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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 253 records · Page 14

Potential Link Between 2020 Mentone, West Texas M5 Earthquake and Nearby Wastewater Injection: Implications for Aquifer Mechanical Properties

Abstract The M5 Mentone earthquake that occurred on March 26, 2020, was the largest event recorded over the last 2 decades in West Texas within the Delaware Basin, a U.S. major petroleum‐producing area. Also, numerous hydrofracturing and wastewater disposal wells are spread across this region. Within a 30 km distance to mainshock, eight class‐II injection wells for industrial wastewater disposal target the deep porous Ellenburger aquifer at an average rate of 1.36 × 10 6 barrel (BBL) per month during 2012–2020. Poroelastic models of fluid diffusion show these nearby injectors collectively imparted up to 80.5 kPa of Coulomb stress at the mainshock location, capable of triggering this M5 event. Assuming the Mentone event occurs when pore‐pressure increase is maximum, the time delay between peak injection and the M5 occurrence corresponds with an optimal permeability of 6.76 × 10 ‐14 m 2 for the Ellenburger aquifer layer, in agreement with independent estimates.

15 GEOTHERMAL ENERGY↗

Projecting Permafrost Thaw of Sub-Arctic Tundra With a Thermodynamic Model Calibrated to Site Measurements

Northern circumpolar permafrost thaw affects global carbon cycling, as large amounts of stored soil carbon becomes accessible to microbial breakdown under a warming climate. The magnitude of carbon release is linked to the extent of permafrost thaw, which is locally variable and controlled by soil thermodynamics. Soil thermodynamic properties, such as thermal diffusivity, govern the reactivity of the soil-atmosphere thermal gradient, and are controlled by soil composition and drainage. In order to project permafrost thaw for an Alaskan tundra experimental site, we used seven years of site data to calibrate a soil thermodynamic model using a data assimilation technique. The model reproduced seasonal and interannual temperature dynamics for shallow (5–40 cm) and deep soil layers (2–4 m), and simulations of seasonal thaw depth closely matched observed data. The model was then used to project permafrost thaw at the site to the year 2100 using climate forcing data for three future climate scenarios (RCP 4.5, 6.0, and 8.5). Minimal permafrost thawing occurred until mean annual air temperatures rose above the freezing point, after which we measured over a 1 m increase in thaw depth for every 1 °C rise in mean annual air temperature. Under no projected warming scenario was permafrost remaining in the upper 3 m of soil by 2100. We demonstrated an effective data assimilation method that optimizes parameterization of a soil thermodynamic model. The sensitivity of local permafrost to climate warming illustrates the vulnerability of sub-Arctic tundra ecosystems to significant and rapid soil thawing.

54 ENVIRONMENTAL SCIENCES↗

Insights into the mechanisms controlling the residual corrosion rate of borosilicate glasses

Borosilicate glasses are widely used to confine high-level radioactive wastes. The lifetime of these materials could reach hundreds of thousands of years if leaching of the glass into groundwater enables the formation of a passivating gel layer. Even in this regime, the glass will never stop corroding as thermodynamic equilibrium between glass and solution cannot be achieved. Therefore, accurate predictions of glass durability including passivation, require a deep understanding of the mechanisms controlling the so-called residual rate. However, despite tremendous efforts, these mechanisms remain poorly understood. Here, focusing on the behavior of the soluble elements of the International Simple Glass (B, Na, and Ca), we show that the residual rate is controlled by the behavior of B, a glass former supposed to dissolve instantaneously when in contact with water and thus widely considered as an ideal tracer. We then demonstrate that B release is controlled by multiple processes highly dependent on the pH. At the beginning of the passivating layer formation, the hydrolysis of B-O-Si linkages is rate-limiting and has an activation energy of ~60 kJ mol –1 , a value slightly lower than that for breaking Si-O-Si linkages. Once the fraction of closed pores resulting from gel restructuring is high enough, then diffusion of both reactants (water molecules) and some products (mainly B aq , Ca aq ) through the growing gel layer becomes rate-limiting. Consequently, B and Ca accumulate in an inner layer referred to as the active zone, with potential feedback on the B-O-Si hydrolysis. A new paradigm, including B as a key element of the system, is proposed to develop a comprehensive model for the corrosion of borosilicate glass.

