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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 55 records · Page 3

Degradation and Accelerated Recovery of Surface Passivation in n+ Poly-Si/SiOx Passivating Contacts for TOPCon Solar Cells

We studied the surface degradation and recovery of fired poly-Si/SiOx passivating contacts during subsequent dark and illuminated annealing. We report on an industrially-viable path for accelerated recovery of surface passivation. The degradation is influenced by the type of doping in the poly-Si. Phosphorus doped n+ poly-Si/SiOx contacts show degradation followed by recovery, undoped poly-Si/SiOx contacts only show recovery during annealing. Boron doped p+ poly-Si/SiOx contacts show neither degradation nor improvement with annealing. Both degradation and recovery are thermally-activated processes and are completely reversible and cyclic in nature. The activation energy of degradation and recovery in dark for n+ poly-Si/SiOx contacts are 1.27 and 1.33 eV respectively. Dark annealing at elevated temperatures is effective for complete recovery but takes a long time (~30 min at 350 degrees C) due to higher activation energies. Annealing under 7.5 Suns of illumination lowers the activation energy for degradation and recovery to 0.88 and 0.90 eV, respectively. Using this data, we have developed an industrially viable post-firing treatment for accelerated recovery of TOPCon cells by annealing them at elevated temperatures and under intense illumination for a few minutes.

14 SOLAR ENERGY↗

NeuDiff Agent: a governed AI workflow for single-crystal neutron crystallography

Large-scale facilities increasingly face analysis and reporting latency as a limiting step in scientific throughput, particularly for structural studies that require iterative reduction, integration, refinement and validation. To improve the time to result and analysis efficiency, NeuDiff Agent is introduced as a governed, tool-using AI workflow for TOPAZ at the Spallation Neutron Source. NeuDiff Agent takes instrument data through reduction, integration, refinement and validation to a validated crystal structure and a publication-ready CIF. NeuDiff Agent coordinates established crystallographic tools under explicit governance by restricting actions to allowlisted tools, enforcing fail-closed verification gates at key workflow boundaries, and capturing complete provenance for inspection, auditing and controlled replay. The present benchmark is limited to structural crystallography for periodic structures; magnetic structure analysis and incommensurate or superspace refinement are outside the scope of the current workflow. Performance is assessed using a fixed prompt protocol and repeated end-to-end runs with two large language model backends, with user and machine time partitioned and intervention burden and recovery behaviors quantified under gating. In a reference-case benchmark, NeuDiff Agent reduces wall time from 435 min (manual) to 86.5 ± 4.7 to 94.4 ± 3.5 min (4.6–5.0× faster) while producing a validated CIF with no checkCIF level A or B alerts. These results establish a practical route to deploy agentic AI in facility crystallography while preserving traceability and publication-facing validation requirements.

Xiao, Zhongcan [ORNL] (ORCID:0000000220761961)↗

Critical slowing of the spin and charge density wave order in thin film Cr following photoexcitation

We report on the evolution of the charge density wave (CDW) and spin density wave (SDW) orders of a chromium film following photoexcitation with an ultrafast optical laser pulse. The CDW is measured by ultrafast time-resolved x-ray diffraction of the CDW satellite that tracks the suppression and recovery of the CDW following photoexcitation. We find that as the temperature of the film approaches a discontinuous phase transition in the CDW and SDW orders, the time scales of recovery increase exponentially from the expected thermal time scales. We extend a Landau model for SDW systems to account for this critical slowing with the appropriate boundary conditions imposed by the geometry of the thin film system. This model allows us to assess the energy barrier between the available CDW/SDW states with different spatial periodicities.

