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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Bedrock architecture, soil texture, and hyporheic zone characterization combining electrical resistivity and induced polarization imaging

The shallow (<15 m depth) subsurface environment of a short reach along a bedrock stream was investigated with electrical resistivity and induced polarization (IP) to map details of bedrock and soil sediments. The bedrock is mostly comprised of limestone, and is generally resistive compared to the overlying soil. The soil-bedrock interface was determined through a trial and error approach using a sharp boundary feature in the inversion model. The inferred bedrock surface determined from the inversions exhibited undulating patterns with troughs and ridges. A near continuous trough ran alongside the stream within the floodplain, and is suggestive of a paleochannel among other interpretations of this feature. The structure of the electrical resistivity above the bedrock showed small-scale elongated features. The chargeability from the IP method showed larger scale features. High values of chargeability were associated with the sediments in the floodplain, and low values were associated with bedrock, stream, and soil on the elevated banks above the stream. If the chargeability is associated with membrane polarization characteristic of clayey soils, then IP seems to highlight the mere existence of clay, while the resistivity may be more discernable of the relative proportion of clay. Vegetation differences may also explain the chargeability distribution, where parts of the survey with high chargeability had dense pine with no understory making the soils more organically rich.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

AMPPED LDRD: Advanced Models of the Physics & Phenomena of Electrical Discharge.

This Laboratory Directed Research and Development (LDRD) project aimed at addressing an unmet need for physics-based models that enable prediction of electrical breakdown in the presence of high voltage gradients and real-world environments. This project focused on understanding coupled plasma-surface feedback phenomena critical to electrical discharge processes and design of breakdown voltages, breakdown times, and breakdown paths. New secondary electron emission and coupled plasma-surface measurement methods and models were developed. Highly reproducible discharge experiments were developed to provide current-voltage data as a function of time, and methods were developed to condition electrodes for predictable discharge. To assess plasma-surface feedback mechanisms, new surface physics capabilities, including measurement systems for local and global photoemission yield and ion-induced secondary electron emission yield were developed. Discharge models were developed to incorporate these yields for predicting discharge behavior to understand influence of surface physics on discharge current and time evolution, and methods to accelerate these simulations were demonstrated. A key finding was that the initiation process of a non-vacuum discharge appears highly dependent on photoemission at the cathode. Advanced diagnostics were developed, including spatial electrical field imaging, spectroscopy of plasmas, and high-speed imaging of discharge event s in metal and dielectric environments. These diagnostics and improved electrical models are a step toward enabling quantitative design margins, assurance of safety architectures, and implementation of novel materials and technologies for wide ranging energy and electronics applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

An integrated Imaging and Modeling Toolbox for Accelerated Development of Root-focused Crops at Field Scales

This project, led by Yuxin Wu at the LBNL, was proposed to develop an integrated imaging-modeling toolbox allowing for accelerated development of root-focused crops at field scales. Our approach is based on a novel root phenotyping method we termed Tomographic Electrical Rhizosphere Imaging (TERI), which provides advanced phenotyping of key root traits by sensing the electrical impedance response of roots and soil to external electrical excitations, and mapping these responses to root and soil properties. The role of Noble Research Institute in this project is to assist TERI model establishment and validation by collecting various above- and below-ground traits data from container- and field-grown plants (mainly wheat). Over the last three years, Noble Research Institute has conducted 3 phases of experiments as proposed including: (Phase 1) greenhouse and hoop-house experiments in wheat and pecan plants grown under controlled container-grown conditions; (Phase 2) space-planted individual plant field experiment using different wheat varieties; and (Phase 3) small-plot planted field experiment using different wheat varieties, as well as using different small grains species including wheat, rye, triticale, oat and barley for increasing plant variation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Electrical design of the flexible imaging diffraction diagnostic for laser experiments (FIDDLE) at the National Ignition Facility (NIF)—Requirements, design, and performance

