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At least 127 records · Page 7

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DOE OSTI2025

Explaining Nonmerger Gamma-Ray Bursts and Broad-lined Supernovae with Close Binary Progenitors with Black Hole Central Engines

For over 25 yr, the origin of long-duration gamma-ray bursts (lGRBs) has been linked to the collapse of rotating massive stars. However, we have yet to pinpoint the stellar progenitor powering these transients. Moreover, the dominant engine powering the explosions remains open to debate. Observations of both lGRBs, supernovae associated with these GRBs, such as broad-line (BL) stripped-envelope (type Ic) supernovae (hereafter, Ic-BL), supernovae (SNe), and perhaps superluminous SNe, fast blue optical transients, and fast x-ray transients, may provide clues to both engines and progenitors. In this paper, we conduct a detailed study of the tight-binary formation scenario for lGRBs, comparing this scenario to other leading progenitor models. Combining this progenitor scenario with different lGRB engines, we can compare to existing data and make predictions for future observational tests. We find that the combination of the tight-binary progenitor scenario with the black hole accretion disk engine can explain lGRBs, low-luminosity GRBs, ultra-long GRBs, and Ic-BL. We discuss the various progenitor properties required for these different subclasses and note such systems would be future gravitational-wave merger sources. We show that the current literature on other progenitor-engine scenarios cannot explain all of these transient classes with a single origin, motivating additional work. We find that the tight-binary progenitor with a magnetar engine is excluded by existing observations. The observations can be used to constrain the properties of stellar evolution, the nature of the GRB, and the associated SN engines in lGRBs and Ic-BL. We discuss the future observations needed to constrain our understanding of these rare, but powerful, explosions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Inferring the Redshift of More than 150 GRBs with a Machine-learning Ensemble Model

Gamma-ray bursts (GRBs), due to their high luminosities, are detected up to a redshift of 10, and thus have the potential to be vital cosmological probes of early processes in the Universe. Fulfilling this potential requires a large sample of GRBs with known redshifts, but due to observational limitations, only 11% have known redshifts (z). There have been numerous attempts to estimate redshifts via correlation studies, most of which have led to inaccurate predictions. To overcome this, we estimated GRB redshift via an ensemble-supervised machine-learning (ML) model that uses X-ray afterglows of long-duration GRBs observed by the Neil Gehrels Swift Observatory. The estimated redshifts are strongly correlated (a Pearson coefficient of 0.93) and have an rms error, namely, the square root of the average squared error $\langle$Δz 2 $\rangle$, of 0.46 with the observed redshifts showing the reliability of this method. The addition of GRB afterglow parameters improves the predictions considerably by 63% compared to previous results in peer-reviewed literature. Finally, we use our ML model to infer the redshifts of 154 GRBs, which increase the known redshifts of long GRBs with plateaus by 94%, a significant milestone for enhancing GRB population studies that require large samples with redshift.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Multi-seasonal measurements of the ground-level atmospheric ice-nucleating particle abundance on the North Slope of Alaska

Atmospheric ice-nucleating particles (INPs) are an important subset of aerosol particles that are responsible for the heterogeneous formation of ice crystals. INPs modulate the arctic cloud phase (liquid vs. ice), resulting in implications for radiative feedbacks. The number of arctic INP studies investigating specific INP episodes or sources increased recently. However, existing studies are based on short-duration field data, and long-term datasets are lacking. Continuous, long-term measurements are key to determining the abundance and variability of ambient arctic INPs and constraining aerosol–cloud interactions, e.g., to verify and/or improve simulations of mixed-phase clouds. Here, we present a new long-duration INP dataset from the Arctic: 2 years of predominantly immersion-mode INP concentrations (n INP ) measured continuously at the National Oceanic and Atmospheric Administration's Barrow Atmospheric Baseline Observatory (BRW) on the North Slope of Alaska. A portable ice nucleation experiment chamber (PINE-03), which simulates adiabatic expansion cooling, was used to directly measure the ground-level INP abundance with an approximately 12 min time resolution from October 2021 to December 2023. We document PINE-03 n INP measurements as well as estimated ice nucleation active surface site density (n s ) over a wide range of heterogeneous freezing temperatures from −16 to −31 °C from which we introduce new season-specific parameterizations suitable for modeling mixed-phase clouds. Collocated aerosol and meteorological data were analyzed to assess the correlation between ambient n INP , air mass origin region, and meteorological variability. Our findings suggest (1) very high freezing efficiency of INPs across the measured temperatures (n s ≈ 2×10 8 –10 10 m −2 for −16 to −31 °C), which is a factor of 10–1000 times greater efficiency as compared to that found in the previous mid-latitude INP measurements in fall using the same instrument; (2) surprisingly high n INP (≥ 1 L −1 at −25 °C) for the examined temperatures throughout the year that were not measured by PINE-03 at other sites; and (3) high n INP in spring, possibly related to arctic haze episodes. Relatively low concentrations of aerosol surface area and contrasting high-INP concentrations at BRW relative to mid-latitude sites are the possible reasons for the observed high freezing efficiency.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Seasonal Performance Characterization of a Gen3 Particle-Based Concentrating Solar Plant With a Spatially Resolved Transient Thermal Storage Model

