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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 37 records · Page 2

Wholly Sustainable, Cost-Effective Carbon Fiber-Nylon Compounds CRADA 592 (Final Report)

Carbon fiber composites have attracted considerable attention due to the potential for substantial mass savings, with many examples now implemented in the low-volume luxury car market. However, migration to higher volume applications has been hindered by: (a) high material cost, (b) high processing times, and (c) perception of low Sustainability. This project will address all three of these barriers: (a) carbon fiber material to replace aluminum in structural components at a cost penalty of no more than $5/Kg-saved (aka weight buy), (b) fitting into high-rate processes for automotive production like injection molding, and (c) end-to-end Sustainable material – based on post industrial waste carbon fiber and nylon 66 and ability to recycle end-of-life auto parts. The opportunity lies in combining DowAksa capabilities in carbon fiber manufacturing, resin chemistry intermediate production with the unique testing capabilities inherent within PNNL. The teams from PNNL and DowAksa held several meetings virtually and in-person in Michigan and at PNNL, including a lab tour at PNNL. Throughout, the teams discussed DowAksa material sources, commercially available recycled base materials, and preliminary material properties. The teams also engaged in multiple discussions and evaluations of potential automotive applications based on the ideas suggested by PNNL. The teams discussed several potential automotive applications in which recycled carbon fiber and recycled PA resin can be used. The PNNL team identified 38 cast aluminum components that can potentially be assessed for redesign using the DowAksa materials system. The PNNL team also identified 27 polyamide components. The teams discussed the lists and narrowed it down to a handful of applications that are exterior and interior to common vehicle architectures. The team also considered semi-structural and structural components and short-listed the highest potential candidates, such as cross-car-beam. The cross-car beam was considered to be highly suitable and potentially viable demonstration applications based on the properties of the materials as well as the weight savings potentials and the reduction in embodied energy by utilizing wholly sustainable materials, since both materials, carbon fiber and resin, were derived from recycled materials. The next step was to reach out to potential OEMs and/or Tier1s who were interested in exploring such technology for future applications. However, the project was terminated, and no further discussions or exchange of information took place. No new data were generated, including no IP and no publications.

36 MATERIALS SCIENCE

Rapid T cell engineering to counter emerging threats (Full Technical Report)

Instead of genetic engineering, we sought to determine if a rapid method of membrane protein delivery could generate functional CAR-T cells in a rapid, safer, cost-effective manner. Using cell free protein synthesis, we generated CAR proteins embedded in a nanodisc, and thus effectively solubilized the protein. We demonstrated the first functional CAR proteins outside of a cellular context. We next tested uptake into immune cells and found extremely high uptake into T cells and multiple other populations of immune cells. We found some evidence of cytotoxicity in vitro conferred by the nanodisc delivered protein.

59 BASIC BIOLOGICAL SCIENCES

China's plug-in hybrid electric vehicle transition: An operational carbon perspective

Assessing the emissions of plug-in hybrid electric vehicle (PHEV) operations is crucial for accelerating the carbon–neutral transition in the passenger car sector. This study is the first to adopt a bottom-up model to measure the real-world energy use and carbon dioxide emissions of China’s top twenty selling PHEV models across different regions from 2020 to 2022. The results indicate that (1) the actual electricity intensity of the best-selling PHEV models (20.2–38.2 kWh/100 km) was 30–40 % higher than the New European Driving Cycle values, and the actual gasoline intensity (4.7–23.5 L/100 km) was 3–6 times greater than the New European Driving Cycle values. (2) The overall energy use of the best-selling models varied among different regions, and the energy use from 2020 to 2022 in Southern China was double that Northern China and the Yangtze River Middle Reach. (3) The top-selling models emitted 4.7 megatons of carbon dioxide nationwide from 2020 to 2022, with 1.9 megatons released by electricity consumption and 2.8 megatons released by gasoline combustion. Furthermore, targeted policy implications for expediting the carbon–neutral transition within the passenger car sector are proposed. In essence, this study explores and compares benchmark data at both the national and regional levels, along with performance metrics associated with PHEV operations. The main objective is to aid nationwide decarbonization efforts, focusing on carbon reduction and promoting the rapid transition of road transportation toward a net-zero carbon future.