The Flexible Imaging Diffraction Diagnostic for Laser Experiments (FIDDLE) is a newly developed diagnostic for imaging time resolved diffraction in experiments at the National Ignition Facility (NIF). It builds on the successes of its predecessor, the Gated Diffraction Development Diagnostic (G3D). The FIDDLE was designed to support eight Daedalus version 2 sensors (six more hCMOS sensors than any other hCMOS-based diagnostic in NIF to date) and an integrated streak camera. We will review the electrical requirements, design, and performance of the electrical subsystems that were created to support this large number of cameras in the FIDDLE. The analysis of the data that the FIDDLE is intended to collect relies heavily on the accurate and well-understood timing of each sensor. We report camera-to-camera timing jitter of less than 100 ps rms and sensor integration times of 2.2 ns FWHM in 2-2 timing mode. Additionally, diffraction experiments on the NIF produce electric fields (EMI) on the order of 1 kV/m, which have been observed to negatively impact the performance of some electrical components of the FIDDLE. We report on the results of testing hCMOS camera electronics in a similar EMI environment generated in an offline lab. In addition, we also summarize the use of a novel approach to using a vector network analyzer as an EMI leak detector to understand and reduce the negative impacts of EMI on the FIDDLE.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Amplitude- and frequency-dependent activation of layer II/III neurons by intracortical microstimulation

Intracortical microstimulation (ICMS) has been used for the development of brain machine interfaces. However, further understanding about the spatiotemporal responses of neurons to different electrical stimulation parameters is necessary to inform the design of optimal therapies. In this study, we employed in vivo electrophysiological recording, two-photon calcium imaging, and electric field simulation to evaluate the acute effect of ICMS on layer II/III neurons. Our results show that stimulation frequency non-linearly modulates neuronal responses, whereas the magnitude of responses is linearly correlated to the electric field strength and stimulation amplitude before reaching a steady state. Temporal dynamics of neurons’ responses depends more on stimulation frequency and their distance to the stimulation electrode. In addition, amplitude-dependent post-stimulation suppression was observed within ~500 μm of the stimulation electrode, as evidenced by both calcium imaging and local field potentials. These findings provide insights for selecting stimulation parameters to achieve desirable spatiotemporal specificity of ICMS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Imaging the electron charge density in monolayer MoS 2 at the Ångstrom scale

Four-dimensional scanning transmission electron microscopy (4D-STEM) has recently gained widespread attention for its ability to image atomic electric fields with sub-Ångstrom spatial resolution. These electric field maps represent the integrated effect of the nucleus, core electrons and valence electrons, and separating their contributions is non-trivial. In this paper, we utilized simultaneously acquired 4D-STEM center of mass (CoM) images and annular dark field (ADF) images to determine the projected electron charge density in monolayer MoS 2 . We evaluate the contributions of both the core electrons and the valence electrons to the derived electron charge density; however, due to blurring by the probe shape, the valence electron contribution forms a nearly featureless background while most of the spatial modulation comes from the core electrons. Our findings highlight the importance of probe shape in interpreting charge densities derived from 4D-STEM and the need for smaller electron probes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A hydrogeophysical framework to assess infiltration during a simulated ecosystem-scale flooding experiment

This study presents a framework to quantify changes in soil saturation in response to flooding caused by extreme hydrologic perturbation on coastal ecosystems at the interfaces and transition between terrestrial and aquatic systems. Subsurface heterogeneity limits the use of in situ measurements to quantify subsurface flow during flooding due to the spatial discontinuity in the measured data. While geophysical methods, including time-lapse electrical resistivity imaging (ERI), are increasingly used to monitor soil hydrological processes, their abilities to parameterize flow models have been underutilized. This study combines background ERI, ground penetrating radar (GPR), time-lapse ERI, soil characterization, and a numerical flow model developed using an Advanced Terrestrial Simulator (ATS) code to quantify the infiltration pathway and describe the hydrological dynamics during a simulated flooding experiment. We assessed the use of two conceptual models developed using [1] ERI and GPR data that described the stratigraphic distribution, and time-lapse ERI that mapped permeability contrast, and [2] information from a national soil database for capturing changes in saturation. Combining the ERI and GPR results with soil core data revealed the stratigraphic heterogeneity at the site with a silty clay layer from 1 to 2 m between an overlying loamy topsoil and an underlying saturated silty sand. This silty clay layer could restrict deep infiltration. The time-lapse ERI showed up to a 35% decrease in resistivity, which correlated with soil moisture data (R 2 value > 0.53) and revealed preferential infiltration zones used to inform the flow model. Numerical simulation results from both the geophysics- and soil database-informed models quantified changes in soil saturation with calculated soil moistures that agreed with field data. The geophysics-informed model captured more of the system’s variability, reflective of shallow subsurface heterogeneities. The framework presented will serve as a precursor for a robust ecohydrological model that can describe the impacts of extreme events induced by climate change on coastal ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Analysis of electrically conductive adhesives in shingled solar modules by X-ray imaging techniques

