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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Uptake and binding of La 3+ and Cr 3+ ions by alkali metal substituted alpha-zirconium phosphate

The conversion of alpha-zirconium phosphate, Zr(HPO 4 ) 2 ·H 2 O, to the K-, Rb-, and Cs-phases and the subsequent ion exchange behavior of these alkali metal phases, A-ZrP, with La 3+ and Cr 3+ have been investigated. The conversion to the A-ZrP phases was achieved by reaction with metal chloride, metal hydroxide solution, and confirmed through various techniques, including X-ray powder diffraction, thermogravimetry analysis, IR spectroscopy, scanning and transmission electron microscopy, and X-ray photoelectron spectroscopy. The effect of material hydration, which increased the interlayer distance, was also examined. The ion exchange behavior of the A-ZrP showed strong affinity for both La 3+ , a representative for trivalent lanthanide metals, and Cr 3+ , a representative for the trivalent transition metals, with a rapid, near quantitative removal of the M 3+ ions at a pH of 3 when the ion concentration was ≤25% of the ion exchange capacity of the materials. Additionally, the ion affinity was shown to be pH and concentration-dependent, decreasing with a decrease in pH or an increase in ion concentration. Lastly, the binding strength of La- and Cr-loaded ZrP materials was examined through a series of leaching experiments in a carbonate buffer, phosphate buffer, HEPES buffer, and a series of EDTA solutions at various concentrations. No observable leaching occurred in the carbonate buffer, phosphate buffer, HEPES buffer, or when the EDTA concentration was below 0.1 mM. These results highlight the potential for the A-ZrP materials to provide a platform for trivalent transition metal and trivalent lanthanide radionuclide capture for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Solution structures in alkali nitrates and nitrites at high concentrations

In highly concentrated electrolyte solutions, where classical models often fail, specific ion–solvent interactions dictate bulk properties. Here, in this study, we combine small-angle X-ray scattering (SAXS) and Raman spectroscopy to link molecular coordination to mesoscale structure across alkali nitrate and nitrite solutions. Our results reveal a structural hierarchy driven by cation identity in that smaller cations (Li + , Na + ) form discrete contact ion pairs, while larger cations (K + , Rb + ) promote increasingly disordered local coordination and extended solute–solvent networks. Using nitrite salts as a structural control, we confirm this organizing principle across different anion geometries. Cs + undergoes a concentration-induced transition to a uniquely ordered state, resulting in a highly structured solution. This work provides a direct, mechanistic explanation for how cation choice dictates the ‘rules’ of solution architecture, offering a predictive basis for understanding phase behavior in complex industrial and environmental systems.

Mergelsberg, Sebastian T. [Pacific Northwest Natio↗
DOE OSTI2025

Alkali triel chalcogenide nanocrystals: a molecular reactivity approach to ternary phase selectivity

Alkali-metal-based materials are promising building blocks for energy conversion and storage technologies. Here, we use a molecular reactivity-based solution-phase approach to selectively synthesize multiple phases and specific polymorphs of lithium- and sodium-containing triel chalcogenide nanocrystals, LiTrCh 2 , NaTrCh 2 , and NaTr 3 Ch 5 , where Tr = Ga and In and Ch = S, Se, and Te. Analogous to the case of binary II–VI and III–V tetrahedral semiconductors, where the two commonly isolated zinc blende and wurtzite polymorphs are separated by only 1–50 meV f.u. −1 , we find that LiTrCh 2 nanocrystals easily adopt tetragonal (chalcopyrite) and orthorhombic polymorphs separated by only 2.7–6.2 meV f.u. −1 Because of this small energy difference, soft colloidal synthesis succeeds in accessing either one of these polymorphs, depending on the specific dichalcogenide precursor used. Highly reactive diethyl diselenide favors the thermodynamically more stable tetragonal I$\bar{4}2$d phase, whereas mildly reactive diphenyl diselenide favors the kinetic, metastable orthorhombic Pna2 1 phase. Density functional theory calculations confirm the relative energies among multiple LiTrCh 2 polymorphs and also model the observed powder X-ray diffraction pattern of a new C2 NaIn 3 Te 5 phase. 7 Li, 69 Ga, and 77 Se solid-state NMR spectra are consistent with phase-pure ternary LiGaSe 2 nanocrystals. A majority of the nanocrystal compositions are visible-light emitters. This work opens the door to new Li/Na-based ternary triel chalcogenide nanostructures for energy storage and conversion applications.

