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Results for “3D electric field”

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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DOE OSTI2022

Single-shot measurements of pulse-front tilt in intense ps laser pulses and its effect on accelerated electron and ion beam characteristics (invited)

Here we report recent single-shot spatiotemporal measurements of laser pulses, including pulse-front tilt (PFT) and spatial chirp, taken at the Compact Multipulse Terawatt laser at the Jupiter Laser Facility in Livermore, CA. STRIPED FISH, a device that measures the complete 3D electric field of fs to ps laser pulses on a single shot, was adapted to near infrared for these measurements. We present the design of the instrument used for these experiments, the on-shot measurements of systematic high-order PFT, and shot-to-shot variations in the measurements of spatiotemporal couplings. Finally, we simulate the effect of PFT in target normal sheath acceleration experiments. These simulations showed that pulse front tilt can steer hot electrons, shape the distribution of the accelerating sheath field, and increase the variability of cutoff energy in the resulting proton spectra. While these effects may be detrimental to experimental accuracy if the pulse front tilt is left unmeasured, hot electron steering shows promise for precision manipulation of the particle source for a range of applications, including irradiation of secondary targets for opacity measurements, radiography, or neutron generation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

An adaptable technique for comparative image assessment: Application to crosswell electromagnetic survey design for fluid monitoring

Reservoir integrity stewardship accompanying carbon capture and sequestration considers fluid extraction and reinjection as a risk-mitigating method against overpressuring that could lead to caprock damage and ensuing [Formula: see text] leakage. Crosswell electromagnetics offers a technically viable monitoring method with the spatial volume coverage necessary for reservoir-encompassing pressure management. However, a certain logistic dilemma for deep gas sequestration into saline and thus electrically conductive aquifers is that crosswell magnetic-field measurements underperform in the imaging of more resistive plume bodies, further exacerbated when vertical arrays intersect, as opposed to surround, plumes. Furthermore, comparative synthetic-data plume imaging of such scenarios rates the information content of magnetic-field versus electric-field 3D crosswell layouts for reservoir and infrastructure conditions of a representative pilot site in a coastal area in Florida. The image quality of the resulting plume replications can be ranked numerically through a newly proposed semblance qualifier, appraising the model goodness of fit to a given reference. In contrast to common least-squares measures for goodness of fit, the semblance formulation uses classifying logistic function types, thus enabling a better distinction of predefined anomaly features.

58 GEOSCIENCES↗

DOE OSTI2022

Slides for MS&T2022: Carbon-Carbon Composites from 3D Printed Preforms Graphitized by Electric Field Assisted Sintering

Formation of Carbon-Carbon (C-C) composite materials requires putting a carbon fiber preform through a cycle of densification, carbonization, and graphitization. This cycle is then repeated until the desired properties are achieved. The graphitization phase is particularly energy demanding as it involves heating the components to in excess of 2000°C. In traditional furnaces this is also quite time consuming as typical heating rates are low, and the actual heat treatment may be limited by component dimensions, as heat is conducted throughout the part primarily by thermal diffusion. Joule heating by means of Electric Field Assisted Sintering (EFAS) systems enables high heating rates and causes the part to be heated from the inside, which eliminates the thermal diffusion time constraint. In our process, C-C composites are formed by pyrolyzation of 3D-printed carbon fiber preforms, vacuum infiltration of naphthalene based mesophase pitch, and carbonization. The part is then graphitized in the EFAS system. By this method graphitization of the composite matrix was achieved in less than an hour. A part density of greater than 1.6g/cc (up to 1.9g/cc demonstrated) was achieved after only two rounds of infiltration and a single graphitization. Overall the process took less than a week which is significantly faster than traditional methods. Optical microscopy and XRD results are discussed to elucidate the internal porosity and characterize the degree of graphitization. Testing was performed showing the impact on fiber direction to electrical and thermal properties of the final part.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Contact-free reversible switching of improper ferroelectric domains by electron and ion irradiation

