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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

PAIReD jet: A multi-pronged resonance tagging strategy across all Lorentz boosts

We propose a new approach of jet-based event reconstruction that aims to optimally exploit correlations between the products of a hadronic multi-pronged decay across all Lorentz boost regimes. The new approach utilizes clustered small-radius jets as seeds to define unconventional jets, referred to as PAIReD jets. The constituents of these jets are subsequently used as inputs to machine learning-based algorithms to identify the flavor content of the jet. We demonstrate that this approach achieves higher efficiencies in the reconstruction of signal events containing heavy-flavor jets compared to other event reconstruction strategies at all Lorentz boost regimes. Classifiers trained on PAIReD jets also have significantly better background rejections compared to those based on traditional event reconstruction approaches using small-radius jets at low Lorentz boost regimes. The combined effect of a higher signal reconstruction efficiency and better classification performance results in a two to four times stronger rejection of light-flavor jets compared to conventional strategies at low Lorentz-boosts, and rejection rates similar to classifiers based on large-radius multi-pronged jets at high Lorentz-boost regimes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Informing electrification strategies of residential neighborhoods with urban building energy modeling

Electrifying end uses is a key strategy to reducing GHG emissions in buildings. However, it may increase peak electricity demand that triggers the need to upgrade the existing power distribution system, leading to delays in electrification and needs of significant investment. There is also concern that building electrification may cause an increase of energy costs, leading to further energy burden for low-income communities. This study uses the urban scale building modeling tool CityBES to assess the electrification impacts of more than 43,000 residential buildings in a neighborhood of Portland, Oregon, USA. Energy efficiency upgrades were investigated on their potential to mitigate the increase of peak electricity demand and energy burden. Simulation results from the calibrated EnergyPlus models show that electrification with heat pumps for space heating and cooling as well as for domestic water heating can reduce CO2e emissions by 38%, but increase peak electricity demand by about 9% from the baseline building stock. Combining electrification measures and energy efficiency upgrades can reduce CO2e emissions by 48% while reducing peak electricity demand by 6% and saving the median household energy costs by 28%. City and utility decision makers should consider integrating energy efficiency upgrades with electrification measures as an effective residential building electrification strategy, which significantly reduces carbon emissions, caps or even decreases peak demand while reducing energy burden of residents.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

A coupled hydrologic-agroeconomic modeling framework to evaluate adaptive irrigation strategies under groundwater withdrawal restrictions

Growing groundwater scarcity requires integrated tools to capture interactions among hydrology, agricultural production, markets, and land use. This study presents an iterative modeling framework that couples hydrologic, crop-yield, and economic models to capture two-way feedback among water availability, agricultural production, and market responses under groundwater constraints. The primary goal of this paper is to describe the methodological development of the coupled framework and demonstrate the significance of iterative model interaction. Applied to the western United States, we evaluated adaptive responses to restricting groundwater use beyond recharge levels, represented through changes in irrigation management and expansion or shrinkage of crop markets through land reallocation. Results demonstrate that the iterative coupling converges to stable equilibrium responses within 10 iterations. At equilibrium, deficit irrigation emerges as the dominant adaptation strategy in California, with irrigation levels stabilizing at approximately 70% of full irrigation demand, while Arizona and New Mexico experience stronger yield sensitivities. Early iterations produce commodity price increases of up to 10% for fruit and vegetable crops; however, these responses moderate as land allocation and production patterns adjust across regions. Deficit irrigation and spatial reallocation of irrigated land partially offset production losses, with variability observed across different states: California maintains yields primarily via deficit irrigation, whereas Arizona and New Mexico will rely mainly on reducing irrigated area to absorb the shock. By capturing feedback between biophysical and economic processes, this approach highlights how irrigation strategies and land-use decisions evolve under water stress and provides a transferable platform for evaluating water management policies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Lagrange-Remap strategy for multi-material fluid-solid simulations using compressive limiters