Pavel, Md Riad Sarkar [Iowa State Univ., Ames, IA ↗
DOE OSTI2022

The impact of the electric field of metal ions on the vibrations and internal hydrogen bond strength in alkali metal ion di- and triglycine complexes

Using infrared predissociation spectroscopy of cryogenic ions, we revisit the vibrational spectra of alkali metal ion (Li+, Na+, K+) di- and triglycine complexes. We assign their most stable conformation, which involves metal ion coordination to all C=O groups and an internal NH⋯NH2 hydrogen bond in the peptide backbone. An analysis of the spectral shifts of the OH and C=O stretching vibrations across the different metal ions and peptide chain lengths shows that these are largely caused by the electric field of the metal ion, which varies in strength as a function of the square of the distance. The metal ion–peptide interaction also remotely modulates the strength of internal hydrogen bonding in the peptide backbone via the weakening of the amide C=O bond, resulting in a decrease in internal hydrogen bond strength from Li+ > Na+ > K+.

Chemistry↗
DOE OSTI2024

Alkali hydroxide (LiOH, NaOH, KOH) in water: Structural and vibrational properties, including neutron scattering results

Structural and vibrational properties of aqueous solutions of alkali hydroxides (LiOH, NaOH, and KOH) are computed using quantum molecular dynamics simulations for solute concentrations ranging between 1 and 10M. Element-resolved partial radial distribution functions, neutron and x-ray structure factors, and angular distribution functions are computed for the three hydroxide solutions as a function of concentration. The vibrational spectra and frequency-dependent conductivity are computed from the Fourier transforms of velocity autocorrelation and current autocorrelation functions. Our results for the structure are validated with the available neutron data for 17M concentration of NaOH in water [Semrouni et al., Phys. Chem. Chem. Phys. 21, 6828 (2019)]. We found that the larger ionic radius [rLi+

Chemistry↗
DOE OSTI2024

Growth of ultra-flat ultra-thin alkali antimonide photocathode films

Ultra-flat, ultra-thin alkali antimonide photocathodes with high crystallinity can exhibit high quantum efficiency and low mean transverse energy of outgoing electrons, which are essential requirements for a variety of applications for photocathode materials. Here, we investigate the growth of Cs 3 Sb on graphene-coated 4H–SiC (Gr/4H–SiC), 3C–SiC, and Si 3 N 4 substrates. Sb is deposited using pulsed laser deposition, while Cs is deposited thermally and simultaneously. We demonstrate, employing x-ray analysis and quantum efficiency measurements, that this growth method yields atomically smooth Cs 3 Sb photocathodes with a high quantum efficiency (>10%), even in the ultra-thin limit (<30 nm). For the Si 3 N 4 substrate, film growth is shown to be polycrystalline, while films grown on Gr/4H–SiC show a high degree of ordering with signs of epitaxy.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Applicability of alkali beam emission spectroscopy on NSTX-U

Understanding fast pedestal dynamics and turbulent transport in the edge and scrape-off layer (SOL) plasma of spherical tokamaks is crucial for the design and operation of future fusion reactors. The alkali beam emission spectroscopy diagnostic technique offers a means to measure the absolute electron density radial profile and fluctuation amplitude in these regions. Here, in this study, we demonstrate that injecting a sodium neutral beam radially into the plasma and analyzing the light emission from its 3p–3s atomic transition using near-orthogonal viewing angles allows for accurate measurement of the electron density profile and fluctuations in the National Spherical Torus Experiment (NSTX) Upgrade spherical tokamak. Our findings indicate a peak signal-to-noise ratio of 118 in the pedestal and 12 in the SOL under typical NSTX plasma conditions. The spatial resolution for the electron density profile is estimated to be between 2 and 8 mm, while for fluctuation measurements, it ranges from 12 to 15 mm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Attosecond time delays at Cooper minima in valence-shell photoionization of alkali-metal and alkaline-earth-metal atoms

