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DOE OSTI2022

Fluid – Fluid Interfacial Area and Its Impact on Relative Permeability - A Pore Network Modeling Study

Abstract Relative permeability (kr) is commonly modeled as an empirical function of phase saturation. Although current empirical models can provide a good match of one or two measured relative permeabilities using saturation alone, they are unable to predict relative permeabilities well when there is hysteresis or when physical properties such as wettability change. Further, current models often result in relative permeability discontinuities that can cause convergence and accuracy problems in simulation. To overcome these problems, recent research has modeled relative permeability as a state function of both saturation (S) and phase connectivity (X). Pore network modeling (PNM) data, however, shows small differences in relative permeability for the same S-X value when approached from a different flow direction. This paper examines the impact of one additional Minkowski parameter (Mecke and Arns, 2005), the fluid-fluid interfacial area, on relative permeability to identify if that satisfactorily explains this discrepancy. We calculate the total fluid-fluid interfacial areas (IA) during two-phase (oil/water) flow in porous media using pore network modeling. The area is calculated from PNM simulations using the areas associated with corners and throats in pore elements of different shapes. The pore network is modeled after a Bentheimer sandstone, using square, triangular, and circular pore shapes. Simulations were conducted for numerous primary drainage and imbibition cycles at a constant contact angle of 0° for the wetting phase. Simultaneous measurements of capillary pressure, relative permeability, saturation, and phase connectivity are made for each displacement. Fluid-fluid interfacial area is calculated from the PNM capillary pressure, the fluid location in the pore elements, and the pore element dimensional data. The results show that differences in the relative permeability at the same (S,X) point is explained well by differences in the fluid-fluid interfacial area (IA). That is, for a larger change in IA at these intersection points, the permeability difference is greater. That difference in relative permeability approaches zero as the difference in IA approaches zero. This confirms that relative permeability can be modeled better as a unique function of S, X, and IA. The results also show that an increase in IA restricts flow decreasing the nonwetting (oil) phase permeability. This decrease is caused by an increase in the throat area fraction compared to the corner area as the total area IA increases. The wetting phase relative permeability, however, shows the inverse trend, in that its relative permeability is greater when IA becomes larger owing to a greater fraction of the total area associated with the corners. The area IA, however, impacts the nonwetting phase relative permeability more than the wetting phase relative permeability. Corner flow improves the wetting phase relative permeability because the wetting phase is continuous there. Finally, a sensitivity analysis shows that relative permeability a is more sensitive to change in S than they are for IA for the case studied implying that if only two parameters are used to model relative permeability it is better to choose S and X.

Engineering↗

NASA NTRS1990

Comparison between analytical models and finite-difference simulations in transmission-line tap resistors and L-type cross-Kelvin resistors

Approximate analytical models of the transmission-line tap resistor and the cross-Kelvin resistor are compared with computer-simulated pseudo-three-dimensional resistor network models. The analytical formulas are in good agreement with the simulations over a useful range of parameters and are readily applied to the extraction of the contact resistivity and the sheet resistances of the semiconducting layer under and outside the contacts. The extraction procedure, which is easily implemented on a personal computer, is carried out for the case of alloyed AuGeNi/GaAs contacts, illustrating the importance of (1) distinguishing between layer sheet resistance under and outside the contacts and (2) considering two-dimensional current flow in the semiconducting layer.

Scorzoni, Andrea↗

NASA NTRS2003

The 2002 NASA Faculty Fellowship Program Research Reports

Contents include the following: System Identification of X-33. Neural Network Advanced Ceramic Technology for Space Applications at NASA MSFC. Developing a MATLAB-Based Tool for Visualization and Transformation. Subsurface Stress Fields in Single Crystal (Anisotropic). Contacts Our Space Future: A Challenge to the Conceptual Artist Concept Art for Presentation and Education. Identification and Characterization of Extremophile Microorganisms. Significant to Astrobiology. Mathematical Investigation of Gamma Ray and Neutron. Absorption Grid Patterns for Homeland Defense-Related Fourier Imaging Systems. The Potential of Microwave Radiation for Processing Martian Soil. Fuzzy Logic Trajectory Design and Guidance for Terminal Area.

