there were negligible change CHF of Cr coatings. XPS studies indicated that the formation or deposition of a few monolayers of hydrophobic carbonaceous species on surface can affect CHF values. The trends in CHF data are discussed in terms of evolution of the surface characteristics of the ATF materials.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Accurate energies for ππ* excited states via exchange scaling: the XS-CASSCF method

The state-averaged complete-active space self-consistent field method (SA-CASSCF) is a widely employed electronic structure method used for studying photochemistry and dynamics owing to its ability to provide a reliable description even of complicated cases while still retaining computational efficiency. However, SA-CASSCF suffers from one Achilles heel, related to the description of ionic ππ* excited states, whose energy is often overestimated by 1–2 eV. In light of this challenge, we present the XS-CASSCF method, a new approach based on the idea of exchange scaling (XS) that screens the involved energy terms to improve the excitation energies of singlet ionic ππ* states. First, we illustrate the power of the XS-CASSCF method using hexatriene and para-quinodimethane as examples, showing that it corrects the targeted ionic states while leaving the other states largely unaffected, giving root-mean-square errors (RMSE) below 0.2 eV for the four lowest states in both cases. Subsequently, XS-CASSCF vertical excitation energies are tested against theoretical best estimates for a set of 11 molecules and 56 excited states. XS-CASSCF performs exceptionally well for the ππ* states of hydrocarbons, reducing the RMSE over 21 excitation energies from 0.96 to 0.27 eV. In the challenging subset of molecules with heteroatoms and a larger number of ππ* and nπ* states, we find that improvements can also be obtained, albeit not as pronounced. We conclude with an outlook into more realistic molecular materials focusing on their singlet–triplet (S 1 /T 1 ) gaps, finding that significant improvements can be obtained along the whole range of S 1 /T 1 gaps studied, going from 0.1 eV to more than 1.5 eV. Owing to notable improvements across significant classes of molecules combined with its conceptual simplicity, we believe that XS-CASSCF is a promising addition to the electronic structure toolbox, serving both as a standalone electronic structure method and as a starting point for further correlated treatment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Fundamental gap of fluorographene by many-body GW and fixed-node diffusion Monte Carlo methods

Fluorographene (FG) is a promising graphene-derived material with a large bandgap. Currently existing predictions of its fundamental gap (Δ f ) and optical gap (Δ opt ) significantly vary when compared with experiment. We provide here an ultimate benchmark of Δ f for FG by many-body GW and fixed-node diffusion Monte Carlo (FNDMC) methods. Both approaches independently arrive at Δf ≈ 7.1 ± 0.1 eV. In addition, the Bethe–Salpeter equation enabled us to determine the first exciton binding energy, Eb = 1.92 eV. We also point to the possible misinterpretation problem of the results obtained for gaps of solids by FNDMC with single-reference trial wave functions of Bloch orbitals. We argue why instead of Δ opt , in the thermodynamic limit,

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Global Phase Diagram of a Spin-Orbital Kondo Impurity Model and the Suppression of Fermi-Liquid Scale

Many correlated metallic materials are described by Landau Fermi-liquid theory at low energies, but for Hund metals the Fermi-liquid coherence scale $T_{FL}$ is found to be surprisingly small. In this Letter, we study the simplest impurity model relevant for Hund metals, the three-channel spin-orbital Kondo model, using the numerical renormalization group (NRG) method and compute its global phase diagram. In this framework, $T_{FL}$ becomes arbitrarily small close to two new quantum critical points that we identify by tuning the spin or spin-orbital Kondo couplings into the ferromagnetic regimes. We find quantum phase transitions to a singular Fermi-liquid or a novel non-Fermi-liquid phase. The new non-Fermi-liquid phase shows frustrated behavior involving alternating overscreenings in spin and orbital sectors, with universal power laws in the spin (ω -1/5 ), orbital (ω 1/ 5 ) and spin-orbital (ω 1 ) dynamical susceptibilities. These power laws, and the NRG eigenlevel spectra, can be fully understood using conformal field theory arguments, which also clarify the nature of the non-Fermi-liquid phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Highly Permeable Rubbery Thin Film Composite Membranes for CO2 Capture from Steel Mills

