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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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16 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Boron Coordination in Multicomponent Glasses: Analytical Models and Machine Learning With Uncertainty

Borosilicate glasses are extensively used in a variety of applications from kitchenware to nuclear waste immobilization due to the strong network formed by the Si-O-B bond that makes it resistant to chemical corrosion and gives it a low thermal expansion. Boron, however, exists in both trigonal BO3 and tetrahedral BO4 bonds in glass systems, which impacts the chemical durability and thermal resistance of the glass, amongst other properties. Boron coordination (N4), or the ratio of the amount of BO4 to BO3 within a glass, may aid in predicting these properties but is difficult to derive without experimental data due to the complexity of impacts from varied glass compositions and processing factors. For this reason, compositional models have been developed to predict boron coordination, but the models typically include a limited number of glass components. To help fill this gap in the models, in this work, a diverse multicomponent glass dataset of 809 glasses is compiled from a literature search, and then a number of analytical and machine learning (ML) models are trained on the dataset. Previously developed modified Bernstein and modified Du Stebbins analytical models were fitted to update parameters with the new dataset. Then, partially Bayesian neural networks, Gaussian process regressor, and heteroskedastic deterministic neural networks were evaluated. The ML models examined all have different strategies to overcome the potential for overfitting as a result of a limited training dataset, and return results that account for model uncertainty, which can be valuable for understanding model reliability. For the first time, cooling rate is introduced as an input parameter for ML models, showing consistent improvements in performance and solidifying the importance of including parameters outside of composition alone for N4 prediction. The machine learning models examined here show promise in accurate predictions of boron coordination in borosilicate glasses, all achieving R2 values of 0.91.

boron coordination↗
DOE OSTI2022

Augmented Adam-Gibbs model for glass melt viscosity and configuration entropy as functions of temperature and composition

As the temperature of glass melt increases, its structure approaches the state of a simple liquid while the configuration entropy approaches a maximum value. We describe this gradual change using a power law function of inverse temperature. The Adam-Gibbs model for glass viscosity as a function of temperature and glass composition augmented in this way is greatly simplified when applied to common glass families occupying moderate composition regions, such as float glass or nuclear waste glasses, on which properties can be approximated as linear functions of composition. The parsimonious model thus obtained is preferable for use in optimizing glass formulation and mathematical modeling of glass melting and forming. For multicomponent glasses with N viscosity-affecting components, the augmented Adam-Gibbs model requires 2N + 3 adjustable parameters. The model efficacy is demonstrated by fitting the model to a viscosity-temperature-composition dataset for low-activity nuclear waste glasses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multivariate analysis: An essential for studying complex glasses

Understanding the impact of individual compositional components on the devitrification of complex multicomponent glasses, for example, 10–50+ oxides, typically requires numerous studies to examine each component's impact. Here we apply exploratory data analysis (EDA) to a heterogeneous data set of silicate glasses to determine the cations’ individual and interacting effects on the crystallization of nepheline (nominally NaAlSiO 4 ). Our data consisted of 795 simulated high-level nuclear waste glasses composed of, on average, 50 oxide components. We determine the interactions in the heterogeneous data that cause deviations from the behavior found in simplified composition studies. Using both univariate and bivariate EDA techniques, we demonstrate the importance of including calculated structural glass parameters on nepheline's devitrification, including field strength, cation-to-anion radius ratio, and single-bond strength. Here, we also show that studies with simplified glass compositions may fall short in generating knowledge directly transferrable to complex glass compositions. The method used in this study has the potential to inform experimental design for simplified compositions (~6+ oxides) that can generate knowledge directly transferrable to complex, multivariable compositions. The observations reported here have broad implications for any study attempting to map the physical properties of a complex glass containing numerous cations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Examining phase separation and crystallization in glasses with X-ray nano-computed tomography