In the present work, the Lagrange-Remap strategy proposed in [1] is extended to multi-material fluid-solid simulations. Both hypo-elastic and hyper-elastic material models are considered to describe the mechanical behavior of the solids. In practice, the deviatoric stress tensor (for hypo-elastic materials) and the left Cauchy-Green tensor (for isotropic hyper-elastic materials) are remapped, while the use of compressive limiters effectively reduces numerical diffusion during the remapping step. The simplicity of this diffuse interface approach is emphasized in the context of multi-material fluid-solid simulations. A series of Lagrange-Remap test cases, involving both solids and fluids, are conducted and compared with reference Lagrangian simulations, demonstrating the robustness and accuracy of the overall numerical strategy.

Compressive limiters↗
DOE OSTI2026

An integrated in-situ coordination strategy enabling high-performance layered cathodes for sodium-ion batteries

O3-type layered transition metal oxide cathodes hold tremendous potential in sodium-ion batteries (SIBs) due to their low cost and high energy density. However, the structure instability associated with detrimental phase transitions and severe interface parasitic reactions exacerbate the material's electrochemical performance degradation. Herein, we develop an integrated in-situ coordination strategy via heteroatomic modulation inducing coherent epitaxial layer to collaboratively enhance the overall framework robustness from surface to bulk. The theoretical calculation and multiple in/ex-situ characterizations demonstrate the charge density around oxygen is redistributed, which promotes the electron localization, thus widening the NaO 2 lattice space and accelerating the Na + transport dynamics. Furthermore, the formed strengthened oxygen bond energy effectively distributes the long-range coordination of Mn 3+ O 6 octahedron, thereby alleviating Jahn-Teller distortion and local stress. Importantly, the in-situ formed conformal buffer layer dramatically relieves the adverse interface side reactions, facilitating the construction of robust cathode-electrolyte interface, which ameliorate the whole structure stability of designed materials. Consequently, the optimized NFMZ@NZO-1.0 exhibits the excellent cycling stability with 80.2% capacity retention after 300 cycles at 1C, and delivers a high discharge capacity of 107.1 mAh g −1 at 10C. In conclusion, this distinctive coupling strategy provides valuable insights for developing high-performance layered cathode materials in SIBs.

Coherent epitaxial layer↗
DOE OSTI2025

The unique architecture of umbrella toxins permits a two-tiered molecular bet-hedging strategy for interbacterial antagonism

Bacteria exist in competitive and rapidly changing environments in which the nature of future threats cannot be easily predicted. Streptomyces coelicolor produces three antibacterial umbrella particles that harbor distinct polymorphic toxin domains and an overlapping set of six diversified lectins. Here, we show that the exquisite specificity of umbrella particles derives from lectin-mediated species-specific binding to previously undescribed hypervariable surface glycoconjugates. A cryo-electron microscopy (cryo-EM) structure of one such lectin in complex with its oligosaccharide substrate defines the molecular basis for targeting through the coordinated recognition of multiple glycan features. Biochemical and genetic studies of several target species, in conjunction with lectin-swapping experiments, support a model whereby S. coelicolor umbrella toxin diversification at the levels of lectin composition and toxin polymorphism represents a unique, two-tiered bet-hedging strategy. Bioinformatic analyses support this as a means by which the unusual architecture of umbrella toxins offers Streptomyces a generalizable strategy to antagonize an unpredictable array of competitors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

An adaptive model-free robotic force control strategy for hydrodynamic real-time hybrid simulation of floating offshore wind turbines

