Search NASASearch

SEARCH · Search NASA

Results for “non-covalent chalcogen bonding”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

398 records · Page 5

Thermodynamics of Tritium Trapping by Point Defects at Interfacial Cr-based Phases of the Al Coating

Density functional theory (DFT) simulations have been carried out to evaluate the potential for tritium trapping by metal vacancies in four phases Cr-containing phases (i.e., Cr3Si, Al0.3Cr0.7, Al8Cr5-HT, and Al8Cr5) identified near the interface between the Al coating and 316 stainless steel (316 SS) cladding. In addition, an ab initio thermodynamics approach has been employed to predict the temperature and T2-partial pressure dependence on the thermodynamics of singly tritiated defects. Key results in this work suggest that metal vacancies in the four phases have the potential to favorably trap tritium species, especially Si vacancies in Cr3Si phase. This overall thermodynamic trend can be correlated to the energy cost of having an interstitial tritium in the lattice, which has been calculated to range from 0.17 eV in Al8Cr5-HT to 0.89 eV in Cr3Si. A comparison of the results from this study with previous theoretical works investigating tritium behavior in other Fe-Al phases identified in the aluminide coating, suggests that metal vacancies are generally able to trap tritium in various Fe-Al aluminide phases. Especially, it was found that Si and Al vacancies would be the most efficient to trap for tritium, followed by Cr vacancies, then Fe and Ni vacancies. In the four Cr-based material phases investigated in this work, it is interesting to note that, in the absences of Fe or Ni species, strong interactions between tritium and the metal vacancies are always occurring by the formation of preferential Cr—T bonds (i.e., no Si—T or Al—T bonds were formed).

Sassi, Michel J.

Development of an Amine Oxide Polyzwitterion Brush Martini Model with Polarizable Water and Ions

Abstract In order to accurately simulate the fouling process of proteins onto polyzwitterion brushes, models that accurately capture the hydration properties and chain conformations of such brushes must first be established. We developed a Martini coarse-grained (CG) model for amine oxide polyzwitterion (PNOMA) brushes, a promising class of antifouling materials, in polarizable water and ions by fitting to all-atom bond and angle distributions, monomer hydration free energy, monomer–monomer distance potential of mean force (PMF), and monomer–salt radial distribution functions (RDFs). Martini 2.2P was selected for compatibility with the established polarizable water and ion models. For comparison with PNOMA, we also constructed models for conventional sulfobetaine (PSBMA) and phosphorylcholine (PMPC) polyzwitterions and the polycation PMETAC using established nonbonded bead types from the literature and refitting bond and angle potentials. We simulated each polymer brush chemistry for varying grafting density and chain length, validating brush height scaling relations against experimental data. The CG models captured the relative hydration strengths among different polyzwitterion chemistries, and brush heights extrapolated to higher molecular weights are in agreement with experimental ellipsometry data. We find that chain swelling of the superhydrophilic PNOMA brushes lies between that of the traditional polyzwitterions PSBMA/PMPC and the polycation PMETAC. For PNOMA brushes in NaCl solution, simulated brush height decreases with salt concentration due to the selectively strong interactions between amine oxide and sodium ions.

Walker, Christopher C. [Oak Ridge National Laborat

An Assessment of the Nevada Test Site for Low-Level Waste Management

This report presents a summary of description information, facilities, and operating practices at the Nevada Test Site. It is concluded that NTS is not only a feasible location for surface and near-surface storage of low-level wastes, but also a potential site for underground storage of higher level wastes.

052002* -- Nuclear Fuels-- Waste Disposal & Storag

Toward Large Field-of-view X-ray Spectrometers with Magnetic Microcalorimeters

A future X-ray telescope mission like Lynx, a X-ray flagship mission concept, requires a large field of view, high energy resolution, and high spatial resolution. The Magnetic Microcalorimeter (MMC) detectors we are developing for such a mission feature a 5-arcminute field of view, approximately 100,000 pixels, each spanning 0.5–1 arcsecond. These detectors require the readout of 8,000 sensors. Three different array types have been designed to meet scientific goals, two of which utilize thermal multiplexing to reduce the number of readout channels in a scheme called “Hydra.” We are currently fabricating detectors on a recently completed buried wiring wafer with connections to every sensor. The sensors are read out using a microwave multiplexer (μMUX) with flux ramp modulation. A single μMUX can read out approximately 1,000 sensors with only two feed lines. We will report on the test of the first two-dimensional μMUX chip, consisting of 78 resonators. μMUX chips that pass screening will be directly bonded to MMC array chips using indium bump bonding. In parallel, we have tested a kinetic inductance traveling wave parametric amplifier (KI-TWPA) to amplify signals at low temperatures. The KI-TWPA exhibits extremely low internal noise, approaching the standard quantum limit. Since the energy resolution of an MMC is primarily limited by the readout system, the KI-TWPA is an ideal amplifier for MMCs with μMUX readout. We recently measured the readout noise of a μMUX with a KI-TWPA, demonstrating its capability for reading out MMC arrays. We present the design and fabrication of the latest MMC detectors, along with its readout performance.