For presentation at the 2024 AIChE Annual Meeting, San Diego, CA, October 27-31, 2024. High-permeance and CO2-selective membranes are needed to make membrane technology economically viable for large-scale deployment of carbon capture from various industrial point sources such as steel mills. Thin film composite (TFC) membranes are necessary for this practical implementation because they can provide high permeance by forming a thin selective layer on top of a porous support layer. This presentation reports the rational design and fabrication of National Energy Technology Laboratory’s highly permeable non-aging TFC membranes achieved by: (1) synthesizing a high-performance rubbery selective material; (2) developing a high-porosity membrane support; (3) optimizing coating methods to assemble the two materials into scalable membranes; and (4) scaling up membrane supports and TFCs via a roll-to-roll process. This talk will also cover the design, computational fluid dynamic simulation, 3D printing, construction, and permeation testing of plate-and-frame membrane modules for an upcoming field demonstration at U. S. Steel’s Edgar Thomson Plant in Braddock, PA.

Zhu, Lingxiang↗
DOE OSTI2025

Rapid Screening of Liquid Metal Wetting for a Materials Compatibility Library

Wetting behavior of molten metals on solid substrates is a critical phenomenon influencing numerous industrial applications, including welding, anti-corrosion coatings, and metal additive manufacturing (AM). In particular, molten metal jetting (MMJ), an emerging AM technology, requires that the molten metal remain pinned at the nozzle exit. Thus, each new metal requires a specific nozzle material to ensure consistent droplet ejection and deposition, making it important to rapidly identify the appropriate wetting combinations. However, traditional measurements of wetting angles require expensive equipment and only allow one combination of materials to be investigated at a time which can be time consuming. This work introduces a rapid screening method based on sessile droplet experiments to evaluate wetting profiles across multiple metal–substrate combinations simultaneously. This study investigates the wetting interactions of molten Al alloy (Al4008), Cu, and Sn on various ceramic and metal substrates to identify optimal material combinations for MMJ nozzle designs. Results demonstrate that Al4008 achieves wetting on ceramic substrates such as AlN, TiO 2 , and SiC, with varying mechanisms including chemical reactions and weak surface interactions. Additionally, theoretical predictions regarding miscibility gaps and melting point differences were verified for Cu and Sn on refractory metals like Mo and W. Findings from this study contribute to the establishment of a materials compatibility library, enabling the selection of wetting/non-wetting combinations for stable MMJ operation. This resource not only advances MMJ technologies but also provides valuable insights for broader applications such as welding, coating, and printed electronics.

Materials science↗
DOE OSTI2023

Fast and accurate reduced-order modeling of a MOOSE-based additive manufacturing model with operator learning

One predominant challenge in additive manufacturing (AM) is to achieve specific material properties by manipulating manufacturing process parameters during the runtime. Such manipulation tends to increase the computational load imposed on existing simulation tools employed in AM. The goal of the present work is to construct a fast and accurate reduced-order model (ROM) for an AM model developed within the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, ultimately reducing the time/cost of AM control and optimization processes. Our adoption of the operator learning (OL) approach enabled us to learn a family of differential equations produced by altering process variables in the laser’s Gaussian point heat source. More specifically, we used the Fourier neural operator (FNO) and deep operator network (DeepONet) to develop ROMs for time-dependent responses. Furthermore, we benchmarked the performance of these OL methods against a conventional deep neural network (DNN)-based ROM. Ultimately, we found that OL methods offer comparable performance and, in terms of accuracy and generalizability, even outperform DNN at predicting scalar model responses. The DNN-based ROM afforded the fastest training time. Furthermore, all the ROMs were faster than the original MOOSE model yet still provided accurate predictions. FNO had a smaller mean prediction error than DeepONet, with a larger variance for time-dependent responses. Unlike DNN, both FNO and DeepONet were able to simulate time series data without the need for dimensionality reduction techniques. Finally, the present work can help facilitate the AM optimization process by enabling faster execution of simulation tools while still preserving evaluation accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The effects of dose, dose rate, and irradiation type and their equivalence on radiation-induced segregation in binary alloy systems via phase-field simulations

