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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 145 records · Page 8

An upgraded G-band differential absorption radar system for future airborne studies

A proof-of-concept, 170 GHz frequency-modulated, continuous-wave (FMCW) radar has been developed for measuring water vapor profiles within the cloudy boundary layer from an airborne platform. The measurement concept exploits the differential absorption accrued by two or more transmitted frequencies in the vicinity of the 183 GHz water absorption line to retrieve range-resolved humidity profiles, so-called differential absorption radar (DAR). The upgraded system design includes important considerations for monostatic radar operation with an open fuselage viewport (i.e. no radome). The radar features an all-solid-state tansmitter with > 0:4 W continuous transmit power, a 60 cm primary aperture and corresponding 58 dB antenna gain, and more than 80 dB transmit/receive isolation, enabling near thermal-noise-limited sensitivity with a 8 dB noise figure receiver. Ice-cloud radar returns are detected beyond 8 km in height from the ground, demonstrating the high sensitivity of the system. In addition to in-cloud humidity profiling capabilities, deployment of a water vapor DAR from an airborne platform enables measurements of total column water vapor (TCWV) for all weather and surface scenarios. Precision estimates and potential biases for future TCWV measurements are discussed.

Monje, Raquel↗

Interpretable Tree-Based and Graph Neural Network Approaches for Novel Solid State Electrolyte Design

All-solid-state batteries with Li metal anode can address the safety issues surrounding traditional Li-ion batteries as well as the demand for higher energy densities. However, the development of solid electrolytes simultaneously possessing high ionic conductivity and good chemical and electrochemical stabilities has proven to be a challenge. I will present our informatics approach to explore the Li compound space for promising solid electrolytes using high-throughput multi-property screening and interpretable machine learning. This is accomplished through the generation of a large database of battery-related materials properties of Li compounds. We use tree-based ensemble learning methods and graph neural network approaches to accurately learn relationships between crystal structures and corresponding thermodynamic and kinetic properties, with interpretability being a major focus. Our models give us the ability to enable rapid discovery and design of novel solid-state battery chemistries.

Materials discovery↗

Interpretable ML Approaches for Novel Solid State Electrolyte Design

All-solid-state batteries with Li metal anode can address the safety issues surrounding traditional Li-ion batteries as well as the demand for higher energy densities. However, the development of solid electrolytes simultaneously possessing high ionic conductivity and good chemical and electrochemical stabilities has proven to be a challenge. I will present our informatics approach to explore the Li compound space for promising solid electrolytes using high-throughput multi-property screening and interpretable machine learning. This is accomplished through the generation of a large database of battery-related materials properties of Li compounds. We use tree-based ensemble learning methods and graph neural network approaches to accurately learn relationships between crystal structures and corresponding thermodynamic and kinetic properties, with interpretability being a major focus. Our models give us the ability to enable rapid discovery and design of novel solid-state battery chemistries.

Shreyas J Honrao↗

Hierarchical screening for Li-based solid electrolytes using fast, interpretable machine-learned potentials

Li-based solid-state electrolyte materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. The prohibitive cost of high-throughput screening with DFT has lead to the development of surrogate models using geometric analysis, empirical potentials, and descriptors for ionic transport. Here, I will discuss a hierarchical screening approach for identifying promising materials using a combination of density functional theory, bond-valence methods, and machine learning potentials generated with the Ultra-Fast Force Fields (UF3) framework. We show how the inexpensive bond-valence method can be used to guide the generation of training samples for machine learning, in addition to filtering candidates. Finally, we apply the hierarchical workflow to screen for ionic conductivity across a database of Li-containing compounds.

Materials discovery↗

P-ACTIVE Project Report

The Phase change material-based actively-tunable filter (P-ACTIVE, Dr. Hyun Jung Kim, the Principal Investigator / PI) project is a NASA Langley Research Center (LaRC)-led research endeavor that began as a NASA CIF (Center Innovation Fund) project in 2019. The goal of P-ACTIVE is to develop all-solid-state tunable optical filters that can serve as low-Size, Weight, and Power (SWaP) replacements to the ubiquitous filter wheel technology current in use, and serve as a starting point for completely new optical component technologies. By using materials commonly used in electronic memory devices, namely chalcogenide phase-change materials (PCMs), in conjunction with nanostructured surfaces with exotic, tailored optical responses (“metasurfaces”), the P-ACTIVE filters are able to tune their optical transmission/reflection behavior in real-time. Because of this new functionality, P-ACTIVE filters are highlighted for NASA science and space programs such as next generation Lidar, landing system (SLS) thermal monitoring, thermal imaging, imaging spectroscopy, and disaster monitoring (e.g., volcanic eruption observations from SmallSats). This document intends to serve as a compendium of the P-ACTIVE project. We begin by describing the project from background science and assume no prior knowledge of the subject. We then address experimental and theoretical results of P-ACTIVE device performance, as well as recent results obtained from the MISSE-14 mission related to space qualification of P-ACTIVE devices and constituent materials. We conclude with a prospective view of the P-ACTIVE technology, and discuss the potential for these filters and other similar metasurface devices to serve NASA’s mission.