Bland, J.↗

DOE OSTI2022

Clean Cities Coalitions: Advancing Affordable, Domestic Transportation Fuels and Technologies Across the Country

This fact sheet provides an overview of the U.S. Department of Energy's (DOE's) Vehicle Technologies Office Clean Cities Coalition Network, which advances affordable, domestic transportation fuels and technologies nationwide. More than 75 active coalitions serve as the foundation of Clean Cities, working in communities across the country to help local decision makers and fleets understand and implement alternative and renewable fuels, idle-reduction measures, fuel economy improvements, new mobility choices, and emerging transportation technologies. At the national level, VTO develops and promotes publications, tools, and other unique resources to support coordinators. At the local level, coalitions leverage these resources to create networks of stakeholders.

accomplishments↗

DOE OSTI2020

Multi-hydrophilic functional network enables porous membranes excellent anti-fouling performance for highly efficient water remediation

Membrane technology is believed as a cost-effective approach for solving the water issues, where as it suffers from serious membrane fouling. Surface grafting and surface coating have been proved to be effective in abating the membrane fouling; however, these processes always need additional procedures and compromise the initial permeance of the membranes. Herein, we developed a kind of highly permeable polyacrylonitrile (PAN) membranes with excellent anti-fouling performance through one-step phase inversion of the PAN casting solution containing water-soluble active additives. During the process, the water-soluble active additives could segregate towards the membrane surface and pore walls; thereby finely tailoring the pore structures of the PAN-based membranes. Moreover, the active additives could react with each other to form crosslinked networks containing multi-hydrophilic functional groups including CH2-O-CH2, -OH or-Si-OH. Consequently, the PAN-based membranes exhibited surprising superhydrophilicity with water contact angle below 10. even after soaking in water for one week and the anti-fouling permeance of the membranes increased significantly with permeance recovery rate above 93%. Interestingly, the modified membranes also demonstrated both high permeances and high separation efficiency, thereby showing strong promise in water environmental remediation including wastewater treatment and oil/water emulsion separation.

Anti-fouling↗

NASA NTRS2013

Bulk Moisture and Salinity Sensor

Measurement and feedback control of nutrient solutions in plant root zones is critical to the development of healthy plants in both terrestrial and reduced-gravity environments. In addition to the water content, the amount of fertilizer in the nutrient solution is important to plant health. This typically requires a separate set of sensors to accomplish. A combination bulk moisture and salinity sensor has been designed, built, and tested with different nutrient solutions in several substrates. The substrates include glass beads, a clay-like substrate, and a nutrient-enriched substrate with the presence of plant roots. By measuring two key parameters, the sensor is able to monitor both the volumetric water content and salinity of the nutrient solution in bulk media. Many commercially available moisture sensors are point sensors, making localized measurements over a small volume at the point of insertion. Consequently, they are more prone to suffer from interferences with air bubbles, contact area of media, and root growth. This makes it difficult to get an accurate representation of true moisture content and distribution in the bulk media. Additionally, a network of point sensors is required, increasing the cabling, data acquisition, and calibration requirements. measure the dielectric properties of a material in the annular space of the vessel. Because the pore water in the media often has high salinity, a method to measure the media moisture content and salinity simultaneously was devised. Characterization of the frequency response for capacitance and conductance across the electrodes was completed for 2-mm glass bead media, 1- to 2-mm Turface (a clay like media), and 1- to 2-mm fertilized Turface with the presence of root mass. These measurements were then used to find empirical relationships among capacitance (C), the dissipation factor (D), the volumetric water content, and the pore water salinity.

