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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 721 records · Page 40

Low-Cost, Easy-To-Integrate and Reliable Grid Energy Storage System with 2 nd Life Lithium Batteries

Batteries retired from electric vehicles have the potential to extend their service as low-cost stationary energy storage systems. However, disperse battery state of health (SOH) and nonuniform battery characters often lead to compromised battery performance and reliability, which greatly hinder their adoption. A Heterogenous Unifying Battery (HUB) system is proposed to stage 2 nd life battery bricks for a period, and enable them to attain improved SOH uniformity, performance, and reliability before being sold for 2 nd life applications, while simultaneously providing grid services. It may offer a technically and economically advantageous solution for the broad utilization of 2 nd use batteries. The goal of this project was to develop the hardware and software that enables the key functions of the HUB system. The first achievement of the project was the development of a 1kW scale proof-of-concept (POC) system, which comprises (i) a modular plug-n-play DC-DC power converter matrix with isolated series output connections to achieve fully independent control of energy flow to each of the connected battery units at low voltage; (ii) enhanced model based control that drives each batteries’ SOH towards uniformity while collectively providing grid energy storage services; and (iii) comprehensive procedures to perform battery diagnostics and prognostics. The second achievement was the development of a 100kW scale HUB system and demonstrated its performance of re-establishing battery SOH uniformity through a period of battery cycling operation. The final HUB system incorporates six DC-DC power converter matrices paired with six battery bricks. Hot swapping of a single battery brick while maintaining consistent system power was demonstrated and system operation was validated to be capable of implementing the approved grid duty cycle and of balancing and conditioning the battery bricks. Through the course of the project, the team optimized the building-block design, form-factors, and adjusted life balancing control. An up-sized 250kW Scale was developed and deployed in October 2022 with pack-level battery form factors, see photo in Figure 1 The third achievement of the project was to perform a techno-economic analysis in order to better understand the cost and revenue potentials in this new “recondition-then-resell" value proposition. The final TEA quantified the economics of new Li-ion batteries as well as second-life batteries processed via reconditioning and traditional binning. Results showed the reconditioned second-life batteries in this project to be economically favorable and viable in grid energy storage markets. The TEA results were published in the Applied Energy journal. The fourth achievement of the project was to deliver a tech-to-market plan for the HUB system that includes funding, IP, and manufacturing strategies. The final T2M plan outlines a business strategy in which the HUB provides a B2B service to EV companies as an alternative to battery recycling that can prepare batteries for 2nd life applications. A company named Smartville Inc. was founded to carry on the commercialization, funding, and technical IP licensing activities of the OPEN project.

25 ENERGY STORAGE↗

FY23 Update: Aerosol Sampling for the Canister Deposition Field Demonstration

This report describes the results of preliminary testing of aerosol monitoring equipment that will be used to continuously monitor the aerosol source term for the multi-year Canister Deposition Field Demonstration (CDFD). These data are required inputs for the development and validation of models for the deposition of dust and potentially corrosive salts on the surface of spent nuclear fuel (SNF) dry storage canisters. Surface salt loads correlate with the extent of corrosion damage on a metal surface, and potentially to the likelihood and timing of initiation of stress corrosion cracks. Aerosols will be monitored at the CDFD site using three instruments. A Dekati ® ELPI+ cascade impactor will be used for real-time monitoring of aerosol particle sizes. It will also collect dust in 14 size bins on impactor targets that can be chemically analyzed to determine the soluble salts present as a function of particle size. However, this instrument can only measure dried aerosols, with a diameter of <10 µm. The second instrument is a Topas laser particle size spectrometer, which provides real-time monitoring of aerosol particle sizes up to ~40 µm in size. It monitors both the ambient (potentially deliquesced) aerosol particle size distributions required for the dust deposition models and the distributions of the equivalent dried particles, allowing correlation with the Dekati ® data. However, it does not discriminate between inert dust particles and salt aerosols, and it does not retain samples of the different particle sizes for later analysis. The third instrument that will monitor aerosols at the CDFD site is a Clean Air Status and Trends Network (CASTNET) tower, which uses a multiple canister system to collect weekly samples for analysis to total suspended aerosol particle compositions and atmospheric gas concentrations. This status report describes work in FY23 to develop the capabilities for using these tools. In two training exercises, the cascade impactor and laser particle sizer were deployed in two different testing environments, one indoor and one outdoor. For the cascade impactor, the tests provided opportunities for the operators to familiarize themselves with impactor substrate preparation, and post-test sample removal and analysis. For the laser particle sizer, the tests were used to evaluate different instrument parameters, to determine the most appropriate settings for capturing transient events. Data and samples were collected for weeks to months for each test, and the results are presented here. In addition to the preliminary testing, contracts were developed with WSP Analytical Labs for sample preparation and analysis of the cascade impactor samples. The impactor tower from outdoor test was delivered to WSP and used to train the staff there in disassembly, sample extraction, sample analysis, and tower reassembly with new target substrates. These are tasks that WSP will be performing routinely for the CDFD project. The CASTNET system cannot be purchased or tested until an actual site has been selected for the CDFD test. Work for this FY has been restricted to preparation of contracts for purchasing the CASTNET tower, and for sample analysis, once the tower is in operation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Quantum Random Walk Simulator Using Ultrafast Optical Switches