The failure mechanisms of electrically conductive adhesives (ECAs) in solar modules are difficult to study since the ECA layer is not easily accessible within the module package. In this work, we present two complementary imaging modalities—X-ray radiography and X-ray microcomputed tomography (XCT)—that reveal important morphological features of the ECA within a shingled module. X-ray radiography uses single X-ray projections to provide fast and non-destructive imaging of the shingled interconnection, illuminating the alignment of the ECA relative to the busbars, the size and shape of the ECA, and the presence of voids within it. Through X-ray radiography, we observed, for example, that the average void coverage area of ECA segments reduced from 36.7% to 4.4% when an ECA was cured for 60 s prior to module lamination. XCT is a three-dimensional imaging technique that can identify regions in which the ECA makes electrical contact to busbars on cells and regions in which the ECA has cracked, among other features. XCT can also be used to image the individual metal particles within ECA, from which the metal volume fraction of an ECA was found here to be 70.4%. This is a quantity that is not often reported by ECA manufacturers but is important to ensure isotropic conduction. As X-ray projections can be performed non-destructively on full modules, the technique may be used to pinpoint ECA failures in accelerated degradation testing. XCT is complementary and is suited to forensic analysis of failing modules.

14 SOLAR ENERGY↗
DOE OSTI2026

Using Explainable Artificial Intelligence to Predict Perovskite Solar Cell Electrical Metastability from Operando Photoluminescence Images in Accelerated Stress Testing

Metal halide perovskite (MHP) solar cells exhibit a metastable response to bias governed by coupled ionic–electronic processes, complicating the conventional reciprocity relation between luminescence intensity and device open-circuit voltage (V oc ). This limits the use of luminescence as a diagnostic for device screening or accelerated stress testing, motivating new approaches that can interpret photoluminescence (PL) signals under nonequilibrium conditions. From the artificial intelligence perspective, we develop an explainable deep learning framework that integrates convolutional neural networks (CNN), long short-term memory (LSTM) layers, and an attention mechanism to learn spatiotemporal features from operando photoluminescence PL image sequences. The model achieves a mean absolute error of ±0.027 V in predicting open-circuit voltage transients and reduces extreme-tail errors by up to 78% compared to physics-based reciprocity calculations. Gradient-weighted Class Activation Mapping (Grad-CAM) provides interpretability by highlighting physically meaningful regions such as electrode edges and emergent defect features. From the engineering application perspective, this framework enables accurate, contactless prediction of device V oc and identification of degradation-relevant features during accelerated aging of perovskite solar cells. This approach demonstrates how explainable AI can enhance operando diagnostics and reliability analysis in photovoltaic devices under nonequilibrium conditions.

14 SOLAR ENERGY↗
DOE OSTI2023

Field evaluation of semi‐automated moisture estimation from geophysics using machine learning

Geophysical methods can provide three-dimensional (3D), spatially continuous estimates of soil moisture. However, point-to-point comparisons of geophysical properties to measure soil moisture data are frequently unsatisfactory, resulting in geophysics being used for qualitative purposes only. This is because (1) geophysics requires models that relate geophysical signals to soil moisture, (2) geophysical methods have potential uncertainties resulting from smoothing and artifacts introduced from processing and inversion, and (3) results from multiple geophysical methods are not easily combined within a single soil moisture estimation framework. To investigate these potential limitations, an irrigation experiment was performed wherein soil moisture was monitored through time, and several surface geophysical datasets indirectly sensitive to soil moisture were collected before and after irrigation: ground penetrating radar, electrical resistivity tomography (ERT), and frequency domain electromagnetics (FDEM). Data were exported in both raw and processed form, and then snapped to a common 3D grid to facilitate moisture prediction by standard calibration techniques, multivariate regression, and machine learning. A combination of inverted ERT data, raw FDEM, and inverted FDEM data was most informative for predicting soil moisture using a random regression forest model (one-thousand 60/40 training/test cross-validation folds produced root mean squared errors ranging from 0.025–0.046 cm 3 /cm 3 ). This cross-validated model was further supported by a separate evaluation using a test set from a physically separate portion of the study area. Machine learning was conducive to a semi-automated model-selection process that could be used for other sites and datasets to locally improve accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Electrical monitoring of saline tracers to reveal subsurface flow pathways in a flat ditch-drained field

