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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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28 records · Page 2

Surface water geochemistry along St. Louis River Estuary (Duluth/Superior, MN/WI)

This dataset is aimed at understanding changes in surface water chemistry associated with urbanization in the Great Lakes region. Surface water chemistry including cations, anions, organic and inorganic carbon, and nitrogen were collected from six locations along St. Louis River – a freshwater estuary entering Lake Superior (Duluth/Superior, MN/WI). The Duluth/Superior, MN/WI metropolitan area is the largest port on the United States side of Lake Superior. Samples were collected near different land uses every two weeks from late July 2023 to the onset of ice cover in November 2023. Water samples were analyzed using In-Situ AquaTroll 500 Multiparameter Sonde with Ammonium Ion Selective Electrode and Chlorophyll-a sensor (unfiltered), METTLER TOLEDO FiveEasy Plus FP20 and METTLER TOLEDO LE407 probe (unfiltered); HACH DR300 Pocket Colorimeter Iron FerroVer (filtered 0.22 μm in field); Shimadzu TOC-L Total Organic Carbon Analyzer with TNM-L Total Nitrogen Unit (filtered 0.22 μm in field); Agilent 8900 triple quadrupole ICP-MS (ICP-QQQ) (filtered 0.22 μm in field); and Dionex ICS-6000 HPIC System (filtered 0.22 μm in field).The data package is comprised of 5 files. dd.csv contains the description of columns in Geochemistry_LSNERR_water.csv and Sampling_sites.csv. flmd.csv contains descriptions of each file in the dataset. README.txt contains description of the dataset structure and file content. Geochemistry_LSNERR_water.csv contains geochemistry data for six sampling locations along the St. Louis River. Sampling_sites.csv contains latitude and longitude coordinates for each of the six sampling site locations along the St. Louis River.This data has not been previously published.

54 ENVIRONMENTAL SCIENCES↗

GPU-Accelerated Analytic Simulation of Sparse Ionization Signal Formation in Pixelated Projection Detector

This paper presents a GPU-accelerated simulation package, TRED, for next-generation neutrino detectors with pixelated charge readout, leveraging community-driven software ecosystems to ensure adaptability and extensibility. We introduce two generic contributions: (i) an effective-charge representation based on Gaussian quadrature rules, in which the linear- interpolation factors for the field response inside each voxel are absorbed into the effective charge, and (ii) a sparse, block- binned tensor representation that enables efficient FFT-based computation of induced signals on readout electrodes for sparsely activated detector volumes. The former captures structure inside a voxel without dense sampling, while the latter achieves low memory usage and scalable runtime, as demonstrated in bench- mark studies. The underlying data representation is applicable to large-scale detectors and to other computational problems involving sparse activity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Performance degradation in proton-conducting ceramic fuel cell and electrolyzer stacks

Proton-conducting ceramics are emerging as enabling materials for efficient electrochemical electricity generation, energy storage, and fuels synthesis. In this work, we present longer-term degradation results for protonic-ceramic fuel cells and electrolyzers based on a BaCe 0.4 Zr 0.4 Y 0.1 Yb 0.1 O 3-δ (BCZYYb) electrolyte. The cells are packaged within unit-cell stacks, including metallic interconnects, current collectors, sealing glasses and gaskets. Durability is found to be superior in protonic-ceramic electrolyzers in comparison to fuel cells. Operating conditions have a large impact on degradation rates; better stability is found at fuel-cell operating temperatures above 600 °C, and electrolyzer steam feeds below 20%. Here, we find that both fuel-cell and electrolyzer degradation is greatly reduced via the introduction of a gadolinium-doped ceria interlayer between the electrolyte and the air–steam electrode. Fuel-cell degradation falls to 1.2% khr –1 under methane fuel at 600 °C; electrolyzer degradation is reduced to 1% khr –1 at 550 °C and 50% steam. Further analyses of electrochemical impedance spectroscopy and distribution of relaxation times provide insight to root processes and degradation phenomena in protonic electroceramics.

