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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Time-dependent THMC properties and microstructural evolution of damaged rocks in excavation damage zone

Modeling coupled thermo-hydro-mechanical-chemical (THMC) processes in host rocks near high-level nuclear waste (HLW) repositories at various time scales is an extremely challenging task. The current study integrates experimental, theoretical, and numerical methods in assessing the evolution of excavation damage zone (EDZ) over time and its implication on the long-term migration of hazardous species. Argillite and rock salt and are the focus of this study. The first part of the report presents a novel time-dependent directional microcrack damage theory for generic brittle rocks. It features detailed statistical description of the microcracks within a damaged solid, permitting a direct upscaling of microscale processes such as crack growth kinetics, crack closure/opening, sliding friction to explain the macroscopic creep, nonlinear elasticity, shear dilation, and loading-unloading hysteresis. This provides a basic platform for describing the anisotropic mechanical and transport properties of damaged rocks during excavation and subsequent THMC loadings. The model is validated and numerically implemented to Finite Element (FE) package ABAQUS through the user-defined material (UMAT) interface and have demonstrated great potential in resolving the time-dependent and anisotropic evolution of damage in the EDZ. The second part of the report presents a multi-scale experimental effort in characterizing the thermal, hydraulic, and mechanical properties of Mancos shale and Avery Island salt. For the Mancos shale, triaxial compression tests are performed at different confining pressures and temperatures to probe its thermomechanical properties relevant to HLW repositories. The obtained stress-strain data are interpreted using the proposed directional damage theory. Post-test specimens are subjected to gas permeability tests to reveal the correlation between permeability and the degree of microcracking. At microscale, temperature-controlled nanoindentation tests are performed and found a linear correlation between fracture toughness and elastic modulus from 25°C to 300°C. For Avery Island salt, we have designed and manufactured a novel relative-humidity controlled uniaxial creep device. Long-term creep tests at low stresses (< 5 MPa) are performed at different levels of relative humidity (RH). Besides confirming the much higher creep rates as one would expect through extrapolating the high-stress creep data, the results reveal that the steady-state creep rate of rock salt is strongly dependent on the ambient RH, an aspect that is often neglected in the literature. Both behaviors can be attributed to the pressure-solution creep mechanism which dominates at low stress and high RH levels. The third part of the report explores a set of numerical strategies in modeling the THMC behavior of porous geomaterials. A fully implicit, monolithic FE solution that can flexibly interface with different material models and coupling mechanisms for THMC problems is developed and verified through the ABAQUS user-defined element (UEL) interface. The scheme is used to study the THM response of a hypothetical HLW storage site with reference to an existing in-situ heater test. Strategies for integrating the UEL and the microcrack UMAT are suggested. Another numerical endeavor of this study is to implement a higher-order asymptotic homogenization method to account for the heterogeneous porous structures. The same method is then extended to perform microstructure-informed thermo-mechanical modeling of generalized continua. The above outcomes of this project provide a strong thrust towards enhancing the fundamental understanding and modeling capability of the long-term evolution of host rocks in EDZ, thus helping achieve the design goal of 1-million-year isolation of high-level nuclear wastes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Accuracy of the time-averaged ponderomotive approximation for laser-plasma accelerator modeling

Reliable modeling of laser-plasma accelerators, where a short and intense laser pulse propagates in an underdense plasma over long distances, is a computationally challenging task. This is due to the great disparity among the scales involved in the modeling, ranging from the micrometer scale of the laser wavelength to, for instance, the meter scale of the laser-plasma interaction length for a multi-GeV-class laser-plasma accelerator. To reduce such imbalance, the time-averaged ponderomotive approximation may be used, where the plasma particle dynamics is analytically averaged over the laser frequency, and only spatiotemporal scales associated with the laser envelope are retained in the calculations, resulting in significant computational savings. Here, we characterize the accuracy and robustness of the time-averaged ponderomotive approximation for a range of laser parameters of interest for present and future laser-plasma accelerators, and we show that the error introduced by the averaging process is small in all relevant cases.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

