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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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429 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Environmental drivers of spatial variation in tropical forest canopy height: Insights from NASA’s GEDI spaceborne LiDAR

Forest canopy height is a fundamental ecosystem property—influencing patterns of forest carbon storage and forest ecosystem responses to climate variability and change. Previous studies have analyzed environmental drivers influencing spatial variation in canopy height at landscape-to-regional scales; however, far less is known about the environmental determinants underlying regional and global scale variation in forest canopy height. Using the canopy height metrics products from Global Ecosystem Dynamics Investigation (GEDI), a space-borne Light Detection and Ranging (LiDAR) instrument specifically designed to characterize forest structure, we analyze the environmental correlates of spatial variation of global tropical forest canopy height. Our study demonstrates that climate, topography, and soil properties account for 75% of the variation in tropical forest canopy height. Elevation, dry season length, and solar radiation are the most important drivers in determining canopy height both locally and regionally. These results emphasize the vulnerability of tropical forest structure to ongoing changes in the earth’s climate and provide a valuable empirical baseline for tropical forest management.

Science & Technology - Other Topics↗
DOE OSTI2026

Resilience Strategies to Ensure Water Supply Continuity During Extended Grid Outages

The towns of Edgartown, Oak Bluffs and Tisbury, on the island of Martha’s Vineyard, MA, are concerned about the effect of prolonged grid outages on continuity of their water supply. Water pumping stations operated by the water utilities that currently serve each of the towns currently have backup power generation that can support water delivery for up to one week during peak water demand periods. Sandia advised on options to extend water supply to two weeks.

Mammoli, Andrea Alberto [Sandia National Laborator↗
DOE OSTI2025

Lepto-axiogenesis with light right-handed neutrinos

We study lepto-axiogenesis in theories where the right-handed neutrino is light enough that its dynamics affect the determination of the baryon asymmetry. When compared with theories of high-scale lepto-axiogenesis where the Majorana neutrino mass may be treated as an effective dimension-five operator, we find that the predicted saxion mass is lower. Two distinct scenarios emerge. In the first, processes that generate the baryon asymmetry are in equilibrium down to the mass of the right-handed neutrino. In the second, the relevant processes never reach equilibrium; the baryon number freezes in. We comment on implications for supersymmetric spectra and discuss constraints on late decays of supersymmetric relics and from dark radiation. In contrast to high-scale lepto-axiogenesis, which predicts superpartners with masses of 10–100 TeV or more, we find this scenario is consistent with a wider range of superpartner masses, all the way down to current direct search bounds.

Axions and ALPs↗
DOE OSTI2026

A multiscale packed-bed reactor model for sustainable ethylene production via chemical looping oxidative coupling of methane

The rising global warming concerns and shale gas discovery have prompted research in the direction of greenhouse gas (GHG), such as methane, reduction and conversion. Oxidative coupling of methane (OCM) offers a pathway to low carbon-intense valorization of methane while producing ethylene, a chemical regarded as central to the petrochemical industry. Even after decades of OCM discovery, researchers keep understanding the process and underlying chemical reactions in a pursuit to achieve industrial viability for OCM. Here, in general, OCM suffers from low C 2 selectivity, yield and reactor temperature runaways due to highly exothermic nature of its reactions. Computational Fluid Dynamics (CFD) tools help analyze spatial gradients within the reactor to deeply understand the diffusion of species, mass and heat transfer phenomena. Furthermore, challenges associated with scaling up such as hot spot formation and parametric sensitivity can be addressed without having to expend on costly experiments. The current paper presents a multiscale packed-bed reactor CFD model coupled with a chemical kinetic model for the chemical looping OCM. The CFD model includes two scales i.e., macroscale for catalyst bed and microscale for individual pellets. Moreover, a chemical kinetic model based on 10 gas-phase reactions is integrated with the CFD model. An additional surface reaction for the formation of gas-phase oxygen from catalyst surface is added to account for the absence of feed oxygen. The model is calibrated against experimental results. The calibrated model captures trends in CH 4 conversion, C 2 selectivity and C 2 yield within a ± 4.35 % range across a temperature range of 700-900 °C. Moreover, model fidelity is evaluated by varying key computational parameters such as mesh resolution and time step size. The model is also verified by varying the inlet methane concentration and the gas hourly space velocity (GHSV) and comparing the results with literature. A sensitivity analysis and scale-up of the current model is undergoing.

