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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

What do physics-informed DeepONets learn? Understanding and improving training for scientific computing applications

Physics-informed deep operator networks (DeepONets) have emerged as a promising approach toward numerically approximating the solution of partial differential equations (PDEs). In this work, we aim to develop further understanding of what is being learned by physics-informed DeepONets by assessing the universality of the extracted basis functions and demonstrating their potential toward model reduction with spectral methods. Results provide clarity about measuring the performance of a physics-informed DeepONet through the decays of singular values and expansion coefficients. In addition, we propose a transfer learning approach for improving training for physics-informed DeepONets between parameters of the same PDE as well as across different, but related, PDEs where these models struggle to train well. This approach results in significant error reduction and learned basis functions that are more effective in representing the solution of a PDE.

Deep operator networks↗
DOE OSTI2025

Regional-scale soil carbon predictions can be enhanced by transferring global-scale soil–environment relationships

Accurate modelling and mapping soil organic carbon are crucial for supporting soil health restoration and climate change mitigation at both regional and global scales. However, regional soil predictions often suffer from data scarcity and high prediction uncertainty. Utilizing a pre-trained global-to-regional soil carbon predictive model can be a potential solution to address this challenge. Despite its promise, how to construct and apply the global-scale model to enhance regional-scale soil carbon mapping remains largely unexplored. Here, we propose the Global Soil Carbon Pre-trained Model (GSoilCPM), a deep-learning-based domain adaptative model, to enhance regional-scale soil carbon predictions. Based on large amount of environmental covariate data and 106,167 soil samples across the globe, we verify our hypothesis of the effectiveness of this 'global-to-regional' modelling strategy. The pre-trained model can be then transferred and fine-tuned to bridge the regional- and global-scale soil–environment relationships. We applied and validated this modelling strategy in four regional-scale study areas, three in the Northern Hemisphere and one in the Southern Hemisphere, each with distinct environmental background. Compared to traditional modelling approaches as a baseline, four case studies all demonstrated significant improvement in prediction accuracy across diverse environments and varying data availabilities. The average percentage improvement across all regions is 10.93% (absolute values decreased by 1.20 g kg−1 averagely) in MAE and 29.04% (absolute values increased by 0.10 averagely) in CCC. The applicability and future horizons of using GSoilCPM were further discussed. We further reveal that regions with fewer soil samples or lower baseline accuracy benefit more from the pre-trained global model. Our findings highlight the advantages of leveraging the generalized knowledge from global models to enhance specifically localized soil modelling, positioning a potential paradigm shift in digital soil mapping, and far-reaching implications for soil monitoring and land management.

Deep learning↗
DOE OSTI2021

Understanding Carbon Dioxide Transfer in Direct Methanol Fuel Cells Using a Pore-Scale Model

Abstract The gas flow of carbon dioxide from the catalyst layer (CL) through the microporous layer (MPL) and gas diffusion layer (GDL) has great impacts on the water and fuel management in direct methanol fuel cells (DMFCs). This work has developed a liquid–vapor two-phase model considering the counter flow of carbon dioxide gas, methanol, and water liquid solution in porous electrodes of DMFC. The model simulation includes the capillary pressure as well as the pressure drop due to flow resistance through the fuel cell components. The pressure drop of carbon dioxide flow is found to be about two to three orders of magnitude higher than the pressure drop of the liquid flow. The big difference between liquid and gas pressure drops can be explained by two reasons: volume flowrate of gas is three orders of magnitude higher than that of liquid; only a small fraction of pores (<5%) in hydrophilic fuel cell components are available for gas flow. Model results indicate that the gas pressure and the mass transfer resistance of liquid and gas are more sensitive to the pore size distribution than the thickness of porous components. To buildup high gas pressure and high mass transfer resistance of liquid, the MPL and CL should avoid micro-cracks during manufacture. Distributions of pore size and wettability of the GDL and MPL have been designed to reduce the methanol crossover and improve fuel efficiency. The model results provide design guidance to obtain superior DMFC performance using highly concentrated methanol solutions or even pure methanol.

