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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Leveraging a Neural Network-Enhanced Reproducing Kernel Particle Method for Multiphysics Degradation Modeling of Energy Storage Materials

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and resulting in reduced performance and service life. A coupled electro-chemo-mechanical reproducing kernel particle method (RKPM) formulation has been developed to analyze this system. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based model construction by RKPM is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. Here, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1, 2] is introduced to effectively model damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RKPM is additionally used to inform how crack opening and closure in turn affect the coupled chemical equations and material microstructure. Reference: [1] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, pp 4422-4454, https://doi.org/10.1002/nme.7040, 2022. [2] Baek, J., Chen, J. S., "A Neural Network-Based Enrichment of Reproducing Kernel Approximation for Modeling Brittle Fracture", Computer Methods in Applied Mechanics and Engineering Vol. 410, 116590, 2024.

degradation↗
DOE OSTI2026

Kernel Enriched Meshfree Multiphysics Degradation Modeling of Energy Storage Materials

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and ultimately diminishing performance and service life. With microstructural images supplied by the National Laboratory of the Rockies (NLR), pixel-based meshfree model construction by the reproducing kernel particle method (RKPM) is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. The first kernel enrichment discussed will be the interface modified reproducing kernel (IM-RK) [1, 2], constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The IM-RK is especially useful for areas in which a known discontinuity-type is expected a priori. The second kernel enrichment to be discussed is a neural network-enhanced reproducing kernel (NN-RK) [3, 4], which is introduced to effectively model non-obvious damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RK is additionally used to inform how crack opening and closure in turn affect the electro-chemo-mechanical responses in the material microstructure. References: [1] Wang, Y., Baek, J., Tang, Y. et al. "Support vector machine guided reproducing kernel particle method for image-based modeling of microstructures," Comput Mech 73, 907-942 (2024). https://doi.org/10.1007/s00466-023-02394-9. [2] Susuki, K., Allen, J. & Chen, J. S.. "Image-based modeling of coupled electro-chemo-mechanical behavior of Li-ion battery cathode using an interface-modified reproducing kernel particle method," Engineering with Computers (2024). https://doi.org/10.1007/s00366-024-02016-9. [3] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, 4422-4454 (2022). https://doi.org/10.1002/nme.7040.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Multiphysics Meshfree Degradation Modeling of Energy Storage Materials with Kernel Enrichment

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and ultimately diminishing performance and service life. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based meshfree model construction by the reproducing kernel particle method (RKPM) is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. The first kernel enrichment discussed will be the interface modified reproducing kernel (IM-RK) [1, 2], constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The IM-RK is especially useful for areas in which a known discontinuity-type is expected a priori. The second kernel enrichment to be discussed is a neural network-enhanced reproducing kernel (NN-RK) [3, 4], which is introduced to effectively model non-obvious damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RK is additionally used to inform how crack opening and closure in turn affect the electro-chemo-mechanical responses in the material microstructure. Reference: [1] Wang, Y., Baek, J., Tang, Y. et al. "Support vector machine guided reproducing kernel particle method for image-based modeling of microstructures," Comput Mech 73, 907-942 (2024). https://doi.org/10.1007/s00466-023-02394-9. [2] Susuki, K., Allen, J. & Chen, J. S.. "Image-based modeling of coupled electro-chemo-mechanical behavior of Li-ion battery cathode using an interface-modified reproducing kernel particle method," Engineering with Computers (2024). https://doi.org/10.1007/s00366-024-02016-9. [3] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, 4422-4454 (2022). https://doi.org/10.1002/nme.7040.

25 ENERGY STORAGE↗
DOE OSTI2024

High temperature thermochemical energy storage materials

Disclosed are high enthalpy thermochemical energy storage materials that exhibit high thermal conductivity and stability at high temperature reaction conditions. Disclosed materials include hydride-based alloys that can undergo high temperature reversible hydrogenation/dehydrogenation reactions without phase change of any metal or metalloid components of the alloy. The materials undergo a reversible exothermic hydrogenation reaction to form a metal hydride and a ternary alloy that includes a high thermal conductivity metal that, in its pure state, would exhibit a phase change at the hydrogenation reaction conditions.