Magntic Microcalorimeters

Global Model Estimates of Atmospheric Al, Ca, Fe, Si, and Ti from Dust and Non-Dust Aerosols Informed by EMIT Surface Mineralogy and Evaluated Against Observations

Atmospheric deposition of micro-nutrients like Fe has been shown to be important for ocean biogeochemistry. The largest source of atmospheric Fe and other elements (e.g., Ca, Al, Si, and Ti) is desert dust, although there are significant non-dust sources in some regions. However, past estimates of these elements have been substantially uncertain due to limited information about the composition of the desert source regions. Here we use elemental distributions estimated from new Earth Surface Mineral Dust Source Investigation (EMIT) observations, which provide mineralogical composition at the surface of the Earth based on imaging spectroscopy measurements from the International Space Station. We add in other sources of these elements (anthropogenic and natural) and compare to a compilation of available surface concentration data from stations over land and from shipborne observations. Our results suggest that the modeled distribution is similar to available observations, but discrepancies still exist in both natural desert dust regions as well as regions dominated by anthropogenic sources. Global budgets for the elements Ca, Al, Fe, Si, and Ti suggest that desert dust remains the dominant source for these elements but anthropogenic or volcanic sources are also important for these elements. Changes in elemental distributions since preindustrial times were also estimated.

aerosols

Enhanced Catalytic Dechlorination of Polyvinyl Chloride (PVC) and H2 Production Enabled by Synergistic Gaδ+/Ga0 Active Sites in Liquid Metal Particles

Polyvinyl chloride (PVC) is ubiquitous yet challenging to recycle due to its tendency to thermally decompose above 250 °C, releasing toxic, corrosive chlorinated compounds, and its inability to melt. Here, we report a catalytic strategy for PVC upcycling at 160 °C using gallium liquid metal particles (Ga-LMP) featuring a dynamic Ga-GaOOH core–shell architecture. These catalysts enable concurrent dechlorination and hydrogen evolution, yielding up to 7% H2 (based on initial hydrogen atoms in PVC) along with a highly dechlorinated (>95%) carbonaceous solid and aqueous HCl. Mechanistic investigations combining X-ray photoelectron spectroscopy, infrared spectroscopy, solid-state NMR, inelastic neutron scattering, and ab initio molecular dynamics reveal a synergistic interplay between Gaδ+ sites in the GaOOH shell and metallic Ga0 in the core. Cationic Ga initiates C–Cl bond activation and HCl formation, while progressive reduction of the shell exposes Ga0 sites that promote C–H activation and H2 evolution. Control experiments with a Ga salt and bulk Ga liquid metal confirmed that neither oxidation state alone can achieve both transformations efficiently. This work establishes a dynamic dual-site paradigm for liquid metal catalysis, in which the in situ evolution and coexistence of oxidized and metallic species enable sequential and cooperative bond activation pathways. These findings provide a general design principle for novel liquid metal catalysts that target challenging polymer transformations under mild conditions.

Zingg, Benjamin [ORNL] (ORCID:0009000914530153)

Discrete Rotational Energy for Polyatomic Molecules in Direct Simulation Monte Carlo

The environments experienced by vehicles upon entry into planetary atmospheres generally result in severe aerothermodynamic loading. These flows are characterized by the formation of strong shock waves, behind which high temperatures and non-equilibrium environments are generated, and the accurate prediction of internal energy relaxation and chemical kinetics becomes important. This manuscript focuses on the internal relaxation of the rotational energy of polyatomic molecules. Previous work has described the implementation of a discrete rotational energy model for diatomic molecules (linear rotators). Later, Gimelshein et. al extended this model to include polyatomic molecular internal energies. However, they did not include details on how to generate the particles at equilibrium conditions and centrifugal distortion was not included in their model. The purpose of the present study is to extend the afore-mentioned models to the treatment of discrete rotational energy in polyatomic molecules with the addition of centrifugal distortion. An overview of the background theory needed for the implementation of the model will be given followed by the model itself and verification of the model. For example, sampled versus Boltzmann distributions are compared in Figure 1 for CH3 (oblate rotator – two quantum numbers) and examples of thermal relaxation behavior for linear and non-linear rotators are presented in Figure 2. In addition, comparisons of thermophysical properties will be presented, as well as examples of adiabatic relaxation and application to hypersonic flow.