Quantum random walk processes have many intriguing applications in high energy physics including the simulation of parton shower evolution. We will present the design and initial results of a fiber loop time-bin quantum walk architecture using the hardware platform already in operation at the Fermilab Quantum Network in which the state of the photon is defined by its time-of-arrival. The fiber loop consists of an unbalanced Mach-Zehnder interferometer implemented using an ultrafast electro-optical switch. The input switch controls the photon path within the interferometer, while the output switch will direct the photon back into the interferometer or to single photon detectors to measure the probability distribution of arrival times. Depending on which path the photon takes each pass through the loop, its wave function will interfere on these optical switches similar to quantum interference on a beam splitter. This work is an important step towards utilizing real-world advantages of quantum information protocols to solve problems in high energy physics.

Cameron, Andrew [Fermilab]↗

Improving the Parameterization of Cloud and Rain Microphysics in E3SM using Novel Observationally-Constrained Bayesian Approach (Final Technical Report)

In this project, we sought to develop new cloud and rain microphysics frameworks within the Energy Exascale Earth System Model (E3SM). This work encompassed two primary avenues of research: 1) Further development of a Bayesian-based scheme called BOSS (Bayesian Observationally-constrained Statistical-physical Scheme) to represent cloud and rain microphysics, testing it in realistic high-resolution cloud models, and implementing it in E3SM; 2) Development of a methodology utilizing machine learning to enable computationally tractable use of tractable use of Markov chain Monte Carlo sampling for Bayesian parameter estimation in Earth system and cloud models. In this project, we adapted the BOSS microphysics scheme, originally formulated for rain-only, to include all liquid-phase microphysical processes for cloud and rain, in particular the processes that mediate between these two categories, for example the conversion from cloud to rain through collision and coalescence of drops. We constrained the scheme via comparison and testing against a detailed model that explicitly represents the evolution of cloud and rain particles, called a bin microphysics scheme.

54 ENVIRONMENTAL SCIENCES↗

Solid State Solar Thermochemical Fuel (SoFuel) for Long Duration Storage

Efficient thermal storage systems, when coupled with renewable energy, enable the decarbonization of numerous industrial processes requiring high temperature steam or air, and provide a path for seasonal building heating, especially for colder climates. Existing thermal storage systems face a significant challenge due to losses inherent to all high temperature systems. A viable route to long-term storage is to use thermochemical reactions to convert concentrated solar energy to a fuel that is shelf-stable and can be stored at room temperature, thus eliminating losses associated with high temperature storage. The Solid-State Solar Thermochemical Fuel (SoFuel) technology developed by Michigan State University, Oregon State University, and Mississippi State University provides reactors and processes with minimal sensible heat losses and allows storing solar energy as a solid-state fuel at room temperature for long duration. The production of SoFuel occurs within a cylindrical cavity reduction chemical reactor that captures concentrated solar radiation from a solar field. Reactive magnesium manganese oxide (Mg-Mn-O) resides within the cylindrical cavity chemical reactor and undergoes thermal reduction as the temperature exceeds 1350°C. The thermally reduced Mg-Mn-O pellets (the SoFuel) are cooled down through a recuperative process and stored within a bin until used. The SoFuel can directly supply up to 1100C heat to an adjacent power plant for electricity generation or industrial heating. Oxidation of SoFuel pellets occurs in a counter flow reactor and supplies heat to the user for electricity generation or industrial processing, after which the fuel is returned to the concentrating solar field where it is regenerated for re-use. Both reactors can be controlled well using a variety of strategies. With the low cost of the material, its cyclability, and the possibility of using the pelletized with on-sun reactors, or with electricity that would be curtailed, this project offers a viable option of medium- and long-term thermal energy storage.