Ward, Patrick A.↗
DOE OSTI2024

Multiphysics Degradation Modeling of Energy Storage Materials via RKPM with a Neural Network-Enhancement

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. A coupled electro-chemo-mechanical reproducing kernel particle method (RKPM) formulation is developed, and a patch-test is formulated to certify optimal convergence of the proposed RKPM method for the coupled physics system. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based model construction by RKPM is then used to represent the complex material microstructures for modeling the coupled physics of these systems. Further, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1, 2] is introduced to effectively model damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. Reference: [1] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, pp 4422-4454, https://doi.org/10.1002/nme.7040, 2022. [2] Baek, J., Chen, J. S., "A Neural Network-Based Enrichment of Reproducing Kernel Approximation for Modeling Brittle Fracture", Computer Methods in Applied Mechanics and Engineering Vol. 410, 116590, 2024.

electro-chemo-mechanical coupling↗
NASA NTRS1996

Sol-gel Technology and Advanced Electrochemical Energy Storage Materials

Advanced materials play an important role in the development of electrochemical energy devices such as batteries, fuel cells, and electrochemical capacitors. The sol-gel process is a versatile solution for use in the fabrication of ceramic materials with tailored stoichiometry, microstructure, and properties. This processing technique is particularly useful in producing porous materials with high surface area and low density, two of the most desirable characteristics for electrode materials. In addition,the porous surface of gels can be modified chemically to create tailored surface properties, and inorganic/organic micro-composites can be prepared for improved material performance device fabrication. Applications of several sol-gel derived electrode materials in different energy storage devices are illustrated in this paper. V2O5 gels are shown to be a promising cathode material for solid state lithium batteries. Carbon aerogels, amorphous RuO2 gels and sol-gel derived hafnium compounds have been studied as electrode materials for high energy density and high power density electrochemical capacitors.

Chung-tse Chu↗
NASA NTRS1977

Cryogenic temperature control by means of energy storage materials

An investigation was conducted to study the concept of thermal control by means of physical or chemical reaction heats for applications involving the storage of cryogens during long-term space voyages. The investigation included some preliminary experimental tests of energy storage material (ESM) effectiveness. The materials considered can store and liberate large amounts of thermal energy by means of mechanisms such as sensible heat, heat of fusion, and physical or chemical reaction heat. A differential thermal analysis was utilized in the laboratory tests. Attention is given to the evaluation of cryogenic ESM thermal control concepts, the experimental determination of phase change materials characteristics, and adsorption ESMs. It is found that an ESM shield surrounded by multiple layer insulation provides the best protection for a cryogen store.

Grodzka, P. G.↗
NASA NTRSDate not supplied

Dielectric Energy Storage Materials for Space Sensors: Effect of Processing on the Performance

This paper explores the development of innovative materials for the dielectric energy storage for space components. The CaCuN 3 Ti 4 O 12 or CCTO belonging to perovskite family is of interest due to its colossal dielectric constant. It was demonstrated that materials synthesized at low temperature show nonequilibrium state and exhibit differences in the dielectric and resistivity values. The goal is to obtain high dielectric constant along with high resistivity values for achieving enhanced breakdown voltage. By using other members of the perovskite structures, it was demonstrated that similar colossal dielectric constant is observed and is dependent on processing methods. We have used heterovalent and dissimilar sized atom to replace Ca +2 ion. Accordingly, we replaced Ca +2 ion with heavy Ga +3 ion and developed gallium-based material system, Ga 2/3 Cu 3 Ti 4 O 12 . Following successful synthesis, we measured its dielectric constant and resistivity and compared with CCTO material system. Results of five sets of samples showed that lower temperature processing demonstrated mechanism of grain growth, but due to copper flow in high temperature processed samples dielectric constant and resistivity values were different.

Dielectric Energy↗
DOE OSTI2026

Pathways to High-Performance Salt Hydrate Thermochemical Energy Storage Materials and Systems

Thermochemical materials (TCMs) based on salt hydrates are promising for thermal energy storage as they combine high energy densities with low reaction temperatures. However, their adoption is hindered by poor structural integrity and degradation under hygrothermal cycling. Storage performance is governed not only by the chemical reaction, but also by the coupled thermo-chemo-mechanical behavior that evolves with cycling. Understanding and controlling this coupling across length scales (material-to-reactor) is necessary to improve TCM stability and lifetime. In this perspective, we discuss the shortcomings of current characterization approaches and emphasize the need for measuring transport properties and structural transformations using in situ techniques that capture the dynamic evolution of these materials. We also outline opportunities for multiscale modeling frameworks that link thermodynamics and mechanics, enabling predictive evaluation of composite architectures designed for cycling stability. We conclude by identifying research questions that must be addressed to transform TCMs into viable energy storage technologies.