Particle-based Gen3 Concentrating Solar Power (CSP) can be paired with high-temperature power cycles (>700 °C) and can have built-in long duration (≥10 hours) thermal energy storage if the working particles are stored properly in thermal energy storage bins. Although high-temperature and long-duration thermal energy storage can mitigate daily intermittencies in solar irradiation, seasonal variability in local meteorological conditions can still have a significant impact on the overall performance of CSP systems. Aside from daily cloud coverage affecting incident solar radiation, wind speed and ambient temperature are also significant variables regarding system heat attenuation, component efficiency, and overall solar conversion efficiency. In this work, we present simulation results for a Gen3 CSP prototype system in operation over four weeks throughout the year in Albuquerque, NM. The meteorological conditions are taken directly from the TMY3 data at the Albuquerque International Sunport, where the hourly Direct Normal Irradiation (DNI), wind speed, and ambient temperature are of particular interest. An investigation of the sensitivity of individual components like storage and ducting to the local meteorological conditions is provided and extended to the overall performance of the CSP system. The results from this study show that the particle inlet temperature at the particle-to-sCO2 heat exchanger can change as fast as 30 °C/min under standard operation in a passive mode.

Plewe, Kaden (ORCID:0000000286826879)↗

DOE OSTI2026

Value of Geothermal Energy Storage for Supply-Side and Demand-Side Applications

This report presents the results of a study examining the value potential for geothermal energy storage (GES), a long-duration energy storage resource that stores thermal and/or geomechanical energy in the subsurface. GES could benefit the overall U.S. power system by temporally shifting electricity generation (supply-side) or meeting building heating and cooling load (demand-side). This report analyzes supply-side and demand-side opportunities independently because of differences in applications and models. Currently there is significant uncertainty about the development costs for GES, with only a limited number of demonstration plants for electric energy storage and building heating and cooling storage developments. In this report, we estimate the value of supply-side and demand-side GES to the bulk power system in the contiguous United States. Because of the significant uncertainty about GES development costs, this analysis does not consider GES deployment costs but instead focuses on the value of GES to the U.S. electricity system. The estimated values of GES provide reference points for economically competitive commercial cost targets. Supply-side GES is modeled as part of an enhanced geothermal system (EGS) generation plant in NREL's Regional Energy Deployment System (ReEDS) capacity expansion model (Ho et al. 2021). In contrast to conventional geothermal plants, which generate constant power, EGS plants have unique features that may allow for in-reservoir energy storage for flexible generation. Demand-side GES for heating and cooling, including seasonal hot and cold storage and short-duration heat pump storage, is incorporated into a price-taker model using Cambium electricity marginal cost projections. To establish an upper bound for the value of GES, analysis focused on favorable scenarios for storage with high generation from zero marginal cost, variable renewable energy resources. High penetrations of variable renewable energy generation can increase hourly electricity price variability, which increases the value of temporal energy arbitrage for storage technologies like GES.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

Equivalence Ratio Scans in a Rotating Detonation Engine

Published data for run times exceeding a few seconds in rotating detonation engines (RDEs) is rare, but long duration tests are necessary to understand both transient and persistent phenomena in RDE operation. Previous work has noted different detonation wave modes at different equivalence ratios. In the current study, multiple long-duration runs with constant air flow rate and variable equivalence ratio are conducted in a hydrogen-fueled, water-cooled RDE. Analysis of the capillary tube averaged pressure (CTAP) data reveals a strong correlation with equivalence ratio as well as a small time dependency due to transient thermal processes. Ion probe measurements are used to analyze detonation wave frequencies and modes, both of which are strongly dependent on the equivalence ratio. Mode transitions are observed to occur consistently as the equivalence ratio is traversed between 0.55 and 0.60. These transitions are also found to be a function of the direction of changing equivalence ratio (ascending or descending) and time.

