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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Nanoscopic Structure of the Interface between Reduced TiO 2– x (110) and Water Vapor

We investigate the interaction between a reduced rutile TiO 2–x (110)-(1×4) surface and water vapor at ambient pressures using atomic force microscopy and X-ray photoelectron spectroscopy (AP-AFM and AP-XPS). Our results reveal that water molecules strongly interact with the reduced surface, leading to hydroxylation and localized clustering of water molecules. In defect-rich regions, AFM tip-induced restructuring causes removal of the topmost surface layer, highlighting the lowered cohesive energy of the surface atoms upon hydroxylation. These findings provide new insights into the water adsorption and restructuring mechanisms on reducible transition metal oxides, relevant for catalytic and environmental applications.

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

Is the Matrix Completion of Reduced Density Matrices Unique?

Reduced density matrices are central to describing observables in many-body quantum systems. In electronic structure theory, the two-particle reduced density matrix (2-RDM) suffices to determine the energy and other key properties. Recent work has used matrix completion, leveraging the low-rank structure of RDMs and approximate theoretical models, to reconstruct the 2-RDM from partial data and thus reduce the computational cost. However, matrix completion is, in general, an under-determined problem. Revisiting Rosina’s theorem (Rosina, M. Queen’s Papers on Pure and Applied Mathematics , 1968, No. 11, 369), we here show that the matrix completion is unique under certain conditions, identifying the subset of 2-RDM elements that enables its exact reconstruction from incomplete information. Building on this, we introduce a hybrid quantum–stochastic algorithm that achieves exact matrix completion, demonstrated through applications to the Fermi–Hubbard model.

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

Formation of Bimetallic Nanoparticles via Exsolution Using a Reducible Metal Oxide Capping Layer

Bimetallic nanoparticles are promising catalysts that can improve performance in heterogeneous catalysis and solid-state electrochemistry. Exsolution is a useful method for forming such nanoparticles; however, it is limited by the elements present within the host oxide lattice. Here, in this work, we develop and demonstrate a strategy to form bimetallic particles from La 0.5 Sr 0.5 Ti 0.94 Ni 0.06 O 3 (LSTN) exsolution and using a reducible SnO 2 capping layer, expanding the range of elements available for bimetallic nanoparticle formation. Using this capping layer strategy, we formed nickel–tin (Ni 0 –Sn 0 ) bimetallic nanoparticles via exsolution. We used in situ near-ambient pressure X-ray photoelectron spectroscopy to monitor surface chemical changes during exsolution, showing that first, SnO 2 volatilized. This SnO 2 loss exposed the perovskite surface of LSTN to reducing conditions, which induced Ni exsolution, and compounded with SnO 2 reduction led to the formation of bimetallic Ni 0 –Sn 0 particles. To evaluate the associated microstructural evolution, we measured grazing incidence small-angle X-ray scattering (GISAXS), which confirmed the loss of the SnO 2 capping layer, and scattering simulations suggested the formation of bimetallic particles. We confirmed the bimetallic nanoparticle composition and morphology by Auger spectroscopy and scanning transmission electron microscopy. The resulting bimetallic nanoparticles were smaller and more thermally stable than the monometallic Ni counterparts on LSTN. This capping layer and exsolution approach allow synthesizing multimetallic nanoparticles and can be applied to other reducible metal oxides and perovskite hosts, broadening the compositional space for advanced catalytic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Can Restoring Tidal Wetlands Reduce Estuarine Nuisance Flooding of Coasts Under Future Sea‐Level Rise?