Focused ion beam (FIB) and scanning electron microscopy (SEM) are used to reversibly switch improper ferroelectric domains in the hexagonal manganite ErMnO 3 . Surface charging is achieved by local ion (positive charging) and electron (positive and negative charging) irradiation, which allows controlled polarization switching without the need for electrical contacts. Polarization cycling reveals that the domain walls tend to return to the equilibrium configuration obtained in the as-grown state. The response of sub-surface domains is studied by FIB cross-sectioning, enabling imaging in the direction perpendicular to the applied electric field. The results clarify how the polarization reversal in hexagonal manganites progresses at the level of domains, resolving both domain wall movements and the nucleation and growth of new domains. Our FIB-SEM based switching approach is applicable to all ferroelectrics where a sufficiently large electric field can be built up via surface charging, facilitating contact-free high-resolution studies of the domain and domain wall response to electric fields in 3D.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Estimating the Electric Fields Driving Lightning Dart Leader Development With BIMAP‐3D Observations

Abstract In this paper, a numerical dart leader model has been implemented to understand the leader's development and the corresponding electric field changes observed by the 3D broadband mapping and polarization (BIMAP‐3D) system. The model assumes the extending leader channel is equipotential and has a linear charge distribution induced by an ambient electric field. The charge distribution induced by the ambient field can be used to model the electric field change at the ground. We then find the ambient electric field which best fits the field change measurements at the two BIMAP stations. The estimated ambient electric field decreases in the direction of dart leader propagation. Our observations and modeling results are consistent with our earlier hypothesis that dart leader speed is proportional to the electric field at the leader tip. The model also supports our earlier analysis that leader speed variations near branch junctions were due to previous charge deposits near the junctions. The modeled tip electric field is generally lower than the breakdown field unless the pre‐dart‐leader channel has a significant temperature of 3,000 K. This is consistent with the fact that dart leaders typically do not form new branches into the virgin air. Furthermore, the tip field is generally close to the negative streamer stability field at ambient temperatures, explaining the nature of the narrow and well‐defined channel structure. In addition to the charge distribution and the ambient and tip electric field, the development of the channel potential and current distribution are also presented.

3D lightning mapping↗

DOE OSTI2021

Atomic Gradient Structures: Atomic Gradient Structure Alters Electronic Structure in 3D across the Bulk and Enhances Photoactivity

Understanding structure–function relationships enables the design of materials with tailored functionalities. The long-standing challenge is to design materials with high active volume to improve the efficiency. Tailored grain boundaries and lattice defects are traditionally used to tune the electronic structure near interfaces or defects to promote electron and hole separation. However, the active volume of point defect sites or interfaces in these traditional photocatalysts is extremely low. In this work, we report a structure with continuous atomic positional deformation across the bulk, altering the electronic structure in three-dimension and creating a significantly high active volume. Such a structure in anatase is obtained and tuned by phase transformation during heating process. Transmission electron microscopy and density functional theory results reveal that atomic deformations result in continuous band bending across the particles, facilitating electron–hole separation, inhibiting their recombination, and inducing dramatically enhanced photoactivity. These findings enable a different materials design paradigm that can potentially be harnessed for a broad range of applications.