Rarefied Gas Dynamics

Justification that the Thermo-Fisher Scientific 241 Am Residues Were Generated by Atomic Energy Defense Activities

The Waste Isolation Pilot Plant (WIPP) Land Withdrawal Act (LWA) as amended by the National Defense Authorization Act for Fiscal Year 1997 (1) requires that for Transuranic (TRU) waste to be eligible for disposal at WIPP, it must have been generated by atomic energy defense activities. The definition of “atomic energy defense activity” is defined in the Nuclear Waste Policy Act of 1982 (NWPA) (2).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W

Model-based, in-situ, non-destructive qualification and certification of parts made by autonomous additive manufacturing

To address the significant productivity challenges associated with the qualification and certification (Q&C) tasks of additively manufactured (AM) parts, which have traditionally relied on rigorous post‐build inspection and testing, we propose an integrated framework that combines model‐based qualification and certification (MBQ&C) with autonomous additive manufacturing (AAM). MBQ&C employs high‐fidelity predictive models, developed within the Integrated Computational Materials Engineering (ICME) paradigm, to simulate process–structure–property–performance relationships for assessing a part’s fitness for use. Since predictive models are commonly machine learning (ML)-based or reduced-order surrogates of validated physics models, they run efficiently, enabling timely inference. In parallel, the self-driving AAM utilises ML-based adaptive, closed‐loop control strategies to avoid, mitigate, or repair defects and anomalies during fabrication, thereby increasing the likelihood of producing acceptable parts. A key feature of the combined AAM-MBQ&C framework is that predictive models explicitly incorporate defects or anomalies that persist after the build, using instance-specific data captured via in-situ sensing. This customisation enables a build‐specific assessment of fitness for use, rather than relying on nominal or generic parameters. Such individualised evaluation provides a robust basis for Q&C-related acceptance decisions relating to each build. Additionally, the rapid solution capabilities of ML or reduced-order models enable the determination of a part’s suitability for service shortly after build completion. As the framework matures, it has the potential to substantially reduce reliance on conventional point‐design approaches—such as time‐consuming post‐build computed tomography scanning and costly destructive testing. Thus, the AAM-MBQ&C framework represents a transformative, scalable strategy for quality assurance of AM components, as parts produced within a stable, validated, and certified envelope can be certified with reduced testing. Key benefits include: (1) significant gains in Q&C productivity through efficient, model-centric assessment; (2) performance-based classification of defects into critical and non-critical categories; (3) the ability to predict potential deviations in the performance of parts affected by real-time, adaptive process control interventions relative to those produced under a certified process, and (4) the enabling of virtual Q&C for service environments that are difficult, hazardous, or impractical to access or reproduce experimentally. Collectively, these capabilities strengthen the business case for AM, particularly for high‐consequence and mission‐critical applications. Finally, although this work focuses on powder-based AM, the proposed techniques could be extended to AM processes employing alternative feedstock forms.

Gunasegaram, Dayalan

Assessment of Molybdate Based Corrosion Inhibitor for use at the Savannah River Tank Farm Cooling Water System

The Savannah River Site (SRS) has relied on 51 underground storage tanks, many dating back to the 1950s, to store radioactive liquid waste generated from nuclear processing and radionuclide production. These tanks use carbon steel cooling coils, cooled by soft, acidic water, to dissipate the decayed heat produced by radioactive waste. For decades, following historical industry practices, chromate has been added to the cooling water (~450 ppm at pH 9-11) to effectively inhibit corrosion, ensuring cooling coil longevity. Inspections of failed coils reveal that chromate-treated surfaces are generally well-preserved.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W

Crossover from quantum to classical transport

Understanding the crossover from quantum to classical transport phenomena has become of fundamental importance not only for technological applications due to the creation of sub-10nm transistors – an important building block of our modern life – but also for elucidating the role played by quantum mechanics in the evolutionary fitness of biological complexes. This article provides a basic introduction into the nature of charge and energy transport in the quantum and classical regimes. Here, it will identify the characteristic transport properties in both limits, and demonstrate how they can be connected through the loss of quantum mechanical coherence. I will identify the salient features of the crossover physics, and demonstrate their importance in opening new transport regimes and for understanding efficient and robust energy transport in biological complexes.

charge

Developments in Fibrous Refractory Composite Insulation

The development of a new insulation material for heat-shielding advanced reusable entry vehicles is reported. The material, called fibrous refractory composite insulation, is a composite of two ceramic fibers with no additional additives to bond the fibers together; it also includes silicon carbide, an emmittance agent, to improve its optical properties at high temperature. One fiber is a drawn 11-micron-diameter aluminoborosilicate fiber, the other fiber is the silica fiber (microquartz) used in producing silica RSI (reusable surface insulation for the Space Shuttle), which is a blown fiber of 1-3 micron diameter and variable length. A composition containing 20%, with a thermal shock resistance of 1.8 that of all silica insulation, has been successfully produced in a pilot plant.