The Effective Fragment Molecular Orbital Method: Achieving High Scalability and Accuracy for Large Systems

The effective fragment molecular orbital (EFMO) method has been developed to predict the total energy of a very large molecular system accurately (with respect to the underlying quantum mechanical method) and efficiently by taking advantage of the locality of strong chemical interactions and employing a two-level hierarchical parallelism. The accuracy of the EFMO method is partly attributed to the accurate and robust intermolecular interaction prediction between distant fragments, in particular, the many-body polarization and dispersion effects, which require the generation of static and dynamic polarizability tensors by solving the coupled perturbed Hartree–Fock (CPHF) and time-dependent HF (TDHF) equations, respectively. Solving the CPHF and TDHF equations is the main EFMO computational bottleneck due to the inefficient (serial) and I/O-intensive implementation of the CPHF and TDHF solvers. In this work, the efficiency and scalability of the EFMO method are significantly improved with a new CPU memory-based implementation for solving the CPHF and TDHF equations that are parallelized by either message passing interface (MPI) or hybrid MPI/OpenMP. Here, the accuracy of the EFMO method is demonstrated for both covalently bonded systems and noncovalently bound molecular clusters by systematically examining the effects of basis sets and a key distance-related cutoff parameter, R cut . R cut determines whether a fragment pair (dimer) is treated by the chosen ab initio method or calculated using the effective fragment potential (EFP) method (separated dimers). Decreasing the value of Rcut increases the number of separated (EFP) dimers, thereby decreasing the computational effort. It is demonstrated that excellent accuracy (<1 kcal/mol error per fragment) can be achieved when using a sufficiently large basis set with diffuse functions coupled with a small R cut value. With the new parallel implementation, the total EFMO wall time is substantially reduced, especially with a high number of MPI ranks. Given a sufficient workload, nearly ideal strong scaling is achieved for the CPHF and TDHF parts of the calculation. For the first time, EFMO calculations with the inclusion of long-range polarization and dispersion interactions on a hydrated mesoporous silica nanoparticle with explicit water solvent molecules (more than 15k atoms) are achieved on a massively parallel supercomputer using nearly 1000 physical nodes. In addition, EFMO calculations on the carbinolamine formation step of an amine-catalyzed aldol reaction at the nanoscale with explicit solvent effects are presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Atomistic Origin of Microsecond Carrier Lifetimes at Perovskite Grain Boundaries: Machine Learning-Assisted Nonadiabatic Molecular Dynamics

The polycrystalline nature of perovskites, stemming from their facile solution-based fabrication, leads to a high density of grain boundaries (GBs) and point defects. However, the impact of GBs on perovskite performance remains uncertain, with contradictory statements found in the literature. We developed a machine learning force field, sampled GB structures on a nanosecond time scale, and performed nonadiabatic (NA) molecular dynamics simulations of charge carrier trapping and recombination in stoichiometric and doped GBs. The simulations reveal long, microsecond carrier lifetimes, approaching experimental data, stemming from charge separation at the GBs and small NA coupling, 0.01–0.1 meV. Stoichiometric GBs exhibit transient trap states, which, however, are not particularly detrimental to the carrier lifetime. Halide dopants form interstitial defects in the bulk, but have a stabilizing influence on the GB structure by passivating undersaturated Pb atoms and reducing the transient trap state formation. On the contrary, excess Pb destabilizes GBs, allowing formation of persistent midgap states that trap charges. Still, the charge carrier lifetime reduces relatively little, because the midgap states decouple from the bands, and charges are more likely to escape back into bands upon a GB structural fluctuation. The atomistic study into the structural dynamics of perovskite GBs and its influence on charge carrier trapping and recombination provides valuable insights into the complex properties of perovskites and the intricate role of GBs in the material performance.