25 ENERGY STORAGE↗

EW Studies and CP Sensitivity in ZH Production at FCC-ee

Charge-Parity (CP) violation is a necessary condition to explain the relative abundance of matter in the universe in comparison to anti-matter. Nevertheless, known sources of CP-violation are insufficient to explain this disparity. Planned to commence its operations in 2040, the Future Circular Collider (FCC-ee) will collide electrons and positrons at a center of mass energy of 240 GeV, which optimizes the rate of production of a Higgs Boson in association with an on-shell Z boson: a process known as Higgs-strahlung. The associated Z boson is selected from electronic, muonic, and hadronic final states, while the Higgs is not explicitly reconstructed, but rather inferred from the recoiling four-momentum in each event. A binned, maximum-likelihood fit characterizes the relative contributions of CP-odd interactions at the HZZ-vertex while incorporating reconstructed detector effects from a proposed design to be used at FCC-ee.

Pinto, Nicholas [Johns Hopkins U.]↗

Hydroscanner: Instrumentation for Water Ingress Imaging in Photovoltaic Module Packaging Materials

A new iteration of the Hydroscanner prototype was designed and built during the execution of the contract. Compared to the previous designs, the communication port was changed from ethernet to USB C, since it provides a more seamless integration as a peripheral unit. An additional advantage is that one single port can be used for both communication and power up of the infrared camera. Although the power requirements are higher than the typical amount provided by a laptop computer, the camera can be run as a peripheral from a docking station when connected to a thunderbolt charging port. The software interface was modified to accommodate two imaging modes, an 8-bit and 14-bit image display. The 8-bit images use a custom colorization scheme that divides all pixels in the image into bins of equal width, such that images containing a wide range of brightness display the intermediate pixel intensities in greyscale values that enhance the contrast. The 14-bit images provide the direct readout from the focal plane array of the camera and can be saved as a text file for later processing in other software packages (MATLAB, Python).

47 OTHER INSTRUMENTATION↗

Leverage modern artificial intelligence (AI) enabled systems for waste reduction

Manufacturing industries continue to face challenges in reducing waste, as upstream strategies such as source reduction and product redesign require a deeper understanding of processes compared to conventional recycling methods. Recent advancements in artificial intelligence (AI) and machine learning (ML) have opened new opportunities to integrate modern computational techniques with traditional waste minimization strategies. This paper explores AI-enabled approaches for product redesign, source reduction, and recycling that can significantly reduce waste generation while improving efficiency and sustainability. AI-driven material substitution and lightweighting in product design enable discovery of novel materials with optimized properties, reducing waste without compromising performance. Reinforcement learning models optimize process parameters, raw material specifications, and machine sequencing to minimize production losses, while Industrial Internet of Things (IIoT) systems paired with AI analytics enhance real-time waste tracking, predictive maintenance, and quality inspection. Furthermore, AI-based demand forecasting and production planning reduce overproduction and excess inventory, as demonstrated in industrial applications. In recycling, ML-powered pattern recognition and robotic sorting technologies achieve higher accuracy in waste segregation, directly improving recycling efficiency. Complementary solutions such as smart bins and AI-enabled waste pickup scheduling optimize collection logistics, reducing both costs and emissions. Although implementation requires upfront investment in infrastructure and training, the long-term benefits include higher material efficiency, reduced waste, improved product quality, and stronger sustainability outcomes across the supply chain. By leveraging AI-enabled systems, manufacturers can align waste minimization efforts with circular economy principles, creating scalable solutions for both industry and society.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Electron-Proton Scattering Event Generation using Structured Tokenization

Recent work such as Omnijet-$\alpha$ has demonstrated that effective tokenization combined with transformer-based architectures can produce effective foundation models for jet physics. While tokenization may help models capture generalizable event characteristics, it also introduces discretization errors that may compromise the precision required for downstream physics analyses. As the number and complexity of the particle features grow, these errors are likely to grow proportionally. In this study, we investigate new tokenization strategies to improve the application of generative transformer models to \textsc{Pythia8} simulations of electron-proton scattering at the Electron-Ion Collider. Specifically, we propose a feature-based structured tokenization approach that utilizes multiple tokens per particle, improving expressivity, while reducing the total number of unique tokens needed. We evaluate this method against grid-based binning, K-means clustering, and vector-quantized variational auto-encoders on the event simulations. Our results show that feature-based structured tokenization reduces discretization error, leading to more accurate generative modeling of particle-level events.