TiO2↗

DOE OSTI2022

Deep learning to estimate permeability using geophysical data

Time-lapse electrical resistivity tomography (ERT) is a popular geophysical method to estimate three-dimensional (3D) permeability fields from electrical potential difference measurements. Traditional inversion and data assimilation methods are used to ingest this ERT data into hydrogeophysical models to estimate permeability. Due to ill-posedness and the curse of dimensionality, existing inversion strategies provide poor estimates and low resolution of the 3D permeability field. Recent advances in deep learning provide us with powerful algorithms to overcome this challenge. This paper presents a deep learning (DL) framework to estimate the 3D subsurface permeability from time-lapse ERT data. To test the feasibility of the proposed framework, we train DL-enabled inverse models on simulation data. Each measurement in both synthetic and field data is standardized by removing the mean and scaling the time-series to unit variance. This pre-processing step is necessary to bring simulation data closer to field observations. Subsurface process models based on hydrogeophysics are used to generate this synthetic data. Training performed on limited simulation data resulted in the DL model over-fitting. An advanced data augmentation based on mixup is implemented to generate additional training samples to overcome this issue. This mixup technique creates weakly labeled (low-fidelity) samples from strongly labeled (high-fidelity) data. The weakly labeled training data is then used to develop DL-enabled inverse models and reduce over-fitting. As both time-lapse ERT (1133048 features/realization) and 3D permeability (585453 features/realization) data samples are from a high-dimensional space, principal component analysis (PCA) is employed to reduce dimensionality. Encoded ERT and encoded permeability are generated using the trained PCA estimators. A deep neural network is then trained to map the encoded ERT to encoded permeability. This mixup training and unsupervised learning allowed us to build a fast and reasonably accurate DL-based inverse model under limited simulation data. Results show that proposed weak supervised learning can capture salient spatial features in the 3D permeability field. Quantitatively, the average mean squared error (in terms of the natural log) on the strongly labeled training, validation, and test datasets is less than 0.5. The R 2 -score (global metric) is greater than 0.75, and the percent error in each cell (local metric) is less than 10%. Finally, an added benefit in terms of computational cost is that the proposed DL-based inverse model is at least O(10 4 ) times faster than running a forward model once it is trained. Data generation, DL model training, and hyperparameter tuning to identify optimal neural network architectures utilized high-performance computing resources while the DL inference is performed on a standard laptop. Approximately, O(10 5 ) processor hours are used for generating data and DL tuning and training. We acknowledge that the data generation and DL model development are expensive. But once a DL model is trained, it can be re-used for inversion rapidly for the given system, with set physics and domain. Note that traditional inversion may require multiple forward model simulations (e.g., in the order of 10 to 1000), which are very expensive. This computational savings ≈ O(10 5 ) – O(10 7 )) makes the proposed DL-based inverse model attractive for subsurface imaging and real-time ERT monitoring applications due to fast and yet reasonably accurate estimations of permeability field.

58 GEOSCIENCES↗

DOE OSTI2022

Performance of Lithium-Ion Batteries with 3D Printed Anodes and Compressible Carbon Structures

Carbon scaffolds have been shown to improve the performance of Li metal anodes in Li-ion batteries by acting as conductive hosts for Li metal plating and stripping. The scaffolds provide a more uniform electric field, and their 3D geometry enables smaller diffusion paths for the Li ions. In this project, several different types of carbon lattices were 3D printed, mechanically tested, and analyzed in coin cells. Planar and 3D printed graphite coatings were evaluated as the baseline, since graphite is a common anode material. The results showed that implementing a 3D graphite lattice into a coin cell improved the Li plating and stripping efficiency compared to the planar coating. However, since graphite can intercalate Li ions, other carbon materials were also explored that should act as better hosts for Li plating/stripping. To improve the compressibility of these non-graphite carbon scaffolds, five different carbon ink formulations were 3D printed in lattice configurations. SEM imaging and compression testing showed that both the final dimensions and the compressibility of the carbon lattices depended on the type of carbon precursors used. The two most suitable compositions were found to be those made with graphene oxide-resorcinol formaldehyde and graphene oxide-ammonium hydroxide. In the future, these formulations will be further refined to increase their mechanical strength, and their performance as scaffold hosts for Li metal anodes will be evaluated in coin cells.

25 ENERGY STORAGE↗

DOE OSTI2023

Resonance cones in cold plasma: Origin, singularities, and power flow

In magnetized tenuous plasma, typical at the plasma edge of fusion devices, a nearly electrostatic wave mode with relatively enhanced electric field can propagate along a specific angle with the magnetic field. For this characteristic, it is known as a “resonance cone.” For instance, these waves can be excited by radio frequency antennas in the ion-cyclotron and lower-hybrid range of frequencies. We consider the resonance cones emitted by idealized spatially extended sources. In 2D, we use a novel geometric construction which generalizes the d'Alembert solution to curved boundaries/moving sources, and show, for the first time, that singular electric fields arise under these conditions, thereby bringing the resonance cones in line with the other resonances of the cold plasma theory. Still in 2D, we give an expression for the amount of power radiated by resonance cones in terms of surface quantities on the source, which is finite despite the singular electric field. In conclusion, we generalize the conclusions regarding the presence and location of singular electric fields to the 3D electromagnetic case.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Three-dimensional modeling of electric-field enhancement in multilayer dielectric gratings arising from inadvertent flaws