33 ADVANCED PROPULSION SYSTEMS

Enriching OpenStreetMap network data for transportation applications: Insights into the impact of urban congestion on accessibility

OpenStreetMap (OSM) data is a valuable open-source resource for various transportation, traffic, and planning applications. However, OSM network data lack operating traffic speed information, which is critical for transport planning and operations. Addressing this shortcoming, this study leverages commercial vendor data (to serve as ground truth) with exogenous, open-source variables characterizing local transport infrastructure, land use, and demographic information to predict average congested traffic speeds on OSM networks. Three machine-learning models were tested and estimated for OSM links with and without speed limit information in the Denver metropolitan region. Among these, XGBoost performed best, with mean absolute errors of 3.27 and 3.62 mph for links with and without speed limits, respectively. The developed models accurately predicted traffic speeds for different hours and days of the week compared to ground truth data. Using these predicted speeds, drive accessibility scores were computed for the Denver region for different time periods using the Mobility Energy Productivity (MEP) metric to understand the impact of congestion on energy-efficient accessibility. Results show that congestion-adjusted drive accessibility can be significantly lower compared to accessibility calculated using free flow speeds. Specifically, weekday evening hours saw a 42 % drop in accessibility due to reduced speeds, particularly around downtown Denver. Across the Denver metro region, approximately half as many opportunities and jobs are accessible in under 20 min by car during the evening peak period relative to free flow conditions. These findings underscore the importance of using congestion-adjusted operating speeds rather than speed limits in accessibility calculations, as reliance on speed limits can substantially overestimate energy-efficient drive accessibility in large, car-centric cities susceptible to significant congestion. In conclusion, the methodology presented here could further enrich OSM network data, making them useful for an even broader range of transportation applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Trends and 2025 Insights on the Rise of Electric Vehicles in the USA

Plug-in electric vehicles (EVs) are reshaping the transportation energy landscape, providing a practical alternative to petroleum fuels for a growing number of applications. EV sales grew 55x in the past decade (2014-2024) and 6x since 2020, driven by technological progress enabled by policies to reduce transportation emissions as well as industrial plans motivated by strategic value of EVs for global competitiveness, jobs and geopolitics. In 2024, 22% of passenger cars sold globally were EVs and opportunities for EVs beyond on-road applications are growing, including solutions to electrify off-road vehicles, maritime and aviation. This Review updates and expands our 2020 assessment of the scientific literature and describes the current status and future projections of EV markets, charging infrastructures, vehicle-grid integration and supply chains in the USA. EV is the lowest-emission motorized on-road transportation option, with life-cycle emissions decreasing as electricity emissions continue to decrease. Charging infrastructure grew in line with EV adoption but providing ubiquitous reliable and convenient charging remains a challenge. EVs are reducing electricity costs in several US markets and coordinated EV charging can improve grid resilience and reduce electricity costs for all consumers. The current trajectory of technology improvement and industrial investments points to continued acceleration of EVs.

33 ADVANCED PROPULSION SYSTEMS

Detection of atomic oxygen and its electronic coherence decays using time-resolved ultrafast coherent Raman scattering