Goldenberg, Steven [Thomas Jefferson National Acce↗

Network of Modified Portable Optical Particle Spectrometers Instrument Handbook

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s portable optical particle spectrometer (POPS) network (Figure 1) provides an aerosol size distribution spectrum from 150 nm to 5 μm in 16 logarithmically spaced bins. The data emanating from this network of up to four matching POPS in weatherproof enclosures comprises one-minute averages of the aerosol size and number spectrum and the co-located temperature and relative humidity. The total particle concentration and sample flow rate are also provided. The sample stream is not dried before its measurement. Two size spectra are provided: the default size distribution corresponds to the calibration using polystyrene latex spheres (PSL), while the second size distribution corresponds to the calibration using size-selected dry ammonium sulfate aerosol. The principal scientific application of the data provided by the ARM POPS is to determine the aerosol size distribution across a region in three disparate locations – the size distribution is broadly relevant to studies of pollution and of conditions in the boundary layer. A high particle concentration can be an indicator of unhealthy levels of pollution; the dispersion of particles in the atmosphere is a predictor of long-range visibility; and particles serve as collectors of condensing gases including water vapor, and thus are a factor in the formation and properties of fogs and clouds, and in the initiation of precipitation.

54 ENVIRONMENTAL SCIENCES↗

QED Radiative Corrections to CC Neutrino Scattering in NOvA

The widely-used (anti)neutrino event generator GENIE accounts for only tree level Charged-Current (CC) (anti)neutrino interactions. In this poster we begin by summarizing previous research into second order QED radiative corrections. After summarizing the theoretical corrections to cross-section distributions in $Q^2$ and $E_\nu$ we analyze the effects of Radiative corrections implemented as a systematic within NOvA's neutrino oscillation analysis framework. We present corrected predictions of (anti)neutrino event spectra at NOvA's far detector, showing an increase in CC cross sections with an increase in reconstructed $E_\nu$ along with a small decrease in low reco $E_\nu$ bins, consistent with the theoretical work.

Tripp, William [Tufts U.]↗

Artifacts in the Aerosol Size Distribution Measured by the Ultra-High-Sensitivity Aerosol Spectrometer (UHSAS)

The ultra-high-sensitivity aerosol spectrometer (UHSAS) (Droplet Measurement Technologies, Longmont, Colorado) is an optical particle size spectrometer that determines aerosol size distributions in the diameter range from 60 to 1000 nm in 100 logarithmically spaced diameter bins1 by measuring the amount of light scattered by individual aerosol particles from a 1054-nm laser. Recently, it was noticed that aerosol size distributions determined by the UHSAS from all U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility sites exhibited modes at diameters greater than ~500 nm (Figure 1, blue arrows). These modes were not present in size distributions determined by another aerosol spectrometer that was co-located with the UHSAS, the Grimm 11D optical particle counter (OPC) (GRIMM Aerosol Technik Ainring GmbH & Co. KG, Germany), which sizes particles into 31 linearly spaced diameters bins from 253 to 35,150 nm using a 683-nm wavelength laser. Additionally, abrupt changes in aerosol particle number concentration with changing particle diameter are seen in UHSAS data at several diameters (Figure 1, red arrows). The purpose of this report is to explain the origin of the modes and the abrupt changes in aerosol size distributions observed by the UHSAS and why they are absent in the data from the Grimm OPC.

54 ENVIRONMENTAL SCIENCES↗

Surface freshening contributes to weak Atlantic Meridional Overturning Circulation (AMOC) in non-eddying ocean simulations

To complete this study, researchers developed a suite of water mass diagnostics to be compatible with E3SM simulation data. These diagnostics were applied to two ocean-sea ice simulations run using E3SM Version 2.0 on non-eddy-resolving and eddy-resolving ocean meshes. The atmospheric component was forced using reanalysis data spanning 1948–2009. The simulations were analyzed over a 5-year period coinciding with surface freshening and AMOC decline in the non-eddying simulation. SWMF was calculated from the surface heat, salt, and freshwater fluxes, and transport across boundaries was calculated from the mesh edge velocities. Both SWMF and cross-boundary transport were binned by density, temperature, and salinity to produce diagnostics in density coordinates and in temperature–salinity coordinates.