Ji et al. [New J. Phys. 26, 093014 (2024)] established a direct link between the photoionization cross section and the attosecond time delay near Cooper minima (CM) in the valence shells of noble-gas atoms. This link is based on the analytic properties of the ionization amplitude in the complex plane of the photoelectron energy, and is particularly sensitive to the winding number of the amplitude around the origin of the complex energy plane. Here, in this study, we demonstrate an analogous relation for photoionization of the valence 𝑛⁢𝑠 shells of alkali-metal atoms (AMA), from Na (𝑛 = 3) to Cs (𝑛 = 6), as well as alkaline-earth-metal atoms (AEMA), from Mg (𝑛 = 3) to Ba (𝑛 = 6). To this end, we employ a fully relativistic formalism that separates the two complementary 𝑛⁢𝑠 1/2 → 𝐸⁢𝑝 1/2 and 𝐸⁢𝑝 3/2 ionization channels. Each of these channels exhibits a phase variation close to 𝜋, but in opposite directions, near their respective Cooper minima. This phase variation vanishes in a nonrelativistic formulation, where the two channels become degenerate. For AMA, due to the threshold proximity of the CM, the universal Coulomb contribution to the time delay must be subtracted. The remaining component of the time delay is target-specific, angular-dependent, and accessible through comparative measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Prediction of exotic magnetic states in the alkali-metal quasi-one-dimensional iron selenide compound Na 2 FeSe 2

The magnetic and electronic phase diagram of a model for the quasi-one-dimensional alkali-metal iron selenide compound Na 2 FeSe 2 is presented. The novelty of this material is that the valence of iron is Fe 2+ , contrary to most other iron-chain compounds with valence Fe 3+ . Using first-principles techniques, we developed a three-orbital tight-binding model that reproduces the ab initio band structure near the Fermi level. Including Hubbard and Hund couplings and studying the model via the density-matrix renormalization group and Lanczos methods, we constructed the ground-state phase diagram. A robust region where the block state ↑↑↓↓↑↑↓↓ is stabilized was unveiled. The analog state in iron ladders, employing 2×2 ferromagnetic blocks, is by now well established, but in chains a block magnetic order has not been observed yet in real materials. The phase diagram also contains a large region of canonical staggered spin order ↑↓↑↓↑↓↑ at very large Hubbard repulsion. At the block-to-staggered transition region, an exotic phase is stabilized with a mixture of both states: an inhomogeneous orbital-selective charge density wave with the exotic spin configuration ↑↑↓↑↓↓↑↓. Our predictions for Na 2 FeSe 2 may guide crystal growers and neutron-scattering experimentalists towards the realization of block states in one-dimensional iron selenide chain materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Revealing the electronic structure of van der Waals antiferromagnetic NiPS 3 through synchrotron-based 𝜇-ARPES and alkali metal dosing

Antiferromagnetic NiPS 3 has recently emerged as a quantum material of considerable interest, thanks to the discovery of multiple new couplings involving electrons, spins, orbitals, phonons, and magnons. However, controversies and open questions persist concerning the fundamental origins of these couplings. A critical piece of information required to advance the understanding is the precise electronic band structure of NiPS 3 . Angle-resolved photoemission spectroscopy (ARPES), combined with alkali metal dosing (AMD), can enable us to directly observe the subtle electronic states that appear around the Fermi surface, offering valuable insights into the intriguing quantum properties and interplays of the examined material. Here, in this study, we present a comprehensive characterization and analysis of the band structure of van der Waals layered antiferromagnet NiPS 3 , leveraging state-of-the-art μ-ARPES measurements supported by density functional theory (DFT) calculations. Theoretical DFT results identify the orbital contributions to the observed bands, providing a precise understanding of the experimental ARPES data. Crucially, AMD enables the observation of conduction band and defect-related states above the valence band maximum in NiPS 3 . Furthermore, temperature dependent ARPES results across the Néel transition temperature of NiPS 3 reveal that the paramagnetic and antiferromagnetic phases have nearly identical band structures, underlining the highly localized character of Ni d states. These findings substantially deepen our understanding of the electronic properties of NiPS 3 and lay a vital foundation for exploring the intriguing quantum phenomena it exhibits.

Cao, Yifeng [Boston Univ., MA (United States); Law↗
DOE OSTI2020

Structure and stability of alkali gallates structurally reminiscent of hollandite

Abstract Single crystals of CsGa 7 O 11 , RbGa 7 O 11 , and RbGa 4 In 5 O 14 were grown from alkali halide melts and their structures were characterized by single crystal and powder X‐ray diffraction. CsGa 7 O 11 and RbGa 7 O 11 adopt the same structure type, reminiscent of the hollandite structure type, as it contains nearly rectangular channels made up of two dimers of edge‐sharing GaO 6 octahedra, and two corner‐sharing octahedron/tetrahedron pairs. The structure of RbGa 4 In 5 O 14 is more complex and is comprised of indium octahedra, gallium trigonal bipyramids, and gallium tetrahedra, and contains similar sized tunnels as CsGa 7 O 11 and RbGa 7 O 11 . CsGa 7 O 11 and RbGa 4 In 5 O 14 were further characterized by TGA, ion exchange experiments, and DFT studies revealing that both structures are thermodynamically stable up to 850°C; however, CsGa 7 O 11 decomposes to GaO(OH) xH 2 O when heated in warm aqueous solutions. CsGa 7 O 11 undergoes ion exchange in both an aqueous solution of RbCl and a RbNO 3 melt, as predicted by DFT studies, where the ion exchange is more extensive in the RbNO 3 melt.