Boyette, Wesley R.↗

DOE OSTI2024

Equivalence Ratio Scans in a Rotating Detonation Engine

Boyette, Wesley R.↗

DOE OSTI2024

Energy Storage

This Energy Exchange 2024 session explores Energy Storage, from currently available to cutting edge systems, and explores benefits and shortcomings related to key mission goals of sustainment, resilience, and emissions reduction. Specifically, this session will explore advancements in long-duration energy storage, organic flow batteries, and rechargeable/non-rechargeable storage. Additionally, we will explore usage advantages (DoD, Commercial, Utility, Residential), system sustainment issues and challenges, and advantages/disadvantages in the integration into existing and legacy electrical systems. The Panel will have a mix of DoD, commercial, and lab/academic experts.

emissions↗

DOE OSTI2024

Unseen Winds: Harnessing High-Altitude Winds in the Southeast USA

This project aims to identify potential sites in the United States for further testing and development of airborne wind energy systems (AWES). Through industry questionnaires and interviews with AWES companies, the study assesses existing test sites' capabilities and gaps, leading to a three-tiered test site strategy: short-duration prototype demonstrations, long-duration technical assessments and power validations, and airspace interaction and deconfliction studies. Notably, the southeastern United States presents significant potential for AWES due to its lack of traditional wind turbines, which is attributed to low wind speeds at lower altitudes. However, wind conditions improve significantly at higher altitudes, making this region a promising candidate for AWES deployment. The project considers factors such as wind resources, infrastructure proximity, social acceptance, and environmental impacts to recommend sites that can support the unique needs of AWES manufacturers and facilitate their commercialization. Early findings suggest rural communities with low grid resiliency could benefit economically and technologically from hosting AWES test sites, especially with operator training centers and potential for long-term skilled employment in future disaster relief and other applications.

17 WIND ENERGY↗

DOE OSTI2024

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗

DOE OSTI2025

Assessing the Economic Value of Underground Thermal Storage for Hybrid Geothermal Power

Solutions are needed to address resource adequacy in the electric power system for highly decarbonized systems. The storage duration, the length of time a storage device can provide continuous output at its rated capacity, must be sufficient to receive full credit toward resource adequacy. Longer peaks and high fractions of variable renewable generation have increased the required duration to potentially seasonal durations. Underground Thermal Energy Storage (UTES) can be adapted to a hybrid storage power plant or heating and cooling applications to satisfy the need for long-duration storage. In this study, we use the Renewable Energy Deployment System (ReEDS) capacity expansion model to evaluate the increase in value for an enhanced geothermal system (EGS) resources by adding UTES. In modeled scenarios, using geothermal without storage as a baseline we compare the increase in economic value for plants with a range of storage characteristics. The added value of a hybrid storage plant changes depending on assumptions including the length of storage duration, efficiency, and ability to charge storage from the grid during periods of low energy prices. Relating proposed characteristics for geothermal UTES hybrids to the modeled economic value provides insight into economically viable costs for developing UTES as well as what combination of technology characteristics and future energy and policy assumptions drive significant value increases.

capacity expansion model↗

DOE OSTI2025

The Design of a Multiphase CO2 Turbine Test Facility

As the energy market continues to evolve with increased renewables, such as solar and wind energy, the need to balance energy demand with its availability has become increasingly more challenging. The country’s aggressive decarbonization goals in the upcoming decades will increase renewable energy market penetration, thus exacerbating the disparity between energy demand and renewable resource availability. Long-duration energy storage technologies, such as pumped thermal energy storage (PTES), are potential solutions to this challenge with high potential round-trip efficiency (RTE), no geological or geographical constraints, and low safety risks. The charge mode of a PTES system operates a heat pump cycle, converting input power to thermal energy in hot and cold reservoirs. Fundamentally, heat pumps are commonly used in daily life, but the operating conditions required by high RTE PTES systems are outside the design experience of these systems. The low-pressure side of the cycle for a supercritical CO2 (sCO2) PTES operates just above the vapor-dome and potentially drives the turbine to expand into the dome, resulting in multiphase operation in the rear stages of the turbine. This paper presents the design of the test facility for an advanced multiphase-tolerant sCO2 turbine for the heat pump of a PTES system. Heat rejection and pressure loss estimations for the multiphase sections of the test loop presented unforeseen challenges.