Wetland restoration is an increasingly popular nature‐based method for flood risk mitigation in coastal communities. In this study, we present a novel method using hydrodynamic modeling and harmonic analysis to quantify wetlands' ability to reduce future nuisance flooding. The method leverages a hydrodynamic model calibrated to present day data and was run for a range of future sea‐level rise (SLR) and wetland restoration scenarios to quantify changes to tidal harmonic amplitudes and phases. The harmonic constituents are used to generate water surface elevations over a time period of interest (e.g., one year) and compared to critical exceedance thresholds such as levee elevations. Then, changes to nuisance flooding are calculated by counting the number of hours critical thresholds are exceeded under different SLR and wetland restoration scenarios. We applied the method to Coos Bay, Oregon, USA as a test case. We found restoration reduces the number of hours nuisance flooding occurs in downtown Coos Bay from 15 hr (present day conditions) to 0 hr (fully restored condition) under median SLR (82 cm by 2100). Restoration had spatially variable impacts on reducing peak flood elevations with minimal impacts near the estuary mouth and greatest impact 32 km inland. The effectiveness of restoration was heavily dependent on future SLR. Restoration was maximally effective in 2050 under all SLR scenarios, less effective in 2100 under median SLR, and not effective under high SLR. Modeling results suggest increased tidal prism and accommodation space are driving restoration‐associated reductions in tidal amplitudes.

Brand, Matthew W. [Louisiana State Univ., Baton Ro↗
DOE OSTI2025

Reducing Long‐Standing Surface Ozone Overestimation in Earth System Modeling by High‐Resolution Simulation and Dry Deposition Improvement

The overestimation of surface ozone concentration in low‐resolution global atmospheric chemistry and climate models has been a long‐standing issue. We first update the ozone dry deposition scheme in both high‐ (0.25°) and low‐resolution (1°) Community Earth System Model (CESM) version 1.3 runs, by adding the effects of leaf area index and correcting the sunlit and shaded fractions of stomatal resistances. With this update, 5‐year‐long summer simulations (2015–2019) using the low‐resolution CESM still exhibit substantial ozone overestimation (by 6.0–16.2 ppbv) over the U.S., Europe, eastern China, and ozone pollution hotspots. The ozone dry deposition scheme is further improved by adjusting the leaf cuticle conductance, reducing the mean ozone bias by 19%, and increasing the model resolution further reduces the ozone overestimation by 43%. We elucidate the mechanism by which model grid spacing influences simulated ozone, revealing distinctive pathways in urban versus rural areas. In rural areas, grid spacing mainly affects daytime ozone levels, where additional NO x emissions from nearby urban areas result in an ozone boost and overestimation in low‐resolution simulations. In contrast, over urban areas, daytime ozone overestimation follows a similar mechanism due to the influence of volatile organic compounds from surrounding rural areas. However, nighttime ozone overestimation is closely linked to weakened NO titration owing to the redistribution of urban NO x to rural areas. Additionally, stratosphere‐troposphere exchange may also contribute to reducing ozone bias in high‐resolution simulations, warranting further investigation. This optimized high‐resolution CESM may enhance understanding of ozone formation mechanisms, sources, and changes in a warming climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Thermal Adaptation of Enzyme‐Mediated Processes Reduces Simulated Soil CO2 Fluxes Upon Soil Warming

Abstract Understanding factors influencing carbon effluxes from soils to the atmosphere is important in a world experiencing climatic change. Two important uncertainties related to soil organic carbon (SOC) stock responses to a changing climate are (a) whether soil microbial communities acclimate or adapt to changes in soil temperature and (b) how to represent this process in SOC models. To further explore these issues, we included thermal adaptation of enzyme‐mediated processes in a mechanistic SOC model (ReSOM) using the macromolecular rate theory. Thermal adaptation is defined here to encompass all potential responses of soil microbes and microbial communities following a change in temperature. To assess the effects of thermal adaptation of enzyme‐mediated processes on simulated SOC losses, ReSOM was applied to data collected from a 13‐year soil warming experiment. Results show that a model omitting thermal adaptation of enzyme‐mediated processes substantially overestimates observed CO 2 effluxes during the initial years of soil warming. The bias against observed CO 2 effluxes was lower for models including thermal adaptation of enzyme‐mediated processes. In addition, for a simulated linear 3°C soil warming over 100 years, models including thermal adaptation of enzyme‐mediated processes simulated SOC losses of a factor of three smaller than models omitting this process. As thermal adaptation of microbial community characteristics is generally not included in models simulating feedback between the soil, biosphere and atmosphere, we encourage future studies to assess the potential impact that microbial adaptation has on soil carbon – climate feedback representations in models. Plain Language Summary A major uncertainty in projecting how much soil organic carbon (SOC) will be converted to CO 2 as a consequence of climate change is related to how soil microbes may adapt to increasing soil temperatures. While this “microbial thermal adaptation” has been shown to occur in short‐term lab incubation experiments, its effect on SOC cycling on a decadal timescale is not clear. To address this knowledge gap, a mechanistic SOC model was used to simulate data collected from a 13‐year soil warming experiment, to assess how microbial thermal adaptation affects predicted SOC losses upon soil warming. The model results show that incorporating microbial thermal adaptation into the model led to reduced CO 2 effluxes from the soil to the atmosphere compared to the common approach of omitting this mechanism. Our results imply that projected SOC losses for the decades to come may be reduced when this mechanism is incorporated in land models. We therefore advocate for more research on the mechanisms controlling microbial thermal adaptation, and how to implement this mechanism in SOC models. Key Points A crucial aspect of soil organic carbon (SOC) models is the representation of soil microbes Predicted soil CO 2 fluxes upon soil warming are reduced when accounting for microbial thermal adaptation On a centennial time scale, this thermal adaptation results in up to a factor of three lower predicted SOC loss

