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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
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↗
DOE OSTI2024

Accelerating particle-in-cell kinetic plasma simulations via reduced-order modeling of space-charge dynamics using dynamic mode decomposition

We present a data-driven reduced-order modeling of the space-charge dynamics for electromagnetic particle-in-cell (EMPIC) plasma simulations based on dynamic mode decomposition (DMD). The dynamics of the charged particles in kinetic plasma simulations such as EMPIC is manifested through the plasma current density defined along the edges of the spatial mesh. We showcase the efficacy of DMD in modeling the time evolution of current density through a low-dimensional feature space. Not only do such DMD based predictive reduced-order models help accelerate EMPIC simulations, they also have the potential to facilitate investigative analysis and control applications. Here, we demonstrate the proposed DMD-EMPIC scheme for reduced-order modeling of current density and speedup in EMPIC simulations involving electron beam under the influence of magnetic field, virtual cathode oscillations, and backward wave oscillator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Drought Reduces Formation, but Enhances Persistence, of Mineral‐Associated Organic Matter in a Grassland Soil

Drought effects are pervasive in terrestrial ecosystems, yet there is limited understanding of how drought impacts the transformation of plant carbon (C) inputs to mineral-associated organic matter (MAOM)—the largest and slowest-cycling pool of soil organic carbon (SOC). In a 12-week 13 C-CO 2 greenhouse labeling experiment, we tracked the formation of MAOM derived from the two dominant sources of plant C input to the mineral soil—living root inputs ( 13 C-rhizodeposits) and decaying root inputs ( 13 C-root detritus)—under normal moisture and droughted conditions in a semiarid grassland soil. At the end of the 12-week period, we also measured the persistence of 13 C-MAOM formed from rhizodeposits versus root detritus via a subsequent persistence assay. Drought reduced the formation of MAOM derived from living roots by decreasing rhizodeposits, reducing microbial growth rates, and altering the composition of organic matter, lipids, and metabolites. Drought initially delayed the formation of MAOM derived from root detritus by slowing the early stages of root litter decomposition (week 4–8), but did not decrease total MAOM formation by the end of the 12-week period. Notably, drought enhanced the persistence of MAOM derived from root detritus, but did not influence the persistence of MAOM derived from rhizodeposits. Our results provide some of the first direct evidence that drought can reduce the formation of MAOM in a grassland soil, but may enhance its persistence, based on the source of plant input from which MAOM is derived.

13C- labeling↗
DOE OSTI2025

Brachypodium SPEECHLESS2 Promoter Drives Expression of a Synthetic EPF to Reduce Stomatal Density in Sugarcane Without Pleiotropic Effects

Stomata are microscopic pores that regulate the exchange of CO 2 and water vapour, making them a major target for engineering plants with improved intrinsic water use efficiency (iWUE). Proof-of-concept studies have demonstrated the potential to increase iWUE by reducing stomatal density (SD) and stomatal conductance (g sw ) by ubiquitously expressing EPIDERMAL PATTERNING FACTOR (EPF) family genes. However, unwanted effects on leaf, stem and reproductive traits are often observed when EPFs are misexpressed in this fashion. We sought to test if these effects result from pleiotropy and to identify a targeted promoter that can circumvent the side effects while retaining the desired reduction in SD. A previously reported synthetic EPF (EPF syn ) was expressed in sugarcane ( Saccharum spp.) using two putatively tissue-specific promoters from Brachypodium distachyon (BdCESA7p and BdSPCH2p) and a ubiquitous control from Zea mays (ZmUBI4p). BdSPCH2p control reduced SD to statistically equivalent levels as ZmUBI4p on the abaxial (23%) and adaxial (23%) leaf surfaces. ZmUB4p and BdCESA7p induce expression in four tissue types often associated with pleiotropic effects in EPF-expressing low SD plants. Transgenic plants carrying either the BdCESA7p or ZmUBI4p EPF syn cassettes displayed leaf chlorosis, reduced leaf nitrogen and chlorophyll content, and altered stem architecture. However, transgenic events harboring the BdSPCH2p EPF syn cassette restricted EPF syn expression to the stomatal development zone and leaf nodal tissues and produced transgenic plants without the associated pleiotropic effects. These results represent an important step toward engineering low-SD crops since they show that targeted gene expression can engineer stomatal patterning without impairing agronomically important traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Novel anaerobic selenium oxyanion reducers native to FGD wastewater for enhanced selenium removal

Biological treatment is a recognized approach for removing selenate and selenite oxyanions present in flue gas desulfurization (FGD) wastewater. However, the knowledge of the specific microbial species or communities responsible for reducing water-soluble selenium oxyanions to insoluble elemental selenium remains limited. In addition, the selenium oxyanion reduction genes and pathways have yet to be understood in these wastewaters. This study characterizes selenium oxyanion-reducing bacteria (SeRB) native to FGD wastewater, and the resulting elemental selenium particles formed. By selecting native SeRB microbes in a defined media, a novel resolution of these organisms has been achieved. This research identifies previously unrecognized selenium oxyanion-reducing capabilities in Anaerosolibacter, alongside predominant SeRB from Mesobacillus and Tepidibacillus genera. This work encompasses both 16S and metagenomic techniques to recover novel metagenome-assembled genomes, distinct to this environment. The biogenic selenium produced by these organisms was predominantly of elemental selenium, either amorphous or with a hexagonal structure. This study identifies the SeRB present in FGD wastewater and characterizes their selenium products, offering crucial insights to enhance the efficiency of biological treatment strategies and the potential of selenium recovery from this industrial waste.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Reducing Frequency Bias of Fourier Neural Operators in 3D Seismic Wavefield Simulations Through Multistage Training

The recent development of neural operator (NeurOp) learning for solutions to the elastic wave equation shows promising results and provides the basis for fast large-scale simulations for different seismological applications. In this article, we use the Fourier neural operator (FNO) model to directly solve the 3D Helmholtz wave equation for fast seismic ground-motion simulations on different frequencies and show the frequency bias of the FNO model, that is, it learns the lower frequencies better comparing to the higher frequencies. To reduce the frequency bias, we adopt the multistage FNO training, that is, after training a stage 1 FNO model for estimating the ground motion, we use a second FNO model as the stage 2 to learn from the residual, which greatly reduced the errors on the higher frequencies. By adopting this multistage training, the FNO models show reduced biases on higher frequencies, which enhanced the overall results of the ground-motion simulations. Thus the multistage training FNO improves the accuracy and realism of the ground-motion simulations.

earthquakes↗
DOE OSTI2024

Enhancing Lifetime and Reducing Costs for Fish Diversion Netting Structures (Final Report)

In this effort Pacific Northwest National Laboratory (PNNL) developed and demonstrated an anti-fouling coating that is effective on fish diversion structures. The coating was based on a previously developed superhydrophobic lubricant infused composite (SLIC) coating but modified for application to flexible substrates. We showed that the new reformulated coating – FlexiSLIC – can be applied to flexible fibrous structures to significantly reduce biofouling of netting and anchor lines, to enable longer operational lifetimes, reduced costs, and more reliable operations. The coating developed in this effort was tested on relevant fish diversion structural netting and rope materials (e.g. nylon, Dyneema, polypropylene) to reduce biofouling. Engagement with industry in the development and demonstration further supported progress toward commercialization of the materials.

36 MATERIALS SCIENCE↗