25 ENERGY STORAGE↗

DOE OSTI2025

Tool-Based Case Studies on Strategic Deployment of Untapped Micro-Pumped Hydro Storage in Michigan

With most classical hydropower sites already utilized and the global push for rapid integration of renewable energy sources accelerating, there is a critical need to identify alternative energy storage solutions. Pumped hydro energy storage, which accounts for the vast majority of global grid-scale storage, remains one of the most cost-effective and long-duration storage technologies available. Hence, this study presents a novel tool designed to assess the untapped potential of inland lakes and reservoirs for micro-PSH, using Michigan’s relatively flat landscape as a case study due to its extensive but underutilized water infrastructure. To ensure accuracy and reliability, the tool incorporates extensive data gathered from authorized sources, covering more than 420 water facilities and potential reservoirs in the state. The tool evaluates key parameters such as horizontal and vertical distances, volume, and the total storage capacity of each reservoir. Its robust assessment framework integrates these metrics to evaluate each site’s potential. The tool’s intuitive interface and geospatial visualizations support actionable insights for planners and scalable deployment of distributed storage infrastructure.

13 HYDRO ENERGY↗

DOE OSTI2026

Robotics for Energy Infrastructure Construction on Earth and Beyond: Pilot Study Exploring Level 3-4 Semi-Autonomous Installation of a Reduced-Scale Photovoltaic Power Plant Prototype: Preprint

There is a growing need to build energy infrastructure at massive scale on both Earth and in space. On Earth, increasing electricity demand from applications such as AI data centers is driving rapid expansion of power systems, while in space, long-duration missions such as lunar operations require reliable and resilient energy infrastructure that can be deployed quickly. These needs outpace the capabilities of conventional construction methods. Robotic construction offers a path to faster, lower-cost, and more consistent deployment, yet most existing approaches focus on automating individual tasks rather than end-to-end assembly. The Industrialized Construction Innovation (ICI) team at the National Laboratory of the Rockies (NLR), in collaboration with the Colorado School of Mines, has been investigating robotics and automation strategies for rapid end-to-end energy infrastructure construction. This paper presents a pilot study demonstrating level 3-4 semi-autonomous, end-to-end robotic assembly of a reduced-scale photovoltaic power plant prototype under terrestrial conditions. The approach combines hardware redesign of photovoltaic components for robotic compatibility, discrete-event and physics-based robotic simulations in synthetic environments, and sim-to-real deployment to execute end-to-end robotic assembly of[NM1.1][NM1.2] tracking components, structural members, photovoltaic modules, and embedded electrical connections. The pilot identifies key limitations like tolerance management, perception and localization, end effector capability, fastening methods, and multi-physics simulation fidelity, that must be addressed to enable end-to-end robotic assembly of full-scale energy infrastructure. The study highlights how these insights inform scaling strategies for terrestrial energy infrastructure and adaptation to unstructured and extreme environments, including off-world scenarios such as robotic assembly of vertical tall lunar towers.

14 SOLAR ENERGY↗

DOE OSTI2026

Advancing the HERO WEC Through Integrated Modeling, Testing, and Field Deployments: Preprint

The Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC) was developed by the National Laboratory of the Rockies as a modular platform for advancing wave-powered desalination technologies. Designed to operate in either a hydraulic or electric configuration, the system enables direct comparison of mechanical-to-water and electrical-to-water conversion pathways using a single hardware architecture. Deployments at the Jennette's Pier test site in 2022 and 2024 demonstrated freshwater production between 60 and 300 gallons per day, including successful operation in wave heights as low as 0.25 m. A structured evaluation approach combining numerical modeling of hydrodynamic and PTO response, controlled laboratory testing, and in-ocean field deployments has been used to characterize and refine system performance. Insights from these efforts are now informing the second-generation HERO WEC (V2), which incorporates improved drivetrain components, refined geometry, enhanced control systems, and design updates aimed at increasing robustness and long-duration survivability. The HERO WEC platform continues to serve as an open-access research asset supporting broader marine energy and desalination development.