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

SeismoGen: Seismic Waveform Synthesis Using GAN With Application to Seismic Data Augmentation

Abstract Detecting earthquake arrivals within seismic time series can be a challenging task. Visual, human detection has long been considered the gold standard but requires intensive manual labor that scales poorly to large data sets. In recent years, automatic detection methods based on machine learning have been developed to improve the accuracy and efficiency. However, the accuracy of those methods relies on access to a sufficient amount of high‐quality labeled training data, often tens of thousands of records or more. We aim to resolve this dilemma by answering two questions: (1) provided with a limited amount of reliable labeled data, can we use them to generate additional, realistic synthetic waveform data? and (2) can we use those synthetic data to further enrich the training set through data augmentation, thereby enhancing detection algorithms? To address these questions, we use a generative adversarial network (GAN), a type of machine learning model which has shown supreme capability in generating high‐quality synthetic samples in multiple domains. Once trained, our GAN model is capable of producing realistic seismic waveforms of multiple labels (noise and event classes). Applied to real Earth seismic data sets in Oklahoma, we show that data augmentation from our GAN‐generated synthetic waveforms can be used to improve earthquake detection algorithms in instances when only small amounts of labeled training data are available.

Wang, Tiantong↗
DOE OSTI2025

Medium-Range Order, Density Fluctuations, and Activated Relaxation in the Equilibrated Deep Glass Regime

A successful microscopic theory of activated relaxation in metastable supercooled liquids is extended to the equilibrated deep glass regime. Surprisingly, the predicted power-law scaling connections of the dynamic barrier with diverse scalar order parameters (medium-range order correlation length, dimensionless compressibility, shear modulus) remain unchanged up to astronomically long timescales, despite a fundamental crossover of equilibrium thermodynamics and structure near the laboratory kinetic vitrification point. Quantitative tests against experiments on aged to equilibrium glass-forming liquids up to nearly 20 decades in time scale reveal good agreement. This conflicts with the idea of a crossover from super-Arrhenius to literal Arrhenius relaxation around the laboratory glass transition temperature, and supports the robustness of the theoretical idea that ultraslow dynamics is causally related to medium-range structural order. Here, new avenues of experimental and theoretical research in the deep glass regime are suggested.

Amorphous materials↗
DOE OSTI2023

High-density integrated delay line using extreme skin-depth subwavelength grating waveguides

Optical delay lines control the flow of light in time, introducing phase and group delays for engineering interferences and ultrashort pulses. Photonic integration of such optical delay lines is essential for chip-scale lightwave signal processing and pulse control. However, typical photonic delay lines based on long spiral waveguides require extensively large chip footprints, ranging from mm 2 to cm 2 scales. Here we present a scalable, high-density integrated delay line using a skin-depth engineered subwavelength grating waveguide, i.e., an extreme skin-depth (eskid) waveguide. The eskid waveguide suppresses the crosstalk between closely spaced waveguides, significantly saving the chip footprint area. Our eskid-based photonic delay line is easily scalable by increasing the number of turns and should improve the photonic chip integration density.

Ahmed, Ishtiaque↗
DOE OSTI2022

Müllerian mimicry and the coloration patterns of sympatric coral snakes

Abstract Coral snakes in the genus Micrurus are venomous, aposematic organisms that signal danger to predators through vivid coloration. Previous studies found that they serve as models to several harmless species of Batesian mimics. However, the extent to which Micrurus species engage in Müllerian mimicry remains poorly understood. We integrate detailed morphological and geographical distribution data to investigate if coral snakes are Müllerian mimics. We found that coloration is spatially structured and that Micrurus species tend to be more similar where they co-occur. Though long supposed, we demonstrate for the first time that coral snakes might indeed be Müllerian mimics as they show some convergence in coloration patterns. Additionally, we found that the length of red-coloured rings in Micrurus is conserved, even at large geographic scales. This finding suggests that bright red rings may be under more substantial stabilizing selection than other aspects of coloration and probably function as a generalized signal for deterring predators.