X-ray nano-computed tomography (nano-CT) is a powerful technique to characterize and visualize 3 dimensional (3D) phenomena in complex glasses at the nanoscale. This technique can offer a unique opportunity to explore the intricate morphology of multicomponent glass and glass-ceramic samples, due to its low X-ray energy and high spatial resolution (down to 50 nm). In the current demonstration paper, nano-CT provided insight into crystallization and phase separation, as well as a variety of other phenomena, including corrosion, fracture, and porosity. At scales ranging from 100 to 20 μm, the microstructures of phase separation in borosilicate, complex silicate, and chalcogenide glass compositions were examined. In addition, crystallites present in simulant nuclear waste glasses, volcanic glasses, and other related samples were explored. Nano-CT analysis can add to the understanding of (1) the formation processes, (2) distributions, interactions, and compositions of phases, and (3) the mechanisms, structures, and growth of crystallization and phase separation. Nano-CT offers wide potential in the field of glass science, especially when (1) common characterization methods are insufficient, (2) simple sample preparation is required, (3) 3D rendering is needed, or (4) compelling images of small, complex features are desired.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Predicting boron coordination in multicomponent borate and borosilicate glasses using analytical models and machine learning

Accurate prediction of boron coordination in multicomponent glasses is critical in glass science and technology as it strongly affects the properties of borate and borosilicate glasses. We have collected a dataset containing 657 glasses from literature with boron coordination values and developed models using analytical functions based on the well accepted Dell, Xiao and Bray model. Good prediction of boron coordination with a R 2 value higher than 0.8 was obtained. The large variation of boron coordination from experiments, originated from sample preparations and characterizations, led to difficulties in obtaining models with better prediction performance. Various machine learning (ML) algorithms were evaluated and slightly better prediction performance was observed; however, interpretation of the ML models is less straight forward. In conclusion, this study developed various models capable of providing quantitative boron coordination predictions, providing insights into its structural roles in multi-component glasses, and suggesting fruitful areas for future research.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Resonant Soft X-ray Scattering Reveals Hierarchical Structure in a Multicomponent Vapor-Deposited Glass

Multiphase vapor-deposited glasses are an important class of materials for organic electronics, particularly organic photovoltaics and thermoelectrics. These blends are frequently regarded as molecular alloys and there have been few studies of their structure at nanometer scales. Here, in this work, we show that a codeposited system of TPD (N,N'-bis(3-methylphenyl)-N,N'-diphenylbenzidine) and DO37 (disperse orange 37), two small molecule glass-formers, separates into amorphous, compositionally distinct phases with a domain size and spacing ca. 10s of nanometers that depends on substrate temperature during deposition. Domains rich in one of the two components become larger and more pure at higher deposition temperatures. We use resonant soft X-ray scattering (RSoXS) complemented with atomic force microscopy (AFM) and photoinduced force microscopy to measure the phase separation, topography, and purity of the deposited films. A forward-simulation approach to RSoXS analysis, the National Institute of Standards and Technology RSoXS Simulation Suite (NIST RSoXS simulation suite), is used with models developed from AFM images to evaluate the energy dependence of scattering across multiple length scales and interpret the RSoXS with respect to structure within the films. We find that the RSoXS is sensitive to a length scale of phase separation buried within the film that is consistent with the surface composition profile, and correlates to the topography to an extent that depends on substrate temperature. We demonstrate that vacuum scattering, which is often ignored in RSoXS analysis, contributes significantly to the features and energy dependence of the RSoXS pattern, and then illustrate how to properly account for vacuum scattering to analyze films with significant roughness. We then use this analysis framework to understand structure development mechanisms that occur during vapor deposition of a TPD-DO37 codeposited glass with results that outline paths to tune morphology in multicomponent materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Evolution of the structure and chemical composition of the interface between multi-component silicate glasses and yttria-stabilized zirconia after 40,000 h exposure in air at 800 °C

The chemical and structural stability of two commercial multicomponent silicate glasses (SCN and G6) in contact with yttria-stabilized zirconia (YSZ) was investigated after exposure times of up to 40,000 h in air at 800 °C. With exposure time, interfacial layers develop at the SCN-YSZ and G6-YSZ interfaces, which were characterized in detail using both quantitative chemical analysis and atomic-resolution imaging. At the SCN-YSZ interface, a Ca-Ba-Si-O reaction phase was found to grow by diffusion control. In G6-YSZ, Raman spectroscopy and electron microscopy revealed a disorganized interfacial reaction later between G6 and YSZ, and the occurrence of cubic to tetragonal to monoclinic phase transformations in YSZ. Finally, this microstructural evolution is discussed in terms of devitrification resistance of glass and diffusion processes at interfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electronic Structures of Iron in Oxide Glasses via 1s3p Resonant Inelastic X-ray Scattering