Nurge, Mark↗

DOE OSTI2025

Accelerating computational fluid dynamics simulation of post-combustion carbon capture modeling with MeshGraphNets

Packed columns are commonly used in post-combustion processes to capture CO 2 emissions by providing enhanced contact area between a CO 2 -laden gas and CO 2 -absorbing solvent. To study and optimize solvent-based post-combustion carbon capture systems (CCSs), computational fluid dynamics (CFD) can be used to model the liquid–gas countercurrent flow hydrodynamics in these columns and derive key determinants of CO 2 -capture efficiency. However, the large design space of these systems hinders the application of CFD for design optimization due to its high computational cost. In contrast, data-driven modeling approaches can produce fast surrogates to study large-scale physics problems. We build our surrogates using MeshGraphNets (MGN), a graph neural network framework that efficiently learns and produces mesh-based simulations. We apply MGN to a random packed column modeled with over 160K graph nodes and a design space consisting of three key input parameters: solvent surface tension, inlet velocity, and contact angle. Our models can adapt to a wide range of these parameters and accurately predict the complex interactions within the system at rates over 1700 times faster than CFD, affirming its practicality in downstream design optimization tasks. This underscores the robustness and versatility of MGN in modeling complex fluid dynamics for large-scale CCS analyses.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Shape Anisotropy-Dependent Leaking in Magnetic Neurons for Bio-Mimetic Neuromorphic Computing

Spiking neural networks seek to emulate biological computation through interconnected artificial neuron and synapse devices. Spintronic neurons can leverage magnetization physics to mimic biological neuron functions, such as integration tied to magnetic domain wall (DW) propagation in a patterned nanotrack and firing tied to the resistance change of a magnetic tunnel junction (MTJ), captured in the domain wall-magnetic tunnel junction (DW-MTJ) device. Leaking, relaxation of a neuron when it is not under stimulation, is also predicted to be implemented based on DW drift as a DW relaxes to a low energy position, but it has not been well explored or demonstrated in device prototypes. Here, in this work, we study DW-MTJ artificial neurons capable of leaky integrate-and-fire (LIF) behavior and demonstrate geometry-dependent leaking dynamics that results in repeatable, tunable LIF operation. Studying the behavior of five different device designs, we show tuning the geometry, stimulating fields and currents, and location of electrical contacts results in a wide range of neuron behavior. Additionally, implementation of an asymmetric notch allows for nonlinear pinning which increased expressivity without sacrificing leaking. The measured behavior is implemented in a simulated spiking neural network that outperforms a 1D model of continuous DW motion and approaches the performance of an ideal LIF activation function. The results show that the analog LIF capability of DW-MTJ neurons combines many desirable neuron functions into a single device, which can result in varied forms of multifunctional neuromorphic computing.

42 ENGINEERING↗

DOE OSTI2022

Time-resolved 3D characterisation of early-age microstructural development of Portland cement

Abstract Time-resolved in-situ synchrotron X-ray microtomography reveals new levels of detail about the chemical and physical processes that take place as Portland cement hardens. The conversion of a fluid paste into a hardened product can be monitored on a sub-minute time-scale, and with sample movement/settlement corrections applied to enable individual particles to be tracked as they react, hydrate, and become interconnected into a single strong monolith. The growth of the strength-giving hydrate phases surrounding cement grains, and of the fluid-filled pore network that surrounds them, is able to be directly viewed at the level of individual cement particles through the application of this tracking protocol. When cement is brought into contact with water, a layer which differs in density from the bulk of the cement grains becomes observable on the grain surfaces during the induction period (during which time the heat evolution from the paste is relatively low). As hydration continues, reaction products grow both from particle surfaces into the initially fluid-filled region, and also into the space originally occupied by the cement particles, forming a density gradient within the microstructure. As the reaction accelerates and larger volumes of solid phases precipitate, the newly-formed solid structure percolates via interconnection of agglomerated low-density outer hydrates, which then densify as hydration continues. This eventually leads to solidification of the structure into a hardened porous matrix. Graphical abstract

36 MATERIALS SCIENCE↗

DOE OSTI2021

Electrochemistry-Induced Restructuring of Tin-Doped Indium Oxide Nanocrystal Films of Relevance to CO 2 Reduction

