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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 451 records · Page 25

High-Accuracy Semiempirical Quantum Models Based on a Minimal Training Set

A great need exists for computationally efficient quantum simulation approaches that can achieve an accuracy similar to high-level theories at a fraction of the computational cost. In this regard, we have leveraged a machine-learned interaction potential based on Chebyshev polynomials to improve density functional tight binding (DFTB) models for organic materials. The benefit of our approach is two-fold: (1) many-body interactions can be corrected for in a systematic and rapidly tunable process, and (2) high-level quantum accuracy for a broad range of compounds can be achieved with ~0.3% of data required for one advanced deep learning potential. Our model exhibits both transferability and extensibility through comparison to quantum chemical results for organic clusters, solid carbon phases, and molecular crystal phase stability rankings. Overall, our efforts thus allow for high-throughput physical and chemical predictions with up to coupled-cluster accuracy for systems that are computationally intractable with standard approaches.

36 MATERIALS SCIENCE↗

Improving Interface Stability of Si Anodes by Mg Coating in Li-Ion Batteries

Silicon (Si) is a promising anode material for high-energy-density lithium-ion batteries (LIBs), but its short calendar life and poor cycling performance prevent its large-scale adoption. Introducing magnesium (Mg) salt into the electrolyte has been recently shown to form a ternary Li–Mg–Si Zintl phase upon lithiation of Si and improve the cycling performance. However, the ternary Zintl phase formation mechanism and its impact on the solid electrolyte interphase (SEI) are not yet well understood. In this work, we demonstrate the formation of a ternary Li–Mg–Si Zintl phase by Mg coating of the Si anode, where Mg diffuses into the Si film upon deposition and intermixes further during the lithiation process. The presence of the Zintl phase improves the interface stability, alters the nature of the SEI, and enhances the cycling performance of the Si anode. This study provides insights into the formation mechanism of the ternary Zintl phase and guidelines for the future design of Si anodes.

25 ENERGY STORAGE↗

Mechanical, Microstructural, and Electrochemical Characterization of NaSICON Sodium Ion Conductors [Poster]

The DOE Office of Electricity views sodium batteries as a priority in pursuing a safe, resilient, and reliable grid. Improvements in solid-state electrolytes are key to realizing the potential of these large-scale batteries. NaSICON structure consists of SiO 4 or PO 4 tetrahedra sharing common corners with ZrO 6 octahedra. Structure forms “tunnels” in three dimensions that can transport interstitial sodium ion. 3D structure provides higher ionic conductivity than other conductors (β’’-alumina), particularly at low temperature. Lower temperature (cheaper) processing compared to β’’-alumina. Our objective was to identify fundamental structure-processing-property relationships in NaSICON solid electrolytes to inform design for use in sodium batteries. In this work, the mechanical properties of NaSICON sodium ion conductors are affected by sodium conduction. Electrochemical cycling can alter modulus and hardness in NaSICON. Excessive cycling can lead to secondary phases and/or dendrite formation that change mechanical properties in NaSICON. Mechanical and electrochemical properties can be correlated with topographical features to further inform design decisions

25 ENERGY STORAGE↗

Process and system for hot and/or cold energy transfer, transport and/or storage

A thermal conveyance system and process for absorbing, transporting, storing, and recovering thermal energy (both hot and cold energy) over a wide range of temperatures from up to 2,100° F., or higher, or cool energy at subzero temperatures in inert and stable particles without the need to maintain a minimum temperature or requiring high system pressures. The process involving the transferring thermal energy to a first transfer fluid and recovering thermal energy from a second transfer fluid wherein the first and the second transfer fluids comprise a two phase thermal media including a gaseous carrier containing a quantity of micron to millimeter sized solid particles.

