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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 OSTI2024

Study of Electric Vehicle Range Loss Associated with Replacement Tires

The FuelEconomy.Gov website has become a trusted source for consumers to find information pertaining to fuel economy and fuel-efficient vehicles. As electric vehicles are an increasingly important part of the light-duty fleet in the U.S., there is a need to expand the website content that is targeted to electric vehicle (EV) owners. This report addresses a concern about which several anecdotal reports have come to the attention of the website support staff. Specifically, some EV owners have observed a sudden, noticeable decrease in their all-electric range when they replace the tires that came with their vehicle when it was new. This change has reportedly led some owners to take their vehicles to the dealership service department out of concern that something had gone wrong with the vehicle.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Final Technical Report on Investigation of Short-range Ordering in Transition Metal Compounds by Diffuse Scattering

Future energy needs and sustainability require new materials with novel properties for such applications as energy production, storage and transport and microelectronics. Quantum materials with several competing interactions at the electronic level offer tremendous opportunity to discover, design and tune properties for such applications. Although it has been recognized that small deviations in atomic positions, driven by the competing electronic interactions, in crystalline materials can have significant impact on properties, it remains a challenge to accurately characterize such deviations (short-range order) due to the lack of advanced instruments and analysis tools to characterize them. This project used the powerful neutron and x-ray scattering instruments recently developed at the DOE user facilities to address this challenge. New methods and efficient analysis tools were employed to uncover the hidden ordering that is behind the unique properties of transition metal compounds. One example of hidden order revealed by this project comes from vanadium (IV) oxide (VO 2 ) and related compounds. The project found that the chemical bonds in VO 2 compete against each other, unlike most crystalline compounds where the chemical bonds cooperate to yield the ordered structure. This helps explain why different measurements yielded different, competing pictures about the nature of VO 2 , which has led to disagreement about where its physical properties come from. Another example from this project of hidden ordering comes from a class of compounds known as condensed Chevrel phases, which are superconducting compounds that are generally believed to be non-magnetic. The neutron scattering methods used in this project revealed evidence of magnetism, which usually does not coexist with superconductivity. In this case, magnetism is believed to be one part of a special type of electronic behavior that can occur in compounds that have one-dimensional bonding character.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Unitary Thermal Energy Management for Propulsion Range Augmentation (UTEMPRA) (CRADA Final Report)

NREL will work with Delphi to develop technology that integrates the thermal management of electric drive vehicle sub-systems into a unified thermal system that reduces auxiliary loads and increases vehicle range. The ultimate goal is to create a cost-effective system which improves climate control efficiency through heat pump operation and waste heat recovery, while maintaining occupant thermal comfort and meeting powertrain thermal requirements. The technology will also aim to reduce the number of independent cooling systems required in electric drive vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Extending the operating range and safety of Li-ion batteries with new fluorinated electrolytes

Orbia Fluor and Energy Materials (formerly Koura) has successfully developed a new class of fluorinated electrolyte solvents for lithium-ion batteries. In collaboration with Silatronix and Argonne National Laboratory, the team synthesized and screened over 20 novel fluorinated compounds, optimizing formulations that significantly enhance battery performance across critical metrics such as thermal stability, fast-charging capability, and cycling life at extreme temperatures. Electrolytes with fluorinated molecules developed in this program demonstrated superior performance in 2 Ah pouch cells, achieving over 1000 fast-charge cycles with minimal capacity fade, outperforming conventional carbonate-based electrolytes. Mechanistic studies revealed that the fluorinated electrolytes promote a stable solid electrolyte interphase at the anode and reduce cathode metal dissolution, contributing to improved long-term stability. These advancements mark a significant step toward safer, more efficient batteries for applications ranging from grid storage to defense systems to electric vehicles. We gratefully acknowledge DOE’s financial support through contract DE-EE0009642.

