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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 OSTI2023

Landau-Ginzburg theory of charge density wave formation accompanying lattice and electronic long-range ordering

Here we propose an analytical Landau-Ginzburg (LG) theory of the charge density waves coupled with lattice and electronic long-range order parameters. Examples of long-range order include the electronic wave function of superconducting Cooper pairs, structural distortions, electric polarization, and magnetization. We formulate the LG free energy density as a power expansion with respect to the charge density and other long-range order parameters as well as their spatial gradients and biquadratic coupling terms. We introduced a biquadratic coupling between the charge density gradient and long-range order parameters as well as nonlinear higher gradients of the long-range order parameters. The biquadratic gradient coupling is critical to the appearance of different spatially modulated phases in charge-ordered ferroics and high-temperature superconductors. We derived the thermodynamic conditions for the stability of the spatially modulated phases, which are the intertwined spatial waves of charge density and lattice/electronic long-range order. The analytical expressions for the energies of different phases, corresponding order parameters, charge density waves amplitudes, and modulation periods obtained in this paper can be employed to guide the comprehensive physical explanation, deconvolution, and Bayesian analysis of experimental data on quantum materials ranging from charge-ordered ferroics to high-temperature superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Evidence of distinct nonpolar/polar ordering at long/short ranges in relaxor ferroelectrics

Distinct atomic nonpolar/polar ordering is determined at long, intermediate, and short ranges using synchrotron x-ray diffraction, Raman scattering, and pair distribution function data in K 0.5 Na 0.5 NbO 3 -doped BaTiO 3 -based relaxor ferroelectrics, viz., (1 - x) Ba 0.9 Sr 0.1 TiO 3 -x KNN 50. Two different polar phases with distinct symmetries are identified at short/intermediate ranges for x = 0.10, where a monoclinic phase at short ranges gradually transforms into a rhombohedral phase at intermediate ranges. Here, in contrast, a nonpolar phase with average cubic symmetry is found to be stable at long ranges for a wide temperature range (100 ≤ T ≤ 500 K). The polar behavior of short/intermediate-range ordering is quantified in terms of the amplitude of ferroelectric phonon mode $Γ^-_4$ (q = 0, 0, 0) (which corresponds to the zone center of the cubic Brillouin zone). The amplitude of the $Γ^-_4$ phonon mode increases with decreasing temperature, suggesting the enhancement of ferroelectric polarization at short/intermediate ranges on lowering temperatures. Enhanced ferroelectric polarization at low temperature is also visible and evident by ferroelectrostriction and is quantified by the increase in magnitude of spontaneous volume ferroelectrostriction. Consequently, Zero thermal expansion is observed at low temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Range cost-effectiveness of plug-in electric vehicle for heterogeneous consumers: An expanded total ownership cost approach

Plug-in electric vehicles (PEV) appears to have sales momentum in major personal vehicle markets but are still at the early market stage. Opportunities to accelerate PEV adoption can be discovered through comprehensive total cost of ownership (TCO) analysis. Understanding the cost-effective electric ranges of PEVs for consumers, manufacturers, and the society is critical for any discussion of PEV mass markets. This study expanded the traditional TCO approach by (1) fully considering heterogeneous consumer driving patterns, (2) quantifying the charging inconvenience and range anxiety cost of battery-electric vehicles (BEVs), and (3) monetizing both tangible and intangible PEV policies. Uncertainties were handled through Monte Carlo simulation. The results suggest that BEVs with an electric range of 250–350 km have the lowest TCO in cities with government-enacted purchase limitations, and internal combustion engine vehicles (ICEVs) have the lowest TCO in cities without purchase limitations, even when considering PEV subsidies. The lowest TCO for some consumer groups is obtained by BEVs with an electric range of 400–450 km, especially in northern China, where the weather is colder. The cost-effective all-electric range for BEVs in each city in 2025 will decrease due to improved battery performance in cold environments and an expanded charging infrastructure. Finally, based on TCO, plug-in hybrid electric vehicles (PHEVs) are currently more suitable for drivers with a high average daily mileage or a large mileage variance. However, by 2025, BEVs with a long driving range may become a more cost-effective choice for these drivers.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Neural Network-Based Electric Vehicle Range Prediction for Smart Charging Optimization