Real-time hybrid simulation (RTHS) - a cyber-physical testing approach - promises to enhance the simulation fidelity of the model-scale experiments used to prototype floating offshore wind turbines (FOWTs). In hydrodynamic RTHS (hydro-RTHS), actuators emulate aerodynamic forces on model-scale FOWT specimens subjected to physical waves in a hydrodynamic laboratory. Robotic arms are promising candidates for actuation in hydro-RTHS due to their compact multi-degree-of-freedom (DOF) capabilities. Unlike classical RTHS for seismic applications, which typically relies on displacement control, hydro-RTHS requires 6-DOF force control on newly designed floating prototypes in a model-scale setting, which presents significant challenges, including modeling uncertainties, directional asymmetry, configuration drift, bandwidth limitations, and time-varying delays. To mitigate these constraints without extensive pre-test calibration, this study proposes an adaptive model-free robotic force control strategy that combines task-space explicit force control with a secondary joint-space pose-keeping task. The Adaptive Feedforward Compensator (AFC) is integrated into the force control loop to compensate for time-varying delay. Experimental testing was conducted using a Franka Emika Panda robotic arm with a 1:50 scale FOWT specimen under operational wind and wave conditions. Results demonstrate stable and consistent 6-DOF force tracking. Effective delay compensation was observed, with low-frequency delay reductions ranging from 71.4% to 91.8% and improvements in low-frequency surge force tracking of 25.0% to 52.1%. This study enhances robotic actuation performance in hydro-RTHS and introduces a force control strategy that supports reliable robotic operation in uncertain floating environments. Future work will explore disturbance-observer mechanisms to further enhance wave rejection capabilities under extreme wind and wave conditions.

17 WIND ENERGY↗
DOE OSTI2026

Lattice-Oxygen-Driven Selective Oxidation Strategy for Stable Argyrodite Solid-State Lithium Metal Batteries

All-solid-state lithium metal batteries (ASSLMBs) with Li6PS5Cl argyrodite electrolytes and high-voltage LiNi0.8Mn0.1Co0.1O2 (NMC811) cathodes offer high energy density but suffer from rapid capacity fading due to the layered-to-rock-salt transition of NMC811 and structural degradation of Li6PS5Cl from parasitic interfacial reactions. Here, we demonstrate a catholyte engineering strategy using a Li2S scavenging additive to suppress interfacial reactivity and preserve the structural and electrochemical stability of both NMC811 and Li6PS5Cl. Incorporating 0.10 wt.% Li2S enables exceptional cycling stability, achieving 76% capacity retention after 550 cycles at C/10 and 88% retention after 800 cycles at C/3 at 60 degrees C, compared with rapid failure in pristine cells. Spectroscopic, electrochemical, and morphological analyses confirm that Li2S maintains electrode integrity by sustaining particle contact and suppressing phase decomposition. This work elucidates interfacial degradation pathways in NMC811/argyrodite systems and introduces a low-cost, scalable strategy to stabilize nickel-rich oxide cathodes in ASSLMBs, advancing their practical viability.

25 ENERGY STORAGE↗
DOE OSTI2024

Process parameter translation strategies for variable directed energy deposition spot size using 316L, copper, and Inconel 625

Directed energy deposition (DED) is a form of additive manufacturing available across a variety of laser spot diameter values, often referred to as spot sizes. However, there is no method to easily transfer process parameters across discrete spot sizes, leading to DED process parameters that are equipment specific and not widely applicable. In this study, a strategy is proposed and investigated for five spot sizes that keep the areal energy density constant while varying power, feed rate, and powder flow during the deposition of 316L stainless steel. An assessment of trends in hardness and microstructure is possible due to the novel production of components of a single material across several spot sizes using a single nozzle on a single DED system. The proposed strategy was used to nullify the hardness drop during functional grading of Inconel 625 and pure copper, enabling fabrication of multi-material sample that does not compromise desirable properties. This application shows the value in establishing more efficient process parameter development and understanding spot size influences on geometric and material property flexibility, to enable a more diverse powder-based DED design space and to increase the industry adoption of DED systems.