Composites↗
DOE OSTI2024

Infrared nanoimaging and nanospectroscopy of electrochemical energy storage materials and interfaces

Electrochemical interfaces are central to the function and performance of energy storage devices. Thus, the development of new methods to characterize these interfaces, in conjunction with electrochemical performance, is essential for bridging the existing knowledge gaps and accelerating the development of energy storage technologies. Of particular need is the ability to characterize surfaces or interfaces in a non-destructive way with adequate resolution to discern individual structural and chemical building blocks. To this end, sub-diffraction-limit low-energy infrared optical probes that exploit near-field interactions within atomic force microscopy platforms, such as pseudoheterodyne nanoimaging, photothermal nanoimaging and nanospectroscopy, and nanoscale Fourier transform infrared spectroscopy, are all powerful emerging techniques. These are capable of non-destructive surface probing and imaging at nanometer resolution. This review outlines recent efforts to characterize ex situ, in situ, and operando electrode materials and electrochemical interfaces in rechargeable batteries with these advanced infrared near-field probes.

25 ENERGY STORAGE↗
NASA NTRS1976

Thermal energy storage material thermophysical property measurement and heat transfer impact

The thermophysical properties of salts having potential for thermal energy storage to provide peaking energy in conventional electric utility power plants were investigated. The power plants studied were the pressurized water reactor, boiling water reactor, supercritical steam reactor, and high temperature gas reactor. The salts considered were LiNO3, 63LiOH/37 LiCl eutectic, LiOH, and Na2B4O7. The thermal conductivity, specific heat (including latent heat of fusion), and density of each salt were measured for a temperature range of at least + or - 100 K of the measured melting point. Measurements were made with both reagent and commercial grades of each salt.

Tye, R. P.↗
NASA NTRS1987

Selection of high temperature thermal energy storage materials for advanced solar dynamic space power systems

Under the direction of NASA's Office of Aeronautics and Technology (OAST), the NASA Lewis Research Center has initiated an in-house thermal energy storage program to identify combinations of phase change thermal energy storage media for use with a Brayton and Stirling Advanced Solar Dynamic (ASD) space power system operating between 1070 and 1400 K. A study has been initiated to determine suitable combinations of thermal energy storage (TES) phase change materials (PCM) that result in the smallest and lightest weight ASD power system possible. To date the heats of fusion of several fluoride salt mixtures with melting points greater than 1025 K have been verified experimentally. The study has indicated that these salt systems produce large ASD systems because of their inherent low thermal conductivity and low density. It is desirable to have PCMs with high densities and high thermal conductivities. Therefore, alternate phase change materials based on metallic alloy systems are also being considered as possible TES candidates for future ASD space power systems.

Lacy, Dovie E.↗
NASA NTRS1987

Selection of high temperature thermal energy storage materials for advanced solar dynamic space power systems

Under the direction of NASA's Office of Aeronautics and Technology (OAST), the NASA Lewis Research Center has initiated an in-house thermal energy storage program to identify combinations of phase change thermal energy storage media for use with a Brayton and Stirling Advanced Solar Dynamic (ASD) space power system operating between 1070 and 1400 K. A study has been initiated to determine suitable combinations of thermal energy storage (TES) phase change materials (PCM) that result in the smallest and lightest weight ASD power system possible. To date the heats of fusion of several fluoride salt mixtures with melting points greater than 1025 K have been verified experimentally. The study has indicated that these salt systems produce large ASD systems because of their inherent low thermal conductivity and low density. It is desirable to have PCMs with high densities and high thermal conductivities. Therefore, alternate phase change materials based on metallic alloy systems are also being considered as possible TES candidates for future ASD space power systems.

Lacy, Dovie E.↗
NASA NTRS1990

Analysis of thermal energy storage material with change-of-phase volumetric effects

NASA's Space Station Freedom proposed hybrid power system includes photovoltaic arrays with nickel hydrogen batteries for energy storage and solar dynamic collectors driving Brayton heat engines with change-of-phase Thermal Energy Storage (TES) devices. A TES device is comprised of multiple metallic, annular canisters which contain a eutectic composition LiF-CaF2 Phase Change Material (PCM) that melts at 1040 K. A moderately sophisticated LiF-CaF2 PCM computer model is being developed in three stages considering 1-D, 2-D, and 3-D canister geometries, respectively. The 1-D model results indicate that the void has a marked effect on the phase change process due to PCM displacement and dynamic void heat transfer resistance. Equally influential are the effects of different boundary conditions and liquid PCM natural convection. For the second stage, successful numerical techniques used in the 1-D phase change model are extended to a 2-D (r,z) PCM containment canister model. A prototypical PCM containment canister is analyzed and the results are discussed.

Kerslake, Thomas W.↗