Range prediction is a standard feature in most modern road vehicles, allowing drivers to make informed decisions about when to refuel. Most vehicles make range predictions through data- or model-driven means, monitoring the average fuel consumption rate or using a tuned vehicle model to predict fuel consumption. The uncertainty of future driving conditions makes the range prediction problem challenging, particularly for less pervasive battery electric vehicles (BEV). Most contemporary machine learning-based methods attempt to forecast the battery SOC discharge profile to predict vehicle range. In this work, we propose a novel approach using two recurrent neural networks (RNNs) to predict the remaining range of BEVs and the minimum charge required to safely complete a trip. Each RNN has two outputs that can be used for statistical analysis to account for uncertainties; the first loss function leads to mean and variance estimation (MVE), while the second results in bounded interval estimation (BIE). These outputs of the proposed RNNs are then used to predict the probability of a vehicle completing a given trip without charging, or if charging is needed, the remaining range and minimum charging required to finish the trip with high probability. Training data was generated using a low-order physics model to estimate vehicle energy consumption from historical drive cycle data collected from medium-duty last-mile delivery vehicles. Here, the proposed method demonstrated high accuracy in the presence of day-to-day route variability, with the root-mean-square error (RMSE) below 6% for both RNN models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Steric Modulation of Protein‐Mediated Nanoparticle Assembly: Controlling Cluster Size, Polydispersity, and FRET Responses by Rebalancing Short‐ and Long‐Range Interactions

Understanding and manipulating protein-nanoparticle interactions is of broad interest to fields ranging from nanomedicine to the biological fabrication of functional hierarchical materials. This study investigates how steric forces introduced by a pegylated derivative of superfolder green fluorescent protein (sfGFP) that is monofunctional for silica binding modulate the delicate interplay of long-range (electrostatic and van der Waals) and short-range (protein-mediated) interactions in pH-responsive silica nanoparticle (SiNP) assembly by bifunctional silica-binding sfGFP. Increasing the length of the PEG segment and pre-incubating SiNPs with increasing concentrations of pegylated proteins enables precise control over cluster size within the 800–1450 nm range with a sixfold decrease in polydispersity index to a remarkable 0.1 endpoint. Weakening short-range attractive interactions via mutagenesis extends this control to clusters in the 50–250 nm range and reveals that the Förster resonance energy transfer (FRET) efficiency of clusters scales linearly with cluster diameter below 230 nm but increases only by 15% as clusters grow to 1450 nm. Furthermore, these findings enable the development of a system that provides an optical readout to dynamic changes in solution conditions enacted by a combination of pH adjustment and ion charge screening.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Atomic-scale probing of short-range order and its impact on electrochemical properties in cation-disordered oxide cathodes

Abstract Chemical short-range-order has been widely noticed to dictate the electrochemical properties of Li-excess cation-disordered rocksalt oxides, a class of cathode based on earth abundant elements for next-generation high-energy-density batteries. Existence of short-range-order is normally evidenced by a diffused intensity pattern in reciprocal space, however, derivation of local atomic arrangements of short-range-order in real space is hardly possible. Here, by a combination of aberration-corrected scanning transmission electron microscopy, electron diffraction, and cluster-expansion Monte Carlo simulations, we reveal the short-range-order is a convolution of three basic types: tetrahedron, octahedron, and cube. We discover that short-range-order directly correlates with Li percolation channels, which correspondingly affects Li transport behavior. We further demonstrate that short-range-order can be effectively manipulated by anion doping or post-synthesis thermal treatment, creating new avenues for tailoring the electrochemical properties. Our results provide fundamental insights for decoding the complex relationship between local chemical ordering and properties of crystalline compounds.