316L↗
DOE OSTI2026

Evaluating CO 2 mitigation strategies in SAF biorefineries: Techno-economic and life cycle analysis

The aviation sector requires scalable decarbonization strategies, and lignocellulosic sustainable aviation fuel (SAF) represents a promising pathway. This study comparatively evaluates the techno-economic analysis and life cycle assessment (LCA) of three CO 2 management strategies integrated within a U.S.-based gasification–Fischer–Tropsch SAF biorefinery: (i) catalytic hydrogenation of captured CO 2 to methanol, (ii) geological CO 2 sequestration, and (iii) mineralization to sodium bicarbonate (NaHCO 3 ). Techno-economic analysis indicates that methanol synthesis requires approximately 26% higher capital investment and 33% higher operating costs than mineralization. Although methanol co-production generates the highest gross revenue, NaHCO 3 production reduces the SAF minimum selling price by approximately 38% relative to both methanol synthesis and geological sequestration pathways, reflecting a more balanced cost allocation through mineral co-product valorization. Geological sequestration lowers operating costs by nearly 50% compared with methanol synthesis but remains highly dependent on carbon credit mechanisms. LCA reveals substantial divergence in climate performance. Relative to methanol synthesis, sequestration improves net greenhouse gas performance by approximately 163%, transitioning the system from net-positive to net-negative emissions. Mineralization further enhances carbon mitigation, achieving roughly 85% greater carbon reduction than sequestration and over sixfold improvement relative to methanol synthesis within the defined system boundary. Sensitivity analysis identified hydrogen price, co-product market value, and process emissions as dominant drivers. Under baseline assumptions, CO 2 mineralization is found to offer the most balanced pathway.

Carbon capture and storage↗
DOE OSTI2025

Improving adhesive bonding of short carbon fiber thermoplastic composites to aluminum alloys with a hybrid laser-plasma surface modification strategy

This study investigates hybrid laser–plasma surface modification strategies for metal–CFRTP (carbon-fiber-reinforced thermoplastic polymer) dissimilar joints to improve their bonding performance, in contrast to existing literature that mostly focuses on either plasma or laser treatment alone. By conducting double cantilever beam (DCB) tests on adhesively-bonded AA5052 and CFRPA66 (carbon-fiber-reinforced polyamide 66) joints, as an example of metal–CFRTP joints, it was found that laser engraving on the metal surface combined with plasma treatment on the CFRTP surface significantly improved the specific fracture energy of the joint by 187% and 31% compared to as-received and plasma-treated-only joints, respectively. However, the hybrid treatment of laser engraving and plasma on the investigated CFRTP surface did not improve the bonding performance of the joints. The underlying mechanisms related to hybrid laser-plasma surface modification strategies were further investigated by examining the surface and cross-sectional morphologies after DCB testing using microscopy. Computational modeling was performed to elucidate the interaction between grooves on the metal substrate and the CFRTP–adhesive interfacial bonding in metal–CFRTP joints. This study provides new insights into developing surface modification methods for achieving strong metal–CFRTP adhesive joints, aimed at lightweighting structural components in automotive, aerospace, and other applications.

Adhesive bonding↗
DOE OSTI2024

A Generation-Storage Coordination Dispatch Strategy for Power System Based on Causal Reinforcement Learning

In the backdrop of global energy transformation, power systems integrating high proportions of renewable energy sources are facing unprecedented challenges in operational stability and dispatch efficiency. To address these challenges, this study introduces a generation-storage coordination real-time dispatch strategy based on Causal Power System Dynamic Reinforcement Learning (CPSDRL). Diverging from traditional reinforcement learning approaches, CPSDRL innovatively incorporates causal inference within the state prediction model - the crux of model-based reinforcement learning - thereby establishing the Power Causal Dynamic Model (PCDM). Assisted by the prior knowledge of power systems, the model significantly enhances prediction accuracy and reliability through a two-stage training process. Utilizing PCDM, this study further applies a direct policy search algorithm to optimize the real-time dispatch strategy. Experimental results indicate that the proposed method improves the stability of generation-storage coordination real-time dispatch and exhibits competitive advantages in sample efficiency and computational speed, compared to traditional model-based and model-free reinforcement learning algorithms. This method is expected to enhance the practicality and adaptability of causal reinforcement learning techniques in power system scheduling and control.

causal reinforcement learning↗
DOE OSTI2025

Estimating the Impacts of Increasing Temperatures and the Efficacy of Climate Adaptation Strategies in Urban Microclimates with Deep Learning