25 ENERGY STORAGE↗
DOE OSTI2025

Expansion of the Direct Feed High-Level Waste Glass Composition in the High Al Range

Baseline glass compositions have been developed and demonstrated for successful immobilization of Hanford high-level waste (HLW) prepared through a pretreatment process. Recent enhanced waste glass formulations have shown promise to increase the waste loading of pretreated sludge compositions from a broader range of HLW feeds. This project proposes to increase the loading of minimally pretreated Hanford HLW in glass by expanding the existing database and glass property-composition models. Estimated direct-feed high level waste (DFHLW) compositions were generated by the Hanford Tank Operations Contractor and used by Pacific Northwest National Laboratory to determine target glass compositions. Gaps in existing data were identified including one high-priority gap in the high Al compositional region. This report summarizes the data collected during the characterization of the DFHLW High Al Glass Matrix. These glasses were intentionally designed with high aluminum concentrations (15 to 30 wt%) and a high likelihood of nepheline formation, which is known to negatively affect glass durability. Some glasses were expected to either fail or approach property constraints to fill data gaps in poorly understood regions of the compositional space due to lack of data. Out of the 50 glasses tested, 14 glasses formed nepheline, while the model predicted nepheline formation in 20 glasses. All quenched glasses met the product consistency test durability constraint; however, 8 glasses failed this constraint after undergoing the canister centerline cooling treatment. Additionally, 17 glasses did not meet the viscosity constraints, 4 failed the EC constraints, and 2 exceeded the allowable T2% for spinel crystal formation. All glasses satisfied the SO 3 solubility limit. The resulting dataset provides valuable information to improve model accuracy and reduce prediction uncertainty. These insights will ultimately support the development of more robust glass formulation strategies, enabling higher waste loadings, reducing operational risks, and expanding the processing envelope.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Feasible Actuator Range Modifier (FARM), a Tool Aiding the Solution of Unit Dispatch Problems for Advanced Energy Systems

Integrated energy systems (IESs) seek to minimize power generating costs in future power grids through the coupling of different energy technologies. To accommodate fluctuations in load demand due to the penetration of renewable energy sources, flexible operation capabilities must be fully exploited, and even power plants that are traditionally considered as base-load units need to be operated according to unconventional paradigms. Thermomechanical loads induced by frequent power adjustments can accelerate the wear and tear. If a unit is flexibly operated without respecting limits on materials, the risk of failures of expensive components will eventually increase, nullifying the additional profits ensured by flexible operation. In addition to the bounds on power variations (explicit constraints),the solution of the unit dispatch problem needs to meet the limits on the variation of key process variables, including temperature, pressure and flow rate (implicit constraints).The FARM (Feasible Actuator Range Modifier) module was developed to enable existing optimization algorithms to identify solutions to the unit dispatch problem that are both economically favorable and technologically sustainable. Thanks to the iterative dispatcher–validator scheme, FARM permits addressing all the imposed constraints without excessively increasing the computational costs. In this work, the algorithms constituting the module are described, and the performance was assessed by solving the unit dispatch problem for an IES composed of three units, i.e., balance of plant, gas turbine, and high-temperature steam electrolysis. Finally, the FARM module provides dedicated tools for visualizing the response of the constrained variables of interest during operational transients and a tool aiding the operator at making decisions. These techniques might represent the first step towards the deployment of an ecological interface design (EID) for IES units.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Long-Range Allosteric Communication Modulated by Active Site Mn(II) Coordination Drives Catalysis in Xanthobacter autotrophicus Acetone Carboxylase

Acetone carboxylase (AC) from Xanthobacter autotrophicus is a 360 KDa α2β2γ2 heterohexamer that catalyzes the ATP-dependent formation of phosphorylated acetone and bicarbonate intermediates that react at Mn(II) metal active sites to form acetoacetate. Structural models of X. autotrophicus AC (XaAC) with and without nucleotides reveal that the binding and phosphorylation of the two substrates occurs ~40 Å from the Mn(II) active sites where acetoacetate is formed. Based on the crystal structures, a significant conformational change was proposed to open and close a tunnel that facilitates the passage of reaction intermediates between the sites for nucleotide binding and phosphorylation of substrates and Mn(II) sites of acetoacetate formation. We have employed electron paramagnetic resonance (EPR), kinetic assays, and hydrogen/deuterium exchange mass spectrometry (HDX-MS) of poised ligand-bound states and site-specific amino acid variants to complete an in-depth analysis of Mn(II) coordination and allosteric communication throughout the catalytic cycle. In contrast with the established paradigms for carboxylation, our analyses of XaAC suggested a carboxylate shift that couples both local and long-range structural transitions. Shifts in the coordination mode of a single carboxylic acid residue (αE89) mediate both catalysis proximal to a Mn(II) center and communication with an ATP active site in a separate subunit of a 180 kDa α2β2γ2 complex at a distance of 40 Å. This work demonstrates the power of combining structural models from X-ray crystallography with solution-phase spectroscopy and biophysical techniques to elucidate functional aspects of a multi-subunit enzyme.