Van de Broek, Marijn↗
DOE OSTI2024

Potential of artificial intelligence in reducing energy and carbon emissions of commercial buildings at scale

Artificial intelligence has emerged as a technology to enhance productivity and improve life quality. However, its role in building energy efficiency and carbon emission reduction has not been systematically studied. This study evaluated artificial intelligence’s potential in the building sector, focusing on medium office buildings in the United States. A methodology was developed to assess and quantify potential emissions reductions. Key areas identified were equipment, occupancy influence, control and operation, and design and construction. Six scenarios were used to estimate energy and emissions savings across representative climate zones. Here we show that artificial intelligence could reduce cost premiums, enhancing high energy efficiency and net zero building penetration. Adopting artificial intelligence could reduce energy consumption and carbon emissions by approximately 8% to 19% in 2050. Combining with energy policy and low-carbon power generation could approximately reduce energy consumption by 40% and carbon emissions by 90% compared to business-as-usual scenarios in 2050.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Doping with phosphorus reduces anion vacancy disorder in CdSeTe semiconductors enabling higher solar cell efficiency

Doping is used in many pn junction devices, such as polycrystalline solar cells, to increase the strength of the junction field to assist charge carrier collection and thus partially mitigate nonradiative recombination losses. We demonstrate a different doping characteristic for inorganic solar cells: using dopants to reduce charge carrier trapping and electronic band tails. Alloying CdTe with Se to form CdSeTe semiconductor reduced recombination, but CdSeTe has more complex defect states which can limit further efficiency gains due to charge carrier trapping and trap-limited mobility. Doping CdSeTe with P (but not N, As, or Sb in this study) reduces band tails (Urbach energies) and lessens the impact of the near valence band trap states, with ambipolar mobilities improving to >50 cm 2 V −1 s −1 , fill factor increasing from 76% to 79%, and efficiencies increasing by 0.9% absolute. Simulations are used to show how such defect reduction improves performance in the radiative limit.

14 SOLAR ENERGY↗
DOE OSTI2026

Non-equilibrium reducing flame aerosol process to create supported high-entropy alloy nanoparticles

High-entropy alloy (HEA) nanomaterials provide opportunities and property combinations for energy and electronic applications, but their practical synthesis faces challenges of elemental immiscibility, metal reducibility, and particle aggregation during their synthesis. Herein, we report a broadly applicable non-equilibrium, scalable, and in-situ reducing flame aerosol process for synthesis of supported HEA nanoparticles. This versatile process can directly load a high concentration of 2 ~ 4 nm HEA nanoparticles on various 1- to 3-dimensional supports. Notably, simultaneous formation of HEA nanoparticles and a mesoporous silica support was successfully realized in a single step. Exploration of this process demonstrates the role of kinetics and entropy on decreasing alloy particle size and altering the reducibility of elements. We propose an entropy-induced reduction mechanism to incorporate oxidizable elements into HEAs, which extends the compositional space of HEA nanoparticles. As a representative catalytic application, we present a RuPdOsIrPt/graphene electrocatalyst with high activity and stability for hydrogen oxidation reaction. Our findings open horizons for high-performance HEA design and applications in diverse fields such as catalysis, electrochemistry, and sensing.