25 ENERGY STORAGE↗

Effects of surface chemical potentials on cation segregation

Surface cation segregation on perovskite-type electrodes is one of the major issues limiting the durability of high-temperature solid-oxide electrochemical cells, and this process is strongly dependent on temperature, the external gas-environment, and impurities in air, such as CO 2 . Here cation segregation on La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3-δ (LSCF) is systematically evaluated under a set of chemical potentials to determine the origin of surface segregation and the dominant factors that govern the segregation process. Temperature is the main driving force for surface strontium segregation as the thermodynamic stability of each phase varies, and the SrO particles appear primarily in a specific operating window. In addition to the required thermal energy, the presence of gaseous oxygen-containing molecules as reactants help drive the precipitation of SrO. Oxygen partial pressure (pO 2 ) controls the defect chemistry of LSCF, leading to promotion or suppression of surface segregation. The presence of CO 2 promotes the nucleation process and suppresses the surface migration step, significantly altering the surface morphology. We also show that A-site deficiency can limit the SrO segregation in certain conditions but shows no effect in others. This study reveals the impact of gas–solid interactions on surface segregation and highlights the subtle relationship between multiple segregation driving forces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microstructural pattern formation during liquid metal dealloying: Phase-field simulations and theoretical analyses

In recent years, liquid metal dealloying has emerged as a promising material processing method to generate micro- and nanoscale bicontinuous or porous structures. Most previous studies focused on the experimental characterization of the dealloying process and on the properties of the dealloyed materials, leaving the theoretical study incomplete to fully understand the fundamental mechanisms of the liquid metal dealloying process. In this paper, we use theoretical models and phase-field simulations to clarify the kinetics and pattern formation during liquid metal dealloying. Our investigation starts from a theoretical analysis of the 1D dissolution of a binary precursor alloy, which reveals that the 1D dissolution process involves two regimes. In the first regime, due to the low solubility of one of the elements in the melt, it accumulates at the solid-liquid interface, which reduces the dissolution kinetics. In the second regime, the interface kinetics reaches a stationary regime where both elements of the precursor alloy dissolve into the melt. Previous works revealed that in the early dealloying stage, the dealloying front is destabilized by an interfacial spinodal decomposition, which triggers the formation of interconnected ligaments. Here we extend this line of work by proposing a linear stability analysis able to predict the initial length scale of the ligaments formed in the initial stage of the dealloying. Combining this analysis with the 1D dissolution model proposed here enables us to better understand the initial conditions (composition of the precursor alloy and the melt) leading to a planar dissolution without interface destabilization. Finally, we report a strong influence of solid-state diffusion on dealloying. Although the solid-state diffusivity is four to five orders of magnitude smaller than in the liquid phase, it is found to affect both dissolution kinetics and ligament morphologies.

36 MATERIALS SCIENCE↗

Superconducting magnesium diboride films for levitation of laser targets

Inertial confinement fusion targets would benefit from being levitated inside hohlraums to avoid capsule support-related implosion perturbations. Levitation inside a magnetic trap requires coating the capsule with a thin film that is superconducting at 20 K. Such non-epitaxial film growth on non-planar substrates is challenging. Here, we study Mg vapor annealing and solid-phase reactive inter-diffusion methods to form superconducting magnesium diboride (MgB 2 ) films on different planar and spherical carbon substrates, evaluating glassy carbon, polycrystalline diamond made by chemical vapor deposition, and carbon deposited by magnetron sputtering of graphite targets. Thin films of B and Mg are produced by magnetron sputtering onto stationary planar or rolling spherical substrates and annealed at either 600 or 850 °C in Mg vapor. The films are characterized by a combination of high-energy ion scattering, electron microscopy, and magnetometry. Results show that the critical superconducting temperature of resultant films depends on film microstructure and oxygen impurity content. The formation of MgB 2 films is also strongly substrate dependent, even in this case of non-epitaxial growth. Important factors to consider are oxygen outgassing of the substrate during thermal processing, substrate surface roughness, and the matching of thermal expansion coefficients of different layers in the multilayer structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Characteristics of Non-Fullerene Acceptor-Based Organic Photovoltaic Active Layers Using X-ray Scattering and Solid-State NMR

With the recent development of non-fullerene acceptors, power conversion efficiencies of bulk-heterojunction organic solar cells have exceeded 18%. The morphology of the BHJ active layer, including packing, ordering, orientation, and phase behavior of the donor(s) and acceptor(s), plays critical roles in determining the device performance. We characterized the morphology of active layers consisting of mixtures of a PTB7/PTB7-Th (donor) and ITIC (acceptor) using grazing incidence wide-angle X-ray scattering, resonant soft X-ray scattering, and solid-state nuclear magnetic resonance (ssNMR) to correlate the morphology with device performance. PTB7-Th/ITIC shows a better device performance than that of PTB7/ITIC due to a smaller π-πstacking distance and smaller domain size of the phase separated morphology. One of PTB7/ITIC samples, processed from mixed solvents (chlorobenzene/benzene = 1:1 by volume), shows a possible partial miscibility and smaller domain size as revealed by ssNMR T 1ρ relaxation times, which is detrimental to device performance. ssNMR results showed that ITIC could crystallize into different forms depending on processing conditions, which may have implications on the manufacturing of devices using it as an ingredient, as well as its long-term stability in service.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A broadband wavelet implementation for rapid ultrasound pulse-echo time-of-flight measurements

