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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 379 records · Page 21

Volatile Organic Compounds in Bankhead National Forest (AMF3). August to September, 2025

The formation of atmospheric aerosols through the transformation of volatile organic compounds (VOCs) is a fundamental process in aerosol-climate interactions, as these particles serve as cloud condensation nuclei and ultimately influence Earth’s radiative balance. However, there remains a critical need to quantify the effects of multiple coexisting VOC precursors on aerosol formation beyond the limitations of laboratory-scale studies. This research aims to advance the mechanistic understanding of secondary organic aerosol formation in the southeastern United States by investigating interactions among coexisting VOC precursors observed at the third ARM Mobile Facility located in the Bankhead National Forest. The dataset was generated from the deployment of Oak Ridge National Laboratory’s PTR-TOF 6000 X2 Proton Transfer Reaction Time-of-Flight Mass Spectrometer (PTR-ToF-MS) for the real-time, continuous monitoring of VOCs from August 21 to September 15, 2025. To minimize sampling artifacts and compound losses, the PTR-ToF-MS inlet was connected to the cabin flow line by replacing the existing Tygon tubing with 1/2-inch outer diameter perfluoroalkoxy (PFA) tubing. The instrument operated on an hourly measurement cycle consisting of 8 minutes of zero-air measurements followed by 52 minutes of ambient air sampling, with a temporal resolution of 10 seconds. The dataset includes concentrations, reported in ppb, of methanol, acetone, acetonitrile, isoprene, methyl vinyl ketone and methacrolein (MVK + MACR), monoterpenes, benzene, toluene, and catechol.

Atmospheric concentration of volatile organic comp↗

Pathways to High-Power-Density Redox Flow Batteries

Redox flow batteries (RFBs) promise to fill a crucial missing link in the energy transition: inexpensive and widely deployable grid and industrial-scale energy storage for intermittent renewable electricity. While numerous lab-scale and demonstration-scale RFBs have been delivered, widespread commercial deployment is still limited by high electrolyte, stack, and balance of plant capital costs. Increasing the power density of RFBs is correlated with lower stack costs, primarily because the area needed for expensive electrode and membrane components to reach a target power density is reduced. Here, in the present contribution, we summarize the areal power densities reported for lab-scale RFBs, critically evaluate major pathways employed for power optimization, and identify opportunities for developing yet-higher power density systems.

25 ENERGY STORAGE↗

The Impact of Alfvénic Shear Flow on Magnetic Reconnection and Turbulence

Magnetic reconnection is a fundamental and omnipresent energy conversion process in plasma physics. Novel observations of fields and particles from Parker Solar Probe (PSP) have shown the absence of reconnection in a large number of current sheets in the near-Sun solar wind. Using near-Sun observations from PSP encounters 4–11 (2020 January–2022 March), we investigate whether reconnection onset might be suppressed by velocity shear. We compare estimates of the tearing mode growth rate in the presence of shear flow for time periods identified as containing reconnecting current sheets versus nonreconnecting times, finding systematically larger growth rates for reconnection periods. Upon examination of the parameters associated with reconnection onset, we find that 85% of the reconnection events are embedded in slow, non-Alfvénic wind streams. We compare with fast, slow non-Alfvénic, and slow Alfvénic streams, finding that the growth rate is suppressed in highly Alfvénic fast and slow wind, and reconnection is not seen in these wind types, as would be expected from our theoretical expressions. These wind streams have strong Alfvénic flow shear, consistent with the idea of reconnection suppression by such flows. This could help explain the frequent absence of reconnection events in the highly Alfvénic, near-Sun solar wind observed by PSP. Finally, we find a steepening of both the trace and magnitude magnetic field spectra within reconnection periods in comparison to ambient wind. We tie this to the dynamics of relatively balanced turbulence within these reconnection periods and the potential generation of compressible fluctuations.