The electrochemical reduction of CO 2 into fuels using renewable electricity presents an opportunity to utilize captured CO 2 . Electrocatalyst development has been a primary focus of research in this area. This is especially true at the nanoscale, where researchers have focused on understanding nanostructure-property relationships. However, electrocatalyst structure may evolve during operation. Indium- and tin-based oxides have been widely studied as electrocatalysts for CO 2 reduction to formate, but evolution of these catalysts during operation is not well-characterized. Here, we report the evolution of nanoscale structure of precise tin-doped indium oxide nanocrystals under CO 2 reduction conditions. We show that sparse monolayer nanocrystal films desorb from the electrode upon charging, but thicker nanocrystal films remain, likely due to an increased number of physical contacts. Upon applying a cathodic voltage of –1.0 V vs RHE or greater, the original 10-nm diameter nanocrystals are no longer visible, and instead form a larger microstructural network. Elemental analysis suggests the network is an oxygen-deficient indium-tin metal alloy. We hypothesize that this morphological evolution is the result of nanocrystal sintering due to oxide reduction. Furthermore, these data provide insights into the morphological evolution of tin-doped indium oxide nanocrystal electrocatalysts under reducing conditions and highlight the importance of post-electrochemical structural characterization of electrocatalysts.

25 ENERGY STORAGE↗

NASA NTRS1992

Data management for community research projects: A JGOFS case study

Since the mid 1980s, much of the marine science research effort in the United Kingdom has been focused into large scale collaborative projects involving public sector laboratories and university departments, termed Community Research Projects. Two of these, the Biogeochemical Ocean Flux Study (BOFS) and the North Sea Project incorporated large scale data collection to underpin multidisciplinary modeling efforts. The challenge of providing project data sets to support the science was met by a small team within the British Oceanographic Data Centre (BODC) operating as a topical data center. The role of the data center was to both work up the data from the ship's sensors and to combine these data with sample measurements into online databases. The working up of the data was achieved by a unique symbiosis between data center staff and project scientists. The project management, programming and data processing skills of the data center were combined with the oceanographic experience of the project communities to develop a system which has produced quality controlled, calibrated data sets from 49 research cruises in 3.5 years of operation. The data center resources required to achieve this were modest and far outweighed by the time liberated in the scientific community by the removal of the data processing burden. Two online project databases have been assembled containing a very high proportion of the data collected. As these are under the control of BODC their long term availability as part of the UK national data archive is assured. The success of the topical data center model for UK Community Research Project data management has been founded upon the strong working relationships forged between the data center and project scientists. These can only be established by frequent personal contact and hence the relatively small size of the UK has been a critical factor. However, projects covering a larger, even international scale could be successfully supported by a network of topical data centers managing online databases which are interconnected by object oriented distributed data management systems over wide area networks.

Lowry, Roy K.↗

DOE OSTI2025

Tunable Crosslinked Ether Polymer Network Electrolytes for High‐Performance All‐Solid‐State Sodium Batteries

All-solid-state batteries (ASSBs) are critical for achieving high energy density and enhanced safety. Solid polymer electrolytes (SPEs) offer key advantages over other electrolytes, including improved safety, flexibility, and interfacial contact. Among the SPEs, ether-based polymers are widely studied due to their ease of processing and high ionic conductivity (σi) in the amorphous state. In this work, the introduction of poly(ethylene glycol) methyl ether methacrylate (PEGMEMA) into an SPE matrix composed of poly(ethylene glycol) diacrylate (PEGDA), poly(ethylene glycol) (PEG2k), and sodium bis(fluorosulfonyl)imide (NaFSI) salt is investigated to facilitate the formation of amorphous, high σ i SPEs through end-group engineering and polymer ratio optimization. PEGMEMA enhances structural integrity via crosslinking with PEGDA through its methacrylate group, while its methyl end group aids ion conduction. A 2:1:7 ratio of PEGDA:PEGMEMA:PEG2k exhibits a σi of 1.16 x 10 -4 S cm -1 and oxidative stability up to 4.4 V at 60 °C. A solid-state cell incorporating this SPE, a Na 2/3 Ni 1/3 Mn 2/3 O 2 (NM12) cathode, and a sodium-metal anode demonstrates excellent cycling stability, retaining over 80 % of its initial capacity for 150 cycles at 60 °C. The findings highlight the potential of end-group engineering in improving the electrochemical performance of SPEs.