Pulse-compression gratings for high-power, short-pulse laser systems are exposed to high electric fields that are further enhanced locally due to their 2D nanostructured surface. This makes them vulnerable to laser-induced damage. The present work considers the effect on electric-field modulation caused by an array of commonly found inadvertent flaws in gratings including fabrication defects, contamination particles, and laser-induced–damage initiation. These defects affect the laser-damage performance characteristics of the grating. To understand the local field-enhancement distribution due these imperfections, 3D modeling of the electric-field distribution is performed with a sufficiently high resolution of 1/74 of the laser wavelength ( λ ) while considering a volume of ≈489 λ 3 . The results provide estimates for the ensuing electric-field intensification and projected reduction of the laser-damage thresholds, as well as the anticipated pattern of damage growth initiation.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Perovskite Grown in Gallium Nitride Nanowire Matrix for Stable and High‐Efficiency X‐Ray Detection

High-quality quasi-2D perovskites in a GaN nano-wire matrix are grown to build a 3D hetero-structure for high-performance X-ray sensing. In the 3D hetero-structure, GaN nano-wire matrix serves as an n-type charge collector that can rapidly extract carriers through the bulk film of the perovskite layer. Together with a p-type top electrode, a p–i–n diode with the 3D hetero-structure is built, that exhibits a rectified current–voltage characteristic. After analyzing the interface energy alignment, it is found that the fermi levels of the perovskite and GaN are aligned in the dark, and a quasi-fermi level splits upon illumination, introducing a built-in electrical field at the interface. As a result, strong photo-induced current is observed from the diode without an external field. Finally, the 3D diode for X-ray detection demonstration is used, revealing a sensitivity of 308.9 µC Gy air -1 cm -2 at an exceptionally low applied field of 0.125 V µm -1 . The X-ray-induced signal from the 3D diode is stable after 155 cycles of X-ray irradiation under a constant electric field. This demonstration informs a new 3D architecture for high-performance X-ray sensing, and it shows that GaN is a robust n-type interface for perovskite optoelectronic devices.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Topology Optimization of 3D Flow Fields for Flow Batteries

We report as power generated from renewables becomes more readily available, the need for power-efficient energy storage devices, such as redox flow batteries, becomes critical for successful integration of renewables into the electrical grid. An important aspect of a redox flow battery is the planar flow field, which is usually composed of two-dimensional channels etched into a backing plate. As reactant-laden electrolyte flows into the flow battery, the channels in the flow field distribute the fluid throughout the reactive porous electrode. We utilize topology optimization to design flow fields with full three-dimensional geometry variation, i.e., 3D flow fields. Specifically, we focus on vanadium redox flow batteries and use the optimization algorithm to generate 3D flow fields evolved from standard interdigitated flow fields by minimizing the electrical and flow pressure power losses. To understand how these 3D designs improve performance, we analyze the polarization of the reactant concentration and exchange current within the electrode to highlight how the designed flow fields mitigate the presence of electrode dead zones. While interdigitated flow fields can be heuristically engineered to yield high performance by tuning channel and land dimensions, such a process can be laborious; this work provides a framework for automating that design process.

25 ENERGY STORAGE↗

DOE OSTI2023

Insights Into Lightning K‐Leader Initiation and Development From Three Dimensional Broadband Interferometric Observations