36 MATERIALS SCIENCE↗

Axial magnetic flux amplification in Hall-magnetohydrodynamic simulations of externally magnetized z-pinches

It is shown that externally magnetized gas-puff z-pinches under compression can exhibit robust axial flux amplification under suitable axial boundary conditions. This effect relies upon the Hall term in the generalized Ohm's law to generate azimuthal currents in the presence of a driving axial electric field. Under dynamic compression, the total current tends to flow in a mostly force-free boundary layer, separating the predominately azimuthal field outside the layer and the predominately axial field inside the layer. The effect only appears to occur if the axial boundaries allow for outflow or absorption of electromagnetic energy. The effect is mitigated by imposing either periodic or conducting axial boundary conditions. A semi-analytic equilibrium analysis agrees with steady-state solutions of the time-dependent electron-magnetohydrodynamic equations and provides an estimate of the scaling of the boundary layer as well as suggesting a scenario for the formation of the boundary layer. When operative, the effect can significantly impede plasma compression due to the increase in axial flux that diffuses into the pre-compressed plasma or through the presence of conductors that inhibit movement of the generated axial flux. Several facilities have noted unusual implosion behavior in z-pinch experiments with applied axial fields that does not appear to be explainable within the standard magnetohydrodynamic model. In conclusion, it is suggested that these experiments can be explained by the axial flux amplification and concentration effect

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multi-scale modeling of wastage layer formation in metallic fuel cladding

Fuel-cladding chemical interaction (FCCI) is a major concern for U-Zr metallic fuels' performance, primarily due to the formation of a brittle layer (wastage) in the cladding. This brittle layer, resulting from intermetallic compounds between cladding constituents Fe, Cr, and lanthanide fission products, significantly impacts the cladding's mechanical integrity. Recent efforts focus on developing a mechanistic modeling framework to understand lanthanide production, transport to the fuel-cladding interface, and phase transformation to intermetallic phases. A multi-scale computational approach has been used to calculate lanthanide transport rates, with atomistic calculations determining Nd diffusivities through the solid fuel matrix and along pore surfaces. These diffusivities inform a mesoscale model to determine an effective diffusion coefficient, accounting for porosity and infiltration with bond sodium. This effective diffusivity is used in engineering-scale simulations via the BISON fuel performance code, which has been validated against EBR-II and FFTF reactor experiments.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Electron-electron interactions in low-dimensional Si:P delta layers

Scientists have long studied the physics of highly disordered conducting systems, seeking to understand the multitude of quantum phenomena that govern how electrons move through material systems. Recently, research into silicon-based quantum computing has made disordered conducting systems, such as Si:P monolayers embedded in isotopically pure Si, technically relevant. Consequently, applying and advancing the theoretical frameworks developed to describe electron behavior in disordered systems is a necessary objective in this field of research. This study investigates key components of dopant-based Si quantum computing devices: embedded regions of highly doped delta layers (δ layers). We examine the transport behavior and the electron-electron interaction (EEI) physics in embedded Si:P δ layers by means of self-consistent magnetotransport measurements. Parameters associated with the electronic transport offer a meaningful quantitative characterization of δ-layer quality and dopant diffusion. In addition, by examining EEI behaviors in a set of samples with embedded Si:P δ layers produced with different PH3 exposure procedures prior to Si encapsulation, we show how details of material synthesis affect the dimensionality of charge carrier interactions in embedded Si:P δ layers. Furthermore, the relationship between δ-layer confinement and EEI screening lengths is established here. This understanding will help validate important models used for device simulation and design and lead to improvements in the control of electrostatic gating of and tunneling transport through Si:P single atom transistors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

MATBOX, an Open-Source Microstructure Analysis Toolbox for Meshing, Generation, Segmentation, and Characterization of 3D Heterogenous Volumes