We report the detection of atomic oxygen and quantitative measurements of its electronic Raman coherence decays in flames and low-temperature plasmas using time-resolved hybrid femtosecond/picosecond coherent anti-Stokes Raman scattering (CARS). Atomic oxygen was detected using the Raman transitions between the spin–orbit coupled triplet ground states. Atomic oxygen was generated in an H 2 /O 2 /Ar diffusion flame and an O 2 /Ar pulsed plasma discharge. Single exponential decays were observed for the O( 3 P 2 )–O( 3 P 1 ) Raman transition at 158.3 cm −1 and the O( 3 P 2 )–O( 3 P 0 ) Raman transition at 227 cm −1 . From the decay measurements, the atomic O Raman linewidths were obtained from 25 to 150 Torr in non-equilibrium plasma and at 760 Torr in a flame. Enhanced signal-to-noise ratios (SNRs) of atomic oxygen and atomic to molecular oxygen signal contrasts were obtained by taking advantage of electronic triplet coherence beating. Enhancement of up to seven times in the atomic O SNR was observed. Furthermore, we also found that the dephasing rates of O 2 (v = 0–3, N = 37) were similar, which provides evidence for the assumption that vibrational excitation does not influence the dephasing of diatomic molecular rotational CARS transitions.

Atomic and molecular spectroscopy

Experimental study of high-energy single-pulse nanosecond discharges in pin-to-pin configuration

Single-pulse pin-to-pin nanosecond pulsed discharges in ambient air (gap distances of 3–7 mm) were investigated at high pulse energies (∼20–30 mJ deposited energy per 11 ns full width at half maximum pulse). A Michelson interferometry setup (532 nm continuous-wave laser) was employed to record time-resolved interferograms of the discharge, enabling spatially resolved calculation of the electron number density. An intensified charge-coupled device camera was used to capture the spatiotemporal evolution of the discharge (streamer formation and spark channel development), and Coherent Anti-Stokes Raman Spectroscopy (CARS) was used to measure post-discharge N 2 vibrational temperatures. Discharge current and voltage were monitored with a back-current shunt. The discharge was initiated with simultaneous cathode-directed and anode-directed streamers that bridge the gap within ∼1 ns and form a luminous, filamentary plasma channel immediately after breakdown. Laser interferometry measurements showed peak electron number densities of the order of 10 1 7–10 18 cm −3 , occurring about 15–20 ns after pulse arrival at the discharge gap. Shorter gap discharges yielded higher peak electron densities, consistent with the higher energy density in the smaller gaps. Spatially, the electron density was highest near the electrodes and decreased toward the midgap region, with 5 and 7 mm gaps exhibiting a pronounced drop in the central channel. CARS indicated initial vibrational temperatures of approximately 4000–6000 K in the spark core of ∼50 ns after the discharge onset, decaying on a ∼500 ns timescale as the plasma cooled and recombined.

Coherent anti-Stokes Raman spectroscopy

WholeTraveler Anonymized Data Phase 1

Phase 1 of the WholeTraveler Study data collection consisted of an online-only survey. This survey captured data on three categories of observable variation in the population relevant to transportation decisions. First, the survey collected traditional demographic data such as age, gender, income, and education level. Second, it collected data across personality, psychological, and preference categories. This included: 1. The "Big Five" inventory personality traits: openness to new experience, conscientiousness, extroversion, agreeableness, and neuroticism; 2. Risk and time preferences; and 3. Environmental preferences. Third, the survey collected data on historical behavior patterns including: 1. Adoption of (as well as interest in) new technologies or innovations (e.g., smartphones, PEVs, solar panels, adaptive cruise control [ACC]); 2. Car ownership history and current car ownership status; 3. Recent mode use across different time scales (e.g., previous week, previous month, previous year); and 4. Timing of major life events such as starting a family as well as overall lifecycle trajectory patterns. Data from Phase 1 and Phase 2 are linked by a unique respondent identifier. Anonymized versions of the Phase 1 and Phase 2 data are both available on Livewire.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Circular Economy for Automotive Shredder Residue