Abstract We report detailed observations of K‐leaders and the activity between them with the three‐dimensional Broadband Interferometric Mapping and Polarization system (BIMAP‐3D) at Los Alamos National Laboratory. It is found that K‐leaders have a general propagation trend of initial acceleration and then gradual deceleration, and the corresponding very high frequency (VHF) radiation power is exponentially correlated with the leader speed. Based on the 3D development and simultaneous electric field change measurement, some simple K‐leaders can be modeled with time‐evolving point charges at the propagating leader tip and at the stationary origin. We found that the charge magnitude increases during the initial acceleration stage and stays relatively constant for the rest of the development. K‐leaders are observed to interact with other branches; the branches affect the leader's propagation speed, and may affect the charge transfer. After the occurrence of a K‐leader, VHF emissions are quenched for several milliseconds. VHF sources then reappear in an impulsive and scattered manner as “twinkling,” and these sources are found not uniquely on the so‐called needles, but also on the main channel. These twinkling sources start near the apparent positive leader tip, and extend back toward the direction of the flash origin at about 10 5 m/s, while the apparent positive tip continues to extend forward at about 10 4 m/s. The twinkling extending toward the direction of flash origin appears to initiate the following K‐leader, although it may be interrupted by a K‐leader along a different branch, or simply die out without more K‐leader activity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Real space iterative reconstruction for vector tomography (RESIRE-V)

Tomography has had an important impact on the physical, biological, and medical sciences. To date, most tomographic applications have been focused on 3D scalar reconstructions. However, in some crucial applications, vector tomography is required to reconstruct 3D vector fields such as the electric and magnetic fields. Over the years, several vector tomography methods have been developed. Here, we present the mathematical foundation and algorithmic implementation of REal Space Iterative REconstruction for Vector tomography, termed RESIRE-V. RESIRE-V uses multiple tilt series of projections and iterates between the projections and a 3D reconstruction. Each iteration consists of a forward step using the Radon transform and a backward step using its transpose, then updates the object via gradient descent. Incorporating with a 3D support constraint, the algorithm iteratively minimizes an error metric, defined as the difference between the measured and calculated projections. The algorithm can also be used to refine the tilt angles and further improve the 3D reconstruction. To validate RESIRE-V, we first apply it to a simulated data set of the 3D magnetization vector field, consisting of two orthogonal tilt series, each with a missing wedge. Our quantitative analysis shows that the three components of the reconstructed magnetization vector field agree well with the ground-truth counterparts. We then use RESIRE-V to reconstruct the 3D magnetization vector field of a ferromagnetic meta-lattice consisting of three tilt series. Our 3D vector reconstruction reveals the existence of topological magnetic defects with positive and negative charges. We expect that RESIRE-V can be incorporated into different imaging modalities as a general vector tomography method. To make the algorithm accessible to a broad user community, we have made our RESIRE-V MATLAB source codes and the data freely available at https://github.com/minhpham0309/RESIRE-V.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Kimberlina 1.2 CCUS Geophysical Models and Synthetic Data Sets