Time-lapse electrical resistivity imaging (ERI) combined with salt tracers can enhance our understanding of subsurface flow and transport in ditch-drained agroecosystems. In a nearly level field adjacent to a drainage ditch, we installed 192 electrodes in a 72-m2 plot along with five hydrometric stations to enable time-lapse ERI monitoring during storms. Immediately prior to a wintertime rainstorm, we applied 5 kg of KBr to a shallow trench located roughly 11 m upgradient from the ditch. Antecedent conditions prior to the storm were wet, assuring a hydrologically connected state that favored tracer dissolution and movement in the subsurface. We monitored the evolution of the tracer plume with ERI over a seven-day period. Four-dimensional (4D) delineation of precipitation and tracer transport using time-lapse ERI showed that the tracer plume moved preferentially downward through a discontinuity in the argillic horizon within the first 57 hrs. Over the following 79 hrs, the tracer plume exhibited steady, lateral movement towards the drainage ditch within a more permeable sandy horizon situated just below the argillic. A spatial moment analysis of logarithmic changes in conductivity in the sand layer revealed seepage velocities ranging from 0.0027 to 0.0482 m d-1; these values were positively correlated with hydraulic gradients, suggesting laminar flow processes typical of sandy aquifers. Increasing groundwater velocities with hydraulic gradients suggest that solute transfers from groundwater to ditch are likely to be faster in storms, especially during wet periods. Even so, predominantly slow lateral transport within the sandy horizon, even during storms, indicates that critical source areas of pollutant loss are likely within a few meters of the ditch.

Robinson, Judith L.↗
DOE OSTI2024

The effect of remnant CdSe layers on the performance of CdSeTe/CdTe photovoltaic devices

Thin film CdTe-based photovoltaic devices have achieved high efficiency above 22 %. The recent improvement in efficiency is due to Se alloying in the CdTe absorbers to form a CdSeTe/CdTe structure. The subsequent band gap grading increases the short circuit current density. The Se can be introduced by depositing a precursor thin film of either CdSe or a CdSeTe alloy and then diffusing the Se into the CdTe during the high temperature cadmium chloride activation process. Using CdSe is preferred because it is easier to control the Se concentration. However, during fabrication of the CdSeTe/CdTe devices, the CdSe thickness needs to be precisely controlled to prevent the retention of a CdSe remnant layer after the activation treatment. Retention of a remnant CdSe layer causes a dramatic reduction in device efficiency. In this work, we show that the reduction in efficiency is caused by a number of factors. The remnant CdSe layer is n-type which moves the position of the p-n junction. Also, it is widely thought that the CdSe remnants are photo-inactive. In this work, we clarify that the individual CdSe grains are actually highly photo-active. However, the grain sizes in the CdSe remnant and the adjacent CdSeTe layer are very small resulting in a high grain boundary area. Although the grain boundaries are passivated with chlorine, cathodoluminescence imaging and electrical measurements show that this is only partially effective. Also, EQE measurements show that the remnant CdSe causes parasitic absorption. Overall, the remnant CdSe layer causes a reduction in short circuit current density and device efficiency. The thickness of the CdSe precursor layer and the cadmium chloride activation process conditions must be precisely optimised to ensure that all the CdSe is consumed and inter-diffused to form the CdSeTe alloy for highest efficiency devices.

CdSe remnant↗
DOE OSTI2024

Resolving the Electron Plume within a Scanning Electron Microscope

Scanning electron microscopy (SEM), a century-old technique, is today a ubiquitous method of imaging the surface of nanostructures. However, most SEM detectors simply count the number of secondary electrons from a material of interest, and thereby overlook the rich material information contained within them. Here, by simple modifications to a standard SEM tool, we resolve the momentum and energy information on secondary electrons by directly imaging the electron plume generated by the electron beam of the SEM. Leveraging these spectroscopic imaging capabilities, our technique is able to image lateral electric fields across a prototypical silicon p–n junctions and to distinguish differently doped regions, even when buried beyond depths typically accessible by SEM. Intriguingly, the subsurface sensitivity of this technique reveals unexpectedly strong surface band bending within nominally passivated semiconductor structures, providing useful insights for complex layered component designs, in which interfacial dynamics dictate device operation. Further, these capabilities for noninvasive, multimodal probing of complicated electronic components are crucial in today’s electronic manufacturing but is largely inaccessible even with sophisticated techniques. These results show that seemingly simple SEM can be extended to probe complex and useful material properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A planar defect spin sensor in a two-dimensional material susceptible to strain and electric fields