organic↗
DOE OSTI2025

Impact of electric vehicle battery recycling on reducing raw material demand and battery life-cycle carbon emissions in China

The rapid growth of electric vehicles (EVs) in China challenges raw material demand. This study evaluates the impact of recycling and reusing EV batteries on reducing material demand and carbon emissions. Integrating a national-level vehicle stock turnover model with life-cycle carbon emission assessment, we found that replacing nickel-cobalt-manganese batteries with lithium iron phosphate batteries with battery recycling can reduce lithium, cobalt, and nickel demand between 2021 and 2060 by up to 7.8 million tons (Mt) (67%), 12.4 Mt (96%), and 37.2 Mt (93%), respectively, significantly decreasing reliance on import. Moreover, battery recycling coupled with reuse can reduce carbon emissions by up to 6,532-6,864 Mt (36.0-37.9%), depending on four recycling methods employed. However, this reuse strategy delays battery recycling and risks lithium supply shortage, necessitating trade-offs between carbon reduction and material supply. Future technologies, such as lithium-sulfur and all-solid-state batteries, despite their energy efficiency, might exacerbate lithium shortage, underscoring the crucial need for increased lithium supply.

25 ENERGY STORAGE↗
DOE OSTI2026

High Purity and Reduced Defects Hard Carbon Synthesis for Sodium-Ion Batteries

Hard carbon (HC) is the state-of-the-art anode material for sodium-ion batteries; however, the high-temperature carbonization of precursors (>1100 °C) often introduces inorganic impurities, an issue that remains largely underexplored. Here, we report a simple synthesis strategy for producing high purity HC by carbonizing a cellulose-derived precursor at 1400 °C under a slightly reducing Ar–H2 atmosphere on a graphite substrate, thereby eliminating the aluminum contamination observed during conventional carbonization on an alumina substrate under Ar. In addition, the modified synthetic condition reduces surface defects and the concentration of oxygen-containing functional groups, thereby altering the interphase formation on the HC surface. At a current density of 20 mA g−1, the impurity-rich HC exhibited an initial coulombic efficiency (ICE) of 74.1% and a reversible capacity of 248.8 mAh g−1. In sharp contrast, the high purity HC delivered a significantly improved ICE of 90.1% and a reversible capacity of 345.1 mAh g−1. These results underscore the critical importance of impurity and defect control during HC synthesis and highlight the clear electrochemical advantages of high purity HC with reduced defects for sodium-ion battery anodes.

Harshita, Lohanni↗
DOE OSTI2024

PHYSLITE - A new reduced common data format for ATLAS

The High Luminosity LHC (HL-LHC) era brings unprecedented computing challenges that call for novel approaches to reduce the amount of real and Monte Carlo-simulated data that is stored, while continuing to support the rich physics program of the ATLAS experiment. With the beginning of LHC Run 3, ATLAS introduced a new common data format, PHYS, that replaces most of the analysis-specific formats that were used in Run 2, and therefore reduces the disk storage significantly. ATLAS also launched the prototype of another common format, PHYSLITE, that is about a third of the size of PHYS. PHYSLITE will be the main format for ATLAS at the HL-LHC and aims to serve 80% of all physics analyses. To simplify analysis workloads and further reduce disk usage it is designed to largely replace user-defined analysis n-tuples and consequently contains pre-calibrated objects. Various forms of validations are in place to ensure correct functionality for users. Developments continue towards HL-LHC to improve the PHYSLITE format further.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

First demonstration of improved yield with reduced adiabat in inertial confinement fusion implosions on the National Ignition Facility