Chemical looping↗
DOE OSTI2021

Design and Realization of Ohmic and Schottky Interfaces for Oxide Electronics

Understanding band alignment and charge transfer at complex oxide interfaces is critical to tailoring and utilizing their diverse functionality. Toward this goal, both Ohmic- and Schottky-like charge transfers at oxide/oxide semiconductor/metal interfaces are designed and experimentally validated. A method for predicting band alignment and charge transfer in ABO 3 perovskites is utilized, where previously established rules for simple semiconductors fail. The prototypical systems chosen are the rare class of oxide metals, SrBO 3 with B = V–Ta, when interfaced with the multifaceted semiconducting oxide, SrTiO 3 . For B = Nb and Ta, it is confirmed that a large accumulation of charge occurs in SrTiO 3 due to the higher energy Nb and Ta states relative to Ti. Furthermore, this gives rise to a high mobility metallic interface, which is an ideal epitaxial oxide/oxide Ohmic contact. On the contrary, for B = V, there is no charge transfer into the SrTiO 3 interface, which serves as a highly conductive epitaxial gate metal. Going beyond these specific cases, this work opens the door to integrating the vast phenomena of ABO 3 perovskites into a wide range of practical devices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Critical Review of Heliostat Design for Concentrating Solar Thermal Technologies

Heliostat designs have undergone a widespread and eclectic development process, with many unique designs demonstrated. However, recent developments do not show the overall cohort converging toward a globally accepted universal design. Here, this study characterizes heliostats by breaking down and evaluating design traits based on emergent patterns from a comprehensive compilation of known heliostat designs spanning several decades. Four main categories for evaluation emerged: heliostat base, heliostat primary axis, heliostat drive, and facet support. Each of these four categories is further defined by four subtypes so that all heliostats fall into a single subtype within each category. The classified heliostats are ranked, yielding several view slices into the heliostat compilation or a breakdown of heliostats by type. An analysis of the breakdown shows several trends: a scale-up of established designs, new approaches at small to medium scales, and a movement toward greater adoption of linear drives. These trends reflect the most meaningful contributing factors to a proposed trajectory for a new era of heliostat designs striving to meet widely considered cost targets of $\$$50/m 2 or $\$$75/m 2 .

14 SOLAR ENERGY↗
DOE OSTI2026

Integrated Magnetics for Multiport Inductive and Conductive Power Transfer Architecture for Electric Vehicles

This paper proposes a shared magnetic arrangement for an electric-vehicle charger that supports both conductive and inductive charging while preserving independent power control at the two ports. In the proposed implementation, the high-frequency transformer used for the conductive path and the resonant inductor required by the inductive path are realized in an integrated form. By combining the magnetic structure and primary-side converter hardware, the charger can deliver improved hardware utilization and higher power density without a corresponding increase in cost or implementation complexity. The paper describes the magnetic realization and presents finite-element and circuit-level simulation results to confirm minimal interaction between the two charging paths. The study demonstrates that the proposed charger is a viable option for flexible, high-power EV charging systems.

Mukherjee, Subho [ORNL] (ORCID:0009000672297925)↗
DOE OSTI2026

Predicting Band-Gap of Inorganic Materials Using Neuromorphic Graph Learning

Predicting properties of inorganic materials is a heavily researched topic, with several new prediction approaches emerging as competitors. One such competitor is graph neural networks, which leverage the structure of the graph to aid in the prediction process. In this work, we propose integration of neuromorphic computation into the graph neural network pipeline. We call this approach Neuromorphic Graph Learning (NGL). We utilize the NGL approach to leverage evolutionary algorithms and a novel Spike Pipeline for Raster Analysis (SPIRE) for the prediction of band gap in inorganic materials.

Mulet, Ian [University of Tennessee (UT)]↗
DOE OSTI2023

Overcoming the Entropy Penalty of Direct Air Capture for Efficient Gigatonne Removal of Carbon Dioxide

Atmospheric carbon poses an existential threat to civilization via global climate change. Hundreds of gigatonnes of carbon dioxide must be removed from earth’s atmosphere in the next three decades, necessitating a low-cost, energy-efficient process to extract low concentrations of carbon dioxide for conversion to a stable material permanently stored for thousands of years. In this work, the challenge of removing gigatonnes of CO 2 is described via the scale of effort and the thermodynamics of collecting and reducing this diffuse chemical, the accumulation of which imparts a substantial entropy penalty on any atmospheric carbon capture process. The methods of CO 2 reduction combined with upstream direct air capture (DAC) including absorption, membrane separation, and adsorption are compared with biomass torrefaction and permanent burial (BTB). A Monte Carlo model assesses the mass, energy, and economics of the full process of biomass torrefaction from biomass collection and transport to stable carbon burial to determine that 95% of scenarios could remove carbon for less than $200 per CO 2 -tonne-equivalent. Torrefied carbon is further discussed for its long-term stability and availability at the scale required to substantially mitigate the threat of climate change.