Electronic structures of iron in glasses are essential for unraveling the effect of transition metals on amorphous networks and controlling the electro-optical and transport properties of advanced glasses and amorphous energy-storing materials. The electronic configurations around iron in glasses, however, remain not well understood due to the structural disorders arising from multiple iron species with distinct valence, coordination, and spin states. Here, the first 1s3p resonant inelastic X-ray scattering (RIXS) for oxide glasses identifies hidden electronic configurations for Fe 2+ and Fe 3+ in amorphous networks. The results allow us to quantify the composition-induced evolution of oxygen ligand–field interactions of high-spin Fe 3d states with varying valence and coordination environments in complex glasses. The distinct electronic structures account for the electronic origins of iron-induced changes in the glass properties. The results offer prospects for a simultaneous probing of valence, coordination, and spin states of transition metals in diverse multicomponent oxide glasses and functional amorphous solids via 1s3p RIXS.

Kim, Yong-Hyun [Seoul National Univ. (Korea, Repub↗
DOE OSTI2023

Viscosity anomaly of a metallic glass-forming liquid under high pressure

Viscosity, as a critical property closely associated with the glass-forming ability of a liquid, has been extensively studied with varying temperatures. However, its pressure dependence has not been well explored yet due to experimental difficulties. Here, we measured the viscosity of a metallic glass-forming liquid, Zr 46 Cu 37.6 Ag 8.4 Al 8 , at pressures up to 6.1 GPa above the melting points by falling-sphere viscometry with ultrafast synchrotron x-ray imaging. Overall, the viscosity increases with pressure, while surprisingly, there is an abrupt drop between 3.2 GPa and 3.7 GPa, indicating the possible existence of a pressure-induced liquid-to-liquid transition. Pressure could change the short- and medium-range orders in the multicomponent glass-forming liquid, as suggested by the different crystalline outcomes after cooling to room temperature at high- and low-pressure ranges. In conclusion, our work extended the viscosity investigation of metallic glass-forming liquids to the high-pressure regime, which will expand our understanding of liquid-liquid transitions and metallic glass formation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Revealing local order via high energy EELS

Short range order (SRO) is critical in determining the performance of many important engineering materials. However, accurate characterization of SRO with high spatial resolution – which is needed for the study of individual nanoparticles and at material defects and interfaces – is often experimentally inaccessible. Here, we locally quantify SRO via scanning transmission electron microscopy with extended energy loss fine structure analysis. Specifically, we use novel instrumentation to perform electron energy loss spectroscopy out to 12 keV, accessing energies which are conventionally only possible using a synchrotron. Our data is of sufficient energy resolution and signal-to-noise ratio to perform quantitative extended fine structure analysis, which allows determination of local coordination environments. To showcase this technique, we investigate a multicomponent metallic glass nanolaminate and locally quantify the SRO with <10 nm spatial resolution; this measurement would have been impossible with conventional synchrotron or electron microscopy methods. Finally, we discuss the nature of SRO within the metallic glass phase, as well as the wider applicability of our approach for determining processing–SRO–property relationships in complex materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Glass formation during combinatorial sputtering in binary alloys

Glass formation is a complex phenomenon influenced by thermodynamic and kinetic aspects, which are often controlled by extrinsic contributions. While bulk metallic glasses are typically multicomponent alloys, binary alloys offer a simplified approach to studying glass formation. In this study, we fabricated 57 binary alloy systems through combinatorial sputtering, where each alloy system is represented in 66 different alloys. We developed an automated analysis to determine structure and composition using X-ray diffraction and energy-dispersive X-ray spectroscopy for over 3700 alloys. We found that ∼17 % of the alloys form glasses under the estimated cooling rate during sputtering of ∼10 8 K/s. Data analysis revealed that commonly used factors like atomic size ratio and heat of mixing are ineffective in predicting glass formation. However, the crystal structure mismatch of the alloys’ elements emerged as the strongest indicator of glass formation under sputtering conditions of binary alloys. Here, the differences in glass formation under slow cooling rates used for bulk glass formation and the here observed glass formation under rapid cooling rates are discussed.