Vehicle production has grown substantially worldwide, and subsequently, End-of-Life (EoL) vehicles entering retirement will grow as well. For example, China, the largest passenger car market worldwide, is expected to have 26.3 million passenger vehicles retiring by 2030. Most vehicles are shredded at EoL to recover metals for the robust metal recycling industry, leaving behind a slew of unwanted materials called automotive shredder residue (ASR) on the order of millions of tonnes every year. Additionally, the average weight of vehicles has gone up to 2600 lbs (1180 Kg) for a small passenger internal combustion engine (ICE) vehicles, 4000 lbs (1814 Kg) for large ICE vehicles, and the electric vehicle (EV) versions are substantially heavier at 1000 lbs (454 Kg) or more compared to combustion engine counterparts. While the increase in weight in EVs is increasing primarily due to the batteries needed to power the car, the materials being substituted into either type of vehicle to reduce weight are polymers and composites.

33 ADVANCED PROPULSION SYSTEMS

Laser Measurements and Modeling of Shock Tunnel Freestream Velocity and Multispecies Thermal Nonequilibrium

Coherent anti-Stokes Raman scattering (CARS) and nitric oxide molecular tagging velocimetry (NO-MTV) were used to characterize the freestream in Sandia’s Hypersonic Shock Tunnel (HST) using a burst-mode laser operated at 100 kHz. Experiments were performed at nominal freestream velocities of 3 and 4 km/s using both air and N 2 test gas. The CARS diagnostic provides nonequilibrium characterization of the flow by measuring vibrational and rotational temperatures of N 2 and O 2 , which are compared to NO temperatures from separate laser absorption experiments. Simultaneous, collinear freestream velocities were measured using NO MTV along with pitot pressure measurements. Furthermore, this extensive freestream dataset is compared to nonequilibrium CFD that is capable of modeling species-specific, vibrational temperatures throughout the nozzle expansion. Significant nonequilibrium between vibrational and rotational temperatures was measured at each flow condition. N 2 exhibits the most nonequilibrium, followed by O 2 and NO. The CFD model captures this trend, although it consistently overpredicts N 2 and O 2 vibrational temperatures. At 3 km/s, the modeled NO nonequilibrium is underpredicted, whereas it is overpredicted at 4 km/s. Good agreement is seen between CFD and the velocity and rotational temperature measurements. Experiments with water added to the test gas yielded no discernable difference in vibrational relaxation.

Aerodynamics

The Impact of Demographic Lifecycle States on Time to Vehicle Purchase: Insights from the Panel Study of Income Dynamics

This study examines the impact of demographic lifecycle stages on the timing of vehicle purchases, using data from the Panel Study of Income Dynamics from 1999 to 2021. Survival analysis was employed to model the duration until households purchase vehicles, incorporating key lifecycle variables such as age, employment status, marital status, childbirth, home ownership, and the presence of school-going children. The life table results indicate that early adulthood (ages 20–35) is the prime period for vehicle acquisition, with significant peaks around ages 25 to 30. Additionally, the instantaneous hazard of purchasing a vehicle is highest in the late 40s and early 50s. According to the Cox proportional hazards model, employment, marital status, and home ownership significantly increase the likelihood of purchasing a vehicle, while living in multi-unit dwellings decreases it. Interaction effects reveal that married individuals with employed spouses are substantially more likely to purchase vehicles. In conclusion, this study serves as a steppingstone toward integrating demographic lifecycle analysis into car ownership modeling that better reflects real-world scenarios and increases the accuracy of policy and strategic planning.

Car ownership

ReachNow EV Driving Data From Seattle, WA, Portland, OR, and New York, NY

ReachNow provided Idaho National Laboratory (INL) with a dataset describing approximately 49,000 trips taken by customers and employees in approximately 100 BMW i3 EVs operating in ReachNow's free-floating car-sharing fleets in Seattle, WA, Portland, OR, and New York, NY between May 2016 and February 2017. Data fields include vehicle rental period start and end timestamps, the location where vehicles were parked at the start and end of rental periods, and distance driven during rental periods. A field categorizing the user during each rental period is also included. This field makes it possible to identify when vehicles were rented by customers and when vehicles were driven by fleet management team employees to reposition, charge, or service the vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Extracting Vehicle Trajectories from Partially Overlapping Roadside Radar