biomass↗
DOE OSTI2026

Characterization of NBCMA—A DAPO Precursor

As part of our investigation into the process optimization of 2,6-diaminopyrazine-1-oxide (DAPO), small-scale sensitivity testing (impact, friction, and ESD) was conducted on the precursor, N-nitroso-bis(cyanomethyl)amine (NBCMA). NBCMA exhibited moderate sensitivity to friction, whereas no sensitivity to impact or spark was observed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Evaluating alternative steam generation pathways in the food industry

Steam generation in the food sector requires substantial energy and cost expenditures, requiring nearly half of its energy intake. Here, we used life cycle assessment and life cycle cost assessment to investigate the cost and energy impacts of steam generating alternatives: NG, biomass and hydrogen boilers and grid-supplied and self-generated electric steam generation systems (electric boilers, renewable thermal energy storage and industrial heat pumps). The analysis starts with a set of average U.S. conditions, where biomass boilers are the most cost-competitive alternative to NG. In a series of scenarios beyond average conditions, the analysis shows energy procurement costs dominate the total life cycle cost for all technologies and, unfortunately, are highly variable geographically and temporally, significantly affecting the viability of the alternatives. Results show that site-energy consumption ranges from 0.3 MMBtu/klb for industrial heat pumps to 1.6 MMBtu/klb for biomass boilers, with heat pumps achieving up to 78% lower energy use compared to natural gas systems. For the steam costs, the results show a range between $\$$8 and $\$$50/klb for NG, with biomass following closely ($\$$11 – $\$$44/klb) and grey hydrogen and IHP next ($\$$13 – $\$$33/klb and $\$$6 - $\$$78/klb), with cost reductions if IHP's cooling is utilized. Factors like operating hours, the need for cooling, and the ability to negotiate utility rates complicate the decision, making site-specific analyses critical. Therefore, we present a decision-making matrix to help manufacturers identify which steam generating technology is the best business decision for their situation. Overall, these results highlight the importance of steam generation for the facility's organizational goals, as well as the criticality of conducting individual site analyses.

Biomass boilers↗
DOE OSTI2025

Exploiting ν-dependence of projected energy correlators in HICs

We extend the recently derived factorization formula for energy-energy correlators to study the analytic structure of general ν-point projected energy correlators in heavy ion collisions. The ν-point projected energy correlators (or, ν-correlators) are an analytically continued family of the integer N-point projected energy correlators, which probe correlations between N final-state particles. By tracking the largest separation (χ) between the N particles, in vacuum, their structure is closely related to the DGLAP splitting functions and exhibits a classical scaling behavior ∼ 1/χ which is modified by resummation through the anomalous dimensions. We show that, in a thermal medium, the ν-correlators display non-trivial angular scaling already at the leading order in perturbation theory. We find that for non-integer values, particularly ν < 1, medium-induced jet function is enhanced compared to ν > 1. This is particularly manifested in the ratios of ν-correlators with respect to the two-point energy correlator, which encodes intrinsic angular information for ν < 1 when compared to large ν values. Moreover, for small-ν values, the ν-correlators appear to saturate at ν = 0.01 . We further confirm our leading-order numerical computations against simulated events from JEWEL for the parton-level production cross-section. Finally, we qualitatively discuss the effect of BFKL resummation for various values of ν.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Micrometer: Micromechanics transformer for predicting full field mechanical responses of heterogeneous materials

Predicting mechanical responses of heterogeneous materials across scales remains a significant challenge. Traditional computational methods often struggle with complex and multiscale nature of these materials, limiting their effectiveness in real-world applications. Here, in this paper, we introduce Micrometer, a vision transformer based deep learning model designed to predict full field mechanical responses of heterogeneous materials, bridging the gap between computer vision and solid mechanics problems. We show that Micrometer, trained on a large-scale high-resolution dataset of 2D fiber-reinforced composites, can achieve state-of-the-art performance in predicting microscale strain fields across a wide range of material properties and loading conditions. Our model demonstrates accuracy and computational efficiency in applications such as computational homogenization and multiscale modeling, reducing computational time by up to two orders of magnitude compared to conventional numerical solvers while maintaining less than 1 % errors in predicting macroscale stress fields. Furthermore, we showcase Micrometer’s adaptability through transfer learning experiments on new materials with limited data, highlighting its potential to tackle diverse scenarios in computational solid mechanics. These results represent a significant step towards AI-driven innovation in materials science, addressing the limitations of traditional numerical methods and paving the way for more efficient simulations of heterogeneous materials across various industrial applications.