slow solar wind↗

Modernizing the Nuclear Industry and New Ways of Working

Nuclear energy is recognized as the most feasible energy source towards achieving nation-wide net-zero goals (COP 208, MIT). Additionally, the demand for reliable, consistent energy supply is soaring with the construction of energy hungry data centers and AI tools. This means the construction of new nuclear and the continuation of current nuclear are a high national priority. However, this leaves the nuclear industry with a workforce challenge. The rising demand for nuclear power is threatened by an underpopulated workforce. There exist a few contributors to the decreased workforce such as skewed workforce demographics resulting in large-scale workforce retirement. Also, some plants have observed difficulty hiring and retaining skill sets that typically comprise the nuclear power workforce – specifically skilled craftsman. Those who are graduating with desirable skills are seeking employment in sectors that are more modern and culturally more aligned with younger generational values. Lastly, within the nuclear sector, skilled employees will be a competitive commodity as advanced plants come online offering work environments that incorporate modern technologies, skill sets, and opportunities for career advancement. These factors emphasize the need for legacy plants to modernize with a focus on the workplace environment and culture that meets younger generations’ skills, cultural expectations, and desire for advancement opportunities. Nuclear plants are actively engaged in deploying advancements that improve the management of systems, structures, and components as well as process improvements and technologies that can reduce the costs of operation and maintenance. However, the advancements must also be analyzed, reviewed and deployed in a manner that considers the impact on how people within the organization collaborate, communicate, make decisions, and solve problems. Neglecting to consider the cultural impact of modernization risks poor adoption, unrealized opportunities, or insignificant change toward helping attract new employees. The traditional way of working is not necessarily the way new generations want to engage with their employer. For instance, in a survey performed by North American Young Generation in Nuclear the top three reasons for younger nuclear employees to seek other job opportunities was seeking better work-life balance, a lack of advancement opportunities, and work culture and leadership style differences (Smyth et al. 2022). Integrated Operations for Nuclear (ION) is an approach for the nuclear industry to create long-term strategic modernization plans and analyze each advancement for the impact on people and processes and measure how those impacts flow up to support high-level, long-term plant goals and requirements. One principle of ION is to replace the current labor-centric operation style in legacy nuclear plants with data-centric collaborative operation styles. This paper will explain how transitioning operations to leverage centralized skills and responsibility, multi-skilled teams, and collaborative decision making can flatten the hierarchical structure in plants, enable greater individual efficacy while also offering more experiences and advancement opportunities to staff. Adopting the ION way of working shifts the industry mind-set towards more networked, collaborative, and modern way of working that will attract skilled, next-generation workers to operate the legacy nuclear fleet.

99 - GENERAL AND MISCELLANEOUS↗

Tri-Level Linear Programming Model for Automatic Load Shedding Using Spectral Clustering

Traditional load shedding schemes can be inadequate in grids with high renewable penetration, leading to unstable events and unnecessary grid islanding. Although for both manual and automatic operating modes load shedding areas have been predefined by grid operators, they have remained fixed, and may be sub-optimal due to dynamic operating conditions. In this work, a distributed tri-level linear programming model for automatic load shedding to avoid system islanding is presented. Preventing islanding is preferred because it reduces the need for additional load shedding besides the disconnection of transmission lines between islands. This is crucial as maintaining the local generation-demand balance is necessary to preserve frequency stability. Furthermore, uneven distribution of generation resources among islands can lead to increased load shedding, causing economic and reliability challenges. This issue is further compounded in modern power systems heavily dependent on non-dispatchable resources like wind and solar. The upper-level model uses complex power flow measurements to determine the system areas to shed load depending on actual operating conditions using a spectral clustering approach. The mid-level model estimates the area system state, while the lower-level model determines the locations and load values to be shed. The solution is practical and promising for real-world applications.

Baquedano-Aguilar, Mario D.↗

Plant Water Profiler: A Water Balance and True Cost of Water Calculator for Manufacturing Plants

As the uncertainty of a sustained water supply, regulatory constraints, competition among end users, and public scrutiny increases, a growing number of manufacturing sectors are adapting to current and emerging water-related risks by optimizing productivity and reducing waste. As a step toward increasing water use efficiency and making informed business decisions, corporations must make an effort to understand and track their water demands, losses, and costs associated with each subsystem within their facilities. Manufacturers are often unaware of the “true cost of water” (i.e., the total costs associated with procurement, treatment, and consumption of water, and wastewater disposal), which reduces the visibility of the actual impact of water-saving measures. To help manufacturers account for water procurement and use in manufacturing operations, quantify the true cost of water, and identify potential areas for water and associated energy cost savings, an open access tool—Plant Water Profiler (PWP)—was developed. The tool is based on water mass balance analysis and has been adopted as the core analysis tool for plant water use assessments, Water In-Plant Training (Water INPLT), as part of the US Department of Energy’s Better Plants program. During three pilot INPLTs conducted in 2019 at three manufacturing facilities, the PWP tool allowed users to understand water flows within the facilities and provided additional capabilities to analyze their water use. This paper describes the methodology behind the PWP tool and its implementation through pilot Water INPLT trainings delivered in three manufacturing facilities in the United States. The three case studies demonstrate opportunities to improve water efficiency and reduce associated costs and the challenges encountered in three different manufacturing sectors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Method and system for rebalancing electrolytes in a redox flow battery system