25 ENERGY STORAGE↗
DOE OSTI2023

Systematic study of short- and long-range correlations in RE 3 TaO 7 weberite-type compounds by neutron total scattering and X-ray diffraction

The atomic structures of the lanthanide tantalates, Ln 3 TaO 7 , series (Ln = Pr, Tb, Dy, Ho, Tm, Yb) were systematically investigated using total scattering techniques. High-energy X-ray and neutron diffraction analysis revealed that the long-range structures can be grouped into three distinct families: (1) ordered Cmcm (Ln = Pr), (2) ordered Ccmm (Ln = Tb, Dy, Ho), and (3) disordered, defect-fluorite Fm$\bar{3}$m (Ln = Ho, Tm, Yb). These findings help to clarify the symmetry discrepancy for the already reported long-range structures in the literature. The short-range analysis of neutron total scattering data via pair distribution functions reveals a high degree of structural heterogeneity across length scales for all compounds, with distinct local atomic arrangements that are not fully captured by the average, long-range structure. The short-range structures at the level of coordination polyhedra are better captured by a set of alternative non-centrosymmetric structural models: (1) C2cm, (2) C222 1 , and (3) C2mm. This establishes a short-range multiferroic character for weberite-type tantalates because ferroelectric interactions compete with magnetic correlations. These ferroelectric interactions are particularly pronounced for the disordered compounds Tm 3 TaO 7 and Yb 3 TaO 7 . In conclusion, the structural differences among the three families are the result of changes in TaO 6 polyhedral tilt (transition between families 1 and 2) and dipolar interactions of off-centered Ta cations (transition between families 2 and 3).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Accurate prediction of global-density-dependent range-separation parameters based on machine learning

In this work, we develop an accurate and efficient XGBoost machine learning model for predicting the global-density-dependent range-separation parameter, ωGDD, for long-range corrected functional (LRC)-ωPBE. This ωGDDML model has been built using a wide range of systems (11 466 complexes, ten different elements, and up to 139 heavy atoms) with fingerprints for the local atomic environment and histograms of distances for the long-range atomic correlation for mapping the quantum mechanical range-separation values. The promising performance on the testing set with 7046 complexes shows a mean absolute error of 0.001 117 a0−1 and only five systems (0.07%) with an absolute error larger than 0.01 a0−1, which indicates the good transferability of our ωGDDML model. In addition, the only required input to obtain ωGDDML is the Cartesian coordinates without electronic structure calculations, thereby enabling rapid predictions. LRC-ωPBE(ωGDDML) is used to predict polarizabilities for a series of oligomers, where polarizabilities are sensitive to the asymptotic density decay and are crucial in a variety of applications, including the calculations of dispersion corrections and refractive index, and surpasses the performance of all other popular density functionals except for the non-tuned LRC-ωPBE. Finally, LRC-ωPBE (ωGDDML) combined with (extended) symmetry-adapted perturbation theory is used in calculating noncovalent interactions to further show that the traditional ab initio system-specific tuning procedure can be bypassed. The present study not only provides an accurate and efficient way to determine the range-separation parameter for LRC-ωPBE but also shows the synergistic benefits of fusing the power of physically inspired density functional LRC-ωPBE and the data-driven ωGDDML model.

Chemistry↗
DOE OSTI2024

Exaggerated Plurivory of Macrophomina phaseolina : Accounting for the Large Host Range Claim and the Shifting of Scientific Language