This synthetic multi-scale and multi-physics data set was produced in collaboration with teams at the Lawrence Berkeley National Laboratory, National Energy Technology Laboratory, Los Alamos National Laboratory, and Colorado School of Mines through the Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative. Data are associated with the following publication: Alumbaugh, D., Gasperikova, E., Crandall, D., Commer, M., Feng, S., Harbert, W., Li, Y., Lin, Y., and Samarasinghe, S., “The Kimberlina Synthetic Geophysical Model and Data Set for CO2 Monitoring Investigations”, The Geoscience Data Journal, 2023, DOI: 10.1002/gdj3.191. The dataset uses the Kimberlina 1.2 CO2 reservoir flow model simulations based on a hypothetical CO2 storage site in California (Birkholzer et al., 2011; Wainwright et al., 2013). Geophysical properties models (P- and S-wave seismic velocities, saturated density, and electrical resistivity) were produced with an approach similar to that of Yang et al. (2019) and Gasperikova et al. (2022) for 100 Kimberlina 1.2 reservoir models. Links to individual resources are provided below: [CO2 Saturation Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-co2-saturation-models); Resistivity Models – [part 1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-1), [part 2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-2), and [part 3](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-3); [Vp Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vp-velocity-models); [Vs Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vs-velocity-models); [Density Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-density-models). The 3D distributions of geophysical properties for the 33 time stamps of the SIM001 model were used to generate synthetic seismic, gravity, and electromagnetic (EM) responses for 33 times between zero and 200 years. Synthetic surface seismic data were generated using 2D and 3D finite-difference codes that simulate the acoustic wave equation (Moczo et al., 2007). 2D data were simulated for six point-pressure sources along a 2D line with 10 m receiver spacing and a time spacing of 0.0005 s. 3D simulations were completed for 25 surface pressure sources using a source separation of 1 km in both the x and y directions and a time spacing of 0.001 s. Links to individual resources are provided below: [2D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-velocity-models) and [2D surface seismic data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-surface-seismic-data). [3D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-velocity-models), and 3D seismic data [year0](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year0), [year1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year1), [year2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year2), [year5](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year5), [year10](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year10), [year15](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year15), [year20](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year20), [year25](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year25), [year30](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year30), [year35](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year35), [year40](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year40), [year45](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year45), [year49](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year49), [year50](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year50), [year51](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year51), [year52](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year52), [year55](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year55), [year60](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year60), [year65](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year65), [year70](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year70), [year75](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year75), [year80](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year80), [year85](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year85), [year90](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year90), [year95](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year95), [year100](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year100), [year110](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year110), [year120](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year120), [year130](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year130), [year140](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year140), [year150](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year150), [year175](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year175), [year200](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year200). The Python scripts to read these models and data are provided [here](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-python-scripts). EM simulations used a borehole-to-surface survey configuration, with the source located near the reservoir level and receivers on the surface using the code developed by Commer and Newman (2008). Pseudo-2D data for the source at [2500 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz2500m) and [3025 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz3025m), used a 2D inline receiver configuration to simulate a response over 3D resistivity models. The [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-csem-data) contain electric fields generated by borehole sources at monitoring well locations and measured over a surface receiver grid. Vector gravity data, both on the surface and in boreholes, were simulated using a modeling code developed by Rim and Li (2015). The simulation scenarios were parallel to those used for the EM: [pseudo-2D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were calculated along the same lines and within the same boreholes, and [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were simulated over 3D models on the surface and in three monitoring wells. A series of [synthetic well logs](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-well-logs) of CO2 saturation, acoustic velocity, density, and induction resistivity in the injection well and three monitoring wells are also provided at 0, 1, 2, 5, 10, 15, and 20 years after the initiation of injection. These were constructed by combining the low-frequency trend of the geophysical models with the high-frequency variations of actual well logs collected in the Kimberlina 1 well that was drilled at the proposed site. Measurements of permeability and pore connectivity were made on cores of Vedder Sandstone, which forms the primary reservoir unit: [CT micro scans](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-ct-micro-scans-of-vedder-formation) and [Industrial CT Images](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-industrial-ct-images-vedder-formation). These measurements provide the range of scales in the otherwise synthetic data set to be as close to a real-world situation as possible. References: Birkholzer, J.T., Zhou, Q., Cortis, A. and Finsterle, S., 2011. A sensitivity study on regional pressure buildup from large-scale CO2 storage projects. Energy Procedia, 4, 4371-4378. Commer, M., and Newman, G.A., 2008. New advances in three-dimensional controlled-source electromagnetic inversion, Geophysical Journal International, 172, 513-535. Gasperikova, E., Appriou, D., Bonneville, A., Feng, Z., Huang, L., Gao, K., Yang, X., Daley, T., 2022, Sensitivity of geophysical techniques for monitoring secondary CO2 storage plumes, Int. J. Greenh. Gas Control, Volume 114, 103585, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2022.103585. Moczo, P., J.O. Robertsson and L. Eisner, 2007, The finite-difference time-domain method for modeling of seismic wave propagation: Advances in geophysics, 48, 421-516. Rim, H., and Y. Li, 2015, Advantages of borehole vector gravity in density imaging, Geophysics, 80, G1-G13. Wainwright, H. M.; Finsterle, S.; Zhou, Q.; Birkholzer, J. T., 2013. Modeling the Performance of Large-Scale CO2 Storage Systems: A Comparison of Different Sensitivity Analysis Methods. International Journal of Greenhouse Gas Control, 17, 189205. https://doi.org/10.1016/j.ijggc.2013.05.007, DOI: 10.18141/1603331. Yang, X., Buscheck, T.A., Mansoor, K., Wang, Z., Gao, K., Huang, L., Appriou, D., and Carroll, S.A., 2019. Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers, International Journal of Greenhouse Gas Control, 90, 102803, https://doi.org/10.1016/j.ijggc.2019.102803.