Juillerat, Christian A.↗
DOE OSTI2020

Vibro-acoustic modulation and data fusion for localizing alkali–silica reaction–induced damage in concrete

This article investigates the application of vibro-acoustic modulation testing for diagnosing damage in concrete structures. The vibro-acoustic modulation technique employs two excitation frequencies on a structure. The interaction of these excitations in the measured response indicates damage through the presence of sidebands in the frequency spectra. Past studies using this technique have mostly focused on metals and composites (thin plates or laminates). Our research focuses on concrete, which is a highly heterogeneous material susceptible to a variety of chemical, physical, and mechanical damage processes. In particular, this article investigates diagnosing cracking in concrete from an expansive gel produced by an alkali–silica reaction in the presence of moisture. Past studies have been limited to damage detection using vibro-acoustic modulation testing, whereas this article extends the technique to damage localization. A cement slab with pockets of reactive aggregate is used to investigate the diagnosis technique. The effects of different testing parameters, such as locations, magnitudes, and frequencies of the two excitations, are analyzed and incorporated in the damage localization methodology. A Bayesian probabilistic methodology is developed to fuse the information from multiple test configurations in order to construct damage probability maps for the test specimen. The results of vibro-acoustic modulation–based damage localization are validated by petrographic study of cores taken from the slab.

Karve, Pranav↗
DOE OSTI2021

Evaluations of the Fates of Alkali Metals, Actinides, Mercury, and Iodine During DWPF Recycle Diversion

The fates of alkali metals, actinides, mercury, and iodine in the Defense Waste Processing Facility Recycle Diversion process (as currently conceptualized) have been evaluated through paper studies based on available knowledge of the chemistry, physical properties, solubility, and volatility of the various species involved. The effect of pH in the range from 9 to 13 has been discussed. Recommendations for additional studies to close technology gaps have been provided, many of which are contingent upon the results of pending testing and sample characterization efforts. There is uncertainty in the amounts of soluble actinides passing through the process filter, though the bulk of the actinides should be captured on the filter with the Recycle Collection Tank solids and the total amounts of actinides should be relatively low. The Recycle Collection Tank pH could impact the fraction of actinides reaching the evaporator, but the primary factors determining the actinide fate are expected to be the amount of CO 2 sorption from air sparging or, for certain actinides (such as plutonium), oxidation and/or sorption to MnO 2 solids from permanganate additions to destroy the glycolate anion. Process optimization could minimize the amounts of actinides passing the filter. Depending upon the levels of mercury observed in recycle stream samples and because of the volatility of mercury, the evaporator should be designed with the capability to remove dense mercury phases from the condensate to avoid exceeding ETP WAC limits. The facility design must be adequate to transfer dense mercury phases and testing to confirm mercury transfer is needed. Simulant containing mercury is recommended for both filtration and evaporation testing. OLI Modeling of the various recycle streams is recommended to provide insight on the fate of iodine. Iodine-spiked simulants are recommended for upcoming evaporation tests. The pro) ect should consider the likelihood and impact of NAS scale formation in the evaporators. Process optimization may be needed to minimize the accumulation of NAS scale and possibly the sorption of actinides in the evaporator. Actual waste testing of the Recycle Diversion filtration and evaporation should include the analysis of actinides, mercury, and iodine to determine their partitioning.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Machine Learning for Processing Ultrasonic Data from Long-Term Monitoring of Concrete with Alkali-Silica Reaction (ASR)

The alkali–silica reaction (ASR) is a phenomenon that leads to material degradation in concrete, resulting in the formation of microcracks and cracks. This deterioration causes a loss of mechanical properties, concrete damage, and even corrosion. To address this issue, ultrasonic nondestructive evaluation can be employed as a technique for long-term monitoring of ASR development and condition assessment of concrete subjected to ASR. However, traditional approaches typically utilize only a few wave parameters, such as wave velocity or amplitude, to characterize ASR-induced concrete damage while disregarding the majority of information present in the ultrasonic signals.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Assessment of Machine Learning for Ultrasonic Nondestructive Evaluation of Alkali–Silica Reaction in Concrete