25 ENERGY STORAGE↗

Damage Modeling of Solid Oxide Fuel Cells Accounting for Redox Effects

This work applies a multiscale mechanistic damage model developed for brittle ceramics and implemented in commercial finite element (FE) packages via user subroutines to study progressive damage in solid oxide fuel cells (SOFC) subjected to thermomechanical loading under normal operating and shutdown conditions including redox effects. The damage model captures the micromechanics of stiffness reduction due to material porosity change and microcracking and integrates the as-obtained stiffness reduction law into a continuum damage mechanics (CDM) formulation for the evolution of microcracks up to fracture. The volumetric “swelling” that occurs during redox is treated in constitutive modeling similarly to thermal expansion, but swelling strains are irreversible. Furthermore, this damage model was first validated through predictions of strength and stress-strain response for the SOFC electrode materials. Next, it has been applied to predict the potential for degradation in a generic planar SOFC stack with large active area cells. Multicell stack models were simulated in both co-flow and counter-flow configurations. In addition, a constant temperature redox cycle was also simulated to capture overall cell electrode damage due to volumetric swelling of the nickel (Ni)-based anode in the anode-supported cells.

25 ENERGY STORAGE↗

Comparison of Machine Learning Algorithms for Natural Gas Identification with Mixed Potential Electrochemical Sensor Arrays

Mixed-potential electrochemical sensor arrays consisting of indium tin oxide (ITO), La 0.87 Sr 0.13 CrO 3 , Au, and Pt electrodes can detect the leaks from natural gas infrastructure. Algorithms are needed to correctly identify natural gas sources from background natural and anthropogenic sources such as wetlands or agriculture. We report for the first time a comparison of several machine learning methods for mixture identification in the context of natural gas emissions monitoring by mixed potential sensor arrays. Random Forest, Artificial Neural Network, and Nearest Neighbor methods successfully classified air mixtures containing only CH 4 , two types of natural gas simulants, and CH 4 +NH 3 with >98% identification accuracy. The model complexity of these methods were optimized and the degree of robustness against overfitting was determined. Finally, these methods are benchmarked on both desktop PC and single-board computer hardware to simulate their application in a portable internet-of-things sensor package. The combined results show that the random forest method is the preferred method for mixture identification with its high accuracy (>98%), robustness against overfitting with increasing model complexity, and had less than 10 ms training time and less than 0.1 ms inference time on single-board computer hardware.

03 NATURAL GAS↗

Time-resolved electrical potential pump – X-ray photoelectron spectroscopy probe developments for investigating dynamic processes occurring at electrochemical interfaces

Electrode–electrolyte interfaces are of critical importance in several fields, including renewable energy, corrosion, and environmental chemistry. However, investigating these interfaces under operational conditions poses considerable challenges due to the limitations of the instrumentation employed. While recent advancements in in situ and operando techniques have enhanced our comprehension of the steady-state properties of solid-liquid interfaces, the dynamic behaviors of these systems remain inadequately explored. This study introduces a time-resolved X-ray photoelectron spectroscopy (XPS) technique designed to capture transient reaction intermediates and charging dynamics at electrified interfaces. The presented proof-of-principle study demonstrates that electrochemical processes, represented by an equivalent electrical circuit (EEC) model, can be probed and understood using square wave voltage pulses of a potentiostat synchronized to the modified data acquisition of an XPS setup. This method offers a valuable alternative to traditional pump–probe techniques, facilitating the investigation of a broader range of electrochemical systems. A dedicated software package for analyzing time- and energy-resolved XPS with a focus on extracting parameters of the EEC is geared towards benchmarking different EECs in future real-world electrochemical experiments.

Electrochemistry↗

Perovskite on Silicon Tandem Solar Cells

Since installing solar panels costs more than the panels themselves, it is critically important to improve the efficiency of the panels so that fewer panels need to be installed. More than 90% of all panels being manufactured are made with silicon solar cells. The most promising approach to reach 27% is to upgrade the panels by adding a second set of cells with a larger band gap that can harvest the higher energy photons in the visible spectrum and generate a higher voltage than silicon is capable of generating. Perovskite semiconductors are very promising for low-cost tandems because they have high band gaps, can be rapidly printed from solutions and have been used to make 25% efficient cells by themselves. If we show that it is possible to make stable tandems with 30% efficiency using materials that could be deposited at low cost and that the energy yield will not be compromised, then private companies would be able to raise the capital needed to manufacture this technology. The main metrics for this project are the power conversion efficiency of a lab-scale perovskite/silicon tandem and the ability to maintain a high power conversion efficiency in perovskite solar cells after accelerated operational stability testing under maximum power point at elevated temperature and 1 sun illumination. In short, this project demonstrates improvements to the perovskite absorber layer, contacts for the perovskite solar cell, and transparent oxide layers for window electrodes to achieve tandem efficiencies of 25% after one year and 27% after two years. By the end of the project, we identify strategies to further improve light management in the tandem devices and outline a pathway to reach 30%.In parallel, stability testing is conducted to evaluate said absorber and contact layers in the perovskite top cell, demonstrating 1000 hours of operation with less than 10% degradation at 1 sun. Our work on this project has made a leading impact on the development of perovskite/silicon tandems. The triple halide perovskite that we developed using iodide, bromide, and chloride and published in Science in March 2020 has received significant interest from other experts in the field at conferences. We took a silicon bottom cell with 21% efficiency, a technology that is responsible for a $30 billion market, and improved it by 30% relative. In addition, we have demonstrated impressive stability of our perovskite semitransparent top cells used in the tandems, showing for the first time packaged devices that pass a variety of IEC stability tests including damp heat, temperature cycling, and UV exposure tests.