36 MATERIALS SCIENCE↗

The Impact of Naphthenic Acids on Dynamic Fluid–Fluid Interactions: Implication for Enhanced Oil Recovery

Previous coreflooding results and wettability analyses in our group show that injection of naphthenic-acid-enriched water can improve oil recovery over traditional waterflooding. This observation is still a subject of research efforts without a definitive explanation. Naphthenic acids (NA) have been reported to drive wettability alteration and increase the water–oil interface elasticity. These alterations depend on the NA carbon number and aqueous-phase salinity, among other conditions, as reported in the literature. Smart-water flooding (SWF) research often links recovery to the initial wettability condition, being higher for initially oil-wet rock. SWF refers to a technique in which the aqueous-phase ion composition or/and salinity are changed to maximize oil recovery. Given NAs’ complex solution behavior, selecting acid combinations that prompt oil recovery is a difficult objective. The aim of this research is to determine the effects of select naphthenic acids on the oil–water interfacial rheology and wettability alteration and how these interfacial effects are associated with oil recovery under spontaneous imbibition. NAs were selected based on their carbon number, molecular structure, and solubility in the saline solution used in this research. We aimed at exploring which NAs should be used to regulate interfacial properties so as to either increase oil recovery or accelerate production. Time-domain nuclear magnetic resonance, interfacial dilatational rheology, and liquid-bridge experiments, i.e., proxy of snap-off, were conducted. A baseline was established using results obtained with a previously tested sulfate-rich aqueous phase, shown to be effective in recovering oil. Results show that NA14 and N18 increase the water–oil interfacial viscoelasticity and induce interfacial healing but led to different recovery factors. N10, while effective at inducing water wetness in oil-wet rock, is ineffective at increasing the recovery factor. We concluded that wettability and oil–water interfacial rheology are not exclusive, and instead they can synergistically favor EOR benefits. Moreover, oil recovery benefits under spontaneous imbibition are shown to depend strongly on the initial wettability conditions.

Medina-Rodriguez, Bryan X. (ORCID:0000000262922831↗

Develop an efficient and cost-effective novel anaerobic digestion system producing high purity of methane from diverse waste biomass

This project focuses on developing an advanced, intensified anaerobic digestion system aimed at transforming the treatment and conversion of organic wastes into valuable products, specifically renewable natural gas. The motivation for this research stems from the limitations of conventional anaerobic digestion technologies, which often face challenges such as long retention times, high operational costs, and incomplete organic material degradation. The new technology called Intensified Versatile Anaerobic Digestion (IVAD), is developed to address these challenges by incorporating innovative reactors and processes that enhance the overall efficiency and output of anaerobic digestion. The significance of this project lies in its potential to revolutionize waste management practices and waste biomass utilization. The IVAD system integrates a hyperthermophilic anaerobic acidification reactor, a hydrothermal treatment (HTT) unit, and both thermophilic and mesophilic methanogenic reactors. This combination enables a higher rate of organic breakdown and energy recovery, resulting in faster processing times, reduced reactor sizes, and lower operational costs compared to traditional systems. Key data include an increase in methane productivity to 1.18 m 3 /m 3 /day, a significant improvement compared to the baseline technology’s 0.64 m 3 /m 3 /day. Additionally, the IVAD system achieves a 45% reduction in levelized cost of energy (LCOE), down to $\$$10.04/MMBTU, and an energy return on investment (EROI) of 3.19, representing an 87% increase over baseline levels. Technical and economic analyses highlight that the IVAD system significantly reduces hydraulic retention time (HRT) and solid retention time (SRT). The HRT for the HTT reactor can be reduced from 1 hour to 0.5 hours, while decoupling SRT from HRT in the anaerobic acidification reactor (AAR) allows for further reductions. These design optimizations lead to smaller reactor volumes, cutting down equipment and construction costs. Despite these advancements, energy consumption remains comparable to conventional methods due to a novel heat recovery strategy, enhancing overall process productivity. The system also achieves in-situ CO 2 removal and ammonia stripping features, resulting in biogas with a methane purity level of 75%, and produces high-quality nitrogen fertilizer as an additional by-product. Public benefits of the IVAD system are substantial, contributing to sustainable waste management and renewable energy production. By providing a scalable solution that can be adopted by dairy farms and similar agricultural operations, the IVAD system helps reduce waste, produce renewable natural gas (RNG) suitable for transportation fuel, and generate fertilizer, supporting a circular economy. This project plays a role in achieving broader environmental objectives by mitigating greenhouse gas emissions and promoting energy independence. Additionally, it offers a pathway for farmers to lower operational costs while adopting practices that are both environmentally sustainable and economically advantageous.