25 ENERGY STORAGE↗

DOE OSTI2021

Mitochondrial Genomes of the United States Distribution of Gray Fox (Urocyon cinereoargenteus) Reveal a Major Phylogeographic Break at the Great Plains Suture Zone

We examined phylogeographic structure in gray fox (Urocyon cinereoargenteus) across the United States to identify the location of secondary contact zone(s) between eastern and western lineages and investigate the possibility of additional cryptic intraspecific divergences. We generated and analyzed complete mitochondrial genome sequence data from 75 samples and partial control region mitochondrial DNA sequences from 378 samples to investigate levels of genetic diversity and structure through population- and individual-based analyses including estimates of divergence (FST and SAMOVA), median joining networks, and phylogenies. We used complete mitochondrial genomes to infer phylogenetic relationships and date divergence times of major lineages of Urocyon in the United States. Despite broad-scale sampling, we did not recover additional major lineages of Urocyon within the United States, but identified a deep east-west split (~0.8 million years) with secondary contact at the Great Plains Suture Zone and confirmed the Channel Island fox (Urocyon littoralis) is nested within U. cinereoargenteus. Genetic diversity declined at northern latitudes in the eastern United States, a pattern concordant with post-glacial recolonization and range expansion. Beyond the east-west divergence, morphologically-based subspecies did not form monophyletic groups, though unique haplotypes were often geographically limited. Gray foxes in the United States displayed a deep, cryptic divergence suggesting taxonomic revision is needed. Secondary contact at a common phylogeographic break, the Great Plains Suture Zone, where environmental variables show a sharp cline, suggests ongoing evolutionary processes may reinforce this divergence. Follow-up study with nuclear markers should investigate whether hybridization is occurring along the suture zone and characterize contemporary population structure to help identify conservation units. Comparative work on other wide-ranging carnivores in the region should test whether similar evolutionary patterns and processes are occurring.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2009

NASA Tech Briefs, May 2009

Topics covered include: Valve-"Health"-Monitoring System; Microstrip Antenna for Remote Sensing of Soil Moisture and Sea Surface Salinity; Biomedical Wireless Ambulatory Crew Monitor; Wireless Avionics Packet to Support Fault Tolerance for Flight Applications; Aerobot Autonomy Architecture; Submillimeter Confocal Imaging Active Module; Traveling-Wave Maser for 32 GHz; System Synchronizes Recordings from Separated Video Cameras; Piecewise-Planar Parabolic Reflectarray Antenna; Reducing Interference in ATC Voice Communication; EOS MLS Level 1B Data Processing, Version 2.2; Auto-Generated Semantic Processing Services; Geospatial Authentication; Maneuver Automation Software; Event Driven Messaging with Role-Based Subscriptions; Estimating Relative Positions of Outer-Space Structures; Fabricating PFPE Membranes for Capillary Electrophoresis; Linear Actuator Has Long Stroke and High Resolution; Installing a Test Tap on a Metal Battery Case; Fabricating PFPE Membranes for Microfluidic Valves and Pumps; Room-Temperature-Cured Copolymers for Lithium Battery Gel Electrolytes; Catalysts for Efficient Production of Carbon Nanotubes; Amorphous Silk Fibroin Membranes for Separation of CO2; "Zero-Mass" Noninvasive Pressure Transducers; Radial-Electric-Field Piezoelectric Diaphragm Pumps; Ejector-Enhanced, Pulsed, Pressure-Gain Combustor; Suppressing Ghost Diffraction in E-Beam-Written Gratings; Target-Tracking Camera for a Metrology System; Polarimetric Imaging using Two Photoelastic Modulators; Miniature Wide-Angle Lens for Small-Pixel Electronic Camera; Modal Filters for Infrared Interferometry; Mo(3)Sb(7-x)Te(x) for Thermoelectric Power Generation; Two-Dimensional Quantum Model of a Nanotransistor; Scanning Miniature Microscopes without Lenses; Manipulating Neutral Atoms in Chip-Based Magnetic Traps; Expansion Compression Contacts for Thermoelectric Legs; Processing Electromyographic Signals to Recognize Words; Physical Principle for Generation of Randomness; DSN Beowulf Cluster-Based VLBI Correlator; Hybrid NN/SVM Computational System for Optimizing Designs; Criteria for Modeling in LES of Multicomponent Fuel Flow; Computerized Machine for Cutting Space Shuttle Thermal Tiles; Orbiting Depot and Reusable Lander for Lunar Transportation; FPGA-Based Networked Phasemeter for a Heterodyne Interferometer; Aquarius Digital Processing Unit; Three-Dimensional Optical Coherence Tomography; Benchtop Antigen Detection Technique using Nanofiltration and Fluorescent Dyes; Isolation of Precursor Cells from Waste Solid Fat Tissue; Identification of Bacteria and Determination of Biological Indicators; Further Development of Scaffolds for Regeneration of Nerves; Chemically Assisted Photocatalytic Oxidation System; Use of Atomic Oxygen for Increased Water Contact Angles of Various Polymers for Biomedical Applications; Crashworthy Seats Would Afford Superior Protection; Open-Access, Low-Magnetic-Field MRI System for Lung Research; Microfluidic Mixing Technology for a Universal Health Sensor; Microfluidic Extraction of Biomarkers using Water as Solvent; Microwell Arrays for Studying Many Individual Cells; Droplet-Based Production of Liposomes; and Identifying and Inactivating Bacterial Spores