As urbanization and climate change progress, understanding and addressing urban heat becomes a priority for climate adaptation efforts. High temperatures concentrated in the urban core can drive increased risk of heat-related death and illness as well as increased energy demand for cooling. However, modeling the urban microclimate is an ongoing field of research typically burdened by an imprecise description of the built environment, incomplete observational records, significant computational cost, and a lack of high-resolution estimates of the impacts of increasing temperatures. Here, we present computationally efficient machine learning methods that can improve the accuracy of urban temperature estimates when compared to historical reanalysis data. These models are applied to a neighborhood in Los Angeles, and we compare the energy benefits of heat mitigation strategies to the impacts of climate change. We find that cooling demand is likely to increase substantially through midcentury, but engineered high-albedo surfaces could lessen this increase by more than 50 %. The corresponding increase in winter gas heating offsets the summer cooling benefit in the current climate, but total annual energy use from combined heating and cooling with electric heat pumps benefits from the engineered heat mitigation strategies under both current and future climates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Metabolic engineering strategies for producing decanoic acid and related oleochemicals: 1-decanol, 2-nonanone, and poly(3-hydroxydecanoate) in Escherichia coli

Medium-chain (mc-) oleochemicals are an important class of renewable chemicals with broad industrial applications; however, their sustainable microbial production remains challenging. In this study, we developed a versatile metabolic engineering and fed-batch strategy to produce C 10 -oleochemicals in Escherichia coli. Central to this approach is an engineered mc-acyl-ACP thioesterase Cl FatB3-tr-D10S with C 10 species accounting for around 70% of the total fatty acids produced. To expand product diversity, we established a decanoyl-CoA pool through co-expression of fadD, enabling downstream conversion into multiple product classes. Through pathway tuning, enzyme bioprospecting, strain engineering and fermentation optimization strategies, we demonstrated selective production of 1-decanol, 2-nonanone and poly(3-hydroxydecanoate) (C 10 -PHA). Production of decanoic acid and 1-decanol were achieved by optimizing expression of Cl fatB3-tr-D10S and, Mt fadD6 and Ma acr, respectively. Leveraging β-oxidation enabled the production of β-ketoacyl-CoA intermediates, which were converted to 2-nonanone via heterologous Mlu fadE, Vf fadB and Ps fadM expression. Additionally, expression of phaJ2 and phaC2 facilitated the conversion of decanoyl-CoA pool into C 10 -PHA homopolymer. Altogether, this work demonstrates a versatile and tunable platform for medium-chain oleochemical production.

1-Decanol↗
DOE OSTI2026

Strategy for Ultranarrow Light Down-Conversion for Displays Based on Bicolor-Emitting 2D Colloidal Heterostructures

The demand for ultranarrow spectral emission below 10 nm is critical for next-generation displays. Although current colloidal nanocrystals are successful in light down-conversion applications, they fall short in matching the stringent color purity requirements set by standards like Rec. 2020. Achieving such narrow linewidths through material engineering alone remains elusive, necessitating innovative light management strategies that avoid optical losses and maintain device efficiency. Here, in this work, we present a novel 2D colloidal heterostructure design, combining a CdSe core nanoplatelet, a CdS crown, and a CdZnS shell, to achieve bright bicolor emission in the solid state (green/red) emission with tunable intensity ratios controlled by excitation power (either optical or electrical). Integration of these nanoplatelets into a dielectric cavity further narrows the emission linewidth to sub-2 nm while enhancing the photoluminescence intensity by up to 200 times, meeting the Rec. 2020 color purity targets. This approach paves the way for a strategy avoiding complex laser-based solutions.