Abstract The boron-vacancy spin defect ( $${\,{{\mbox{V}}}}_{{{\mbox{B}}}\,}^{-}$$ V B − ) in hexagonal boron nitride (hBN) has a great potential as a quantum sensor in a two-dimensional material that can directly probe various external perturbations in atomic-scale proximity to the quantum sensing layer. Here, we apply first-principles calculations to determine the coupling of the $${\,{{\mbox{V}}}}_{{{\mbox{B}}}\,}^{-}$$ V B − electronic spin to strain and electric fields. Our work unravels the interplay between local piezoelectric and elastic effects contributing to the final response to the electric fields. The theoretical predictions are then used to analyse optically detected magnetic resonance (ODMR) spectra recorded on hBN crystals containing different densities of $${\,{{\mbox{V}}}}_{{{\mbox{B}}}\,}^{-}$$ V B − centres. We prove that the orthorhombic zero-field splitting parameter results from local electric fields produced by surrounding charge defects. This work paves the way towards applications of $${\,{{\mbox{V}}}}_{{{\mbox{B}}}\,}^{-}$$ V B − centres for quantitative electric field imaging and quantum sensing under pressure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Data and scripts associated with the manuscript "Estimating soil moisture and salinity response to simulated coastal flooding using time-lapse electrical resistivity and induced polarization monitoring”

This package contains geophysics datasets generated during the simulated ecosystem-flooding experiment – TEMPEST (Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatment). These geophysics data consist of Electrical Resistivity Imaging (ERI) and Induced Polarization (IP) datasets collected to estimate the soil moisture and salinity response to the simulated coastal flooding experiment. In addition to using geophysics datasets to estimate soil moisture and salinity response, petrophysical relationship between the measured resistivity and moisture content and salinity using the multisalinity. This package consists of two folders: “MultiSalinity Experiment” folder and “TEMPEST Experiment and petrophysical conversion” folders. The “MultiSalinity Experiment” folder contains the datasets generated from the multisalinity experiment used to develop the petrophysical reslationship. The “TEMPEST Experiment and petrophysical conversion” folder contains ERI, IP, Ground Penetrating Radar (GPR) and Electromagnetic Induction (EMI) datasets collected during the TEMPEST experiment. This study shows the ability to used geophysical datasets in estimating moisture content and salinity at scale will be useful in calibrating Earth System Models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Data and scripts associated with the manuscript "A Hydrogeophysical Framework to Assess Infiltration During a Simulated Ecosystem-Scale Flooding Experiment”

This package contains the data and scripts used in "A hydrogeophysical framework to assess infiltration during a simulated ecosystem-scale flooding experiment" (Adebayo et al., 2023). The Geophysics folder contains two subfolders containing Ground Penetrating Radar (GPR) and Electrical Resistivity Imaging (ERI) datasets acquired between August 23 and August 26, 2021. The GPR subfolder contains raw data (Tempest_Project.GPZ) and processed results using the Sensors and Software EKKO Project software. The ERI subfolder contains two additional subfolders named Static and Timelapse. The Static subfolder contains background resistivity datasets acquired before infiltration, both raw and inverted results using the ResIpy code. The Timelapse subfolder contains repeated resistivity datasets acquired during infiltration on two profiles, along with raw and inverted results using the ResIpy code. The Flow model folder contains ATS model simulation files. The Geophysics-informed subfolder contains simulation datasets for two profiles generated using information from the geophysics data. The National_database-informed subfolder contains simulation datasets for two profiles generated using information from a national soil database. Each subfolder contains initial simulation results, multiple ensembles, and final simulation files. The Sensitivity_analysis folder contains the observation files exported from the flow model, notebooks used in running the code, and sensitivity analysis results showing the sensitivity of different parameters over a 48-hour period. We used mutual information-based global sensitivity analysis for the sensitivity analysis, following Jiang et al., 2022. This study shows a novel approach that integrates geophysical data with hydrological modeling to understand subsurface flow during coastal flooding.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Optical Detection of Crack Separation in Si PV Modules

Studying the mechanical behavior of silicon cell fractures is critical for understanding changes in PV module performance. Traditional methods of detecting cell cracks, e.g., electroluminescence (EL) imaging, utilize electrical changes and defects associated with cell fracture. Therefore, these methods reveal crack locations, but do not operate at the time or length scales required to accurately measure other physical properties of cracks, such as separation width and behavior under dynamic loads.

14 SOLAR ENERGY↗