Radiation-induced segregation is a phenomenon commonly observed in many alloys which consists of the redistribution of elements (solute or interstitial impurities) under irradiation. The onset and development of radiation-induced segregation can only occur when a sufficient flux of defects is sustained and defect sinks are present. Irradiation dose, dose rate, and particle types all affect defect flux. In this work, we employ a phase-field model to examine the effects of dose, dose rate, and type of incident particles on radiation-induced segregation behavior in a model binary alloy. The phase-field model takes into account the formation and evolution of point defects as well as defect clusters, the diffusion and clustering of alloy species, the presence of additional extrinsic defect sinks in the form of dislocations, and two different methods of radiation-damage insertion, which are intended to simulate either light-ion/electron irradiation via Frenkel pairs or heavy-ion irradiation in the form of cascades. Our results show a dose-rate and particle-type dependence on the amount of solute segregation. We show that the material systems exposed to higher dose rates are less subjected to solute segregation at equivalent doses. We also show that such dose-rate-dependence behavior is due to a delay of the incubation dose at which radiation-induced segregation effectively starts. Particle type and the presence of dislocations can accentuate this behavior. Our model predictions correlate with many experimental observations made over the years on radiation-induced segregation providing credence to the simulation results. The methodology presented in this study allows for a first-order prediction of the dose rate at which proxy irradiation experiments could be performed to approximate radiation-induced segregation behaviors seen in targeted irradiation conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Ab initio ultrafast spin dynamics in solids

Spin relaxation and decoherence is at the heart of spintronics and spin-based quantum information science. Currently, theoretical approaches that can accurately predict spin relaxation of general solids including necessary scattering pathways and are capable of nanosecond to millisecond simulation time are urgently needed. We present a first-principles real-time density-matrix approach based on Lindblad dynamics to simulate ultrafast spin dynamics for general solid-state systems. Through the complete first-principles descriptions of pump, probe, and scattering processes including electron-phonon, electron-impurity, and electron-electron scatterings with self-consistent electronic spin-orbit couplings, our method can directly simulate the ultrafast pump-probe measurements for coupled spin and electron dynamics over nanoseconds at any temperatures and doping levels. We first apply this method to a prototypical system GaAs and obtain excellent agreement with experiments. We found that the relative contributions of different scattering mechanisms and phonon modes differ considerably between spin and carrier relaxation processes. In sharp contrast to previous work based on model Hamiltonians, we point out that the electron-electron scattering is negligible at room temperature but becomes dominant at low temperatures for spin relaxation in n-type GaAs. We further examine ultrafast dynamics in novel spin-valleytronic materials: monolayer and bilayer WSe 2 with realistic defects. We find that spin relaxation is highly sensitive to local symmetry and chemical bonds around defects. For the bilayer WSe 2 , we identify the scattering pathways in ultrafast dynamics and determine relevant dynamical properties, essential to its utilization of unique spin-valley-layer locking effects. In conclusion, our work provides a predictive computational platform for spin dynamics in solids, which has potential for designing new materials ideal for spintronics and quantum information technology.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Topological Exact Flat Bands in Two-Dimensional Materials under Periodic Strain

Here we study flat bands and their topology in 2D materials with quadratic band crossing points under periodic strain. In contrast to Dirac points in graphene, where strain acts as a vector potential, strain for quadratic band crossing points serves as a director potential with angular momentum . We prove that when the strengths of the strain fields hit certain “magic” values, exact flat bands with emerge at charge neutrality point in the chiral limit, in strong analogy to magic angle twisted-bilayer graphene. These flat bands have ideal quantum geometry for the realization of fractional Chern insulators, and they are always fragile topological. The number of flat bands can be doubled for certain point group, and the interacting Hamiltonian is exactly solvable at integer fillings. We further demonstrate the stability of these flat bands against deviations from the chiral limit, and discuss possible realization in 2D materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Optical properties of Mo and amorphous MoOx, and application to antireflection coatings for metals