Battery performance is strongly correlated with electrode microstructural properties. To account for its impact, lithium-ion battery (LIB) models either abstract the microstructural heterogeneity of composite electrodes using effective macroscopic properties (macro- or meso- scale models) or directly solve the system of equations on the microstructure geometry or mesh (microstructure-scale models). Therefore, to be adequate, both families of models require information from the microstructure geometry, which can be provided by the numerical tool presented in this work. MATBOX is a MATLAB open-source application [1] developed by NREL for performing various microstructure-related tasks including microstructure numerical generation, image filtering and microstructure segmentation, microstructure characterization and correlation, visualization, and microstructure meshing. MATBOX was originally developed for the analysis of LIB electrode microstructures; however, the algorithms provided by the toolbox are widely applicable to other heterogeneous materials. The toolbox provides a user-friendly experience thanks to a Graphical-User Interface, requires no coding by the user, and is well documented. This presentation will illustrate various MATBOX features for the characterization of a LIB electrode, including a fully automated Representative Volume Element (RVE) analysis, the numerical generation of complex 'virtual' microstructure, including dual-layer electrodes and carbon-binder additive phase, and the meshing of a complex NMC/graphite full cell microstructure suitable for 3D finite-element modeling. Other modules (segmentation, visualization, and correlation) will be briefly presented. Thanks to its modular, open-source approach, MATBOX can easily incorporate third-party algorithms to eventually build a standard in the field that will benefit the whole scientific community. Effective diffusion coefficient [2], additive phase numerical generation [3], and meshing [4] third-party algorithms have been already integrated in the toolbox with more to come.

DIRECT ENERGY CONVERSION,MATHEMATICS AND COMPUTING↗

Effect of non-solvent from the phase inversion method on the morphology and performance of the anode supported microtubular solid oxide fuel cells

The microstructure of the anode in anode-supported solid oxide fuel cells has significant influence on the cell performance. Here, microtubular Ni-yttria stabilized zircona (Zr 0.8 Y 0.2 O 2 , YSZ) anode support has been prepared by the phase inversion method. Different compositions of non-solvent have been used for the fabrication of the Ni-YSZ anode support, and the correlation between non-solvent composition and characteristics of the microstructure of the anode support has been investigated. The presence of ethanol or isopropanol in the non-solvent can inhibit the growth of the finger-like pores in the anode support. With the increase of the concentration of ethanol or isopropanol in the non-solvent, a thin dense layer can be observed on the top of the prepared tubular anode support. In addition, the mechanism of pore formation is explained based on the inter-diffusivity between the solvent and the non-solvent. Lastly, the prepared microtubular solid oxide fuel cells (MT-SOFCs) have been tested, and the influence of the anode microstructure on the cell electrochemical performance is analyzed based on a polarization model.

36 MATERIALS SCIENCE↗

Bulky Cation-Modified Interfaces for Thermally Stable Lead Halide Perovskite Solar Cells

Charged conjugated organic molecules offer promising prospects for reducing nonradiative recombination at interfaces in perovskite solar cells, while protecting the active layer from moisture. However, several studies have shown that the heat induced diffusion of these cations leads to irreversible solar cell degradation. Passivation molecules for perovskite can reconstruct the film surface into lower-dimensional phases when exposed to thermal stress, impeding charge extraction and affecting the photoconversion efficiency (PCE) of devices. In this work, we study how molecular interactions between passivation molecules and 3D CsFAPbI 3 perovskite impact stability and charge extraction at the perovskite/hole transport layer interfaces. Two model π- conjugated molecules are studied: 2-([2,2′-bithiophen]-5-yl)ethan-1-aminium iodide (2TI) and 2-(3‴,4′-dimethyl-[2,2′:5′,2″:5″,2‴- quaterthiophen]-5-yl)ethan-1-ammonium iodide (4TmI). We demonstrate that the speed of surface layer reconstruction under thermal stress can be controlled by the cation size and correlate these structural changes with the solar cell performance and stability. Devices treated with 2TI and 4TmI achieve PCEs over 21% and maintain their performance under thermal stress. Our findings demonstrate that thermal stability in PSCs can be achieved via the design engineering of passivation agents, offering a blueprint for developing next-generation passivation molecules.