Composite materials↗
DOE OSTI2026

Effect of Oxidizing Impurities on the Corrosion Behavior of Structural Alloys Exposed to MgCl 2 Molten Salt Vapor

The corrosion behavior of structural alloys SS304 and IN617 when exposed to vapors of MgCl 2 molten salt at 764 °C for 100 h in an argon atmosphere was investigated as a function of the level of oxidizing impurities (e.g., NaOH) present in the salt. Increasing the concentration of oxidizing impurities in the salt caused an increase in corrosion in both structural alloys, as measured by Cr depletion layers. A poorly adhered oxide scale layer containing Mg, Al, and Cr was observed on the surface of the metals, and local attack was observed as well. The Ni-based IN617 showed lower Cr depletion and less scale formation than the Fe-based SS304. These results demonstrate that oxidizing impurities in the molten salt will impact the vapor phase corrosion for structural members exposed to the molten salt headspace. This finding is highly relevant for understanding the effects of the vapor phase in molten salt applications, including molten salt thermal energy storage, molten salt nuclear reactors, and molten salt electrochemistry.

25 ENERGY STORAGE↗
DOE OSTI2023

Surface analysis insight note: Illustrating the effect of adventitious contamination on Pt photoemission peak intensities

Adventitious carbon contaminations are not only omnipresent and used for charge referencing of XPS spectra but also can alter the apparent presence of the element peaks that span over the large spectral window of binding energies. This Insight note describes the effect of an adventitious contamination layer on Pt and presents, in brief, the approach whereby the component spectra are derived for ion beam cleaned Pt samples that can then utilize linear mathematics to peak fit said spectra thus quantifying the amount of each component including that assigned to the contamination itself of Pt metal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Nanostructuring and Underscreening of Bisalt Electrolytes with Dual-Anion Effects: Insights from Small-Angle Scattering Prepeak Analysis

Using small-angle neutron scattering, we studied the nanostructure of a prototypical D(H)-bonded network electrolyte, alkaline sodium aluminate bisalt, at concentrations up to solute volume fraction of ~0.5. Analysis of the structure factor prepeak at 0.1 < Q < 1.0 Å-1 showed that its evolution is associated with nanoscopic species distribution in water-anion network., with differences in characteristic distance d between OD- and Al(OD)4- anions related to their distinct sizes and interactions. When the solute volume fraction approached 0.5, a common/maximum value of ~4.5 Å was found for the correlation length ? that characterizes the electrostatic force in concentrated electrolyte solution before precipitation occurred. This implies that the solutions’ morphology and behavior at high concentrations may be governed by geometric factors, rather than the chemistry of the specific anion. Furthermore, the scaling of ? with concentration yielded an exponent of 1.25(1), suggesting that ? is limited to a few Å. By combining the current observations of structural heterogeneity at the nanoscale, with dynamic heterogeneity at the microscopic scale from our previous quasi-elastic neutron scattering study, we have established a structural origin of local “caging” and restricted structural relaxation processes. These local solvent-solute interactions not only control dynamics heterogeneity in concentrated electrolytes but also are responsible for crystallization processes in industrial setting, such as aluminum production and radioactive waste treatment.

Wang, Hsiu-Wen↗
DOE OSTI2026

SODAs: sparse optimization for the discovery of differential and algebraic equations

Differential-algebraic equations (DAEs) integrate ordinary differential equations (ODEs) with algebraic constraints, providing a fundamental framework for developing models of dynamical systems characterized by time-scale separation, conservation laws and physical constraints. While sparse optimization has revolutionized model development by allowing data-driven discovery of parsimonious models from a library of possible equations, existing approaches for dynamical systems assume DAEs can be reduced to ODEs by eliminating variables before model discovery. This assumption limits the applicability of such methods for DAE systems with unknown constraints and time scales. We introduce sparse optimization for differential-algebraic systems (SODAs), a data-driven method for the identification of DAEs in their explicit form. By discovering the algebraic and dynamic components sequentially without prior identification of the algebraic variables, this approach leads to a sequence of convex optimization problems. It has the advantage of discovering interpretable models that preserve the structure of the underlying physical system. To this end, SODAs improves since SODAs is singular numerical stability when handling high correlations between library terms, caused by near-perfect algebraic relationships, by iteratively refining the conditioning of the candidate library. We demonstrate the performance of our method on biological, mechanical and electrical systems, showcasing its robustness to noise in both simulated time series and real-time experimental data.

DAE↗