Source record↗

DOE OSTI2023

Machine learning methods for particle stress development in suspension Poiseuille flows

Numerical simulations are used to study the dynamics of a developing suspension Poiseuille flow with monodispersed and bidispersed neutrally buoyant particles in a planar channel, and machine learning is applied to learn the evolving stresses of the developing suspension. The particle stresses and pressure develop on a slower time scale than the volume fraction, indicating that once the particles reach a steady volume fraction profile, they rearrange to minimize the contact pressure on each particle. Here we consider how the stress development leads to particle migration, time scales for stress development, and present a new physics-informed Galerkin neural network that allows for learning the particle stresses when direct measurements are not possible. The particle fluxes are compared with the Suspension Balance Model with good agreement. We show that when stress measurements are possible, the MOR-physics operator learning method can also capture the particle stresses.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

From force chains to nonclassical nonlinear dynamics in cemented granular materials

In this letter, we present evidence for a mechanism responsible for the nonclassical nonlinear dynamics observed in many cemented granular materials that are generally classified as mesoscopic nonlinear elastic materials. We demonstrate numerically that force chains are created within the complex grain-pore network of these materials when subjected to dynamic loading. The interface properties between grains along with the sharp and localized increase of the stress occurring at the grain-grain contacts leads to a reversible decrease of the elastic properties at macroscopic scale and peculiar effects on the propagation of elastic waves when grain boundary properties are appropriately considered. These effects are observed for relatively small amplitudes of the elastic waves, i.e., within tens of microstrain, and relatively large wavelengths, i.e., orders of magnitude larger than the material constituents. The mechanics are investigated numerically using the hybrid finite-discrete-element method and match those observed experimentally using nonlinear resonant ultrasound spectroscopy.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Final Report DE-FE0031785 Mohsen Ahmadian, Ph.D. Demonstration of Proof of Concept of a Multiphysics Approach for Real-Time Remote Monitoring of Dynamic Changes in Pressure and Salinity in Hydraulically Fractured Networks