A broadband wavelet approach to ultrasonic pulse-echo time-of-flight measurements is described. The broadband approach significantly reduces the time required for frequency-dependent pulse-echo measurements, enabling studies of dynamic systems ranging from biological systems to solid-state phase transitions. The described broadband approach is demonstrated in parallel with the more traditional frequency stepping approach to perform ultrasound time-of-flight measurements inside a large volume Paris-Edinburgh press in-situ at a synchrotron source. The broadband wavelet data acquisition process was found to be 1-2 orders of magnitude faster than the steppedfrequency approach, with no compromise in data quality or determined results.

47 OTHER INSTRUMENTATION↗

Extraction and Separation of Rare-Earth Elements from Coal Fly Ash and Leachate using a Recyclable Ionic Liquid

Coal fly ash (CFA) can be a promising source for recovering rare-earth elements (REEs), as it contains a broad range of REEs with average concentrations frequently exceeding those in traditional rare earth mines. Recent research from our group has demonstrated that REEs can be preferentially extracted from CFA solids using a recyclable ionic liquid (IL), betainium bis-(trifluoromethylsulfonyl)imide ([Hbet][Tf2N]). When CFA was heated with the mixture of IL and an aqueous solution above 65°C, most leached REEs partitioned into the IL phase and were separated from the bulk elements. Subsequent acid stripping of the REE-loaded IL removed the REEs and regenerated the IL for reuse in multiple extraction cycles. This IL-based REE-CFA recovery method has been applied to ten CFA samples derived from different coal sources, including ash recovered from disposal ponds. Analysis of 34 elements confirmed the process consistently achieved high REE recovery efficiency, with strong selectivity over bulk and trace elements across diverse CFA types. In addition to the IL-solid extraction, the performance of [Hbet][Tf2N] in extracting REEs from fly-ash leachates have been evaluated by four commonly used leaching reagents, including HCl, HNO3, H2SO4, and citrate. During the IL-leachate extraction, [Hbet][Tf2N] was mixed and heated with a Class C fly ash leachate generated from each leaching reagent, followed by an acid stripping. It was observed that the partitioning and recovery of REEs increased as the leachate pH increased from 3 to 11. Among the investigated leachates, HCl and citrate proved to be the most compatible with IL extraction, exhibiting a slightly higher REE recovery and a lower non-REE co-extraction compared to the IL-solid extraction. Sc, Y, Nd, Sm, Gd, Dy, and Yb consistently showed a high recovery rate from both CFA solids and leachates. Notably, Pr, Tb, and Ho, which were not previously leached from the CFA solids, were partially recovered from the leachates. Overall, our studies revealed the strong potential of [Hbet][Tf2N] for effectively recovering REEs from leachates, highlighting its applicability as a sustainable strategy for other aqueous REE feedstocks. Furthermore, a techno-economic analysis will be performed to quantify the economic viability of the IL-based REE recovery method and guide future process improvement.

42 ENGINEERING↗

An Atom-Precise Approach to Damp First-Order Phase Transitions and Its Implications for Neuromorphic Signal Processing