54 ENVIRONMENTAL SCIENCES↗

Quantification of LEU Holdup using gamma ray imaging and inverse transport solver

Holdup is the residual amount of special nuclear material (SNM) remaining in a processing facility after the bulk materials have been cleaned out. In commercial uranium processing facilities, quantification of holdup is a major challenge because of the highly variable shapes and sizes of the deposits. Any method that attempts to generalize and calibrate deposit shapes in order to quantify holdup will be prone to high uncertainties. Uncertainties on the order of ±50% are typical in holdup results. In international safeguards applications, a ±50% uncertainty can result in a large amount of material unaccounted for (MUF) thereby increasing the difficulty of detecting material diversion and facility misuse. An imaging-based methodology has been developed with the objective of significantly reducing this uncertainty by using the true deposit shape, instead of relying on oversimplified geometric assumptions. The project is a collaboration between ORNL, Y-12, and the University of Tennessee, Knoxville, TN. Uranium sources of known masses were measured using the Germanium Gamma-ray Imager (GeGI), a high-resolution imaging spectrometer, creating a pixelated map for each spectral bin. Two different gamma imaging methods are employed in this work: coded aperture imaging and Compton imaging. A validated MonteCarlo model of the detector has been developed using the GEANT4 code for determining the intrinsic response of the detector, its enclosure, and the coded aperture mask. An inverse transport solver based on the Markov Chain Monte-Carlo approach known as Differential Evolution Adaptive Metropolis (DREAM) is employed to use the measurement data from the image pixels (coded aperture or Compton) to solve for the mass of 235 U in the deposit. A reliable method based on the DREAM solver has been developed to flag the infinite thickness condition of a uranium deposit. The project team is working towards improving the image reconstruction for Compton imaging so that a better localization of the source can be achieved. Besides treating the coded aperture and Compton imaging methods independently, the project is also evaluating a combined method that uses the Compton scatter data from a coded aperture measurement. GEANT4 simulations are being performed to evaluate the combined approach. The impact on the DREAM optimization as the source thickness progressively approaches infinite thickness is being evaluated. A number of uranium sources available at ORNL have been measured, and the DREAM results have been tested and validated for the coded aperture imaging. A similar effort will be carried out to validate the Compton based method once the development of algorithms for better localization are complete. The imaging based quantification is very amenable to unattended monitoring of holdup accumulation at key measurement points. A proof of concept measurement has been completed to demonstrate this capability The current work used the high energy resolution imager GeGI. However, the approach and methodologies are applicable to other imagers such as the cadmium zin telluride (CZT) based imager manufactured by H3D, Inc.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Exclusive $|V_{ub}|$ determinations using Padé Approximants

We determine the CKM parameter |V ub | from the exclusive semileptonic decays B→πℓν ℓ and B s →Kℓν ℓ , employing Lattice QCD theoretical information on the form factors in combination with experimental measurements of the differential branching ratio distributions. Using Pad\'{e} approximants to the participating form factors we obtain |V ub |=3.86(11)x10 -3 and |V ub |=3.58(9)x10 -3 from the analyses of the individual decay channels, respectively, and |V ub |=3.68(5)x10 -3 from a simultaneous analysis of both decays. Our results highlight the importance of the decay B s →Kμν μ in complementing the traditional B→πℓν ℓ one in the exclusive determination of |V ub | , and strengthens the case for precise measurements of the differential B s →Kℓν ℓ decay rate with a finer resolution of the q 2 bins, as it would definitely allow achieving more conclusive results for |V ub | .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

HiC manuscript: bulk metagenomic data_MG_raw Upload

The raw bulk metagenomic data were trimmed and de-novo assembled. The assemblies were screened for viral contigs (by virsorter2, Deepvirfinder, VIBRANT, checkV) and binned to generate MAGs that were further refined by Hi-C read links.

59 BASIC BIOLOGICAL SCIENCES↗

EAGLES Liquid Cloud Testbed Large Eddy Simulation Library (v2)

This library consists of large eddy simulation (LES) model output using the PINACLES codebase coupled to the Hebrew University Fast Spectral Bin Microphysics scheme representing shallow, liquid phase clouds from a range of global liquid cloud testbed regions as well as some well known LES model intercomparison cases. This data is particularly suitable for examining microphysical modeling assumptions in coarser-scale models, and was used for this purpose in the work "“Evaluation of Autoconversion Representation in E3SM.v2 using an Ensemble of Large-Eddy Simulations of Low-Level Warm Clouds” by M. Ovchinnikov, P.-L. Ma, C. M. Kaul, K. G. Pressel, M. Huang, J. Shpund, and S. Tang

Kaul, Colleen M↗

EAGLES Liquid Cloud Testbed Large Eddy Simulation Library (v3)

This library consists of large eddy simulation (LES) model output using the PINACLES codebase coupled to the Hebrew University Fast Spectral Bin Microphysics scheme representing shallow, liquid phase clouds from four global liquid cloud testbed regions. This data is particularly suitable for examining interactions among cloud, aerosol, and turbulence in warm, boundary-layer clouds and for developing, assessing and refining parameterizations for coarser-scale models.

Kaul, Colleen M↗