Electrochemistry↗
DOE OSTI2020

Electron transfer in nonpolar media

The Marcus theory of electron transfer views fluctuating orientations of permanent dipoles as the nuclear mode bringing the donor and acceptor into the tunneling resonance. Electronic polarization of the solvent is excluded as the fast mode adiabatically following the electronic density. This view, valid for solids, does not apply to molecular liquids where molecular translations (density fluctuations) modulate the induction interaction of the donor-acceptor complex with the solvent. This mechanism of promoting radiation-less electronic transitions is considered here in the framework of the perturbation liquid-state theory. The reorganization energy of electron transfer in nonpolar solvents is nonzero and reaches the values of 0.1–0.3 eV for typical molecular sizes and solvents used in applications. The reorganization energy scales quadratically with the molecular polarizability of the solvent and decays as the inverse fifth power with the size of the donor and acceptor. The combination of the entropic character of the density fluctuations, driven by re-packing of molecular cores, with the short range of induction solute–solvent interactions leads to the violation of the fluctuation–dissipation theorem for the variance of the donor-acceptor energy gap. An explicit, approximately hyperbolic, dependence of the reorganization energy on temperature is predicted. It leads to a non-Arrhenius kinetic law for the rate constant of electron transfer in nonpolar liquid solvents.

14 SOLAR ENERGY↗
DOE OSTI2025

Model-based analysis of solute transport and potential carbon mineralization in the active layer of a hillslope underlain by permafrost with seasonal variability and climate change

Permafrost carbon, stored in frozen organic matter across vast Arctic and sub-Arctic regions, represents a substantial and increasingly vulnerable carbon reservoir. As global temperatures rise, the accelerated thawing of permafrost releases greenhouse gases, exacerbating climate change. However, freshly thawed permafrost carbon may also experience lateral transport by groundwater flow to surface water recipients such as rivers and lakes, increasing the terrestrial-to-aquatic transfer of permafrost carbon. Mobilization and subsurface transport mechanisms are poorly understood and not accounted for in global climate models, leading to high uncertainties in the predictions of the permafrost carbon feedback. Here, we focus on a hillslope in Endalen Valley, Svalbard, as a representative example of a high-Arctic hillslope underlain by continuous permafrost. We analyze solute transport in the form of a non-reactive tracer representing dissolved organic carbon (DOC) using a physics-based numerical model with the objective to study governing cryotic and hydrodynamic transport mechanisms relevant for warming permafrost regions. We first analyze transport times for DOC pools at different locations within the active layer under present-day climatic conditions and proceed to study susceptibility for deeper ancient carbon release in the upper permafrost due to thaw under different warming scenarios. Results suggest that DOC in the active layer near the permafrost table experiences rapid lateral transport upon thaw due to saturated conditions and lateral flow, while DOC close to the ground surface experiences slower transport due to flow in unsaturated soil. Deeper permafrost carbon release exhibits vastly different transport behaviors depending on warming and thaw rate. Gradual warming leads to small fractions of DOC being mobilized every year, while the majority moves vertically through percolation and cryosuction. Abrupt thaw resulting from a single very warm year leads to faster lateral transport times, similar to active layer DOC released in saturated conditions. Lastly, we analyze the potential susceptibility of DOC to mineralization to CO 2 prior to export due to soil moisture and temperature conditions. We find that high liquid saturation during transport coincides with very low mineralization rates and potentially inhibits mineralization into CO 2 before export. Overall, the results highlight the importance of subsurface hydrologic and thermal conditions for the retention and lateral export of permafrost carbon by subsurface flow.

