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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Aerosol Optical Tweezers Elucidate the Chemistry, Acidity, Phase Separations, and Morphology of Atmospheric Microdroplets

Aerosol particles represent unique chemical environments because of their high surface area-to-volume ratio that promotes the effects of interfacial chemistry in confined environments. Properties such as viscosity, diffusivity, water content, pH, and morphology—following liquid–liquid phase separation—can strongly alter how a particle interacts with condensable vapors and reactive trace gases, thus modifying its continual evolution and environmental effects. Our understanding of this chemical evolution of atmospheric particulate matter and its environmental impacts is largely limited by our ability to directly observe how these critical particle properties respond to the addition or reactive uptake of new chemical components. Aerosol optical tweezers (AOT) stably trap particles in focused laser beams, providing positional control and the retrieval of many of these critical properties required to understand and predict the chemistry of aerosolized microdroplets. The analytical power of the AOT stems from the retrieval of the cavity-enhanced Raman spectrum induced by the trapping laser. Analysis of the whispering gallery modes (WGMs) that resonate as a standing wave around the droplet’s interface, provide high accuracy measurements of the droplet’s size, refractive index (and thus a measurement of composition), and can distinguish between core–shell, partially engulfed, and homogeneous morphologies. In this study, we have advanced the ability to determine the properties of the core and shell phases in biphasic droplets, including obtaining high-accuracy pH measurements. These capabilities were applied to perform AOT physical chemistry experiments on authentic secondary organic aerosol (SOA) produced directly in the AOT chamber by ozonolysis of terpene vapors. The propensity of the SOA to phase separate as a shell from a wide range of nonpolar to polar core phases was observed, along with the discovery of a stable emulsified state of SOA particles in an aqueous salt droplet. Micron-thick SOA shells did not impede the gain or loss of water or squalane from the core to the surrounding air, indicating no significant diffusional limitations to condensational growth or partitioning even under dry conditions. These experiments formed the foundation of a new framework that predicts how the phase-separated morphology of complex aerosols containing organic carbon evolves during continual atmospheric oxidation processes. Increases in oxidation state will quickly drive conversion from a partially engulfed to core–shell morphology that has dramatically different chemical reactivity since the core phase is completely concealed by the shell. The recent advances in the experimental capabilities of the AOT technique such as presented here enable novel experimental methodologies that provide insights into the chemistry and multidimensional properties of aerosol microdroplets, and how these coevolve and respond to continual chemical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Electrochemical Characterization of Degradation Modes of High-Voltage Li x Ni 0.33 Mn 0.33 Co 0.33 O 2 Electrodes

While deeply charged high-voltage cathodes can improve battery energy density, understanding and preventing any accelerated cell degradation is crucial to practical success. Here, to analyze the degradation of LiNi x Mn y Co 1–x–y O 2 (NMC) type material charged to 4.3 and 4.5 V, a physics-based model is applied to cycling data to obtain parameter estimates indicative of degradation modes, which are validated by simple electrochemical measurements and further interpreted by materials characterization. Growth rates of interfacial impedance and active material loss are greater at 4.5 V, as might be expected. However, when charged to 4.5 V, degradation rates are initially lower at a cycling C-rate of 1.0 C than at 0.5 C. Once degradation mode changes are quantified, simulations evaluate the contribution of individual degradation mode to performance losses and provide estimates of the energy-power correlation (Ragone plots) of cells after cycling.

25 ENERGY STORAGE↗
DOE OSTI2020

Understanding important features of deep learning models for segmentation of high-resolution transmission electron microscopy images

Cutting edge deep learning techniques allow for image segmentation with great speed and accuracy. However, application to problems in materials science is often difficult since these complex models may have difficultly learning meaningful image features that would enable extension to new datasets. In situ electron microscopy provides a clear platform for utilizing automated image analysis. In this work, we consider the case of studying coarsening dynamics in supported nanoparticles, which is important for understanding, for example, the degradation of industrial catalysts. By systematically studying dataset preparation, neural network architecture, and accuracy evaluation, we describe important considerations in applying deep learning to physical applications, where generalizable and convincing models are required. With a focus on unique challenges that arise in high-resolution images, we propose methods for optimizing performance of image segmentation using convolutional neural networks, critically examining the application of complex deep learning models in favor of motivating intentional process design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