D B Leiser

Robust optimization of flexible diafiltration systems for critical mineral separations

This paper provides major contributions in expanding the literature for membrane process design with critical mineral recovery applications and showcasing the importance of robust design techniques for reducing risks of underperformance in such systems. Here, a membrane process flowsheet featuring PrOMMiS membrane models for recovering lithium/cobalt from spent batteries is showcased, uncertainty in membrane sieving and localized fouling are considered, and robust designs are obtained using the PyROS toolset. This paper is intended for a general audience of researchers working in critical minerals, membranes, and optimization related areas.

36 MATERIALS SCIENCE

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

Gas-mediated defect engineering in earth-abundant Mn-rich layered oxides for non-aqueous sodium-based batteries

Gases are often by-products of battery materials during cell formation and degradation, affecting the cycle life and safety of rechargeable batteries. However, understanding gas-mediated (electro)-chemical reactions and nanoscale structural transformations during the synthesis of battery electrode materials remains challenging because of the lack of suitable characterization routes and the complexity of the interplay between thermodynamics and kinetics. Here, in this study, we use operando synchrotron X-ray diffraction, in situ transmission X-ray microscopy and multiscale modelling to elucidate the reaction pathways and microstructural defect development of earth-abundant Mn-rich layered oxides as positive electrode materials for sodium-based batteries. In particular, we demonstrate the dominant role of CO 2 over O 2 and H 2 O (g) in modulating the competition between entropy and enthalpy during solid-state synthesis. Using Ni 0.25 Mn 0.75 CO 3 as a model precursor, we reveal that CO 2 generation favours the formation of entropy-driven metastable intermediates, suppresses closed pore/nanovoids formation and decreases chemical heterogeneity and residual lattice strain of Mn-rich layered oxides during the synthesis. This result motivates a fast-sintering strategy to promote CO 2 release, which ultimately leads to improved chemo-mechanical and electrochemical stability of the Mn-rich positive electrodes when tested in non-aqueous Na metal coin cells.

36 MATERIALS SCIENCE

Assembly bias and local Primordial non-Gaussianity from DESI DR1 quasars

The analysis of the large-scale clustering of quasars (QSO) observed by the Dark Energy Spectroscopic Instrument (DESI) represents a promising avenue for constraining local Primordial non-Gaussianity (PNG), parameterized by f NL . The signal to be constrained is the scale-dependent bias induced in the 2-point clustering of the considered tracer sample. The resulting constraints on f NL , however, are fully degenerate with the local PNG bias parameter b ϕ , dependent on the assembly bias parameter p. Using IllustrisTNG hydrodynamical simulations, we select a QSO sample reflecting the selection criteria and properties of DESI QSOs, and provide a robust prior for p, and thus for b ϕ , building on the findings of Fondi et al. 2024. We find a distribution with mean p̅ ≃ 1.4 with weak redshift dependence, stable to selection noise and consistent with the expected recent merger history typical of quasar-hosting halos. By comparing with the CAMELS simulations we demonstrate that this prior is robust to astrophysical assumptions and cosmic variance. Finally, applying this prior to the DESI DR1 dataset, we derive updated constraints on local PNG, obtaining f NL = -3.3±9.2.

cosmological parameters from LSS

Laser Welding Dissimilar Reflective Alloys

This project, jointly sponsored by Rocketdyne and CSTAR, involves the development of laser joining of materials which have heretofore been impractical to bond. Of particular interest are joints between stainless steel and copper and also aluminum 6061 to aluminum 2219. CSTAR has a unique opportunity in this area since both the process and development and diagnostics are of interest to industry. Initial results using the pulse tailored laser welding technique developed in CLA for joining crack sensitive materials have proven promising for the aluminum joints based upon metallurgical and electronic microprobe analysis. A declaration of success requires additional mechanical testing. A CW technique has been applied to the stainless-copper joining with some preliminary success. These joints are of significant interest for aeronautics and rocket propulsion applications and the project is expected to continue.

M H Mccay