Evolutionary Biology↗
DOE OSTI2022

A scale-wise analysis of intermittent momentum transport in dense canopy flows

We investigate the intermittent dynamics of momentum transport and its underlying time scales in the near-wall region of the neutrally stratified atmospheric boundary layer in the presence of a vegetation canopy. This is achieved through an empirical analysis of the persistence time scales (periods between successive zero-crossings) of momentum flux events, and their connection to the ejection–sweep cycle. Using high-frequency measurements from the GoAmazon campaign, spanning multiple heights within and above a dense canopy, the analysis suggests that, when the persistence time scales ( $t_p$ ) of momentum flux events from four different quadrants are separately normalized by $\varGamma _{w}$ (integral time scale of the vertical velocity), their distributions $P(t_p/\varGamma _{w})$ remain height-invariant. This result points to a persistent memory imposed by canopy-induced coherent structures, and to their role as an efficient momentum-transporting mechanism between the canopy airspace and the region immediately above. Moreover, $P(t_p/\varGamma _{w})$ exhibits a power-law scaling at times $t_{p}<\varGamma _{w}$ , with an exponential tail appearing for $t_{p} \geq \varGamma _{w}$ . By separating the flux events based on $t_p$ , we discover that around 80 % of the momentum is transported through the long-lived events ( $t_{p} \geq \varGamma _{w}$ ) at heights immediately above the canopy, while the short-lived ones ( $t_{p} < \varGamma _{w}$ ) only contribute marginally ( $\approx 20\,\%$ ). To explain the role of instantaneous flux amplitudes in momentum transport, we compare the measurements with newly developed surrogate data and establish that the range of time scales involved with amplitude variations in the fluxes tends to increase as one transitions from within to above the canopy.

Mechanics↗
DOE OSTI2020

Spectral form factors of clean and random quantum Ising chains

We compute the spectral form factor of two integrable quantum-critical many-body systems in one spatial dimension. The spectral form factor of the quantum Ising chain is periodic in time in the scaling limit described by a conformal field theory; we also compute corrections from lattice effects and deviation from criticality. Iin this work, criticality in the random Ising chain is described by rare regions associated with a strong randomness fixed point, and these control the long-time limit of the spectral form factor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Fusion Innovation and the Valley of Death—Lessons from Fission

Over the past several decades, the United States (U.S.) and other countries have done important research and development in advanced nuclear energy technologies, both fission and fusion. The urgency of our current climate, energy, and security needs have prompted a concerted effort by innovators, investors, and the public sector to transition from research and development (R&D) to demonstration and commercialization—to cross the proverbial “valley of death.” The stakes are high: humanity needs clean energy options, and the failure of any promising alternative will lower our odds of success. The process of moving an innovation into use has often been described in phases that begin with early research and end with deployment at scale. Between those two phases lies an area often referred to as the “valley of death” because it can require a long period of time, large investments, and often includes significant challenges related to regulation, standardization, and entering markets already structured around incumbent technologies. What can we learn from recent experience with fission to inform our path forward with fusion? At least five key lessons rise to the top: 1) Set bold targets; 2) Empower the private sector; 3) Engage with regulators and the public; 4) Address costs and markets; and 5) Deliver results. Here, this editorial will consider each of these in turn.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

A Perspective on ferroelectricity in hafnium oxide: Mechanisms and considerations regarding its stability and performance

Ferroelectric hafnium oxides are poised to impact a wide range of microelectronic applications owing to their superior thickness scaling of ferroelectric stability and compatibility with mainstream semiconductors and fabrication processes. For broad-scale impact, long-term performance and reliability of devices using hafnia will require knowledge of the phases present and how they vary with time and use. In this Perspective article, the importance of phases present on device performance is discussed, including the extent to which specific classes of devices can tolerate phase impurities. Following, the factors and mechanisms that are known to influence phase stability, including substituents, crystallite size, oxygen point defects, electrode chemistry, biaxial stress, and electrode capping layers, are highlighted. Herein, discussions will focus on the importance of considering both neutral and charged oxygen vacancies as stabilizing agents, the limited biaxial strain imparted to a hafnia layer by adjacent electrodes, and the strong correlation of biaxial stress with resulting polarization response. Areas needing additional research, such as the necessity for a more quantitative means to distinguish the metastable tetragonal and orthorhombic phases, quantification of oxygen vacancies, and calculation of band structures, including defect energy levels for pure hafnia and stabilized with substituents, are emphasized.