03 NATURAL GAS↗

Anomalous lattice expansion of bcc Ta in helium-loaded diamond anvil cells

Anomalous lattice expansion of bcc Ta is observed in helium-loaded diamond anvil cell (DAC) experiments near 6 GPa and above 400 K, while co-loaded W, Mo, and Au exhibit normal thermal expansion. The Ta volume expansion increases with temperature, reaching ~14% near 650 K before plateauing, and is largely retained after recovery to ambient conditions. Time-resolved measurements at 500 K reveal progressive expansion over several hours, consistent with gradual, thermally activated He incorporation. The largely retained expansion during subsequent cooling and holding at 400 K indicates that the incorporated He is predominantly kinetically trapped. The data reveal two distinct regimes: below ~550 K, modest and spatially uniform expansion consistent with interstitial He trapping at isolated, randomly distributed vacancies; above ~550 K, He-vacancy cluster growth producing dramatically larger expansion, peak broadening, and a core–shell microstructure revealed by micron-resolution X-ray diffraction mapping. These results demonstrate that He is not always a passive pressure medium in DAC experiments and reveal a previously unrecognized regime of He-mediated lattice modification in Ta, complementing conventional ion-implantation studies relevant to nuclear and fusion structural materials.

Diamond anvil cell↗

Recent Advances in Cladding Material Extraction from Fuels in Nuclear Fuel Cycles

An improved recycling and recovery process for the cladding material from spent nuclear fuels is very important toward confirming nuclear energy to support ongoing sustainable development of nuclear management by reducing waste and conserving resources. Nuclear spent fuel cladding materials such as zirconium alloys have economic values and can be recovered, and their recovery eliminates problems in waste disposal and conserves valuable resources. Over 110 published reports and journal articles are reviewed and summarized herein, with a main focus on documenting recovery techniques used to recover cladding materials from spent nuclear fuel and recent developments. Several recovery techniques which are used at present times, such as mechanical separation, chemical dissolution, and hydrometallurgical processes have been covered with examples and discussions. Difficulties within the recovery process are also discussed, and most probable areas for future research in improving efficiency and sustainability of recovering cladding material are identified and discussed at the end. Here, this review could be an important document to the field of spent nuclear fuel reprocessing, recovering valuables and thereby offering guidance on how to effectively manage, safely handle, and reduce nuclear waste. In addition to reducing the volume and radiotoxicity of high-level waste, this review also highlights the potential economic benefit of recovering zirconium from spent fuel cladding by relating typical zirconium metal prices to the mass of cladding per tonne of spent fuel, illustrating that the recoverable material value is non-negligible compared with back-end fuel-cycle costs.

Mondal, Kunal [Oak Ridge National Laboratory (ORNL↗

Thermal stress in degraded forests in the Brazilian Amazon Arc of Deforestation

Understanding thermal stress in tropical forests has taken on new urgency in light of accelerating climate change and expansion of deforestation and forest degradation. Degraded tropical forests in particular may be approaching critical temperature thresholds even more rapidly than intact forests, with implications for tree survival and ecosystem recovery. We investigate thermal stress in degraded tropical forests within the Brazilian Amazon Arc of Deforestation. Using land surface temperature data from the ECOsystem Spaceborne Thermal Radiometer Experiment on the international Space Station (ECOSTRESS), we compared canopy temperatures of intact, selectively logged, and burned forests in Feliz Natal, Mato Grosso, Brazil. Upper canopy temperatures in previously burned forests were 4.1% higher (mean = 36.5 °C) and 50.9% more variable compared to intact and logged forests, which showed remarkably similar temperature distributions (means of 34.9 °C and 35.1 °C, respectively). Modeled leaf temperature distributions based on canopy temperature measurements from one of the warmest days in a 2 year dry season record indicated that 87% of leaves in the warmest burned forest patches exceeded the temperature threshold where respiration surpasses photosynthesis, compared to approximately 72%–74% in intact and logged forests, respectively, in the same time period. After controlling for environmental factors, burned forests were predicted to be 2.6 °C warmer on average [1.39 °C–3.96 °C, 95% credible interval] than intact forests across a 5–40 m canopy height range. Burned forests showed modest thermal recovery over time, with temperatures decreasing by approximately 1.2 °C over a 30 year recovery period. In contrast, logged forests showed minimal thermal differences from intact forests (−0.353 on average, [−1.125–0.274, 95% credible interval]) and negligible change (0.15 °C) over the same timeframe. While the absolute probabilities of exceeding damaging thermal thresholds remain low across all forest types under current climate conditions, the probability of leaves exceeding temperatures that cause permanent leaf damage was ten times higher in burned forests, with implications for the future of burned forest regeneration in water-limited regions of the Amazon basin. In particular, the combination of higher mean temperatures, greater temperature variability, and more frequent exposure to damaging thermal thresholds implies that burned tropical forests will experience substantially higher mortality rates and slower biomass recovery compared to intact and selectively logged forests, especially in water-limited regions where trees cannot rely on evaporative cooling to moderate canopy temperatures.