CCUS↗

DOE OSTI2025

Electric Drive Technologies Consortium (EDTC)/ Cost competitive, high-Performance, highly Reliable (CPR) Power Devices on 4H-SiC (Final Report)

4H-Silicon carbide (4H-SiC) is a wide bandgap semiconductor that offers superior material properties over silicon, including higher critical electric field, thermal conductivity, and electron saturation velocity. These advantages make 4H-SiC highly attractive for high-voltage, high-efficiency power electronics. However, realizing the full potential of SiC requires device technologies that are not only high-performing but also manufacturable and reliable under real-world operating conditions. This report summarizes the outcomes of a five-year R&D effort funded by the U.S. Department of Energy (DOE) under the Electric Drive Technologies Consortium (EDTC), focused on developing cost-competitive, high-performance, and highly reliable (CPR) power devices on 4H-SiC substrates. The program targeted scalable and manufacturable 1.2 kV-class SiC MOSFETs optimized for next-generation electric vehicles, renewable energy systems, and industrial power conversion. The project delivered transformative advancements in SiC power device performance and ruggedness. Particularly, Specific on-resistance (R on,sp ) was reduced by up to 37%, from ~4.0 m$\Omega \cdot$cm 2 in earlier designs to an industry-leading 2.40 m$\Omega \cdot$cm 2 , driven by optimized doping, refined JFET widths, and layout engineering. Breakdown voltages (BV) exceeded 1600 V, marking improvement over legacy baselines, and demonstrating the robustness of newly implemented junction profiles and edge terminations. Short-circuit withstand time (SCWT) saw a remarkable 4$\times$ increase, from ~2 $\mu$s to over 8 $\mu$s, achieved through the successful deployment of deep P-well structures (~1.8–2.0 $\mu$m) via channeling implantation. This innovative process breakthrough enabled precise junction formation without MeV-class implantation tools, reduced leakage under high field stress, and allowed even the shortest-channel devices (down to 0.3 $\mu$m) to achieve both high BV and excellent ruggedness—breaking the traditional trade-off between conduction efficiency and blocking capability. Several novel architectures pushed the performance envelope further. JBSFETs—featuring embedded Schottky portions—eliminated bipolar degradation and drastically reduced third-quadrant leakage, while Ladder MOSFETs introduced a clever orthogonal conduction path that achieved a 15.4% reduction in R on,sp over standard linear designs. Switching performance reached new benchmarks: short-channel devices showed a 31% reduction in total switching energy compared to 0.5 $\mu$m counterparts, while maintaining manageable gate drive requirements. Layout-optimized structures not only improved transconductance but also accelerated switching transitions, pointing to real-world benefits in converter-level efficiency. The devices also passed rigorous reliability validation. Stress-tested across TDDB, HTGB, HTRB, HVP, and burn-in, the devices screened under 30 V/10 hr and 43 V/1 s protocols consistently exhibited tighter lifetime distributions and long-term oxide robustness. These screening techniques proved effective in identifying latent defects and ensuring deployment-grade reliability. Meanwhile, advanced 3D TCAD simulations revealed and resolved electric field hotspots—particularly in HEXFET corners—where fields exceeding 4.8 MV/cm were mitigated through geometry-aware layout corrections. Overall, the results of this project demonstrate a manufacturable and scalable SiC power device platform that addresses key DOE performance targets for efficient, robust, and reliable 1.2kV 4H-SiC Power Devices. The developed technologies represent a meaningful step forward in the commercial readiness of high-voltage SiC solutions and provide a strong foundation for continued advancement in wide bandgap power electronics.