Neuromorphic computing inspired by mammalian intelligence aims to emulate the nonlinear dynamics of biological neurons and synapses to achieve fast, low-energy, and highly efficient information processing. Brain-inspired computing relies on the design and discovery of materials exhibiting nonlinear current–voltage profiles, frequently underpinned by electronic state transitions, to achieve spiking neurons and dynamically tunable synapses. A signature challenge in the design of artificial neurons is controlling the steepness of first-order transitions in active elements, as abrupt transitions are at risk of driving unstable voltage and temperature oscillations, which result in catastrophic device failure. A critical knowledge gap is the lack of structure–function correlations mapping the composition and atomistic structure of crystalline solids to nonlinear dynamical response characteristics. Here, we address the key question of how modification of atomistic structure correlates with alteration of neuron-like functionality. Constructing oscillator circuits from millimeter-scale single crystals enables high-resolution atomic structure solutions, which we use to demonstrate that the selective positioning of Pb cations modifies charge ordering along a one-dimensional CuxV2O5 framework even at low insertion stoichiometries, thereby providing an atom-precise design parameter for damping first-order transitions. We use temperature-variant X-ray diffraction and X-ray spectroscopy to elucidate the suppression of Cu-ion shuttling based on the precise positioning of Pb ions in seven-coordinated tunnel interstitial sites as the mechanistic basis for transition broadening, thus bridging a critical gap between statistical mechanics and quantum chemical descriptions of phase transitions. Such mechanistic understanding thus paves the way to site-selective modification strategies for modulating the sharpness of first-order transitions, with an exemplary demonstration here in tuning neuronal signal processing.

Crystal structure↗

Combining synchrotron X-ray diffraction, mechanistic modeling and machine learning for in situ subsurface temperature quantification during laser melting

Laser melting, such as that encountered during additive manufacturing, produces extreme gradients of temperature in both space and time, which in turn influence microstructural development in the material. Qualification and model validation of the process itself and the resulting material necessitate the ability to characterize these temperature fields. However, well established means to directly probe the material temperature below the surface of an alloy while it is being processed are limited. To address this gap in characterization capabilities, a novel means is presented to extract subsurface temperature-distribution metrics, with uncertainty, from in situ synchrotron X-ray diffraction measurements to provide quantitative temperature evolution data during laser melting. Temperature-distribution metrics are determined using Gaussian process regression supervised machine-learning surrogate models trained with a combination of mechanistic modeling (heat transfer and fluid flow) and X-ray diffraction simulation. The trained surrogate model uncertainties are found to range from 5 to 15% depending on the metric and current temperature. The surrogate models are then applied to experimental data to extract temperature metrics from an Inconel 625 nickel superalloy wall specimen during laser melting. The maximum temperatures of the solid phase in the diffraction volume through melting and cooling are found to reach the solidus temperature as expected, with the mean and minimum temperatures found to be several hundred degrees less. The extracted temperature metrics near melting are determined to be more accurate because of the lower relative levels of mechanical elastic strains. However, uncertainties for temperature metrics during cooling are increased due to the effects of thermomechanical stress.

36 MATERIALS SCIENCE↗

Synergistic Self-Assembly of Oxoanions and d-Block Metal Ions with Heteroditopic Receptors into Triple-Stranded Helicates

Cooperativity effects among the interconnected anion and cation binding sites can profoundly alter the performance of heteroditopic receptors in selective ion pair recognition, processes that are oftentimes pertinent to biological systems and chemical separations. In this paper, we report the effect of the linker that connects both binding sites on self-assembly of heteroditopic receptors in the presence of divalent first-row transition metal salts in solution and solid phase. Introduction of backbone flexibility in the receptor results in the formation of triple-stranded ion-pair helicates with an extraordinary selectivity towards CuSO 4 through an anion-induced fit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fracture Dynamics in Silicon Anode Solid-State Batteries

Solid-state batteries (SSBs) with silicon anodes could enable improved safety and energy density compared to lithium-ion batteries. However, degradation arising from the massive volumetric changes of silicon anodes during cycling is not well understood in solid-state systems. Here, we use operando X-ray computed microtomography to reveal micro- to macro-scale chemo-mechanical degradation processes of silicon anodes in SSBs. Mud-type channel cracks driven by biaxial tensile stress form across the electrode during delithiation. We also find detrimental cracks at the silicon/ solid electrolyte interface that form due to local reaction competition between neighboring domains of different sizes. Continuum phase-field damage modeling quantifies stress-driven channel cracking and shows that the lithiated silicon stress state is critical for determining the extent of interfacial fracture. This work reveals the mechanisms that govern SSBs compared to conventional lithium-ion batteries and provides guidelines for engineering chemomechanically resilient electrodes for high-energy batteries.