Brazilian Amazon Arc of Deforestation↗

Co-Firing Switchgrass and Waste Coal in A Power Plant: A Techno-Economic and Life Cycle Evaluation for The Ohio River Valley (SWITCH) (Final Technical Report for Ohio State/FE0032204)

Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.

01 COAL, LIGNITE, AND PEAT↗

Spatio-Kinetic Electronic Heterogeneity in MoS 2 Revealed by Ultrafast Electron Microscopy: Implications for Optoelectronics

There is broad interest in layered, two-dimensional (2D) semiconductors owing to their high optical absorption and ability to heterogeneously integrate with various substrates. In such layered semiconductors, mesoscopic imperfections, such as surface step edges, may affect charge carrier kinetics and device performance, but studying their effects on carrier transport with sufficient spatial and temporal resolution is a challenge. Using scanning ultrafast electron microscopy, we image the near-surface charge carrier kinetics with μm/ps spatiotemporal resolution in single-crystal MoS 2 samples with surface steps tens of nanometers in height. We find an approximately 3-fold increase in surface trap density near such surface steps compared to the uniform, flat surface regions. Despite the difference in trap state density, filling of the traps occurs over the same time scale (∼100 ps), but carrier recovery is much slower near the step compared to the uniform regions of the material. Furthermore, these results provide an approach to measure ultrafast dynamics and determine the required uniformity of layered materials depending on the speed limit constraints for specific applications.

SEM↗

Quantification of the Crack Evolution Process by Extracting Relevant Signal Components from Wave Propagation and Diffusive Transport Front Measurements

Wave propagation and diffusive transport phenomena in a geological rock sample undergoing crack evolution process are expected to interact with the mechanical discontinuities in the medium. The measurements of the signals associated with these phenomena can be used to assess and monitor the crack-driven micromechanical alterations in the rock. Different wave/diffusion phenomena, such as sonic propagation, pressure diffusion, and acoustic emission (AE), are sensitive to different elements of the mechanical discontinuities generated during the evolution of the crack clusters from initiation to coalescence. Sonic propagation, AE, and pressure diffusion monitoring have the potential to map the crack evolution because the transmitter-receiver arrays can be designed, arranged and tuned to (1) achieve maximum recovery of the scattered waveforms and travel times, (2) capture the later arrivals and multiple reflections, and (3) illuminate large rock volume. However, the structural/topological complexities of the mechanical discontinuities, complex distribution of the stress fields, complex mechanical alterations in media, and fluid redistribution in the crack system pose serious challenges for the detection and modeling of the crack evolution process (from here on, we will use the term ‘crack evolution process’ to mean that the crack evolution occurred under shallow crustal conditions). For purposes of accurately accounting such complexities and heterogeneities in the absence of reliable physical laws, simulation methods, and signal processing techniques, my early-career research proposal will develop and apply novel data-driven machine learning methods to: (1) extract signal components relevant to the various phases of crack evolution and (2) generate a 2D visual map of the crack evolution process.