Macrophomina phaseolina is a plant pathogenic fungus that is frequently described as having a broad host range encompassing more than 500 species. We noticed that citations provided in support of this statement do not actually demonstrate such a broad host range. To elucidate the true documented host range of this fungus, we initiated a literature meta-analysis of 894 publications on M. phaseolina since 1913. We discovered that the first host range summaries did not require Koch's postulates or other experimental demonstrations of pathogenicity. Most of the available early host claims were based on tenuous associations between the fungus and symptoms, sometimes without reporting isolation or morphological examination in vitro. These statements apparently led to a pattern of increasingly exaggerated host range claims, without support from a primary reference, until the claim that M. phaseolina has 500 hosts became common in the early 2000s. At present, the scientific community typically requires Koch's postulates to characterize pathogenicity on a new host. Among all the available literature, we only found primary experimental evidence for M. phaseolina’s pathogenicity on 97 hosts; 74 hosts confirmed by Koch's postulates and 23 hosts with all steps from Koch's postulates completed except for recovery of the pathogen from symptomatic tissues. This study demonstrates how scientific concepts can change over time and necessitate changes to historic axioms. We propose that the hyperbole surrounding the host range of M. phaseolina has obscured an accurate depiction of its biology.

Plant Sciences↗
DOE OSTI2022

Incoherent range-based holography of far-distant objects using LIDAR

Los Alamos National Laboratory has developed an incoherent, long-range, sub-centimeter resolution (LIDAR) with which we achieve centimeter-scale reflection holography at extremely long ranges. The system consists of a pulsed laser and photon-counting receiver. This combination yields round-trip time of flight data to illuminate parts of the object of interest. The aggregation of these data for many LIDAR pulses yields a plot with a range on the X axis and reflectance on the Y axis, which we refer to as a range profile. Observing that the range profile is a projection of the reflection map of the object onto the view vector, we collect profiles from a variety of viewing angles and invert these data to form an image. We adapt imaging algorithms from the field of computer aided tomography to suit our application and present results from imaging demonstrations at a 10 km range.

Hoffmann, Mitchell P. (ORCID:0000000170551324)↗
DOE OSTI2020

Factors Impacting Range Hood Use in California Houses and Low-Income Apartments

Venting range hoods can control indoor air pollutants emitted during residential cooktop and oven cooking. To quantify their potential benefits, it is important to know how frequently and under what conditions range hoods are operated during cooking. We analyzed data from 54 single family houses and 17 low-income apartments in California in which cooking activities, range hood use, and fine particulate matter (PM 2.5 ) were monitored for one week per home. Range hoods were used for 36% of cooking events in houses and 28% in apartments. The frequency of hood use increased with cooking frequency across homes. In both houses and apartments, the likelihood of hood use during a cooking event increased with the duration of cooktop burner use, but not with the duration of oven use. Actual hood use rates were higher in the homes of participants who self-reported more frequent use in a pre-study survey, but actual use was far lower than self-reported frequency. Residents in single family houses used range hoods more often when cooking caused a discernible increase in PM 2.5 . In apartments, residents used their range hood more often only when high concentrations of PM 2.5 were generated during cooking.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Energy Cost Analysis and Operational Range Prediction Based on Medium- and Heavy-Duty Electric Vehicle Real-World Deployments across the United States

While the market for medium- and heavy-duty battery-electric vehicles (MHD EVs) is still nascent, a growing number of these vehicles are being deployed across the U.S. This study used over 2.3 million miles of operational data from multiple types of MHD EVs across various regions and operating conditions to address knowledge gaps in total cost of ownership and operational range. First, real-world energy cost savings were determined: MHD fleets should experience energy cost savings each year from 2021 to 2035, regardless of vehicle platform, with the greatest savings seen in transit buses (up to USD 4459 annually) and HD trucks (up to USD 3284 annually). Second, to help fleets across various geographies throughout the U.S. assess the suitability of EVs for their year-round operating needs, operational range was modeled using the XGBoost algorithm (R2: 70%) given 22 input features relevant to vehicle efficiency. Finally, this paper recommends (1) that MHD fleets apply energy-saving practices to minimize the impacts of cold temperatures and high congestion levels on vehicle efficiency and range, and (2) that local hauling fleets select trucks with a nominal range nearly double the expected maximum daily range to account for range losses under local, urban driving conditions.