Biochemistry & Molecular Biology↗
DOE OSTI2024

Symmetry Breaking in the Lowest-Lying Excited-State of CCl4: Valence Shell Spectroscopy in the 5.0–10.8 eV Photon Energy Range

We report absolute high-resolution vacuum ultraviolet (VUV) photoabsorption cross-sections of carbon tetrachloride (CCl4) in the photon energy range 5.0–10.8 eV (248–115 nm). The molecular spectrum and electronic structure have been comprehensively investigated together with quantum chemical calculations, providing geometries, bond lengths, vertical excitation energies and oscillator strengths. The major electronic excitations have been assigned to valence and Rydberg transitions which are also accompanied by vibrational excitation assigned to degenerate stretching, v3′t2 and degenerate deformation v4′t2 modes. The rather complex nuclear dynamics along the degenerate deformation mode, v4′t2, have been thoroughly investigated by Time-Dependent Density Functional Theory (TD-DFT) method. The relevant Jahn–Teller distortion operative within the lowest-lying electronic excited-state is shown here for the first time in order to yield a weak absorption feature at 6.156 eV. Further calculations on the potential energy curves for the singlet excited-states along the C–Cl stretching coordinate show the relevance of efficient C–Cl bond excision.

Biochemistry & Molecular Biology↗
DOE OSTI2025

Long-Range Azimuthal Correlation, Entanglement, and Bell Inequality Violation by Spinning Gluons at the Large Hadron Collider

We apply the recently developed concept of the nucleon energy–energy correlator (NEEC) for the gluon sector to investigate the long-range azimuthal angular correlations in proton–proton collisions at the Large Hadron Collider. The spinning gluon in these collisions will introduce substantial nonzero cos(2Φ) asymmetries in both Higgs boson and top quark pair productions, where Φ is the azimuthal angle between the forward and backward energy correlators in the NEEC observables. The genesis of the cos(2Φ) correlation lies in the intricate quantum entanglement. Owing to the substantial cos(2Φ) effect, the NEEC observable in Higgs boson and $t\bar{t}$ production emerges as a pivotal avenue for delving into quantum entanglement and scrutinizing the Bell inequality at high-energy colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Long Range Plan: Dense matter theory for heavy-ion collisions and neutron stars

Since the release of the 2015 Long Range Plan in Nuclear Physics, major events have occurred that reshaped our understanding of quantum chromodynamics (QCD) and nuclear matter at large densities, in and out of equilibrium. The US nuclear community has an opportunity to capitalize on advances in astrophysical observations and nuclear experiments and engage in an interdisciplinary effort in the theory of dense baryonic matter that connects low- and high-energy nuclear physics, astrophysics, gravitational waves physics, and data science. This is a white paper prepared by a group of nuclear physicists during the 2023 LRP process.

Lovato, Alessandro↗
DOE OSTI2026

Analysis of Power Electronic Solutions for Wide-Range Wave Energy Input

Wave energy is a largely untapped energy source with the potential to provide 290 TWh per year to the continental United States. As a new technology, wave energy converters are less efficient and reliable compared to established energy sources, leaving the vast energy of the sea largely unutilized. Wave energy is uniquely inconsistent, with large fluctuations. Paired with harsh operating environments and difficulty in repair, the power electronics designed to harvest wave energy need to be reliable, cost-effective, and able to work in a wide operating band. The literature on existing power electronics in wave energy converters and lessons learned across other industries provide a framework of topologies to simulate. WEC-Sim, an open-source hydrodynamic platform in MATLAB Simulink developed by the National Laboratory of the Rockies, was used to simulate a wide range of power electronics under a variety of wave conditions. This paper provides a comprehensive investigation into existing wave energy power electronics converters, state-of-the-art topologies that can be applied to wave energy, and novel solutions to wave conversion.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Multi-range vehicle speed prediction using vehicle connectivity for enhanced energy efficiency of vehicles

An integrated speed prediction framework based on historical traffic data mining and real-time V2I communications for CAVs. The present framework provides multi-horizon speed predictions with different fidelity over short and long horizons. The present multi-horizon speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs) as a case study. The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the present data mining strategy over long prediction horizons. Despite the uncertainty in long-range CAV speed predictions, the vehicle level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal-driving and conventional BTM strategy.