Hamm, Alexandra [Stockholm Univ. (Sweden)] (ORCID:↗
DOE OSTI2025

Control Selection for the Neutralization Tank in the Aqueous Recovery System at the Savannah River Plutonium Processing Facility

The Aqueous Recovery System (ARS) at the Savannah River Plutonium Processing Facility (SRPPF) recovers and purifies plutonium (Pu) using aqueous chemistry techniques. The neutralization tanks in the ARS collect the waste streams, containing various impurities and greatly reduced concentrations of Pu, that are produced during aqueous processing. Criticality safety is primarily achieved in the ARS by using geometrically favorable process vessels. However, due to the geometry of neutralization tanks, each tank is administratively limited to no more than 450 g Pu, thus representing the transition from geometry to mass control. To ensure that this mass limit is not exceeded, an administrative control requires taking two samples of any solution to be sent to a neutralization tank. Normal operations are expected to result in less than 50 g Pu in a neutralization tank filled to its capacity of 250 L. Process upsets may cause an inadvertent transfer of up to 1000 g Pu to a neutralization tank, producing a system that is potentially not subcritical for all possible configurations of the tank. To ensure that a neutralization tank remains safety subcritical, passive engineered controls (e.g.changing tank geometry or adding fixed poisons), active engineered controls (e.g. interlocks), and administrative controls (e.g. soluble poisons and valve isolation) were considered and their viability evaluated. Ultimately, the team chose an administrative, dual-valve isolation strategy. This paper will thoroughly discuss the various control strategy options and why many of the options were not feasible for maintaining criticality safety.

Dressman, Phillip M. [Savannah River Nuclear Solut↗
DOE OSTI2020

Size- and concentration-dependent Eu 2+ /Eu 3+ mixed luminescent characteristics of rare-earth-doped CaF 2 nanoparticles and their monolithic epoxy nanocomposites

CaF 2 is a promising luminescent host material for a wide range of applications, due to its high transparency, non-hygroscopy, low refractive index, low density, low backscattering efficiency, and abundance in nature. Here we report the photoluminescence (PL) and cathodoluminescence (CL) characteristics of rare-earth-doped CaF 2 nanoparticles and their composite monoliths with epoxy with visible emissions. The CaF 2 nanoparticles of ca. 36, 108 and 305 nm were prepared by a facile solution-mixing process and subsequent hydrothermal treatment. As the particle size decreases, the luminescence intensity increases for single-doped particles, while oppositely decreases for codoped particles because of energy transfer. Further, Eu 2+ - and Tb 3+ -codoped CaF 2 nanoparticles exhibit red emission, providing an efficient path for red emission through an energy transfer by Tb 3+ bridging without direct Eu 3+ doping. The effects of size and concentration are found to be pronounced in CL than PL, as the charge transfer between Eu 2+ and Eu 3+ reduces the concentration quenching in CL. The luminescence emission characteristics of epoxy/CaF 2 monoliths are different from those of particles due to the interactions with the epoxy molecules, and thus the energy transfer is hindered in PL while not in CL, enabling them for high-energy irradiation applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Single-Electron Transfer Stabilizes Metastable Alane in a Bipyridine-Functionalized MOF Nanopore

Nanoconfinement of metastable hydrides such as alane (AlH 3 ) in functionalized porous frameworks represents a promising yet largely untapped strategy for high-capacity energy storage. Despite its potential, the underlying mechanisms responsible for the thermodynamic stabilization of metastable hydrides are poorly understood. Here, in this study, concepts from solution Lewis acid–base chemistry were applied to a crystalline metal–organic framework (MOF) to stabilize AlH 3 . The long-range order and synthetically versatile pore chemistry enabled us to reveal the intimate details of the hydride-host interactions. Powder X-ray diffraction (PXRD) of AlH 3 -infiltrated UiO-67bpy (Zr 6 O 4 (OH) 4 (bpydc) 6 ; bpydc 2– = 2,2′-bipyridine-5,5′-dicarboxylate) confirms that the framework maintains its crystallinity up to 250 °C and is stable under 70 MPa H 2 pressure. We find that thermodynamic stabilization arises from coupled single-electron and hydrogen-atom transfer from AlH 3 to bipyridine-containing linkers. Electron paramagnetic resonance detects a bipyridyl radical with an anisotropic g-tensor (g values of 2.00132, 2.00215, and 2.00275), consistent with Bader charge analysis predicting 0.82 e – transferred from the hydride to the MOF. These findings establish critical structure–property relationships underpinning AlH 3 stabilization and suggest general strategies for tuning the thermodynamics and kinetics of metastable materials.