metamaterial↗

Hierarchical Screening for Li-Based Solid Electrolytes Using Fast, Interpretable Machine-Learned Potentials

Li-based solid-state electrolyte materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. The prohibitive cost of high-throughput screening with DFT has lead to the development of surrogate models using geometric analysis, empirical potentials, and descriptors for ionic transport. Here, I will discuss a hierarchical screening approach for identifying promising materials using a combination of density functional theory, bond-valence methods, and machine learning potentials generated with the Ultra-Fast Force Fields (UF3) framework. We show how the inexpensive bond-valence method can be used to guide the generation of training samples for machine learning, in addition to filtering candidates.

Materials discovery↗

High-Throughput Screening of Li Solid-State Electrolytes With Bond Valence Methods and Graph Neural Networks

Li-based solid-state electrolyte (Li-SSE) materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. We present a high-throughput screening approach for Li-SSE materials using a combination of bond-valence methods and graph neural networks. We demonstrate the screening approach with a dataset containing tens of thousands of Li-containing compounds. Furthermore, we combine the machine-learning screening procedure with an isovalent substitution scheme to generate and screen additional Li SSE candidates beyond existing databases. Finally, we discuss relative importances of geometric and bond-valence quantities in the training of graph neural networks, providing insight for future modeling of ionic conductivity in Li-SSE materials.

Materials discovery↗

Space Qualification Studies of AOTF Devices Under the MISSE-11 Mission

The acousto-optic tunable filter (AOTF) devices are used in a variety of applications including hyperspectral and spectrapolarimetric based imaging. The AOTF devices provide several advantages including speed and random access to desired spectral bands and enable all-solid-state operation that are attractive for space applications. In this paper, the performance of Tellurium Dioxide (TeO 2 ) and Mercurous Bromide (Hg 2 Br 2 ) AOTF devices in space environment carried out under the NASA’s Materials International Space Station Experiments 11 (MISSE-11) mission is discussed. The purpose of the MISSE-11 mission was to study materials and devices subjected to space conditions for long term while attached to the International Space station (ISS). The TeO 2 AOTF was developed for short wavelength IR (SWIR) operation while the Hg 2 Br 2 AOTF device was developed for long wavelength IR (LWIR) operation. These devices were attached to the ISS platform for more than a year. Pre-flight and post-flight performance characterization were performed on these devices. In the case of TeO 2 AOTF, the preflight efficiency was around 87% with a center frequency at 68MHz while the post-flight efficiency was around 83%. However, the optical transmission of Hg 2 Br 2 AOTF had deteriorated considerably. The details of performance testing and analysis of both AOTF devices are discussed.

Space Qualification↗

Screening of Li-Based Solid Electrolytes Using Bond-Valence Methods and Graph Neural Networks

Li-based solid-state electrolyte (Li-SSE) materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. We present a high-throughput screening approach for Li-SSE materials using a combination of bond-valence methods and graph neural networks. We demonstrate the screening approach with a dataset containing tens of thousands of Li-containing compounds. Furthermore, we combine the machine-learning screening procedure with an isovalent substitution scheme to generate and screen additional Li SSE candidates beyond existing databases. Finally, we discuss relative importances of geometric and bond-valence quantities in the training of graph neural networks, providing insight for future modeling of ionic conductivity in Li-SSE materials.

Materials discovery↗

Fabricating Solid-State Batteries for Electric Aviation

All-solid-state lithium batteries are widely reputed as the next major step in energy storage technology on account their drastically improved safety over wet cells, as solid electrolytes lack the volatile compounds in wet electrolytes that make them combustible. This enhanced safety enables a far wider range of products and vehicles to go fully electric and aligns with future NASA missions that require high performing, reliable, and safe batteries. However, they currently face issues with implementation in consumer products due to the often-poor mechanical properties of the solid electrolyte and relative difficulty to manufacture. Typical solid-state electrolyte challenges were bypassed by incorporating a range of polymeric binders into a solid electrolyte suspension and cast onto a composite carbon-sulfide cathode to create a single bilayer film. The resulting films display superior flexibility and durability compared to solid-electrolyte films typically discussed in literature without compromising the thinness of the films. The bilayer film was then punched into 12.7 cm diameter discs and 4 cm by 5 cm sheets, pressed, and assembled into coin cells and pouch cells respectively.