Binary alloys↗
DOE OSTI2024

Reliability of Materials and Components for Solid Oxide Fuel Cells

Planar stack solid-oxide fuel cells (SOFCs) require seals that must operate reliably under demanding conditions for lifetimes of 40000 hours. This includes temperature fluctuations between 800°C and RT during on and off cycles, thermal stresses, oxidizing environments and chemical degradation to name a few. This comprehensive report provides results from long term testing of two commercially available multicomponent barium alkali silicate glasses: SCN and G6, chosen as sealing candidates. In this scope, the glass seals were deposited on YSZ and Al 2 O 3 substrates simulating electrolytes (Zrbased) and coatings (both zirconia and Al 2 O 3 ). The seal-substrate couples were subjected to 800°C under air and steam+H 2 +N 2 environments up to 40000 hours to test their integrity under real operating conditions. Extensive studies on the effects of exposure have been conducted over the span of testing at various time intervals. Within the context of characterization, mechanical properties such as density, roughness, thermal expansion and glass transition, viscosity and wettability behavior; and microstructural properties such as glass chemistries, defect formation (cracks and pores), phase transformations (devitrification) and glass-interface reactions are investigated. Results and discussions are provided with a focus on the degradation of the properties over long term interrupted testing.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Mapping structural heterogeneity at the nanoscale with scanning nano-structure electron microscopy (SNEM)

Here, in this work, we explore the use of scanning electron diffraction (also known as 4D-STEM) coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order (structure and chemistry) as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr 65 Cu 17.5 Ni 10 Al 7.5 bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modeled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don’t require energy filters on the instrument. We spatially map different quantities of interest (QoI’s), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI’s. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Solid-solid phase transition via the liquid in a Pd 43 Cu 27 Ni 10 P 20 bulk metallic glass under conventional conditions

The microscopic mechanism of solid-solid phase transitions is a long-standing fundamental issue in materials science. Here we directly report the experimental evidence of the existence of an intermediate liquid during the solid-solid phase transition in a bulk Pd 43 Cu 27 Ni 10 P 20 alloy by in situ high temperature high energy X-ray diffraction, combined with the differential scanning calorimetry at slow heating rates down to 5 K/min. We elucidate that this intermediate liquid is attributed to the melting of the low-melting-point crystalline phases, rather than induced by the elastic stress energy along the interface proposed in literatures. This could also be a general feature in multicomponent alloys if a low-melting-point crystalline phase is formed together with other crystalline phases during heating. Furthermore, all results obtained here are scientifically sound and provide new insight into the phase transition theory, which will trigger more studies on the microscopic mechanism of solid-solid phase transition via an intermediate liquid.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Anion exchange membranes based on (3-acrylamidopropyl) trimethylammonium chloride (APTA) and phenyl Acrylate: Impact of crosslinker and crosslinker content on physiochemical properties and transport behavior of acetate and formate

CO 2 reduction cells are innovative devices that convert CO 2 into valuable chemicals, such as formate (OFm - ) and acetate (OAc - ), at the cathode. One of the key challenges in these devices is the development of ion exchange membranes that enable the transport of charge carriers between electrodes while minimizing the transfer of CO 2 reduction products. This study focuses on the preparation and characterization of crosslinked anion exchange membranes (AEMs) made of phenyl acrylate (PA) and (3-acrylamidopropyl) trimethylammonium chloride (APTA), crosslinked with either poly(ethylene glycol) diacrylate (PEGDA) or N,N’-methylenebisacrylamide (MBAA). Here, the membranes are characterized to understand their physiochemical properties and corresponding transport behavior through characterization of water volume fraction, mechanical properties, ionic conductivity, ion exchange capacity, water contact angle, glass transition temperature as well as their permeability and solubility to formate and acetate. MBAA crosslinked membranes exhibit higher Young’s modulus and lower strain at break compared to PEGDA-crosslinked membranes, which is attributed to their shorter chain length. Within a series of membranes of varied comonomer content, for either PEGDA or MBAA as crosslinker, permeabilities generally follow free volume theory (increasing permeability with increasing water content where water content increases with decreasing crosslinker content). Interestingly, for membranes with different crosslinkers but analogous water volume fraction significant differences (∼2 orders of magnitude) in permeability are observed which we attribute to differences in chain mobility as characterized through the glass transition temperature.

25 ENERGY STORAGE↗