Shivanna, Mohana [Sandia National Laboratories (SN↗
DOE OSTI2025

Scaling deep learning for material imaging with a pseudo 3D model for domain transfer

The recent introduction of deep learning methods for image processing has greatly advanced the characterization of materials using three-dimensional (3D) X-ray imaging techniques. However, deep learning models often have difficulty performing consistently across images owing to unavoidable variations in imaging conditions, which create inconsistencies even for the same material. As a result, networks must frequently be retrained for new datasets, limiting their applicability and generalization. Thus, it is critical to reduce the variations between images to enable a single model to process multiple datasets. Herein, we introduce P3T-Net, a pseudo-3D domain transfer network that transfers diverse 3D images into a uniform domain before processing using deep learning models. Remarkably, P3T-Net enables the reuse of previously trained networks for processing new images and considerably reduces the computational cost of transferring 3D images across domains. These unique capabilities were demonstrated in the following scenarios: (i) image enhancement of fast scans for geological rock and hydrogen fuel cells, (ii) enhancement of images to match the quality of multi-source imaging for lithium-ion batteries, (iii) accurate segmentation of images captured under different conditions, and (iv) tera-scale 3D transfer (10 11 voxels) on a single GPU. Overall, the proposed approach addresses cross-domain inconsistencies across various materials and conditions, thereby enabling more robust and generalizable deep learning solutions for a wide range of material imaging tasks.

25 ENERGY STORAGE↗
DOE OSTI2022

MISPR : an open-source package for high-throughput multiscale molecular simulations

Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Measurement of the branching fraction of ψ ( 2 S ) → γ π 0

Based on ( 2712.4 ± 14.1 ) × 10 6 ψ ( 2 S ) events, 7.9 fb − 1 ψ ( 3773 ) data, and 0.8 fb − 1 off-resonance data samples collected with the BESIII detector, we measure the branching fraction of ψ ( 2 S ) → γ π 0 and e + e − → γ π 0 form factor at momentum transfers Q 2 ∼ 13 GeV 2 . The e + e − → γ π 0 cross section is fitted with considering the interference between the ψ ( 2 S ) and continuum amplitudes and two solutions are found, B = 3.74 × 10 − 7 with ϕ = 3.93 rad and B = 7.87 × 10 − 7 with ϕ = 2.08 rad . Here, B is the branching fraction of ψ ( 2 S ) → γ π 0 and ϕ is the relative phase angle between the ψ ( 2 S ) and continuum amplitudes. Due to insufficient off-resonance data, the branching fraction B ( ψ ( 2 S ) → γ π 0 ) is determined to be in the range [ 2.7 , 9.7 ] × 10 − 7 within 1 standard deviation of the contour region. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2020

Computationally Efficient AC Resistance Model for Stator Winding With Rectangular Conductors

The resistance of the electric machine’s windings is an important parameter when analyzing the machine’s performance, as conduction losses in the winding are often the largest loss component. However, this resistance changes with frequency due to the skin and proximity effects, making it challenging to accurately estimate these losses. In this article, a computationally efficient, general method of calculating the ac resistance of an electric machine winding with rectangular conductors is presented. The method uses a 1-D magnetoquasi-static model of the stator slot region to develop boundary transfer relations between individual turns. These relations are then used to create an impedance matrix from which the ac resistance can be calculated. This technique is more flexible than previous solutions since it can accommodate different winding configurations such as fractional-pitch windings. It is shown that a fractional-pitch winding has a lower ac resistance than a full-pitch winding. Finally, finite-element analysis simulations and experimental results are used to validate the proposed method.