Alkali–silica reaction (ASR) is a type of material degradation in concrete structures that leads to concrete cracking and rebar corrosion, thereby reducing the material’s structural integrity and the overall structure’s lifetime and raising safety concerns. Ultrasonic nondestructive evaluation (NDE) has been proven to be a valuable technique for assessing concrete properties and monitoring ASR progression in concrete. However, the deployment and analysis of ultrasonic NDE and its data requires specialized expertise, often relying on the engineer’s subjective interpretation. With the surge in computational power, artificial intelligence (AI) and machine learning (ML) algorithms have become popular in automating NDE data analysis. Various industrial sectors are increasingly adopting ML algorithms for NDE data analysis with a growing emphasis on AI–assisted automation. Regulatory agencies are also preparing for this technological shift, anticipating corresponding revisions in standards. Thus, there is an urgent need to identify the capabilities and limitations of current ML technologies for the evaluation of concrete material properties and damage status. Furthermore, the effects of various factors on ML model performance must be thoroughly investigated. The study summarized herein evaluated the effectiveness of two ML models (i.e., support vector regression (SVR) and deep neural network (DNN)) in predicting concrete material damage induced by ASR based on the long-term ultrasonic monitoring data. Four distinct concrete specimens were cast with artificially induced ASR, and over a period exceeding 500 days, ultrasonic signals and expansion data were continuously collected. For the SVR model, wave velocity and 12 other wave features were extracted from the ultrasonic signals, with 6 out of 13 features selected as input for the model. Different combinations of training and testing datasets were designed to explore factors influencing prediction performance, including the range of data within training and testing sets, in addition to various signal preprocessing methodologies. These findings suggest the importance of using a training dataset with a broader data range compared with testing datasets for improved model performance alongside consistent signal preprocessing across datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Performance Comparison of Machine Learning Models for Ultrasonic Nondestructive Evaluation of Alkali-Silica Reaction in Concrete

Alkali-silica reaction (ASR) causes concrete degradation, leading to cracking, rebar corrosion, and reduced structural integrity, which raises safety concerns. Ultrasonic nondestructive evaluation (NDE) effectively assesses concrete properties and monitors ASR progression. However, its deployment and analysis require specialized expertise and subjective interpretation. As computational power increases, artificial intelligence (AI) and machine learning (ML) algorithms are increasingly being used to automate NDE data analysis across various industries for AI-assisted automation. Regulatory agencies are adapting to this technological shift, prompting a need to evaluate current ML technologies’ capabilities and limitations in assessing concrete material properties and damage. This report presents a comparative analysis of four ML regression models for predicting concrete material damage induced by ASR expansion using long-term ultrasonic data monitoring. The models investigated include linear regression (LR), support vector regression (SVR), shallow neural networks (NN), and deep neural networks (DNN). LR, SVR, and shallow NN models use features extracted from ultrasonic signals, whereas the DNN model processes time-domain ultrasonic signals and frequency spectra directly. The study systematically compared the models’ performance from various perspectives, including model input, prediction performance, and generalization ability. The findings indicate significant variability in model performance, with some ML algorithms achieving very high or very low prediction accuracy depending on the preprocessing and feature engineering (extraction and selection) applied. Key insights include the observation that shallow ML models (LR, SVR, and shallow NNs) require meticulous preprocessing and feature extraction to achieve high accuracy. In contrast, the DNN model, although it bypasses the need for feature engineering, necessitates extensive preprocessing to mitigate noise and computational demands. The SVR model emerged as the top performer among the shallow models, and the DNN model exhibited superior performance on specific datasets but struggled with generalization across specimens from different batches. Additionally, the SVR model is sensitive to temperature variations, whereas the DNN model is robust in this regard. Using recurrent neural networks is recommended for future ASR expansion prediction studies. Recurrent neural networks’ inherent ability to capture temporal dependencies and long-term patterns makes them well suited for analyzing sequential ultrasonic monitoring data. Overall, the results and conclusions of this study could provide insights into the capabilities and effectiveness of ML when applied to ultrasonic NDE data and help identify best practices for using ML for ultrasonic NDE of concrete material properties.

36 MATERIALS SCIENCE↗