36 MATERIALS SCIENCE↗

Specific features of fluorescence transfer in multiply scattering randomly inhomogeneous layers under intense laser pumping

Based on the analysis of experimental data on the effect of the pulsed laser pump intensity on the spectral properties and the size of the fluorescent response zone in randomly inhomogeneous fluorescent layers, we found that the amplification of spontaneous and stimulated emission significantly affects the statistical properties of the propagation lengths of the fluorescent field partial components in the layers. The experiments are performed with layers of SiO{sub 2} and TiO{sub 2} nanoparticles saturated with rhodamine 6G, pumped by 532-nm laser radiation in the intensity range corresponding to the transient regime from excitation of spontaneous fluorescence to random lasing in the layer. The experimental data are compared with the results of statistical modelling of fluorescence transfer. It is shown that, even at a pump intensity below the random lasing threshold, the spontaneous emission amplification in a layer leads to a significant increase in the contributions to the fluorescence response from partial components with propagation lengths much larger than the layer thickness. This can be interpreted as a manifestation of the quasi-waveguide effect, in which the probability of propagation of diffuse fluorescence components along the layer over distances many times greater than its thickness and the size of the pumped region increases significantly with a decrease in the characteristic radiation amplification length in the layer. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Enhancing Unknown Waveform Detection by Learning Intra and Inter-domain Dependencies with Advanced Attention Fusion Mechanisms

Detection of unknown waveforms in mission-critical communications is a crucial area of interest for the Department of Energy (DoE). Traditional methods and recent deep learning-based approaches often assume that the training set includes all possible classes, which is impractical for detecting new waveforms. This limitation gives rise to the problem of open-set recognition (OSR), which involves correctly identifying known classes while detecting and rejecting unknown or unseen classes. To address this limitation, we propose a novel dual-domain complex-valued neural architecture that jointly processes time-domain and frequency-domain signal representations using transformer mechanisms. A transformer model is a deep learning architecture that uses self-attention mechanisms to process and learn relationships in sequential data. Our model employs a cosine similarity loss to extract domain-specific features and incorporates a transformer architecture in the latent space to weigh the importance of different features from the time and frequency domains. The transformer layer includes stacked self-attention and cross-attention modules to learn intra-domain and inter-domain dependencies, creating a more holistic signal representation. An attention-based fusion module intelligently combines the time and frequency-domain features using multi-head attention, enabling the network to learn the optimal feature for each domain in each input signal. Quantitative results demonstrate the impact of these architectural choices on overall performance, showing significant improvement after incorporating self and cross-attention modules and using complex attention fusion over simple weighted fusion. Our ongoing work will focus on addressing the limitations of threshold-based OSR methods by developing a novel generative framework that integrates a conditional diffusion probabilistic model (DPM). DPM is a generative framework that learns to synthesize complex data by reversing a gradual noising process using a neural network trained to denoise step-by-step. Our goal is to leverage the inherent strengths of DPMs for identifying unknown signals more robustly. One primary advantage of using a DPM is its ability to provide a more reliable anomaly score based on the model's reconstruction error, rather than relying solely on classifier confidence. Additionally, the iterative denoising process of DPMs makes this approach naturally resilient to low Signal-to-Noise Ratio (SNR) conditions, where traditional methods often fail. By implementing this generative framework, we aim to enhance the model's capability to accurately detect unknown waveforms and maintain performance in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗

Estimating viscoelastic compliance of desiccating cementitious materials using drying prism tests

Highlights: • Determining relative humidity and degree of reaction of desiccating cementitious materials via an integrated method • Extracting moisture diffusion coefficient of cement mortar using the mass loss data of the prism specimens • Estimating uniaxial viscoelastic compliance of cement mortar using the shrinkage strain data of the prism specimens An integrated modeling approach to determining internal relative humidity and degree of reaction of desiccating cementitious materials has been developed. By simultaneously accounting for both self-desiccation and external drying, the model is capable of predicting the evolution of material properties of desiccating cementitious materials. Using the mass loss data of the prism specimens, the moisture diffusion coefficient of a nonlinear model for cement mortar was determined. Additionally, a previous poroviscoelastic shrinkage model was modified and extended. Through comparison of predicted and measured axial strain of the prism specimens, the viscoelastic compliance of cement mortar was extracted. The present work revealed that it is possible to use a simple drying prism test to fit the moisture diffusion coefficient and creep compliance of cementitious materials, though the comparison of the extracted viscoelastic compliance with measured compliance was only reasonable if the outer layer of the drying mortar was presumed to have microcracking.