14 SOLAR ENERGY↗

Photostability of Ambient-Processed, Conjugated Polymer Electrochromic Devices Encapsulated by Bioderived Barrier Films

Polymer-based electrochromic devices (ECDs) are a promising technology for enabling low-voltage, disposable displays, yet are currently limited by photo-oxidative bleaching of the active materials. Here, renewable barrier films composed of cellulose and chitin are presented as an alternative to poly(ethylene terephthalate) (PET) for encapsulating ECDs. To assess barrier film effectiveness, lateral ECDs composed of poly(3,4-propylenedioxythiophene-(CH 2 OEtHx) 2 ) (P(ProDOT)) active layers were constructed and encapsulated with a multilayer barrier consisting of chitin nanofibers and cellulose nanocrystals spray cast onto a cellulose acetate substrate (oxygen transmission rate (OTR) = 29 cm 3 m –2 day –1 ), a commercially available PET film (OTR = 8.5 cm 3 m –2 day –1 ), and a high-performance PET-Al 2 O 3 multilayer barrier film (OTR < 1 cm 3 m –2 day –1 ). The photodegradation of the P(ProDOT) active layer was determined by measuring the evolution of the colorimetric contrast (ΔE*) and switching speeds as a function of light exposure (100 mW cm –2 , AM 1.5 G light). Photodegradation was found to proceed at a similar rate for all encapsulated devices (roughly 10 times more slowly than unencapsulated devices), highlighting the opportunity for replacing petroleum packaging with bioderived barrier films. Analysis of the switching kinetics, the shifts in optical absorbance, and evidence of chemical degradation indicate that both photochemical breakdown of the electrolyte and cross-linking of the P(ProDOT) active material are key drivers for loss of device performance when oxygen flux to the active material is limited. Furthermore, pathways toward better understanding photodegradation are then proposed with sustainability in mind for future ECD design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Field and Model Data Associated with the Manuscript “Drivers of Streamflow Intermittency in Humid Regions: 1. Evaluating Above- and Below-ground Controls of Flow Persistence in a Forested Catchment”

This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in a forested catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, ground penetrating radar (GPR), continuous self-potential (SP) monitoring, electromagnetic (EM) imaging, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Contains two subfolders: Synthetic and Field_Application subfolder. Synthetic subfolder contains the ATS XML input script (can be opened using any code editor) for the four synthetic hydrological cases tested (Connected and gaining, Connected and losing, Disconnected and losing, and dry stream). It also includes other experimental cases to test the influence of precipitation and concentration gradient. For each synthetic case, the flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.mph can be opened with the commercial software COMSOL and requires a license) is executed using the ATS output data to simulate the potential field. It also includes the Synthetic_model_plot.ipynb (can be opened using any code editor) to visualize the SP result and generate manuscript figures. The data subfolder contains mesh files to run both the ATS (.exo and .stl files can be viewed using Paraview; .h5 files can be opened using HDFView software and h5py Python package) and COMSOL models. Field_Application subfolder contains two subfolders: ES_MDA_inversion and Final_Model. ES_MDA_inversion contains the Python script (.py can be opened using any code editor) and SP observation data used to run the Ensemble Smoother with Multiple Data Assimilation (ES-MDA) inversion sequence to get the optimal model parameters. The Final_model subfolder contains the ATS XML input scripts, data files, output data for the two SP sites. The same workflow steps outlined for the Synthetic subfolder apply here. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) EM Contains the CSV file of the EM data from the DUALEM-42, including spatial coordinates (x, y, z), apparent conductivity, and in-phase measurements at 2 m coil separations for horizontal coplanar (HCP) and perpendicular (PRP) geometries. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion (.resipy can be opened with the open-source ResIPy software). 6) GPR Includes GPR field datasets collected at 100 MHz and 250 MHz antenna frequencies, along with the processing/interpretation project file (GPR_process.gpz can be viewed using EKKO_Project 6, a commercial software by Sensors & Software that requires a license). 7) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 8) SP Contains the SP data collected in field at the two SP sites (one in the perennial reach and the other in the intermittent reach), provided as DAT files. 9) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). It also includes DTW.ipynb, a Jupyter notebook containing the code for the dynamic time warping (DTW) with sliding window to evaluate SP signal synchronicity.