42 ENGINEERING↗
DOE OSTI2020

Construction-Scale Concrete Additive Manufacturing and its Application in Infrastructure Energy Storage

Construction is filled with labor intensive, hazardous, and often wasteful processes. It is also an enormous industry, so improvements in efficiency could have a tremendous economic impact. Construction-scale additive manufacturing is one path toward achieving those improvements. In this paper, a construction-scale additive manufacturing system, called Sky-BAAM, is presented. In addition to possibly leading to more energy-efficient construction practices, leveraging additive manufacturing in construction opens the solution space to more energy efficient building design. One such design, the EMPOWER wall, is also presented in this paper. The exterior of the wall is shaped to maximize heat transfer, while acting as form work for an internal energy-storage system. This allows energy to be stored in the wall during off-peak times and retrieved during peak periods.

Atkins, Celeste↗
DOE OSTI2021

Light transport with weak angular dependence in fog

Random scattering and absorption of light by tiny particles in aerosols, like fog, reduce situational awareness and cause unacceptable down-time for critical systems or operations. Computationally efficient light transport models are desired for computational imaging to improve remote sensing capabilities in degraded optical environments. To this end, we have developed a model based on a weak angular dependence approximation to the Boltzmann or radiative transfer equation that appears to be applicable in both the moderate and highly scattering regimes, thereby covering the applicability domain of both the small angle and diffusion approximations. An analytic solution was derived and validated using experimental data acquired at the Sandia National Laboratory Fog Chamber facility. The evolution of the fog particle density and size distribution were measured and used to determine macroscopic absorption and scattering properties using Mie theory. A three-band (0.532, 1.55, and 9.68 µ m) transmissometer with lock-in amplifiers enabled changes in fog density of over an order of magnitude to be measured due to the increased transmission at higher wavelengths, covering both the moderate and highly scattering regimes. The meteorological optical range parameter is shown to be about 0.6 times the transport mean free path length, suggesting an improved physical interpretation of this parameter.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Supo Thermal Model Development IV

This report describes the continuation of the Computational Fluid Dynamics (CFD) model of the Supo cooling system described in the reports, Supo Thermal Model Development, II, and III. In the previous reports, the solution natural convection of Supo was simulated using a 2D, axisymmetric model that altered the actual geometry. A 3D geometry of Supo will more accurately estimate the natural convection heat transfer coefficient (HTC) of the system since Supo contains several non-symmetric internal components that can only be modeled in 3D. This, in turn, will improve the natural convection HTC results for comparison purposes with past operational data and previous 2D CFD results. Unfortunately, the complexities of performing multiphase 3D CFD simulations has proven too large of a task for our current capabilities. Instead, this report will focus on the 3D model development for the 2.39 kW/L (31.3 kW) case and limitations and challenges associated with the 3D simulations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Nanowire and micro wire fabrication technique and product

A continuous or semi-continuous process for fabricating nanowires or microwires makes use of the substantially planar template that may be moved through electrochemical solution to grow nanowires or microwires on exposed conductive edges on the surface of that template. The planar template allows fabrication of the template using standard equipment and techniques. Adhesive transfer may be used to remove the wires from the template and in one embodiment to draw a continuous wire from the template to be wound around the drum.

Sumant, Anirudha V.↗
DOE OSTI2021

Transfer-Learnt Energy Models for Predicting Electricity Consumption in Buildings with Limited and Sparse Field Data

Modeling energy consumption is critical for energy-efficient utilization of the electric appliances in a building, smart grid programs (like demand-response), and many other smart home applications. State-of-the-art energy modeling techniques either rely on theoretical models, or extensive instrumentation of the building envelope to gather ``big" data to train a deep neural network. While theoretical models are often limited by their estimation accuracy, it is not always feasible to gather a significant amount of field data. In this paper, we explore transfer learning-based strategies to train much more accurate model for energy estimation when using a sparse field data. We transferred knowledge, in the form of data and parameters, from the simulation framework to the field data. We evaluated the efficacy of our approach on field data collected from six commercial buildings and our results indicate that transfer learning-based models trained over one month data can perform comparative (and in some cases better) than the state-of-the-art machine learning and deep learning solutions.

Jain, Milan↗