To form antireflection (AR) coatings to hide metal architecture in display technologies, we deposited thin films of metal Mo and oxide MoOx by sputtering targets of various compositions using pure Ar sputter gas. The optical constants [n,k] of these samples were measured by the direct numerical solution of reflectance and transmittance at each wavelength point measured. We find that 50 nm films are uniform in the growth direction, but for thicker 100 nm samples, evidence exists for nonuniform growth, where the top 20 nm appears to be metal rich. From these [n,k], negative Tauc bandgap energies show these oxides are semi-metals. We then identified the specific composition (x) that optimizes the AR response for a host of metals (Al, Cu, Ag, Au). Finally, two methods were used to understand why these MoOx materials function well as AR media, including (i) using phasor rays and (ii) developing a universal expression for the AR condition that applies to both dielectric and metal substrates. In (i), we find two characteristics for AR of metals: (a) its optical thickness should be roughly π3, not the π2 for dielectrics, since for MoOx, their [r^ij,t^ij] Fresnel phases differ from the usual [180°, 0°] of dielectrics; and (b) the medium incorporates a k-dominant strategy whose function is to absorb the energy that is reflected at the AR/metal interface. In (ii), the universal AR condition is found to be r^01+r^12z^=0. For dielectrics, this reduces to the well-known nAR=nairnsub condition. However, for metals, a concise analytic expression is lacking since this expression is highly nonlinear but is easily solved by numerical methods.

Tsu, David V. (ORCID:0000000295903418)↗
DOE OSTI2023

Topological enhancement of nonlinear transport in unconventional point-node semimetals

The topological singularity of the Bloch states close to the Fermi level significantly enhances nonlinear electric responses in topological semimetals. Here, we systematically characterize this enhancement for a large class of topological nodal-point fermions, including those with linear, linear-quadratic, and quadratic dispersions. Specifically, we determine the leading power-law dependence of the nonlinear response functions on the chemical potential μ defined relative to the nodal point. We identify two characteristics that qualitatively improve nonlinear transports compared to those of conventional Dirac and Weyl fermions. First, the type-II (overtilted) spectrum leads to the log μ enhancement of nonlinear response functions having zero scaling dimension with respect to μ, which is not seen in a type-I (moderately or not tilted) spectrum. Second, the anisotropic linear-quadratic dispersion increases the power of small-μ divergence for the nonlinear response tensors along the linearly dispersing direction. Furthermore, our work reveals new experimental signatures of unconventional nodal points in topological semimetals as well as provides a guiding principle for giant nonlinear electric responses.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

GPU-Accelerated Solution of the Bethe–Salpeter Equation for Large and Heterogeneous Systems

We present a massively parallel GPU-accelerated implementation of the Bethe–Salpeter equation (BSE) for the calculation of the vertical excitation energies (VEEs) and optical absorption spectra of condensed and molecular systems, starting from single-particle eigenvalues and eigenvectors obtained with density functional theory. The algorithms adopted here circumvent the slowly converging sums over empty and occupied states and the inversion of large dielectric matrices through a density matrix perturbation theory approach and a low-rank decomposition of the screened Coulomb interaction, respectively. Further computational savings are achieved by exploiting the nearsightedness of the density matrix of semiconductors and insulators to reduce the number of screened Coulomb integrals. We scale our calculations to thousands of GPUs with a hierarchical loop and data distribution strategy. The efficacy of our method is demonstrated by computing the VEEs of several spin defects in wide-band-gap materials, showing that supercells with up to 1000 atoms are necessary to obtain converged results. We discuss the validity of the common approximation that solves the BSE with truncated sums over empty and occupied states. In conclusion, we then apply our GW-BSE implementation to a diamond lattice with 1727 atoms to study the symmetry breaking of triplet states caused by the interaction of a point defect with an extended line defect.