ATS↗

Depowering of Batteries to Reduce Cost of Ownership

(1) Executive Summary: End of life batteries (EOLBs) present a cost and safety liability for their owners and stakeholders. This is due flammability, energy, and power with EOLBs. Current approaches include cumbersome, expensive packaging, specialized shipping, regulated storage, and they are responsible for over half of the cost of recycling. They all expensively and inadequately address symptoms. OnTo has developed and proven a simple way to resolve the problem systemically, through depowering of lithium-ion batteries (and most any battery other than lead). The low-cost process removes flammability, power, and energy in EOLBs through non-toxic chemical processing. The opportunity for commerce of inert scrap is at least $5 billion greater than the commerce in hazardous scrap, all made possible through OnTo’s technology for efficiency and safety. (2) Depowering Improves Safety and Decreases Cost of Battery Ownership: OnTo’s depowering technology will remove half of the cost of EOLB management and recycling. Without this technology, EOLB recycling will always be a liability. EOLB is hazardous due to inherent flammability of electrolyte and lithium. The shipping and commerce of EOLBs is costly and dangerous all along the chain of custody from owner, dealership/shop, shipper, second-life sorter, (shipper again), and finally to the destination facility recycler. OnTo’s depowering service renders inert most any EOLB packs, modules, and cells. The technology uses a brief, non-toxic treatment applicable to most any chemistry. The industry needs a safe, simple, modular, and inexpensive method to render EOLBs as inert scrap. OnTo’s deactivation system is scalable to the needs of any customer along the EOLB chain of custody. (3) Evidence of Successful Depowering: Untreated batteries will catch fire and explode under abuse conditions such as heat or crush. Slide 2 below shows that untreated batteries will blow-up and expel their internal components with heating, after OnTo’s depowering treatment, the same battery is inert with the same heat treatment (Fig. 7 in the slide). Depowering also removes electrolyte reactivity, eliminating the production of HF and other toxins (Fig 6. in the slide) The depowering process is applicable to large, 26 Ah cells. Fig. 5 in the slide shows the removal of all the electrolyte from whole cells. Removal of flammable material from an EOLB contributes to the inert behavior. OnTo developed this technology through a project supported by the US Department of Energy EERE program, with partners including Seattle King County Metro Transit. While OnTo has generated evidence of successful depowering of batteries, in 2020, a follow-on voucher opportunity for third party analysis of depowered cells and materials was approved through CalTestBed. The expertise of the battery and materials research groups at Lawrence Berkeley National Laboratory will characterize these depowered cells to provide better understanding of the materials level changes in depowering. (4) Pilot Plant for Depowering EOLBs: Making the spoke work in hub-and-spoke While other companies are marketing the hub-and-spoke approach for recycling EOLBs, they rely on dangerous, expensive shredding methods with flimsy IP protection. OnTo offers the only patented, proven ability to depower EOLBs from most any chemistry – at half of the capital cost required for shredding, while eliminating the liability, danger, and waste streams inherent with shredding. The proposed commercial pilot facility is (5) OnTo Technology LLC Company: OnTo develops advanced battery recycling innovations that produce manufacturing quality electrode materials from recycled batteries. Their patented Cathode-healing™ and Deactivation/Depowering processes improve safety and reduce the cost of recycling. OnTo’s breakthrough technologies produce advanced materials for manufacturing batteries useful in applications from portable power to electric vehicles. Contact: Steve Sloop OnTo Technology LLC, 63221 Service Road, STE F, Bend, OR 97703, ssloop@onto-technology.com , 541-389-7897

deactivation↗