Qiu, Yin (ORCID:0009000900948794)↗
DOE OSTI2020

Impact of multimode range and location on urban fuel economy on a light-duty spark-ignition based powertrain using vehicle system simulations

Multimode engine operation uses two or more combustion modes to maximize engine efficiency across the operational range of a vehicle to achieve higher overall vehicle fuel economy than is possible with a single combustion mode. More specifically for this study, multimode solutions are explored that make use of boosted SI under high load operation and other advanced combustion modes such as advanced compression ignition (ACI) under part-load conditions to enable additional engine efficiency improvements across a broader range of the engine operating map. ACI combustion has well-documented potential to improve efficiency and emissions under part-load operation but poses challenges that limit full engine speed-load range. This study investigates the potential impact of ACI operational range on simulated fuel economy to help focus research on areas with the most opportunity for improving fuel economy. These simulations make use of a vehicle model, discretized engine data, and employ a systematic exploration of ACI operational range to estimate multimode fuel economy for a mid-size passenger vehicle over U.S. Environmental Protection Agency’s Urban Dynamometer Driving Schedule. The results of this study highlight operational ranges with the highest potential fuel economy and correspondingly areas of focus for multimode research and ACI engine operation1.

Curran, Scott↗
DOE OSTI2024

Consumer-Oriented Energy Use and Range Metrics for Battery Electric Vehicles

The present study was motivated by a need to expand information for consumers offered through the FuelEconomy.Gov website. To that end, a power-based modeling approach has been used to examine the effect of steady-speed driving on estimated range for model year 2020 – 2023 battery electric vehicles (BEVs). This approach allowed rapid study of a broader range of BEV models than could be accomplished through vehicle tests. Publicly accessible certification test results and other data were used to perform a regression between cycle-average tractive power requirements and the resulting electrical power. Importantly, this regression enabled estimation of electric power and energy use over a range of steady highway speeds. These analyses in turn allowed projection of vehicle range at differing speeds. The projections agree within 6% with available 65 MPH manufacturer test data. Analyses of vehicles from model years 2020 – 2023 show that the 5-cycle range and energy use values from the window stickers of new vehicles are reasonable values for steady-speed driving at 65 MPH. Range decreases by a median value of approximately 15% for each 10 MPH increase in speed. The 5-cycle energy use (in kW-Hr / 100 miles) and energy economy (in miles / kW-Hr) derived from the 5-cycle energy use are reasonable estimates for 65 MPH steady speed driving. Energy economy decreases by about 0.5 miles / kW-Hr for every 10 MPH increase in speed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Optimizing the tuning range of the Fermilab Recycler 53MHz RF cavities by exploiting the avoided crossing of the tuner and cavity modes

The electromagnetic eigenmodes of the Fermilab Recycler RF cavities were simulated with ACE3P running on NERSC's 'Perlmutter' supercomputer in an attempt to optimize their tuning range to comfortably support slip-stacking. A theory, based on coupled circuits and avoided crossings, was developed to explain the origins of the tuning range for tuner-cavity waveguide systems. This provided a logical, rigorous method to carry out this optimization, although engineering problems due to high voltages in the tuner and the operational $\mu$ range of the garnet had to be carefully implemented. It was shown that the desired goal of 10kHz of tuning was not attainable with the current cavity specifications. The maximum tuning range obtained was 5.59kHz for a single tuner with a coaxial line of length 63in. A double tuner cavity was also studied using the simulation software, although with little improvement in the tuning range. A promising technique to improve the tuning range involving the desynchronization of the garnets' magnetic permeabilities is proposed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Understanding Electric Vehicle Range and Charging Needs: Interactions Between Ambient Temperature, Commute Patterns, and State-of-Charge Usage