When action is not least for systems with action-dependent Lagrangians

The dynamics of some non-conservative and dissipative systems can be derived by calculating the first variation of an action-dependent action according to the variational principle of Herglotz. This is directly analogous to the variational principle of Hamilton commonly used to derive the dynamics of conservative systems. In a similar fashion, just as the second variation of a conservative system’s action can be used to infer whether that system’s possible trajectories are dynamically stable, so too can the second variation of the action-dependent action be used to infer whether the possible trajectories of non-conservative and dissipative systems are dynamically stable. In this paper, I show, generalizing earlier analyses of the second variation of the action for conservative systems, how to calculate the second variation of the action-dependent action and how to apply it to two physically important systems: a time-independent harmonic oscillator and a time-dependent harmonic oscillator.

Physics↗
DOE OSTI2023

Manifold projection image segmentation for nano-XANES imaging

As spectral imaging techniques are becoming more prominent in science, advanced image segmentation algorithms are required to identify appropriate domains in these images. We present a version of image segmentation called manifold projection image segmentation (MPIS) that is generally applicable to a broad range of systems without the need for training because MPIS uses unsupervised machine learning with a few physically motivated hyperparameters. We apply MPIS to nanoscale x-ray absorption near edge structure (XANES) imaging, where XANES spectra are collected with nanometer spatial resolution. We show the superiority of manifold projection over linear transformations, such as the commonly used principal component analysis (PCA). Moreover, MPIS maintains accuracy while reducing computation time and sensitivity to noise compared to the standard nano-XANES imaging analysis procedure. Finally, we demonstrate how multimodal information, such as x-ray fluorescence data and spatial location of pixels, can be incorporated into the MPIS framework. We propose that MPIS is adaptable for any spectral imaging technique, including scanning transmission x-ray microscopy, where the length scale of domains is larger than the resolution of the experiment.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Closing the loop between microstructure and charge transport in conjugated polymers by combining microscopy and simulation

A grand challenge in materials science is to identify the impact of molecular composition and structure across a range of length scales on macroscopic properties. We demonstrate a unified experimental–theoretical framework that coordinates experimental measurements of mesoscale structure with molecular-level physical modeling to bridge multiple scales of physical behavior. Here we apply this framework to understand charge transport in a semiconducting polymer. Spatially-resolved nanodiffraction in a transmission electron microscope is combined with a self-consistent framework of the polymer chain statistics to yield a detailed picture of the polymer microstructure ranging from the molecular to device relevant scale. Using these data as inputs for charge transport calculations, the combined multiscale approach highlights the underrepresented role of defects in existing transport models. Short-range transport is shown to be more chaotic than is often pictured, with the drift velocity accounting for a small portion of overall charge motion. Local transport is sensitive to the alignment and geometry of polymer chains. At longer length scales, large domains and gradual grain boundaries funnel charges preferentially to certain regions, creating inhomogeneous charge distributions. While alignment generally improves mobility, these funneling effects negatively impact mobility. The microstructure is modified in silico to explore possible design rules, showing chain stiffness and alignment to be beneficial while local homogeneity has no positive effect. This combined approach creates a flexible and extensible pipeline for analyzing multiscale functional properties and a general strategy for extending the accesible length scales of experimental and theoretical probes by harnessing their combined strengths.

42 ENGINEERING↗
DOE OSTI2023

A new step forward in realistic cluster lens mass modelling: analysis of Hubble Frontier Field Cluster Abell S1063 from joint lensing, X-ray, and galaxy kinematics data

We present a new method to simultaneously and self-consistently model the mass distribution of galaxy clusters that combines constraints from strong lensing features, X-ray emission, and galaxy kinematics measurements. We are able to successfully decompose clusters into their collisionless and collisional mass components thanks to the X-ray surface brightness, as well as use the dynamics of cluster members, to obtain more accurate masses exploiting the fundamental plane of elliptical galaxies. Knowledge from all observables is included through a consistent Bayesian approach in the likelihood or in physically motivated priors. We apply this method to the galaxy cluster Abell S1063 and produce a mass model that we publicly release with this paper. The resulting mass distribution presents different ellipticities for the intra-cluster gas and the other large-scale mass components as well as deviation from elliptical symmetry in the main halo. We assess the ability of our method to recover the masses of the different elements of the cluster using a mock cluster based on a simplified version of our Abell S1063 model. Thanks to the wealth of mutliwavelength information provided by the mass model and the detected X-ray emission, we also found evidence for an ongoing merger event with gas sloshing from a smaller infalling structure into the main cluster. In agreement with previous findings, the total mass, gas profile, and gas mass fraction are all consistent with small deviations from the hydrostatic equilibrium. This new mass model for Abell S1063 is publicly available, as the lenstool extension used to construct it.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Multiple valence-space and core-excited band terminations in Ho and Er isotopes