This work presents a methodology for extracting vehicle trajectories from six partially-overlapping roadside radars through a signalized corridor. The methodology incorporates radar calibration, transformation to the Frenet space, Kalman filtering, short-term prediction, lane-classification, trajectory association, and a covariance intersection-based approach to track fusion. The resulting dataset contains 79,000 fused radar trajectories over a 26-h period, capturing diverse driving scenarios including signalized intersections, merging behavior, and a wide range of speeds. Compared to popular trajectory datasets such as NGSIM and highD, this dataset offers extended temporal coverage, a large number of vehicles, and varied driving conditions. The filtered leader–follower pairs from the dataset provide a substantial number of trajectories suitable for car-following model calibration. The framework and dataset presented in this work has the potential to be leveraged broadly in the study of advanced traffic management systems, autonomous vehicle decision-making, and traffic research.

33 ADVANCED PROPULSION SYSTEMS

Transportation in net-zero emissions futures: Insights from the EMF-37 model intercomparison study

Transportation is currently the largest source of U.S. anthropogenic CO 2 emissions, at about a third of the total. Achieving net-zero emissions by mid-century will require substantial reductions in transportation emissions across passenger and freight travel. Here we leverage a model intercomparison study to explore the role of transportation in scenarios achieving net-zero economy-wide CO 2 emissions by 2050. We find the transport sector is poised to play the most significant role in reducing demand-side emissions, mostly driven by technology substitution, as modeling results suggest a limited role for mode shifting and for reduced use of personal car travel in the U.S. Among various technology solutions, models show agreement that passenger on-road vehicles will largely transition to electric vehicles (EVs), while solutions to decarbonize heavier travel modes are more diverse and include greater use of liquid biofuels and hydrogen. Research should continue to investigate the evolution of on-road electrification, the role of biofuels and hydrogen across heavier travel modes, and the role of mode shifting and travel behavior change to support personal transportation decarbonization at national and regional scales to temper the rapid growth in clean fuel and electricity demand.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Citizen science coupled with machine learning to quantify green-blue infrastructure cooling potential in Maricopa County, Arizona

Here, this study investigates the spatiotemporal cooling performance of green and blue infrastructure (GBI) in the Dobson Ranch urban neighborhood in Phoenix, Arizona. We leveraged citizen science near-surface (2 m) air temperature (Tair) measurements to train a highly accurate Tair predicting LightGBM machine learning model (R 2 : 0.986, MAE: 0.251 °C, RMSE: 0.585 °C). On June 16, 2024, the park area exhibited approximately 1 °C cooling effect (relative to the neighborhood mean) during both day and night. In contrast, the nearby artificial lake exhibited a stronger cooling effect of 2.4 °C during the day but a slight warming of 0.3 °C at night. At 00:00, locations 50 m downwind of the park were 0.3 °C warmer than the park, while locations 50 m upwind were 0.8 °C warmer. At 11:00, we observed that the downwind area is 0.8 °C cooler and the upwind area is 0.6 °C warmer—at the same 50 m distances relative to the park. We also observed 1 °C cooler and warmer effects respectively at the same 50 m downwind and upwind locations at 19:00 on June 17, 2024. Our data-driven analysis highlights potential limitations of car-traverse measurements, showing that failure to account for temporal variations during the traverse can lead to overestimation of Tair at night and underestimation during the day. Our analysis also showed only a weak correlation (coefficient: 0.48) between Landsat-derived land surface temperature (LST) and model predicted Tair at the time of the local Landsat overpass (∼11.00). This highlights the potential error of relying solely on LST for human thermal exposure analysis—particularly within the heterogenous built-environment.