36 MATERIALS SCIENCE↗
DOE OSTI2020

On the Correspondence between Seasonal Forecast Biases and Long-Term Climate Biases in Sea Surface Temperature

In this paper, the correspondence between mean sea surface temperature (SST) biases in retrospective seasonal forecasts (hindcasts) and long-term climate simulations from five global climate models is examined to diagnose the degree to which systematic SST biases develop on seasonal time scales. The hindcasts are from the North American Multi-Model Ensemble and the climate simulations are from the Coupled Model Intercomparison Project. The analysis suggests that most robust climatological SST biases begin to form within 6 months of a realistically initialized integration, although the growth rate varies with location, time, and model. In regions with large biases, interannual variability and ensemble spread is much smaller than the climatological bias. Additional ensemble hindcasts of the Community Earth System Model with a different initialization method suggest that initial conditions do matter for the initial bias growth, but the overall global bias patterns are similar after 6 months. A hindcast approach is more suitable to study biases over the tropics and sub-tropics than over the extra-tropics because of smaller initial biases and faster bias growth. The rapid emergence of SST biases makes it likely that fast processes with times scales shorter than the seasonal time scales in the atmosphere and upper ocean are responsible for a substantial part of the climatological SST biases. Studying the growth of biases may provide important clues to the causes and ultimately the amelioration of these biases. Further, initialized seasonal hindcasts can profitably be used in the development of high-resolution coupled ocean-atmosphere models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy (Workshop Report)

The US Department of Energy’s (DOE’s) Advanced Manufacturing Office held the virtual workshop entitled “Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy” in November and December 2020. The workshop brought together participants from universities/laboratories, industries, equipment manufacturers, technology vendors, nongovernmental organizations, and subject-matter experts to discuss transformative technologies and strategies to substantially improve the performance (e.g., energy productivity, thermal efficiency, reduced greenhouse gas [GHG] emissions, reduced number of process steps) of thermal processing systems in the industrial sector. The US industrial sector accounts for 32% of the nation’s primary energy use (including feedstocks), and refining, chemicals, pulp and paper, iron and steel, and food products represent the top energy-consuming sectors. Thermal processing or process heating represents the largest energy use category; it accounts for 63% of all energy use in manufacturing. Additionally, thermal processing is the largest contributor of carbon dioxide (CO2) generation, resulting from combustion of fuels and process related chemical reactions, such as in the case of cement and lime production. The challenge of achieving net-zero industrial GHG emissions is colossal considering the established industrial base that depends mainly on carbon-based processes and energy sources; the time frame and cost to replace carbon-based energy sources and feedstocks; and the long-term outlook for development with large-scale adaptation of alternative non carbon–based technologies. The goals of the DOE Advanced Manufacturing Office Thermal Process Intensification Workshop were as follows: (1) Identify R&D gaps and opportunities to facilitate transformative improvement in industrial thermal processes beyond current technologies and allow for entirely new methods for processing materials; (2) Gain insight into new and innovative approaches to thermally intensify processes, reduce heat demand, harness waste heat, and use fuels and hydrocarbon feedstocks more efficiently; (3) Identify the R&D pathways to thermal process intensification (TPI) with the highest potential for impact and adoption by the industrial sector; (4) Define areas of research, development, and demonstration (RD&D) activities to accelerate development and application of emerging and transformative technologies to intensify thermal processes in industry. The scope and focus of the workshop were defined to meet these goals. Based on the available data for energy use and GHG emissions, the industries that collectively use more than 80% of the total process heating energy consumption were selected as primary focus areas. The chosen industries were combined into the following four groups based on similarities in their thermal processes: high-temperature metal processing (iron and steel industry, alumina-aluminum industry); high-temperature nonmetal and mineral processing (cement and glass industry); medium- to low-temperature thermal processing (food processing and pulp and paper industry as part of forest products sector); and hydrocarbon processing (petroleum refining and chemical industry). Furthermore, all potential TPI technologies associated with the processes defined were considered as part of the workshop. Different types of TPI technologies possible in industrial in the document.