A method of rebalancing electrolytes in a redox flow battery system comprises directing hydrogen gas generated on the negative side of the redox flow battery system to a catalyst surface, and fluidly contacting the hydrogen gas with an electrolyte comprising a metal ion at the catalyst surface, wherein the metal ion is chemically reduced by the hydrogen gas at the catalyst surface, and a state of charge of the electrolyte and pH of the electrolyte remain substantially balanced.

25 ENERGY STORAGE↗

Method and system for rebalancing electrolytes in a redox flow battery system

A method of rebalancing electrolytes in a redox flow battery system comprises directing hydrogen gas generated on the negative side of the redox flow battery system to a catalyst surface, and fluidly contacting the hydrogen gas with an electrolyte comprising a metal ion at the catalyst surface, wherein the metal ion is chemically reduced by the hydrogen gas at the catalyst surface, and a state of charge of the electrolyte and pH of the electrolyte remain substantially balanced.

Song, Yang↗

Method and system for rebalancing electrolytes in a redox flow battery system

A method of rebalancing electrolytes in a redox flow battery system comprises directing hydrogen gas generated on the negative side of the redox flow battery system to a catalyst surface, and fluidly contacting the hydrogen gas with an electrolyte comprising a metal ion at the catalyst surface, wherein the metal ion is chemically reduced by the hydrogen gas at the catalyst surface, and a state of charge of the electrolyte and pH of the electrolyte remain substantially balanced.

Song, Yang↗

Methods and system for rebalancing electrolytes in a redox flow battery system

A method of rebalancing electrolytes in a redox flow battery system comprises directing hydrogen gas generated on the negative side of the redox flow battery system to a catalyst surface, and fluidly contacting the hydrogen gas with an electrolyte comprising a metal ion at the catalyst surface, wherein the metal ion is chemically reduced by the hydrogen gas at the catalyst surface, and a state of charge of the electrolyte and pH of the electrolyte remain substantially balanced.

Song, Yang↗

Geomechanical and flow implications with continued bioconversion of coal to methane: Experiments and modeling

Microbial conversion of coal to methane is a promising technology during transition of coal-based energy from conventional coal mining to natural gas recovery from coal. Significant research advances have been made towards engineering ideal microbial communities and nutrients for bio-stimulation of coal. However, actual field applications require geomechanical and flow behavior characterization of coal during the bioconversion process as well as gas production over the life of the created “biogenic gas reservoirs”. This work presents the results of an experimental investigation to estimate gas/methane production using bioconversion of coal and analyses of variations in bulk modulus, strain and permeability. Bulk modulus of coal demonstrated time-dependent behavior with continued bioconversion of solid coal. The phenomenon was modeled using mass balancing in a closed environment and the logistic equation based biogenic gas production with time. The modeled gas production and changes in modulus of coal showed excellent agreement with the corresponding experimental results. Next, numerical simulation of biogenic conversion of coal in a constant stress in-situ condition, replicating the Huff ‘n Puff method under field conditions, was carried out. The results showed that bioconversion can lead to decrease in effective stress, increase in permeability and decrease in the modulus of coal with time. Repeated recharge of coal with nutrients and recovering the produced gas, that is, sequential cycles of Huff n’ Puff, showed further increase in permeability and decrease in coal strength, potentially leading to coal failure in-situ, further increasing the permeability, thus enhancing the prospect of field application of the technology.

01 COAL, LIGNITE, AND PEAT↗

Stochastic DC optimal power flow with reserve saturation

We propose an optimization framework for stochastic optimal power flow with uncertain loads and renewable generator capacity. Our model follows previous work in assuming that generator outputs respond to load imbalances according to an affine control policy, but introduces a model of saturation of generator reserves by assuming that when a generator’s target level hits its limit, it abandons the affine policy and produces at that limit. This is a particularly interesting feature in models where wind power plants, which have uncertain upper generation limits, are scheduled to provide reserves to balance load fluctuations. Here, the resulting model is a nonsmooth nonconvex two-stage stochastic program, and we use a stochastic approximation method to find stationary solutions to a smooth approximation. Computational results on 6-bus and 118-bus test instances demonstrate that by considering the effects of saturation, our model can yield solutions with lower expected generation costs (at the same target line violation probability level) than those obtained from a model that enforces the affine policy to stay within generator limits with high probability.