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DOE OSTI2021

Advanced strategies for the development of porous carbon as a Li host/current collector for lithium metal batteries

Lithium metal is considered a promising anode material for high-energy-density rechargeable batteries because of its high specific theoretical capacity (3860 mAh g -1 , low mass density (0.534 g cm -3 ), and low electrochemical redox potential (-3.04 V vs. the standard hydrogen electrode). However, the high reactivity of Li with the electrolyte leads to the formation of an unstable solid electrolyte interphase (SEI) and continuous side reactions. Also, the non-uniform lithium-ion flux and infinite volume expansion of Li metal cause the growth of Li dendrites. These pose significant safety challenges and cause rapid capacity fading of the lithium metal batteries (LiMBs). To resolve these issues, a low-cost, easily processed, lightweight, high-performance carbon-based porous matrix is considered promising to host Li metal deposition. The three-dimensional (3D) porous nano/microstructured carbon provides sufficient space for Li accommodation during Li plating, buffers the volume changes during Li plating/stripping, and lowers the effective current density contributing to dendrite-free Li deposition. Besides, the outstanding electrochemical and mechanical stability, flexibility and the high electronic conductivity enable the nano/microstructured carbon to serve as both Li host and current collector. The development of 3D carbon/Li composite by mechanical roll-press techniques not only eliminates the complex and risky procedure of making carbon/Li composite based on Li plating or molten Li infusion but also stabilizes the capacity at higher Li plating/stripping rates. Recently, there is an advancement in the lithiophilic decorations of 3D structure to introduce sufficient nucleation sites and the development of artificial SEI on top of the 3D matrix to suppress Li dendrite formation. Such 3D structural modifications create a uniform electric field, lower the Li nucleation overpotential, provide strong mechanical and chemical stability, and stabilize the interface thereby inhibiting the degradation of lithium and the electrolyte. Here we summarize the research progress on porous carbon/Li composites in terms of materials type, structure, fabrication technique, their electrochemical battery performance, and identify the critical challenges that need to be addressed for high-energy-density practical LiMBs.

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DOE OSTI2026

Numerical Investigation of Fluid Flow and Space Charge in Liquid Argon Time Projection Chamber (LArTPC) Detectors

Overview This project focused on developing a high-fidelity numerical framework to simulate the multiphysics environment within Liquid Argon Time Projection Chamber (LArTPC) detectors. The primary objective was to characterize the complex interplay between ion transport, background fluid dynamics, and electric field distortions—a critical factor for the calibration and sensitivity of next-generation High Energy Physics experiments, such as DUNE. Technical Achievements The research successfully yielded a hybrid numerical space-charge solver utilizing a Cell-Centered Finite Volume Method (FVM) for ion transport coupled with a Finite Element Method (FEM) for electric potential. Key accomplishments include: • Verification & Validation: The 3-D solver was rigorously verified against 1-D analytical solutions, demonstrating high numerical accuracy in predicting space-charge-induced field deviations. • Field Distortion Analysis: 3D simulations revealed that space charge effects introduce significant non-uniformities in the electric field. Critically, the research identified that background LAr flow velocities, when comparable to ion drift velocities, markedly exacerbate these distortions. • Technology Transfer: The resulting source code and comprehensive user manuals were successfully transferred to collaborators at Fermilab, providing a portable computational tool for the broader scientific community. Challenges and Future Directions While the space-charge solver achieved all performance metrics, the integrated fluid dynamics modeling encountered convergence challenges stemming from the extreme 200-fold disparity in length scales between the detector's 37 mm inlet pipes and the 8-meter global domain. To address this, the project has identified a clear technical pivot toward Hierarchical Geometric Adaptive Mesh Refinement (HG-AMR). By implementing an h-type refinement strategy with hanging nodes, future iterations of this solver will be capable of resolving localized high-gradient inlet flows without the prohibitive computational costs of regular grids. This advancement, combined with data-driven uncertainty quantification based on MicroBooNE-style calibration, will enable the precise modeling of detector responses in large-scale cryogenic environments where direct measurement remains difficult. Impact The computational tools developed under this award provide a foundation for enhancing the energy resolution and spatial reconstruction of noble liquid detectors. By bridging the gap between theoretical fluid dynamics and experimental field calibration, this work supports the DOE’s mission to advance the frontiers of neutrino physics and dark matter detection.

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