Laser-driven, indirect-drive inertial confinement fusion (ICF) experiments at the National Ignition Facility (NIF) recently achieved a target gain greater than one, where fusion energy output exceeds input laser energy [Abu-Shawareb et al., Phys. Rev. Lett. 132, 065102 (2024)]. Despite this milestone, gain levels remain insufficient for practical applications such as inertial fusion energy, making performance improvement critical. One promising approach is increasing fuel compression by lowering the implosion adiabat. To explore reduced adiabat, experiments were conducted modifying the laser pulse shape and shock timing of an existing 1.9-MJ-drive implosion design performing near the ignition cliff [Abu-Shawareb et al., Phys. Rev. Lett. 129, 075001 (2022)]. These experiments demonstrated increased compression and fusion yield in ICF implosions at the NIF by using a lower fuel adiabat, and increased compression with a reduced adiabat in high-density carbon ablators. The updated design achieved up to 80% higher fusion yield and 14% greater fuel compression compared to the previous best-performing 1.9-MJ experiment, with repeatable performance, and is the only implosion design to achieve a target gain exceeding one with < 2.04 MJ laser energy. Notably, this work was made possible because of recent advances in target quality and pulse shape control allowing experimental access to the ignition regime, and thereby increased sensitivity to adiabat. This work addresses a long-standing question in ICF research and lays the foundation for higher target gains through optimized implosion strategies. It underscores the potential of reduced adiabat designs to enhance compression and fusion yields for future ICF applications.

Hohenberger, M. [Lawrence Livermore National Labor↗
DOE OSTI2026

A Fast and Accurate Reduced-Order Model for High-Intensity Transferred Arc Discharges

Arc discharges are widely used in welding, plasma smelting, and other industrial processes, where variations in operating conditions strongly affect arc stability, temperature distribution, and energy transfer. Accurate modeling of these phenomena typically requires computationally expensive high-fidelity simulations. This study presents a hierarchy of three arc discharge models with progressively reduced physical fidelity. The high-fidelity model provides a fully physics-resolved reference, the reduced-order model reproduces the dominant thermal and flow characteristics of the arc with reasonable accuracy, and the Elenbaas-Heller model captures key trends in a simplified, rapid formulation. This hierarchy demonstrates that reduced-order model can effectively balance predictive fidelity and computational efficiency, providing practical tools for arc simulation and parametric studies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Electromagnetic coil optimization for reduced Lorentz forces

Abstract The reduction of magnetic forces on electromagnetic coils is an important consideration in the design of high-field devices such as the stellarator or tokamak. Unfortunately, these forces may be too time-consuming to evaluate by conventional finite element modeling within an optimization loop. Although mutual forces can be computed rapidly by approximating large-bore coils as infinitely thin, this approximation does not hold for self-forces as it leads to an unphysical divergence. Recently, a novel reduced model for the self-field, self-force, and self-inductance of electromagnetic coils based on filamentary models was rigorously derived and demonstrated to be highly accurate and numerically efficient to evaluate (Hurwitz et al 2024 IEEE Trans. Magn. 60 7001614). In this paper, we present an implementation of the reduced self-force model employing automatic differentiation within the simsopt stellarator design software and use it in derivative-based coil optimization for a quasi-axisymmetric stellarator. We show that it is possible to significantly reduce point-wise forces throughout the coils, though this comes with trade-offs to fast particle losses and the minimum distance between coils and the plasma surface. The trade-off between magnetic forces and coil-surface distance is mediated by the minimum coil–coil distance for coils near the inboard side of the ‘bean’ cross-section of the plasma. The relationship between forces and fast particle losses is mediated by the normal field error. Coil forces can be lowered to a threshold with minimal deterioration to losses. Importantly, the magnet optimization approach here can be used also for tokamaks, other fusion concepts, and applications outside of fusion.