54 ENVIRONMENTAL SCIENCES

E-scooter safety: How attitudinal factors influence risky behavior among shared e-scooter riders

In recent years, e-scooter usage for short-distance trips has grown rapidly. This surge in e-scooter use, combined with the high exposure of e-scooter riders to accident risk, has sparked concerns regarding e-scooter safety. Despite some studies focusing on e-scooter safety, little is known about how attitudinal factors lead e-scooter riders to engage in risky riding behaviors. In this paper, we developed a survey-based empirical model to identify the attitudinal factors influencing engagement in risky behaviors among e-scooter users. We used survey data collected from 420 shared e-scooter users in Chicago in 2022. The survey showed that 47.7% of respondents had experienced at least one collision or fall-off while riding e-scooters. We employed the Partial Least Squares Structural Equation Model (PLS-SEM) to examine the relationships between latent attitudinal factors and risky behavior engagement. Moreover, we conducted Permutation Multi-group Analysis (PMGA) to assess the moderating effect of socio-demographic factors within the estimated model. The findings suggest that riders’ unsafe riding attitude and riding confidence are the most influential factors shaping their risky behavior engagement. In addition, accident experience, infrastructure suitability, perceived enjoyment, traffic risk perception, and operational risk perception are among the other significant predictors. Among socio-demographic factors, gender, age, education, and car use frequency significantly influence riders’ engagement in risky behaviors. The results highlight the importance of infrastructure suitability and accident experience in analyzing e-scooter users’ riding behavior. The developed model advances our understanding of factors contributing to e-scooter riders’ risky behavior engagement. The findings offer valuable insights for policymakers and e-scooter vendors aiming to mitigate e-scooter users’ accident risk. Specifically, we recommend three safety countermeasures: (1) safety training programs to encourage a safer attitude, (2) practice-based initiatives to enhance riding confidence, and (3) infrastructure improvements, especially the expansion of bike lanes.

E-scooter

Bismuth-oxo Clusters for Next Generation Extreme Ultraviolet Light Photolithography

Photolithography is the primary technique used for the patterning of semiconducting materials for chip manufacturing; however, as requisite pattern dimensions and feature sizes continue to decrease, state-of-the-art lithographic methods now require the use of 13.5 nm extreme ultraviolet (EUV) light. The shift toward these higher energy wavelengths of light has resulted in a need for new single component materials, with high EUV absorption cross sections and high etch resistance. Herein, we report the exploration of Bi 9 O 7 (hfac) 13 as the first bismuth oxo cluster based EUV photoresist. It was determined this material has an exceptional EUV linear absorption coefficient (24 μm –1 ), nearly an order of magnitude larger than commercially available chemically amplified resists (CARs) (∼5 μm –1 ). Additionally, the resist was determined to be highly sensitive to EUV exposure and displayed a dose-to-gel of 10 mJ/cm 2 , undergoing ligand decomposition during exposure and cross-linking during the postexposure bake, which was supported by FTIR and residual gas analysis. In conclusion, this class of bismuth-oxo cluster resists can lead to the development of more efficient, effective and safe EUV resist materials required for next-generation photolithography.

MacKenzie, Harvey K. [Univ. of Victoria, BC (Canad

The CP-PAW Code Package for First-Principles Calculations from a User’s Perspective

CP-PAW is a combined electronic structure and ab initio molecular dynamics code to perform mixed quantum and classical simulations of atomistic condensed phase systems, such as solids, liquids, and molecular systems. As the name suggests, the CP-PAW code unifies the all-electron projector augmented-wave (PAW) method with the Car–Parrinello (CP) approach to determine not only the electronic and nuclear ground states of condensed matter but also to study their properties and dynamics. In addition to briefly outlining the underlying theory, the focus will be on the unique aspects of CP-PAW and how to correctly employ them as a user. How to install CP-PAW using the new build system will also be briefly mentioned.

Blöchl, Peter E [Institute for Theoretical Physic