58 GEOSCIENCES↗

Lessons Learned: Summary of Insights From the HERO WEC and Waves to Water Deployments Between 2022 and 2024

In 2020, a team from the National Renewable Energy Laboratory (NREL) partnered with the East Carolina University Coastal Studies Institute to develop a small, modular, wave-powered point absorber desalination prototype. That prototype, known as the hydraulic and electric reverse osmosis wave energy converter (HERO WEC), was intended to de-risk the installation activities planned for the Waves to Water Prize sponsored by the Water Power Technologies Office. The NREL team was given approximately 18 months to design, build, bench test, and deploy the HERO WEC prototype. Since the initial HERO WEC development, it has been used for two in-lab test programs and three ocean deployments. The first in-lab test program focused on ensuring that the overall operation of the device occurred as expected and on validating the operation of safety systems such as pressure relief valves or electrical breakers for load mitigation. The second in-lab test program was the first time the NREL team leveraged NREL’s large-amplitude motion platform to characterize the performance of the HERO WEC. Of the three in-water deployments, the first deployment was effectively an installation and recovery practice with no meaningful wave activity during the time that it was installed. The second deployment was a 2-week effort that enabled both the electric and hydraulic configurations of the device to be in the water for approximately 5 days each. This deployment was also the first time that the team had the opportunity to perform a drivetrain swap on the Coastal Studies Institute research vessel. The third deployment had to be split into two separate installations due to minor damage incurred from the WEC spinning during the initial installation. This report summarizes the deployments, the challenges encountered with each deployment, and the lessons learned for future work.

16 TIDAL AND WAVE POWER↗

A Deep Learning Approach for In-Network Synchrophasor Missing Data Recovery Using Programmable Network Switches

Phasor measurement unit (PMU) networks deliver accurate and timely measurements, which is essential for managing today’s electric power systems. To ensure data quality and enhance the cyber-resilience of PMU networks against malicious attacks and data errors, this study presents an online PMU missing data recovery scheme by leveraging P4 programmable switches. The data plane incorporates a customized PMU protocol parser that abstracts the necessary payload data for recovery. Recovery processes are executed in the control plane using a pre-trained machine learning model. Both traditional and advanced ML models, such as transformer and TimeGPT, are explicitly employed for data prediction. This approach ensures rapid and precise data recovery. Performance evaluations focus on recovery speed and accuracy, using a real dataset from a campus microgrid. With 20% missing PMU data, the mean absolute percentage error for voltage magnitude is 0.0384%, and the phase angle error discrepancy is approximately 0.4064%.

Phasor Measurement Unit, Machine Learning, Program↗

Comparison of microprecipitation methods for polonium source preparation for alpha spectrometry

Detection of radioactive isotopes of polonium is important for understanding natural processes, management and assessment of radioactive waste, and nuclear forensics applications. Further, the most common methods for preparation of polonium samples for alpha spectrometry are electrodeposition and spontaneous deposition which are time consuming. Here, we compare three approaches utilizing rapid microprecipitation from bismuth phosphate, copper sulfide, or tellurium alongside traditional spontaneous deposition methods. From these experiments, results show that copper sulfide microprecipitation recoveries are similar to spontaneous deposition on silver and less time consuming with an approximate five-fold decrease in preparation time, including in the presence of complex matrices like seawater.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Asymptotic-preserving gyrokinetic implicit particle-orbit integrator for arbitrary electromagnetic fields

We extend the asymptotic preserving and energy conserving time integrator for charged-particle motion developed in Ricketson and Chacón (2020) to include finite Larmor-radius (FLR) effects in the presence of electric-field length-scales comparable to the particle gyro-radius (the gyro-kinetic limit). We introduce two modifications to the earlier scheme. The first is the explicit gyro-averaging of the electric field at the half time-step, along with an analogous modification to the current deposition, which we show preserves total energy conservation in implicit PIC schemes. The number of gyrophase samples is chosen adaptively, ensuring proper averaging for large timesteps and the recovery of full-orbit dynamics in the small time-step limit. The second modification is an alternating large and small time-step strategy that ensures the particle trajectory samples gyrophases evenly. We show that this strategy relaxes the time-step restrictions on the scheme, allowing even larger speed-ups than previously achievable. We demonstrate the new method with several single-particle motion tests in a variety of electromagnetic field configurations featuring gyro-scale variation in the electric field. Finally, the results demonstrate the advertised ability to capture FLR effects accurately even when significantly stepping over the gyration time-scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Small-angle scattering interferometry with neutron orbital angular momentum states