2D nanocrystals↗
DOE OSTI2025

Depolymerization as a Design Strategy: Depolymerization Etching of Polymerization-Induced Microphase Separations

Thermally triggered depolymerization has traditionally been viewed through the lens of sustainability and recycling, not as a constructive tool for materials design. Herein, we show that selective, thermally triggered depolymerization to gaseous monomer serves as a solvent-free strategy for generating porosity in nanostructured polymer materials, offering a means to bypass the mass transport limitations inherent in conventional solution-based etching. As a demonstration platform, we employed polymerization-induced microphase separation (PIMS) to generate disordered bicontinuous block copolymer structures with embedded depolymerizable domains. By incorporating a methacrylate block susceptible to thermal depolymerization within a cross-linked, depolymerization-resistant styrenic matrix, we developed a process we term depolymerization etching of polymerization-induced microphase separations (DEPIMS). This approach enables highly selective and efficient domain removal via reversion to monomer to produce mesoporous materials with high surface areas (>200 m 2 /g). Subsequent surface functionalization yielded mesoporous adsorbents with tunable uptake kinetics and among the highest dye adsorption capacities reported for PIMS-derived materials, demonstrating the adaptability of the DEPIMS platform for chemical separations. DEPIMS can also be extended to a gram-scale, one-pot approach to yield mesoporous materials with recoverable monomer in under 12 h. These findings reposition thermal depolymerization from a sustainability tool to a broadly enabling strategy for scalable, on-demand fabrication of functional nanostructured materials.

Depolymerization↗
DOE OSTI2026

A Three-Component Strategy for Synthesizing High-Entropy Alloy Nanoparticles with High-Index Facets

Controlling the shapes and, more importantly, exposed facets (high-index facets (HIFs), especially) of high-entropy alloy (HEA) nanoparticles is not yet possible. Herein, a three-component synthetic strategy for obtaining tetrahexahedral (THH)-shaped HIF-HEA nanoparticles through a combined alloying-dealloying strategy and liquid-metal mediation process is reported. Metal precursors are first alloyed with Ga to form multielemental nanoparticles and then alloyed with a volatile metal. Selectively dealloying the volatile metal from the nanoparticles is used to regulate their surface energies; the Ga stabilizes the HEA phase, and the trace element stabilizes the HIFs, resulting in THH-shaped HEA nanoparticles (seven different types) with {210} HIFs. Finally, nanoparticle megalibraries containing millions of THH-shaped HIF-HEAs on 4 cm 2 chips with size and composition control shows generalizability and scalability for materials discovery purposes.

alloys↗
DOE OSTI2024

Evaluation of a Reference-Free Collision Cross Section Calibration Strategy for Proteomics Using SLIM-Based High-Resolution Ion Mobility Spectrometry–Mass Spectrometry

Ion mobility spectrometry (IMS) is a gas-phase analytical technique that separates ions with different sizes and shapes and is compatible with mass spectrometry (MS) to provide an additional separation dimension. The rapid nature of the IMS separation combined with the high sensitivity of MS-based detection and the ability to derive structural information on analytes in the form of the property collision cross section (CCS) makes IMS particularly well-suited for characterizing complex samples in -omics applications. In such applications, the quality of CCS from IMS measurements is critical to confident annotation of the detected components in the complex -omics samples. However, most IMS instrumentation in mainstream use requires calibration to calculate CCS from measured arrival times, with the most notable exception being drift tube IMS measurements using multifield methods. The strategy for calibrating CCS values, particularly selection of appropriate calibrants, has important implications for CCS accuracy, reproducibility, and transferability between laboratories. The conventional approach to CCS calibration involves explicitly defining calibrants ahead of data acquisition and crucially relies upon availability of reference CCS values. In this work, we present a novel reference-free approach to CCS calibration which leverages trends among putatively identified features and computational CCS prediction to conduct calibrations post-data acquisition and without relying on explicitly defined calibrants. We demonstrated the utility of this reference-free CCS calibration strategy for proteomics application using high-resolution structures for lossless ion manipulations (SLIM)-based IMS-MS. In conclusion, we first validated the accuracy of CCS values using a set of synthetic peptides and then demonstrated using a complex peptide sample from cell lysate.

59 BASIC BIOLOGICAL SCIENCES↗