17 WIND ENERGY↗

Example of exponentially enhanced magnetic reconnection driven by a spatially bounded and laminar ideal flow

In laboratory and natural plasmas of practical interest, the spatial scale Δ d at which magnetic field lines lose distinguishability differs enormously from the scale a of magnetic reconnection across the field lines. In the solar corona, plasma resistivity gives a/Δ d ~ 10 12 , which is the magnetic Reynold number R m . The traditional resolution of the paradox of disparate scales is for the current density j associated with the reconnecting field Brec to be concentrated by a factor of Rm by the ideal evolution, so j ~ B rec /µ 0 Δ d . A second resolution is for the ideal evolution to increase the ratio of the maximum to minimum separation between pairs of arbitrarily chosen magnetic field lines, Δ max /Δ min , when calculated at various points in time. Reconnection becomes inevitable where Δ max /Δ min ~ R m . A simple model of the solar corona will be used for a numerical illustration that the natural rate of increase in time is linear for the current density but exponential for Δ max /Δ min . Reconnection occurs on a time scale and with a current density enhanced by only ln(a/Δ d ) from the ideal evolution time and from the current density B rec /µ 0 a. In both resolutions, once a sufficiently wide region, Δ r , has undergone reconnection, the magnetic field loses static force balance and evolves on an Alfv´enic time scale. The Alfv´enic evolution is intrinsically ideal but expands the region in which Δ max /Δ min is large.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Modeled estimates of permafrost hydrology and related fields for pan-Arctic region over the period 1980-2100

This dataset contains gridded estimates of total runoff (mm/day); subsurface runoff (mm/day); snow water equivalent (SWE, mm/day); vertical upward water flux of combined surface evaporation, evapotranspiration, and snow sublimation (mm/day); and soil temperature (C) across the pan-Arctic basin from simulations of the Permafrost Water Balance Model (PWBM v4). These data were generated to allow researchers to advance understanding of the changes unfolding in the Arctic's terrestrial water cycle under the influences of climate warming, hydrological cycle intensification, and permafrost thaw. The dataset will enable researchers to address important questions spanning multiple disciplines. For example, how will rising river flows exported to the coast impact critical zone ecosystems, near-shore ice dynamics, and ocean biogeochemical processes. Spatial resolution is 25x25 km with N=39926 grid cells spanning the domain. Three forcing datasets were used to drive simulations at an implicit daily time step over the period 1980-2100. Daily air temperature, precipitation, and wind speed data from the WATCH Forcing Data methodology applied to ERA5 reanalysis (W5E5) were used for meteorological forcings over the period 1980-2019. Simulations for the period 1980-2100 used meteorological data from two global climate models; IPSL-CM6A-LR and MPI-ESM1-2-HR. The PWBM hydrological outputs are organized by grid and month in gzipped ASCII text files within each archived tar file. Soil temperature is organized by grid cell and day of year from DOY 205 to DOY 260. No special software is required to work with these data. The package contains spatial domain and river basin information files. These data are most useful for analyses of the spatial and temporal variations in terrestrial hydrology and soil thermal dynamics. A manuscript describing the model simulations and associated analysis has been accepted for publication in The Cryosphere (Rawlins and Karmalkar, 2024).

54 ENVIRONMENTAL SCIENCES↗

Prefabricated Zero Ascend Omnispecies (ZAO) Modular Fish Passage Modules Using Advanced Manufacturing Techniques

The Zero Ascend Omnispecies (ZAO) fish passage attraction module “ZAO Attractor” is a novel system designed to facilitate upstream passage for a broad spectrum of fish species, with a particular focus on American shad and river herring (alewife and/or blueback herring). Combining the use of prefabricated, modular components with advanced manufacturing, the ZAO aims to provide a cost-effective and scalable solution for fish passage attractions across various hydropower sites. The system features a surface level entry, so fish do not need to climb. In addition, it is designed to be adjusted and repositioned to create the most effective attraction flows by managing the outflows from hydropower turbines. Budget Period 1 (BP1) focused on the design and modeling of the ZAO Attractor and demonstrated the engineering feasibility of a modular, prefabricated, hydrodynamically efficient structure with surface level entry and passage. It was discovered that there were limited published studies on the direct correlation between quantified flow patterns and fish attraction, emphasizing the need for controlled studies to observe and measure these effects. In Budget Period 2 (BP2), controlled studies with live fish were prioritized to address these complexities. In conclusion, the ZAO fish passage attraction module presents a promising approach to fish passage at hydropower stations, with the potential to balance environmental concerns with renewable energy development. However, further field validation and optimization are necessary to ensure its effectiveness and practicality in real-world applications.