Amini, Mohammad Reza↗
DOE OSTI2026

A STUDY OF SHORT-RANGE CORRELATED PAIR FORMATION MECHANISMS

Short-Range Correlations (SRCs) refers to pairs of nucleons that are temporary high density fluctuations with high relative momenta and lower center-of-mass momenta com pared to the nuclear Fermi momentum (kF). SRCs account for 20–25% of the nucleons in medium to heavy nuclei, make up essentially all nucleons with momentum greater than kF, and contribute most of the kinetic energy carried by nucleons in nuclei. The existing semi-inclusive and exclusive measurements only cover a handful of light nu clei or heavy elements. This does not allow for a systematic study of the dependence of SRC pairs on nuclear mass and proton-neutron asymmetry. It also does not allow for insights into SRC pairing mechanisms. Therefore, we systematically studied the individual probabilities for finding SRC protons in symmetric and neutron-rich asymmetric nuclei d, 9Be, 10B, 11B, 12C, 40Ca, 48Ca, 54Fe, and 197Au. We measured the (e,e'p) reaction in kinematics dominated by scattering off mean-field nucleons (k = kF) and nucleons in SRC pairs (k = kF) at the Thomas Jefferson National Accelerator Facility (JLab) in Hall C of the Continuous Electron Beam Accelerator Facility (CEBAF) in the Fall of 2022. The measured results were used to determine the SRC pairing probabilities for protons to examine how pairing depends on nuclear mass, proton-neutron asymmetry, and nuclear shell structure. The extracted cross-section ratios were also compared to theoretical calculations. We found that SRC pair formation depends more on the nuclear shell structure with sharp increases locally within the general trend of a slower increase with larger A. We also found that intra-shell pairing has a much larger influence than inter-shell pairing. Comparisons to theory suggest that angular momentum selection rules are important to SRC pair formation and can provide new constraints for new theoretical models.

Swan, Noah [Old Dominion Univ., Norfolk, VA (Unite↗
DOE OSTI2025

Enhancing Short-Range Weather Forecasts through Temporal Variation Encoding: A Multiperiod Embedding Approach

Machine learning (ML) techniques have emerged as promising approaches to improve regional weather forecast accuracy and reliability through data-driven methods. We propose a novel ML-based weather forecasting model, the Multiperiod Embed Net (MPENet). A key distinguishing feature of MPENet is its explicit utilization of the inherent cyclic nature in weather dynamics, unlike the autoregressive strategies commonly used in other ML weather forecasting approaches. Critical cyclic structures are identified via Fourier analyses of dynamic time series. Cyclicity in the convolutional representation is achieved by transforming one-dimensional time series of meteorological variables into two-dimensional tensors based on identified periods. This approach enables the model to leverage intrinsic weather patterns, enhancing regional forecast performance. To demonstrate the effectiveness of MPENet, we conduct a comparative analysis with Nvidia’s FourCastNet. Both models are trained on High-Resolution Rapid Refresh (HRRR) data from 2015 to 2022, over a 192 km × 192 km region in Tennessee. The comparisons are performed locally at two specific locations known to have different weather dynamics due to orographic effects: Crossville, on the relatively flat Cumberland Plateau with fewer topographic airflow disruptions, and Oak Ridge, in the ridge-and-valley region, where airflow is heavily influenced by surrounding valleys and mountains. Our results indicate that FourCastNet achieves strong accuracy at very short lead times, while MPENet maintains competitive skill and shows advantages in capturing temporal evolution over longer periods. Cross-correlation analyses of MPENet and FourCastNet predictions with the HRRR data suggest that encoding critical cyclicity into the network architecture leads to improvements in the forecasting skill.

Artificial intelligence↗