25 ENERGY STORAGE↗

Ab initio Geochemistry of Hydrous Phases (Final Report)

Hydrous phases are among the most important Earth components. They are important for a broad suite of Earth processes, including the origin of life. From both thermodynamic and structural perspectives, however, they represent some of the most complex naturally occurring materials: their bonding often includes a combination of covalent solid, weak ionic, van der Waals, and hydrogen bonding, all within large unit cells. Most are solid solutions, and many are prone to variations in layer packing. Thermodynamic modeling of these materials is fundamental for understanding present and past natural processes, including those that shaped—and continue to shape—the structure and evolution of our planet. Yet, the thermodynamic properties of these materials at appropriate conditions are challenging to measure. To make significant progress and attain a deep understanding of these materials requires an atomistic theoretical approach.

36 MATERIALS SCIENCE↗

A Guideline to Mitigate Interfacial Degradation Processes in Solid‐State Batteries Caused by Cross Diffusion

Abstract Diffusion of transition metals across the cathode–electrolyte interface is identified as a key challenge for the practical realization of solid‐state batteries. This is related to the formation of highly resistive interphases impeding the charge transport across the materials. Herein, the hypothesis that formation of interphases is associated with the incorporation of Co into the Li 7 La 3 Zr 2 O 12 lattice representing the starting point of a cascade of degradation processes is investigated. It is shown that Co incorporates into the garnet structure preferably four‐fold coordinated as Co 2+ or Co 3+ depending on oxygen fugacity. The solubility limit of Co is determined to be around 0.16 per formula unit, whereby concentrations beyond this limit causes a cubic‐to‐tetragonal phase transition. Moreover, the temperature‐dependent Co diffusion coefficient is determined, for example, D 700 °C = 9.46 × 10 −14 cm 2 s −1 and an activation energy E a = 1.65 eV, suggesting that detrimental cross diffusion will take place at any relevant process condition. Additionally, the optimal protective Al 2 O 3 coating thickness for relevant temperatures is studied, which allows to create a process diagram to mitigate any degradation with a minimum compromise on electrochemical performance. This study provides a tool to optimize processing conditions toward developing high energy density solid‐state batteries.

Chemistry↗

A finite difference informed random walker (FDiRW) solver for strongly inhomogeneous diffusion problems

In nature, many complex multi-physics coupling problems exhibit strong diffusivity inhomogeneity. For instance, in the context of radionuclide absorption by porous wasteform materials within a flowing waste stream, the difference of species’ diffusivity in solid and liquid phases spans by 3~8 orders of magnitude. To solve the diffusion equations with strongly inhomogeneous diffusivity, traditional discretization-based methods, such as the Finite Difference Method (FDM), require infinitesimally small time steps (<10 -10 ) as high spatial resolutions are employed in most microstructure evolution processes, leading to prohibitively high computational costs. Here, this work developed an integrated numerical approach (FDiRW: Finite Difference informed Random Walk) to tackle this challenge. The idea is that utilizing the Random Walk concept, the fast diffusion is modeled as a superposition of point source’s solution for a concentration distribution while FDM is used to obtain the point source’s solution at each node. A mesh-coarsening algorithm is developed to generate an exclusive coarse mesh for FDiRW approach to maximize its efficiency. The effectiveness of the coarse mesh-based FDiRW approach is validated by benchmarking Finite Difference solutions. Numerical results demonstrated that FDiRW achieves a remarkable 1000x computational efficiency improvement over FDM while preserving desired accuracy for a medium-sized model of 192 × 192 × 192 grids. Finally, as models scale up, a floating-point operations (PLOPs) analysis of the FDiRW algorithm reveals that its computational complexity grows quadratically in terms of the number of nodes employed in computation.

36 MATERIALS SCIENCE↗

3D Printable All-Polymer Epoxy Composites

Herein, 3D printable polymer-toughened epoxy resin composites are reported. Epoxy resins are widely used due to their excellent properties, such as thermal and chemical stability. However, their applications are limited by traditional mold-based manufacturing and their high brittleness. Mixtures of homopolymers, diblock copolymers, and triblock copolymers composed of poly(phenylene ether), poly(styrene), poly(methyl methacrylate), and poly(ethylene oxide) that self-assemble into micelles in the uncured resin are employed, providing a balance of structure, creep resistance, and flowability that enables 3D printing processing techniques and a retention of dimensional fidelity from the time of printing throughout the cured state. The precured ink is solid at room temperature and has strong shear-thinning behavior at elevated temperature for printing. As the printed parts cure, the polymer morphology evolves via reaction induced phase separation to yield finished composites with enhanced mechanical properties, including a 40% increase in the impact strength compared to the neat epoxy, without compromising thermal properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