Hurwitz, Siena (ORCID:0000000166599659)↗
DOE OSTI2025

Polyphenol rewiring of the microbiome reduces methane emissions

Methane mitigation is regarded as a critical strategy to combat the scale of global warming. Currently, ~40% of methane emissions originate from microbial sources, which is causing strategies to suppress methanogens—either through direct toxic effects or by diverting their substrates and energy—to gain traction. Problematically, current microbial methane mitigation knowledge lacks detailed microbiome-centered insights, limiting translation across conditions and ecosystems. Here we utilize genome-resolved metatranscriptomes and metabolomes to assess the impact of a proposed methane inhibitor, catechin, on greenhouse gas emissions for high-methane-emitting peatlands. In microcosms, catechin drastically reduced methane emissions by 72%–84% compared to controls. Longitudinal sampling allowed for reconstruction of a catechin degradation pathway involving Actinomycetota and Clostridium, which break down catechin into smaller phenolic compounds within the first 21 days, followed by degradation of phenolic compounds by Pseudomonas_E from Days 21 to 35. These genomes co-expressed hydrogen-uptake genes, suggesting hydrogenases may act as a hydrogen sink during catechin degradation and consequently reduce hydrogen availability to methanogens. In support of this idea, there was decreased gene expression by hydrogenotrophic and hydrogen-dependent methylotrophic methanogens under catechin treatment. There was also reduced gene expression from genomes inferred to be functioning syntrophically with hydrogen-utilizing methanogens. We propose that catechin metabolic redirection effectively starves hydrogen-utilizing methanogens, offering a potent avenue for curbing methane emissions across diverse environments including ruminants, landfills, and constructed or managed wetlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Reducing the Energy Consumption of Magnetic Resonance Imaging and Computed Tomography Scanners: Integrating Ecodesign and Sustainable Operations

This review aims to provide valuable insights into how energy consumption in magnetic resonance imaging (MRI) and computed tomography (CT) scanners can be effectively monitored, managed, and reduced, thereby contributing to more sustainable medical imaging practices. Demand for advanced imaging technologies such as MRI and CT scanners continues to increase, and understanding the resultant impact on greenhouse gas emissions requires a thorough evaluation of their energy consumption. Here, this review examines the energy monitoring and consumption characteristics of MRI and CT scanners, highlighting potential approaches for energy savings. An overview of MRI and CT principles, hardware components, and their associated energy consumption is provided. After addressing the technical aspects, the hardware and software requirements essential for accurate energy metering are detailed. Baseline measurements of energy consumption data are then provided as a foundation to understand current usage patterns and identify areas for improvement. Ongoing efforts to reduce energy consumption are categorized into 3 main strategies: operations, scanner design enhancements, and active scanning techniques, including accelerated MRI protocols. Ultimately, we emphasize that achieving sustainability in medical imaging requires collaboration across disciplines. By incorporating eco-friendly design in new imaging equipment, we can reduce the environmental impact, promote sustainability, and set a health care industry standard for a healthier planet.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

First Demonstration of Improved Fusion Yield with Increased Compression through Reduced Adiabat in Inertial Confinement Fusion Experiments at the National Ignition Facility

Recent advancements in indirect-drive inertial confinement fusion (ICF) experiments at the National Ignition Facility (NIF) have achieved a significant milestone by demonstrating target gains greater than one, yet future applications necessitate much higher target gains. One approach to achieving improved implosion performance is to pursue increased fuel compression via a lowered implosion adiabat. Experiments have been performed testing a reduced adiabat by introducing small changes to the drive laser pulse shape and the resulting shock timing for an existing implosion design at 1.9 MJ laser drive with near-ignition performance (experiment N210808). Experiments using the updated design demonstrate, for the very first time, increased compression and fusion yield in ICF implosions on the NIF by using a lower fuel adiabat, and increased compression with a reduced adiabat in high-density carbon ablators. Compared to the previously best-performing experiment with a laser energy of 1.9 MJ, these experiments exhibit increases of up to 80% and 14% in nuclear fusion yield and fuel compression, respectively, and with repeatable performance. Further, it is the only implosion design to have achieved a target gain exceeding one with a laser energy of less than 2 MJ. These findings highlight the efficacy of reduced adiabat designs in achieving higher compression and fusion yields, offering a promising pathway for future ICF applications. In conclusion, this Letter not only addresses a long-standing question in ICF but also paves the way for achieving higher target gains with optimized implosion strategies.

Hohenberger, M. [Lawrence Livermore National Labor↗