13 HYDRO ENERGY↗

Modulation of Uptake and Reactivity of Nitrogen Dioxide in Metal-Organic Framework Materials

We report the modulation of reactivity of nitrogen dioxide (NO 2 ) in a charged metal–organic framework (MOF) material, MFM-305-CH 3 in which unbound N-centres are methylated and the cationic charge counter-balanced by Cl - ions in the pores. Uptake of NO 2 into MFM-305-CH 3 leads to reaction between NO 2 and Cl - to give nitrosyl chloride (NOCl) and NO 3 - anions. A high dynamic uptake of 6.58 mmol g -1 at 298 K is observed for MFM-305-CH 3 as measured using a flow of 500 ppm NO 2 in He. In contrast, the analogous neutral material, MFM-305, shows a much lower uptake of 2.38 mmol g -1 . The binding domains and reactivity of adsorbed NO 2 molecules within MFM-305-CH 3 and MFM-305 have been probed using in situ synchrotron X-ray diffraction, inelastic neutron scattering and by electron paramagnetic resonance, high-field solid-state nuclear magnetic resonance and UV/Vis spectroscopies. The design of charged porous sorbents provides a new platform to control the reactivity of corrosive air pollutants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

River–aquifer interactions enhancing evapotranspiration in a semiarid riparian zone: A modelling study

The hydrologic flows across the river–aquifer interface play an important role in groundwater dynamics and biogeochemical reactions within the subsurface; however, little is known about the effects of river–aquifer interactions on land surface processes. In this study, we developed a fully coupled three-dimensional (3D) land surface and subsurface model at a high resolution (~1 km) that accounts for high-frequency hydrologic exchange flow conditions to investigate how river–aquifer interactions modulate surface water budgets in the Upper Columbia-Priest Rapids watershed, a typical semiarid watershed located in the northwestern United States where river stage fluctuates in response to reservoir releases changing. Our results show that the spatiotemporal dynamics of river–aquifer interactions are highly heterogeneous, driven mainly by river-stage fluctuations. Adding 6.64 × 10 6 m 3 year –1 of water over the watershed from the river to groundwater owing to the lateral flow, river–aquifer interactions led to an increase in soil evaporation and transpiration supplied by higher soil moisture content, particularly in deeper subsurface. In a hypothetic future scenarios where a 5-m rise in river stage was assumed, the hydrologic flow exchange rates were intensified, resulting in higher surface water over the entire watershed. Overall, lateral flow induced by river–aquifer exchanges leads to an increase in evapotranspiration of ~75% in the historical period and of ~83% in the hypothetical future scenario. Finally, our study demonstrates the potential of coupled model as an effective tool for understanding river–aquifer–land surface interactions, and indicates that river–aquifer interactions fundamentally alter the water balance of the riparian zone for the semiarid watershed and will likely become more frequent and intense in the future under the effects of climate change.

54 ENVIRONMENTAL SCIENCES↗

Physics-informed machine learning of redox flow battery based on a two-dimensional unit cell model

In this paper, we present a physics-informed neural network (PINN) approach for predicting the performance of an all-vanadium redox flow battery, with its physics constraints enforced by a two-dimensional (2D) mathematical model. The 2D model, which includes 6 governing equations and 24 boundary conditions, provides a detailed representation of the electrochemical reactions, mass transport and hydrodynamics occurring inside the redox flow battery. To solve the 2D model with the PINN approach, a composite neural network is employed to approximate species concentration and potentials; the input and output are normalized according to prior knowledge of the battery system; the governing equations and boundary conditions are first scaled to an order of magnitude around 1, and then further balanced with a self-weighting method. Our numerical results show that the PINN is able to predict cell voltage correctly, but the prediction of potentials shows a constant-like shift. To fix the shift, the PINN is enhanced by further constrains derived from the current collector boundary. Finally, we show that the enhanced PINN can be even further improved if a small number of labeled data is available.

25 ENERGY STORAGE↗