Electric vehicle (EV) performance can vary substantially under real-world operating conditions, particularly due to ambient temperature effects on energy consumption, battery behavior, and thermal management requirements. This study quantifies how weather conditions, daily driving patterns, and State-of-Charge (SOC) usage strategies jointly influence EV driving range, charging frequency, and overall energy efficiency. A detailed and experimentally validated Autonomie vehicle model is developed, integrating a powertrain, a mono-zonal cabin model, and a battery electro-thermal model. Three battery sizes (200-, 300-, and 400-mile homologated ranges) are assessed across five commute profiles (20–200 miles) and six ambient temperatures (−18 °C to 50 °C), including scenarios with and without preconditioning. Results show that extreme temperatures could significantly decrease the maximum achievable range by up to 55% in cold conditions (−18 °C) and 40% in hot conditions (50 °C), relative to moderate conditions. Larger battery packs retain a greater fraction of their nominal range under thermal stress, while smaller packs experience sharper relative penalties due to the higher contribution of thermal loads to total energy demand. The analysis further demonstrates that limiting operation to partial SOC windows (e.g., 80–20%), a common real-world practice, significantly reduces achievable range and increases charging frequency, particularly in cold weather. Thermal preconditioning while plugged in is shown to mitigate these effects for short trips, reducing energy consumption by up to 31% in hot conditions and 7% in cold conditions. The findings demonstrate how climate, SOC usage behavior, and thermal management jointly shape the practical driving capability of EVs, highlighting the importance of efficient thermal management and realistic user charging strategies for ensuring reliable EV operation across diverse climatic scenarios.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Home range and resource selection of Virginia opossums in the rural southeastern United States

The Virginia opossum (Didelphis virginiana) has a rapidly expanding distribution in North America, but many aspects of its ecology remain relatively understudied, particularly in rural areas of its core range. We collected GPS telemetry data from 93 opossums in a rural, non-agricultural landscape in South Carolina, USA (2018–2019) to examine factors influencing space use and resource selection. Estimated male home ranges (99% utilization distributions) were on average 50% larger than those of females (mean home range 115.9 ± 103.7 ha vs 76.7 ± 75.0 ha). The home range size decreased on average by 20% with each 20% increase in deciduous land cover but was not affected by season or other landscape factors. Core area sizes (65% utilization distributions) were not influenced by sex (mean core area size 29.1 ± 23.7 ha and 22.4 ha ± 13.8 for males and females, respectively) or season, but the core area size decreased by 14% with each 400 m increase in distance from a permanent water source. Resource selection by opossums primarily occurred at the landscape level. Both males and females generally selected for wetlands while avoiding pine forests and developed/open areas, likely the result of differences in resource availability and predation risk between habitats. Opossums also tended to select for linear features such as unpaved roads and edge habitat, which may facilitate movement across the landscape. Finally, the home ranges we documented are among the largest recorded for opossums in the USA, likely the result of the relatively low resource abundance throughout our study area due to comparatively minimal anthropogenic influence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Application of Wireless Charging at Seaports for Range Extension of Drayage Battery Electric Trucks

Even though heavy-duty battery electric trucks (BETs) have become commercially available, their range limitation still hinders widespread adoption. Drayage has been regarded as a suitable application for early BETs due to typically having limited daily mileage. However, drayage operation can vary widely and some form of range extension may still be needed for BETs operating in this application. Here, in this paper, wireless charging at port terminals is proposed for this purpose. Potential wireless charging zones at port terminals are identified, and efficacy of wireless charging to extend BET range in drayage operation is verified by simulating the activity of 20 BETs from a drayage operator serving the ports of Los Angeles and Long Beach, using a microscopic BET energy consumption model. Furthermore, an optimization problem is formulated for optimal wireless charging zone planning from the port authority's perspective, considering subsets of the identified zones, and charging power options to choose from, for different budget ranges. In this context, zone planning means determining which areas of the port terminals should be selected for installing wireless charging systems, and what level of charging power should be for each selected zone's system. For each budget range, the optimization problem is solved using genetic algorithm to determine an optimal zone plan that provides the maximum amount of energy through wireless charging per unit cost of installation. The results show that wireless charging can aid improving activity completion of the simulated fleet by 5%, and further optimizing the zone plan can achieve similar performance with lower cost.

33 ADVANCED PROPULSION SYSTEMS↗