High-spin structures of holmium (𝑍 = 67) and erbium (𝑍 = 68) isotopes are presented near mass 160, a region where collective and single-particle modes of excitation compete in the generation of angular momentum at the highest experimentally attainable spins in atomic nuclei. The level schemes of the 156,157,158 Ho isotopes have been significantly extended, reaching spins in the 40⁢ℏ to 55⁢ℏ range, through multiple experiments utilizing the Gammasphere spectrometer. In particular, several new noncollective band-terminating states are reported for these nuclei. The nature of these states, including both valence-space terminations and core-excited oblateconfigurations, is discussed in terms of proton particle-hole (p-h) excitations across the semimagic 𝑍 = 64 shell closure. Cranked-Nilsson–Strutinsky (CNS) calculations have been used to interpret the nature of these noncollective states. The corresponding terminating states in 154–159 Er are also included, providing a systematic description of band termination in this mass region. In addition, three weak rotational structures have been assigned to 157 Ho at the highest spins. These collective bands are proposed to be based on a triaxial strongly deformed nuclear shape, involving neutron p-h excitations across the 𝑁 = 82 shell gap.

150 ≤ A ≤ 189↗
DOE OSTI2021

Diagnosis of information scrambling from Hamiltonian evolution under decoherence

We apply a quantum teleportation protocol based on the Hayden-Preskill thought experiment to quantify how scrambling a given quantum evolution is. It has an advantage over the direct measurement of out-of time ordered correlators when used to diagnose the information scrambling in the presence of decoherence effects stemming from a noisy quantum device. We demonstrate the protocol by applying it to two physical systems: Ising spin chain and SU(2) lattice Yang-Mills theory. To this end, we numerically simulate the time evolution of the two theories in the Hamiltonian formalism. The lattice Yang-Mills theory is implemented with a suitable truncation of Hilbert space on the basis of the Kogut-Susskind formalism. On a two-leg ladder geometry and with the lowest nontrivial spin representations, it can be mapped to a spin chain, which we call Yang-Mills-Ising model and is also directly applicable to future digital quantum simulations. Here, we find that the Yang-Mills-Ising model shows the signal of information scrambling at late times.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Factors influencing quantum evaporation of helium from polar semiconductors from first principles

While there is much indirect evidence for the existence of dark matter (DM), to date it has evaded detection. Current efforts focus on DM masses over ~GeV—to push the sensitivity of DM searches to lower masses, new DM targets and detection schemes are needed. In this work, we focus on the latter—a novel detection scheme recently proposed to detect 10–100 meV phonons in polar target materials. Previous work showed that well-motivated models of DM can interact with polar semiconductors to produce an athermal population of phonons. This new sensing scheme proposes that these phonons then facilitate quantum evaporation of 3 He from a van der Waals film deposited on the target material. However, a fundamental understanding of the underlying process is still unclear, with several uncertainties related to the precise rate of evaporation and how it can be controlled. In this work, we use ab initio density functional theory calculations to compare the adsorption energies of helium atoms on a polar target material, sodium iodide, to understand the underlying evaporation physics. We explore the role of surface termination, monolayer coverage, and elemental species on the rate of He evaporation from the target material. Using this, we discuss the optimal target features for He-evaporation experiments and their range of tunability through chemical and physical modifications such as applied field and surface termination.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Evaluated Nuclear Structure Data File (ENSDF)

Contains recommended nuclear structure and decay data for all the known nuclides, which are obtained following a critical review of all available experimental data, supplemented with systematic trend studies and theoretical models. ENSDF data include (i) nuclear level properties, such as observation source, energy, half-life, decay modes, spin and parity; (ii) gamma ray energies, intensities, multipolarities, mixing ratios and conversion coefficients; (iii) nuclear radiation energy and intensity as well as radiation-specific data for different radiation types, such as such as gammas, alphas, betas and neutrons. Data for about 220 nuclides are fully evaluated each year; additionally, many datasets are partially updated each year. Nearly all the evaluation work is supported by the US Nuclear Data Program. The National Nuclear Data Center at Brookhaven National Laboratory is responsible for coordinating the evaluation effort as well as its web and journal dissemination.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