Batteries↗

Cathode Modeling of Solid-State Batteries

The search for safe, reliable, and compact high-capacity energy storage devices has led to increased interest in all-solid-state battery research. The use of solid electrolytes provides enhanced safety and durability due to their reduced flammability and increased mechanical strength compared to organic liquid electrolytes. Still, the use of solid electrolytes remains challenging. Computational modeling plays a substantial role in addressing these challenges. A particle dynamics electromechanical model for simulating electrochemical processes in a solid-state battery cathode will be presented. The model presents cathode microstructure at the particle level as a mixture of ionically conductive solid electrolyte particles, electrically conductive carbon additives, and cathodic reactant particles. After densification, the particle connectivity is analyzed to reconstruct the complex electric network connecting reactant particles with an anodic and cathodic current collectors through the electrolyte and carbon particles. The Kirchhoff’s matrix equation describing this electric network, is solved to obtain values of various critical parameters, such as the overall conductivity of the cathode for lithium ions and electrons, cathodic reactant material utilization, and the distribution of the electric current and voltages within the cathode. In addition, by representing the reactant particles as electrolyte or galvanic microcells governed by the Butler-Volmer electrochemical equation, the overall performance of battery cells during charge or discharge processes, respectively, can be predicted for a given cathodic powder composition. The presented model, executed on a high-performance computing architecture, essentially provides a valuable guidance in designing and developing future solid-state batteries.

solid-state battery↗

Low-temperature liquid-phase synthesis of lithium thiophosphate-borohydride solid electrolyte with high room-temperature ionic conductivity

Embodiments relate to a scalable liquid-phase synthesis technique of lithium thiophosphate-borohydride solid electrolytes with high ionic conductivity at room temperature and its use in all-solid-state lithium batteries. A battery comprises an anode, a cathode, and a solid electrolyte layer positioned between the anode and the cathode. The liquid-phase synthesized solid electrolyte material can be used as the solid electrolyte layer or incorporated into anodes or cathodes.

Wang, Donghai [Pennsylvania State Univ., Universit↗

Anion sublattice design enables superionic conductivity in crystalline oxyhalides

Solid-state batteries are attractive energy storage systems as a result of their inherent safety, but their development hinges on advanced solid-state electrolytes (SSEs). Most SSEs remain largely confined to single-anion systems (e.g., sulfides, oxides, halides, and polymers). Through mixed-anion design strategy, we develop crystalline Li 3 Ta 3 O 4 Cl 10 (LTOC) and its derivatives with excellent ionic conductivities (up to 13.7 millisiemens per centimeter at 25°C) and electrochemical stability. The LTOC structure features mixed-anion spiral chains, consisting of corner-shared oxygen and terminal chlorine atoms, which induces continuous “tetrahedron-tetrahedron” Li-ion migration pathways with low energy barriers. Additionally, LTOC demonstrates holistic cathode compatibility, enabling solid-state batteries operation at 4.9 volts versus Li/Li + and low temperature, down to −50°C. In conclusion, these findings describe a promising class of superionic conductors for high-performance solid-state batteries.

Zhao, Feipeng [Western University, London, ON (Can↗

Pushing the Limits: Maximizing Energy Density in Silicon Sulfide Solid‐State Batteries

Here, for the first time, we demonstrate a silicon solid-state battery (SSB) architecture that achieves >400 Wh kg −1 , approaching the theoretical limit for silicon-based SSBs. This configuration features a 99.9 wt% micro-Si, a thin sulfide solid electrolyte (SSE), and a high-loading NMC811. Key to these results is strategically selecting and evaluating the processing techniques, whether wet or dry, for the negative electrode, positive electrode and thin sheet-type SSE. Excessive lithium incorporation into the silicon host, beyond the Li 3.75 +Si phase to form a LiSi composite, is essential to match the high capacity of the positive electrode. This SSB achieves over 1000 cycles for a 2 mAh cm −2 with ≈80% capacity retention and 94% capacity retention for 3 mAh cm −2 over 500 cycles at 25 °C. Post analysis identifies the primary capacity decay mechanisms as oxidation at the NMC/SSE interface and structural disruptions within NMC. Meanwhile, the Si electrode maintains a robust solid-electrolyte interphase layer, minimizing capacity decay. This study highlights the necessity for improved NMC coatings, lattice oxygen stabilization, and a durable positive electrode-electrolyte interface to improve the long-term stability of SSBs. Strategies leading to a single-layer pouch cell SSB exceeding 400 Wh kg −1 are developed.