36 MATERIALS SCIENCE↗

Systematic Evaluation of Counterpoise Correction in Density Functional Theory

A widespread belief persists that the Boys–Bernardi function counterpoise (CP) procedure “overcorrects” supramolecular interaction energies for the effects of basis-set superposition error. To the extent that this is true for correlated wave function methods, it is usually an artifact of low-quality basis sets. The question has not been considered systematically in the context of density functional theory, however, where basis-set convergence is generally less problematic. We present a systematic assessment of the CP procedure for a representative set of functionals and basis sets, considering both benchmark data sets of small dimers and larger supramolecular complexes. The latter include layered composite polymers with ~150 atoms and ligand–protein models with ~300 atoms. Provided that CP correction is used, we find that intermolecular interaction energies of nearly complete-basis quality can be obtained using only double-ζ basis sets. Furthermore, this is less expensive as compared to triple-ζ basis sets without CP correction. CP-corrected interaction energies are less sensitive to the presence of diffuse basis functions as compared to uncorrected energies, which is important because diffuse functions are expensive and often numerically problematic for large systems. Our results upend the conventional wisdom that CP “overcorrects” for basis-set incompleteness. In small basis sets, CP correction is mandatory in order to demonstrate that the results do not rest on error cancellation.

74 ATOMIC AND MOLECULAR PHYSICS↗

Cooperative mechanisms behind nanoscale smoothing on metal surfaces: From adatom diffusion to step nucleation

Many technologies require stable or metastable surface morphology. Here, in this paper we study the factors that control the metastability of a common feature of rough surfaces: “hillocks.” We use low energy electron microscopy to follow the evolution of the individual atomic steps in hillocks on Pd(111). We show that the uppermost island in the stack often adopts a static, metastable configuration. Modeling this result shows that the degree of the metastability depends on the configuration of steps dozens of atomic layers lower. Our model allows us to link surface metastability to the atomic processes of surface evolution.

Fernandes Cauduro, Andre Luis↗

Uncovering grain and subgrain microstructure at the scale of additive manufacturing melt tracks with a scalable cellular automaton solidification model

Metal additive manufacturing, characterized by rapid solidification, yields refined grains with a distinctive cellular subgrain microstructure that plays a pivotal role in determining material properties. Due to the significant computational expense demanded to simulate the required physics with submicron spatial resolution, their numerical simulations have been limited to proof-of-concept studies to either 2D or small subregions of a melt pool. In this study, an open-source, scalable, solidification code, muMatScale, based on the cellular automaton method, has been developed to predict the grain and the underlying subgrain microstructure over an entire melt pool. The model incorporates flexible parallelization schemes, utilizing MPI and OpenMP GPU Offloading, in addition to appropriate multi-physics specific to non-equilibrium rapid solidification in AM. The impact of nucleation parameters on grain microstructures was investigated with a focus on grain size variations and morphology transitions. With selected nucleation parameters, the simulation predicted the grain size, subgrain morphology, crystallographic orientation, and microsegregation aligned with experimental measurements. The model demonstrates that epitaxial grain growth is a dominant factor at the melt pool boundary, influencing grain size variation under different grain sizes in the build plate while maintaining consistent primary dendrite arm spacing under identical thermal conditions. Here, the highly efficient numerical model enables large-scale simulations with a spatial resolution of 100 nm or less, unveiling unprecedented insights into thermal and solutal diffusion driven grain growth, and the subgrains with microsegregation within grains in 3D across scales. muMatScale will enable the linking of submicron length-scale microstructure to part-level material behavior by investigating fundamental solidification problems at the intercellular scale in many-track and many-layer builds.