16 TIDAL AND WAVE POWER↗

DOE OSTI2024

Designer Fluorescent Redoxmer Self‐Reports Side Reactions in Nonaqueous Redox Flow Batteries

The state of health (SOH) is a critical measure for evaluating and predicting performance of redox flow batteries (RFBs). However, diagnosing SOH of RFBs is often challenging due to the overwhelming complexity of the electrolytes and associated electrochemical reactions. Designing active molecules or redoxmers that can autonomously exhibit property changes upon specific stimuli may provide a viable way for early diagnosis of SOH. Herein, a dimerized redoxmer, DGL-N-CH 3 , was designed and synthesized by linking blue-green fluorescent monomers through a diglycolamide linker. While DGL-N-CH 3 still maintains similar electrochemical behavior and strong fluorescence, we observe a unique side reaction when cycling DGL-N-CH 3 in H-cells, which leads to a side product, NHCH 3 -BzNSN via linker cleavage. Interestingly, NHCH 3 -BzNSN also emits fluorescence but at a longer wavelength. By taking advantage of this unique fluorescent change that corresponds to the growth of NHCH 3 -BzNSN, we successfully established the capacity decay of DGL-N-CH 3 H-cell cycling, exemplifying a proof-of-concept self-reporting redoxmer design towards in situ SOH monitoring.

25 ENERGY STORAGE↗

DOE OSTI2024

Fundamental benchmarking of the discharge properties of negative electrodes in lead acid batteries

The unprecedented scale of energy storage deployment needed to allow high penetration of intermittent renewable energy sources into the electrical grid places significant economic cost and performance targets on battery technologies. Lead batteries, owing to their highly abundant and inexpensive raw materials, can be considered an important solution to grid storage as long as they achieve high material utilization, fast recharge rates, and long cycle life. To address the limitations in material utilization, we need to revisit the electrochemical processes during the discharge step and answer the following question: what are the fundamental limits of the discharge reaction? In this work we discuss how well-defined lead metal surfaces with nanometer scale roughness allow us to resolve the accessible discharge capacity for both faradaic and non-faradaic processes as a function of electrolyte concentration and in the presence of traditional additives. The direct connection between PbSO 4 layer morphology and discharge rates gives us important insights on the mechanism of discharge as related to the dissolution and passivation events. In conclusion, this work sets the stage for reimagining the design of lead batteries with implications to grid storage applications.

25 ENERGY STORAGE↗

DOE OSTI2026

Planning for Seattle at the Convergence of Resilience and Energy

Grid reliability metrics obscure important temporal, spatial, and categorical considerations for increasing energy resilience. Systemwide or feeder-level outage metrics do not identify which kinds of services are affected by outages, where, and for how long. These outage metrics indicate the impacts of outages but cannot measure the consequences to customers that could result from those outages. The consequences of power outages for surrounding community members are caused by disruptions to electricity-dependent critical services, rather than to electricity itself. Power outages can decrease a community's access to healthcare, fuel, safe indoor temperatures, and provisions like food and water. This project developed critical service access, a new consequence-focused resilience metric that quantifies the relative access to critical services provided to households by distribution infrastructure during normal conditions and major disruptions. We use a spatially granular grid analysis that facilitates targeted resilience interventions; dividing feeders into isolatable sections and combining those sections with the critical service access metric allows us to identify where energy improvements like solar-plus-storage microgrids could create the most benefits for community members by protecting access to food, fuel, health, shelter, and public safety services. We identify locations in a South Seattle study area that could be high priorities for resilience investment and summarize their potential neighborhood-scale resilience benefits. This analysis was complemented by direct feedback from study area residents collect through a survey and focus groups. Results can help utilities understand how and where long power outages can create real consequences for customers, set strategic targets based on that understanding, and measure the potential benefits of energy resilience upgrades for more informed decisions.

14 SOLAR ENERGY↗