Hydraulic fracturing has evolved into a multistep process with varying flow rates, carrier fluids (e.g., gel or slickwater), proppant loadings, and proppant grain sizes. As a result, primary recovery from a hydraulically fractured tight-oil reservoir is often a tiny fraction of the original oil in place, ranging between 5 and 10%. As stated in the FOA1990, “part of this problem is due to the inability of current well completion processes to effectively stimulate the entire reservoir volume in contact with the wellbore. Innovative technologies are needed that can help improve the effectiveness of reservoir completion methods, maximize stimulated reservoir volumes, and optimize recovery over the entire producing life span of a well”. We first need to enhance the current fracture diagnostic techniques to improve a well-completion design. However, detecting and delineating a subsurface hydraulic fracture is extremely difficult because the induced fracture network is only fractionally propped, and these propped fractures are generally very thin. Microseismic and tiltmeter monitoring techniques can provide information on the fracture extent but provide little or no information on the movement and final distribution of proppant or production fluids. On the other hand, electromagnetic (EM) imaging has shown the capability to monitor proppant distribution throughout the fracture area, especially in the presence of Electrically Active Proppants (EAPs). A previous EM survey of hydraulic fracturing at the Devine Fracture Pilot Site (DFPS) and subsequent EM code developments demonstrated this survey as a robust technique to remotely interrogate the extent of the EAP-filled hydraulic fracture during its propagation. The objectives of the project were threefold: (1) to capitalize on the material properties of an EAP to demonstrate remote monitoring of relative changes in pressure, pressure, and flow that are commonly encountered during production from a hydraulically fractured reservoir; (2) to evaluate EM imaging tools, to achieve Objective 1 in near real-time; and (3) to develop a multi-physics joint inversion approach to precisely predict flow patterns and physiochemical changes within an EAP-filled fracture network. This research project was built upon our previous work at the Devine Test Site managed by the Bureau of Economic Geology (BEG) at The University of Texas at Austin (UT-Austin). It also leveraged a significant investment from the Advanced Energy Consortium (AEC) to address the DOE's interest in subsurface flow, containment, and characterization by multiple signals. This three-year and three-month project succeeded in demonstrating the feasibility of a real-time dynamic fluid flow mapping technique at Technology Readiness Level 5 (TRL5) by utilizing a commercially available surface-based Controlled-Source Electromagnetic (CSEM) method (Objectives 1, 2). We demonstrated that injections into an EAP-filled fracture could be successfully coupled with real-time electric field measurements on the surface, leading to remote monitoring of dynamic changes within the EAP-filled fracture. Furthermore, the observed electric field in our study is influenced by bottomhole pressure, flow rate, and salinity, which is demonstrated by comparing these parameters with the electrical field potentials. EM simulations solely based on assumptions of fracture conductivity changes during injection did not reproduce the whole measured electric field magnitudes. Preliminary estimates showed that including Streaming Potential (SP) in our geophysical model is likely needed to reduce the simulation misfit.

02 PETROLEUM↗

DOE OSTI2025

Deciphering the Evolution of Current Distribution in Hybrid Silver Vanadium Oxide / Carbon Monofluoride Cathodes within Lithium Primary Batteries

For batteries to function effectively all active material must be accessible requiring both electron and ion transport to each particle. A common approach to generating the needed conductive network is the addition of carbon to create a composite electrode. An alternative approach is the electrochemically induced formation of conductive reaction products where the electrochemically generated materials are in intimate contact with the active material contributing to effective connection of each active particle. Furthermore, this study probes silver vanadium oxide (Ag 2 V 4 O 11 , SVO), carbon monofluoride (CF x ), and hybrid SVO/CF x electrodes in lithium batteries. Ex situ XRD identifies Ag 0 as a reduction product from SVO and LiF from CF x that can be followed as a function of depth-of-discharge (DOD). Spatially-resolved operando energy dispersive x-ray diffraction reveals that the presence of SVO alleviates reaction heterogeneity in the electrodes which are electron transfer limited in the absence of sufficient Ag 0 . Synchrotron X-ray tomography on discharged cathodes reveals the distribution of silver particles where the particles are more closely spaced near the current collector indicating multiple nucleation sites for their formation. Finally, operando isothermal microcalorimetry is used to determine the heat dissipation of the parent and hybrid battery types. Using material enthalpy potentials, we determine the current distribution between the two active materials for the discharging hybrid cathode adding further insight to the diffraction analysis. Taken together, these results provide a comprehensive understanding of hybrid SVO/CF x cathodes and give guidance on optimal compositions that balance power and energy density considerations.

36 MATERIALS SCIENCE↗