25 ENERGY STORAGE↗

All‐Solid‐State Batteries With Mechanically Stable Interfaces Consisting of a Zero‐Strain Cation‐Disordered Rocksalt Cathode

Interface stabilization is critical to the development of working all‐solid‐state batteries. Rigid cathode/solid electrolyte interfaces often disintegrate due to anisotropic volume change of cathode‐active materials, resulting in irreversible capacity loss. Herein, we demonstrate that Li 1.211 Mo 0.467 Cr 0.3 O 2 (LMCO), a pioneering cation‐disordered rocksalt oxide (DRX) cathode that has intrinsically small volume change upon lithium intercalation, can be integrated with a thiophosphate‐based solid electrolyte for all‐solid‐state batteries. Interface stability of the all‐solid LMCO cell was investigated by electrochemical impedance spectroscopy, X‐ray micro‐computed tomography, and electron microscopy. Since LMCO was initially synthesized as a layered phase exhibiting a large volume change, interface disintegration can be observable in the early cycles. As layered LMCO phase‐transformed into DRX LMCO in subsequent cycles, reintegration of the interfaces occurs within a pressurized cell as a result of its zero‐stain behavior. Consequently, the DRX LMCO cathode maintains interface integrity, and thus electrical wiring, over an extended number of cycles, leading to improved capacity retention with small internal cell resistance.

DRX↗

Fast ionic conduction achieved through the design and synthesis of ceramic heterointerfaces

Lithium (Li) chloride and iron oxychloride (FeOCl), typically nonconductive, were combined to form a [Li 1+δ Cl] δ+ /[FeOCl] δ- heterointerface composite material (LFH), achieving ionic conductivities of >1 mS cm -1 . Analysis techniques (scanning transmission electron microscopy [STEM] and electron energy-loss spectroscopy [EELS]) indicated that the microstructure of LFH consisted of an amorphous LiCl-based shell surrounding a crystalline FeOCl-based core. Electrochemical measurements alongside solid-state 6,7 Li nuclear magnetic resonance (NMR) and molecular dynamic simulations revealed Li+ as the sole conductive species, with a diffusion barrier of ~0.25 eV. X-ray photoelectron spectroscopy (XPS) and X-ray absorption fine structure (XAFS) results further supported interstitial Li + diffusion at the heterointerface and within the LiCl phase, made possible by the heterointerface. Despite susceptibility to electronic conductivity, iron’s defects and multivalency (Fe³⁺, Fe²⁺) enable the Fe–O–Cl framework to accept Cl - , facilitating Li⁺ ionic conduction. Finally, a prototype solid-state cell (showing 97% Coulombic efficiency) demonstrated the viability of this heterointerface design for applications in energy storage.

36 MATERIALS SCIENCE↗

Liquid-like solid-state diffusion of lithium ions in super-halide-rich argyrodite

The development of solid electrolytes with high ionic conductivity is essential for advancing safer, high-energy-density solid-state batteries, where lithium site distribution in the sublattice strongly affects ion transport. Here, we report a super-halide-rich argyrodite, Li 5.3 PS 4.3 Cl 1.7 , with remarkable room-temperature ionic conductivity (11.4 ± 0.7 mS cm -1 ) due to population of two additional interstitial lithium sites induced by vacancy redistribution. Prominent lithium density between lithium sites and elevated atomic displacement parameters indicate liquid-like diffusive behavior resembling sublattice melting. Combining electrochemical impedance spectroscopy, pulsed-field gradient NMR, and T 1 relaxation methods, we demonstrate that the augmented conductivity partly arises from a low energy barrier (0.08 eV) at the local scale, attributed to a three-site lithium distribution that drives correlated lithium dynamics. This work advances our understanding of the structure-dynamics interplay in super-halide-rich argyrodites, and highlighting their potential as solid-state battery electrolytes in cells with a coated single-crystal NMC82 cathode that achieve 170 mAh/g capacity at a 0.2 C rate .

25 ENERGY STORAGE↗