Absorption spectra↗
DOE OSTI2022

Easy-plane anisotropic-exchange magnets on a honeycomb lattice: Quantum effects and dealing with them

We provide analytical and numerical insights into the phase diagram and other properties of the extended Kitaev-Heisenberg model on the honeycomb lattice in the easy-plane limit, in which interactions are only between spin components that belong to the plane of magnetic ions. This parameter subspace allows for a much-needed systematic quantitative investigation of spin excitations in the ordered phases and of their generic features. Specifically, we demonstrate that in this limit one can consistently take into account magnon interactions in both zero-field zigzag and field-polarized phases. For the nominally polarized phase, we propose a regularization of the unphysical divergences that occur at the critical field and are plaguing the 1/S approximation in this class of models. For the explored parameter subspace, all symmetry-allowed terms of the standard parametrization of the extended Kitaev-Heisenberg model, such as K, J, and Γ, are significant, making the offered consideration relevant to a much wider parameter space. Furthermore, the dynamical structure factor near the paramagnetic critical point illustrates this relevance by showing features that are reminiscent of the ones observed in α–RuCl 3 , underscoring that they are not unique and should be common to a wide range of parameters of the model and, by extension, to other materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Multicomponent Nanoparticle Synthesis for Advanced Manufactured Melt Wire Development

Additive manufacturing (AM) based direct-write technologies have emerged as a predominant enabler for the fabrication of advanced passive sensors in-pile applications. This work continues previous efforts with the modification and optimization of synthesis methods for multi-component nanoparticle systems used to support the development, fabrication and testing of AM sensors for peak temperature detection. For this report, bismuth, bismuth/platinum, tin, tin/silver, tin/zinc, indium, and indium/silver bi-metallic nanoparticles were synthesized using the wet chemical methods. The nanoparticles were then characterized with x-ray fluorescence to evaluate the elemental composition and differential scanning to determine the melting point and mass loss of the samples. Results continue to show that bi-metallic nanoparticles are a viable pathway for the fabrication of high-resolution AM melt wires.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Sustainable Aviation Fuel via Hydroprocessing of Catalytic Fast Pyrolysis Oil

Cycloalkanes have been identified as a promising alternative for sustainable aviation fuel (SAF) in a recent US Department of Energy Review of Technical Pathways to SAF. Cycloalkanes can provide desirable SAF properties, including energy density, and, in addition, they may be able to provide necessary seal swelling and leakage protection and replace undesirable aromatics in aviation fuel. Catalytic fast pyrolysis (CFP) followed by hydroprocessing constitutes a platform well suited for converting biomass to cycloalkanes. CFP oils are rich in phenolic compounds and, depending on CFP catalyst, in aromatic hydrocarbons, which can both be hydrogenated to form cycloalkanes. In this work, we report results from hydroprocessing of two types of CFP oil to produce fractions boiling in the sustainable aviation fuel range and meeting tested aviation fuel specifications. CFP oils prepared over a zeolite catalyst (ZSM-5) and a hydrodeoxygenation catalyst (Pt/TiO2) were hydroprocessed over a sulfided NiMo/Al2O3 catalyst in a two-stage process (1st stage ~250 degrees C and 2nd stage 385 degrees C) in a continuous trickle-bed hydrotreater. The hydrotreated product contained 39-40% material boiling in the SAF range by distillation with a carbon efficiency of 36-37% from CFP oil to SAF fraction. The SAF fractions consisted of 82-87% of cycloalkanes, had non-detectable oxygen contents and lower heating values (LHV) above the jet fuel minimum limit of 42.8 MJ/kg. The SAF-range product also had acceptable volatility and freeze and flash points per aviation fuel specifications. The results suggest a promising pathway for SAF production via the catalytic fast pyrolysis pathway. Methods to enhance the yield of SAF will be discussed.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