36 MATERIALS SCIENCE↗

Diffusion of Sn donors in β-Ga 2 O 3

Diffusion of the n-type dopant Sn in β-Ga 2 O 3 is studied using secondary-ion mass spectrometry combined with hybrid functional calculations. The diffusion of Sn from a Sn-doped bulk substrate with surface orientation (001) into an epitaxial layer is observed after heat treatments in the temperature range of 1050–1250 °C. Calculated formation energies of Sn-related and intrinsic defects show that the migration of Sn is mediated by Ga vacancies ( V Ga ) through the formation and dissociation of intermittent mobile V Ga Sn Ga complexes. The evolution of the Sn concentration vs depth profiles after heat treatments can be well described by a reaction–diffusion model. Using model parameters guided by the hybrid functional calculations, we extract a V Ga Sn Ga complex migration barrier of 3.0 ± 0.4 eV with a diffusion coefficient of 2 × 10 –1 cm 2 /s. The extracted migration barrier is consistent with our theoretical predictions using the nudged elastic band method, which shows migration barriers of 3.42, 3.15, and 3.37 eV for the [100], [010], and [001] directions, respectively.

36 MATERIALS SCIENCE↗

Two-dimensional simulations of internal gravity waves in a $\mathrm{5M_⊙}$ zero-age-main-sequence model

Main-sequence intermediate-mass stars present a radiative envelope that supports internal gravity waves (IGWs). Excited at the boundary with the convective core, IGWs propagate towards the stellar surface and are suspected to impact physical processes such as rotation and chemical mixing. Using the fully compressible time-implicit code MUSIC, we study IGWs in two-dimensional simulations of a zero-age-main-sequence 5 solar mass star model up to 91 percent of the stellar radius with different luminosity and radiative diffusivity enhancements. Our results show that low-frequency waves excited by core convection are strongly impacted by radiative effects as they propagate. This impact depends on the radial profile of radiative diffusivity which increases by almost 5 orders of magnitude between the centre of the star and the top of the simulation domain. In the upper layers of the simulation domain, we observe an increase of the temperature. Our study suggests that this is due to heat added in these layers by IGWs damped by radiative diffusion. We show that non-linear effects linked to large amplitude IGWs may be relevant just above the convective core. Both these effects are intensified by the artificial enhancement of the luminosity and radiative diffusivity, with enhancement factors up to 10 4 times the realistic values. Our results also highlight that direct comparison between numerical simulations with enhanced luminosity and observations must be made with caution. Finally, our work suggests that thermal effects linked to the damping of IGWs could have a non-negligible impact on stellar structure.

79 ASTRONOMY AND ASTROPHYSICS↗

VeloxChem: A Python-driven density-functional theory program for spectroscopy simulations in high-performance computing environments

An open-source program named VeloxChem has been developed for the calculation of electronic real and complex linear response functions at the levels of Hartree–Fock and Kohn–Sham density functional theories. With an object-oriented program structure written in a Python/C++ layered fashion, VeloxChem enables time-efficient prototyping of novel scientific approaches without sacrificing computational efficiency, so that molecular systems involving up to and beyond 500 second-row atoms (or some 10,000 contracted and in part diffuse Gaussian basis functions) can be routinely addressed. In addition, VeloxChem is equipped with a polarizable embedding scheme for the treatment of the classical electrostatic interactions with an environment that in turn is modeled by atomic site charges and polarizabilities. The underlying hybrid message passing interface (MPI)/open multiprocessing (OpenMP) parallelization scheme makes VeloxChem suitable for execution in high-performance computing cluster environments, showing even slightly beyond linear scaling for the Fock matrix construction with use of up to 16,384 central processing unit (CPU) cores. An efficient—with respect to convergence rate and overall computational cost—multifrequency/gradient complex linear response equation solver enables calculations not only of conventional spectra, such as visible/ultraviolet/X-ray electronic absorption and circular dichroism spectra, but also time-resolved linear response signals as due to ultra-short weak laser pulses.

97 MATHEMATICS AND COMPUTING↗