Methods to prepare and characterize neutron helical waves carrying orbital angular momentum (OAM) were recently demonstrated at small-angle neutron scattering (SANS) facilities. These methods enable access to the neutron orbital degree of freedom which provides new avenues of exploration in fundamental science experiments as well as in material characterization applications. However, it remains a challenge to recover phase profiles from SANS measurements. We introduce and demonstrate a novel neutron interferometry technique for extracting phase information that is typically lost in SANS measurements. An array of reference beams, with complementary structured phase profiles, are put into a coherent superposition with the array of object beams, thereby manifesting the phase information in the far-field intensity profile. We demonstrate this by resolving petal-structure signatures of helical wave interference for the first time: an implementation of the long-sought recovery of phase information from small-angle scattering measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Simulating Continuum-based Redshift Measurement in the Roman’s High Latitude Spectroscopic Survey

We investigate the capability of the Nancy Grace Roman Space Telescope’s (Roman) Wide-Field Instrument G150 slitless grism to detect red, quiescent galaxies based on the current reference survey. We simulate dispersed images for Roman reference High-Latitude Spectroscopic Survey (HLSS) and analyze two-dimensional spectroscopic data using the grism Redshift and Line Analysis (Grizli) software. This study focus on assessing Roman grism’s capability for continuum-level redshift measurement for a redshift range of 0.5 ≤ z ≤ 2.5. The redshift recovery is assessed by setting three requirements of: σ z = $\frac{|z–z_{true}|}{1+z}$ ≤ 0.01, signal-to-noise ratio≥ 5 and the presence of a single dominant peak in redshift likelihood function. We find that, for quiescent galaxies, the reference HLSS can reach a redshift recovery completeness of ≥50% for F158 magnitude brighter than 20.2 mag. We also explore how different survey parameters, such as exposure time and the number of exposures, influence the accuracy and completeness of redshift recovery, providing insights that could optimize future survey strategies and enhance the scientific yield of the Roman in cosmological research.

Astronomical simulations↗

A Software/Hardware Framework for Efficient and Safe Emergency Response in Post-Crash Scenarios of Battery Electric Vehicles

The adoption rate of battery electric vehicles (EVs) is rapidly increasing. Electric vehicles differ significantly from conventional internal combustion engine vehicles and vary widely across different manufacturers. Emergency responders (ERs) and recovery personnel may have less experience with EVs and lack timely access to critical information such as the extent of the stranded energy present, high-voltage safety hazards, and post-crash handling procedures in a user-friendly manner. This paper presents a software/hardware interactive tool named Electric Vehicle Information for Incident Response Solutions (EVIRS) to aid in the quick access to emergency response and recovery information. The current prototype of EVIRS identifies EVs using the VIN or Make, Model, and Year, and offers several useful features for ERs and recovery personnel. These features include integration and easy access to emergency response procedures tailored to an identified EV, vehicle structural schematics, the quick identification of battery pack specifications, and more. For EVs that are not severely damaged, EVIRS can perform calculations to estimate stranded energy in the EV’s battery and discharge time for various power loads using either EV dashboard information or operational data accessed through the CAN interface. Knowledge of this information may be helpful in the post-crash handling, management, and storage of an EV. The functionality and accuracy of EVIRS were demonstrated through laboratory tests using a 2021 Ford Mach-E and associated data acquisition system. The results indicated that when the remaining driving range was used as an input, EVIRS was able to estimate the pack voltage with an error of less than 3 V. Conversely, when pack voltage was used as an input, the estimated state of charge (SOC) error was less than 5% within the range of 30–90% SOC. Additionally, other features, such as retrieving emergency response guides for identified EVs and accessing lessons learned from archived incidents, have been successfully demonstrated through EVIRS for quick access. EVIRS can be a valuable tool for emergency responders and recovery personnel, both in action and during offline training, by providing crucial information related to assessing EV/battery safety risks, appropriate handling, de-energizing, transport, and storage in an integrated and user-friendly manner.

25 ENERGY STORAGE↗