42 ENGINEERING↗
DOE OSTI2023

Laser-Induced Ultrafast Demagnetization and Spin Switching (Final Report)

The information technology revolution demands bigger and faster magnetic storage devices. The funded research focuses on a new frontier - Laser-induced ultrafast all-optical spin switching (AOS), where a single laser pulse can switch spins from one direction to another permanently, without a magnetic field, on a time scale of 1-10 picoseconds, 2-3 orders of magnitude faster than the existing technology. The funded research has successfully resolved a long-standing issue in ultrafast demagnetization whether the lattice contributes to the demagnetization. We developed a high level first-principles theory and employed a massively parallel computer to pin down the details of the physical mechanisms that are inaccessible to other methods. This unique feature allows us to compute the force on each atom in both bulk and monolayer systems. We find that it is indeed true there is a nonzero force on each atom, but the idea of vibration contribution is not crucial to our basic understanding of physics. This paves the way to future experimental, theoretical and technological developments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

The Binary–Host Connection: Astrophysics of Gravitational-Wave Binaries from Host Galaxy Properties

Gravitational waves from the merger of binary neutron stars (BNSs) are accompanied by electromagnetic counterparts, making it possible to identify the associated host galaxy. In this work, we explore how properties of the hosts relate to the astrophysical processes leading to the mergers. It is thought that the BNS merger rate within a galaxy at a given epoch depends primarily on the galaxy's star formation history, as well as the underlying merger time-delay distribution of the binary systems. The stellar history of a galaxy, meanwhile, depends on the cosmological evolution of the galaxy through time, and is tied to the growth of structure in the universe. We study the hosts of BNS mergers in the context of structure formation by populating the UniverseMachine simulations with gravitational wave (GW) events, based on a simple time-delay model. We find that different time-delay distributions predict different properties of the associated host galaxies, including the distributions of stellar mass, star formation rate, halo mass, and local and large-scale clustering of hosts. Moreover, BNSs merging today with short delay times occur preferentially in hosts with high star formation rates, while those with long delay times live in dense regions within massive halos that have low star formation. Here, we show that with ${ \mathcal O }(10)$ events from current GW detector networks, it is possible to make preliminary distinctions between formation channels which trace stellar mass, halo mass, or star formation rate. We also find that strategies to follow-up GW events with electromagnetic telescopes can be significantly optimized using the clustering properties of their hosts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Demonstration of 10+ hour energy storage with Φ1" laboratory size solid oxide iron–air batteries

Long duration electricity storage (LDES) with 10+ hour cycle duration is an economically competitive strategy to accelerate the penetration of renewable energy into the utility market. Unfortunately, none of the available energy storage technologies can meet the LDES requirements in terms of duration and cost. The newly emerged solid-oxide iron–air batteries (SOIABs) with energy-dense solid iron as an energy storage material have inherent advantages for LDES applications. Herein, we report for the first time the LDES capability of SOIABs even at a laboratory scale. We show that SOIABs with an Ir-catalyzed Fe-bed can achieve excellent energy density (625 W h kg –1 ), long cycle duration (12.5 h) and high round-trip efficiency (~90%) under LDES-related working conditions. Finally, given the excellent low-rate performance and the use of earth-abundant, low-cost Fe as an energy storage material, we conclude that the SOIAB is a well-suited battery technology for LDES applications.

25 ENERGY STORAGE↗
DOE OSTI2025

Probing long-range forces between neutrinos with cosmic structures

We study the consequences of new long-range forces between neutrinos on cosmic scales. If these forces are a few orders of magnitude stronger than gravity, they can induce perturbation instability in the nonrelativistic cosmic neutrino background in the late time universe. As a result, the cosmic neutrino background may form nonlinear bound states instead of free-streaming. The implications of the formation of nonlinear neutrino bound states include enhancing matter perturbations and triggering star formation. Based on existing measurements of the matter power spectrum and reionization history, we place new constraints on long-range forces between neutrinos with ranges lying in 1 kpc ≲ m ϕ − 1 ≲ 10 Mpc . Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