GentenMPI: Distributed Memory Sparse Tensor Decomposition

GentenMPl is a toolkit of sparse canonical polyadic (CP) tensor decomposition algorithms that is designed to run effectively on distributed-memory high-performance computers. Its use of distributed-memory parallelism enables it to efficiently decompose tensors that are too large for a single compute node's memory. GentenMPl leverages Sandia's decades-long investment in the Trilinos solver framework for much of its parallel-computation capability. Trilinos contains numerical algorithms and linear algebra classes that have been optimized for parallel simulation of complex physical phenomena. This work applies these tools to the data science problem of sparse tensor decomposition. In this report, we describe the use of Trilinos in GentenMPl, extensions needed for sparse tensor decomposition, and implementations of the CP-ALS (CP via alternating least squares) and GCP-SGD (generalized CP via stochastic gradient descent) sparse tensor decomposition algorithms. We show that GentenMPl can decompose sparse tensors of extreme size, e.g., a 12.6-terabyte tensor on 8192 computer cores. We demonstrate that the Trilinos backbone provides good strong and weak scaling of the tensor decomposition algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Preconditioning for Hyper-reduction in Reduced Order Models

Many projection-based reduced order models (pROM) that utilize the governing equation and data to accelerate physical simulations can be applied to nonlinear dynamical systems. To avoid full order model (FOM) scale update for each time step, hyperreduction techniques are developed to sample high dimensional nonlinear terms. Our study aims to investigate if preconditioning the least-squares problem used for the nonlinear approximation can improve the robustness of the condition number of the problem while achieving high accuracy. In our study, we use the row-normalization matrix motivated by the Christoffel function as the preconditioner and solve the corresponding weighted least-squares problem. Numerical results for Lagrangian hydrodynamics examples are analyzed to explore how the preconditioner works compared to existing hyper-reduction techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Multimode Characterization Approach for Understanding Cell-Level PV Performance and Degradation

Cell-level degradation processes impact the economic viability and large-scale deployment prospects for both established and emerging photovoltaic (PV) technologies. This project addresses the need to develop experimental and device-modeling approaches for studying cell-level degradation processes in photovoltaic (PV) devices using a variety of characterization techniques that provide access to complementary material and device properties. Our results demonstrate that by coupling characterization results with device modeling it is possible to develop comprehensive understanding of processes leading to performance limitations and degradation. This project developed a suite of novel measurement techniques including pulsed-light-bias operando X-ray and photoelectron spectroscopy (popXPS), light-biased scanning microwave impedance microscopy (sMIM), and near-field transport imaging (TI). In addition, operando characterization methodologies and in situ stressing capabilities have been developed and applied for techniques including electron-beam-induced current (EBIC), cathodoluminescence (CL), and Kelvin probe force microscopy (KPFM). Device-physics models were developed and applied to simulate correlative, multi-mode measurements to extract material and device parameters that control performance degradation. These characterization and modeling techniques were applied in a multi-mode approach to probe cell-level degradation mechanisms in Cd(Se,Te) and hybrid perovskite PV devices. Together these efforts contribute to foundational PV degradation science by establishing a framework for understanding PV performance degradation at the cell level and benefit the U.S. PV industry by providing resources in the form of novel experimental capabilities, knowledge gained, and available expertise that can accelerate research and development of improved PV device materials and architectures. The project provided a comprehensive understanding of degradation in baseline Cd(Se,Te) solar cells provided by our collaborators at Colorado State University (CSU). EBIC and CL-based measurements and revealed unusual collection and recombination profiles in these devices, which underwent significant changes with during stressing. KPFM and operando XPS measurements showed that device stressing permanently alters energy-band alignments at the (Mg,Zn)O/Cd(Se,Te) interface, which in turn account for an observed loss in fill factor. Studies on hybrid perovskite devices were hampered to a significant extent by delays related to the pandemic. Nevertheless, a set of hybrid perovskite devices (supplied through an NREL-industry partnership) were stress tested and characterized with techniques including EBIC, sMIM, popXPS/popUPS and optically excited TI. Available results from these measurements informed the device modeling effort and suggest that defects and related band offsets at the C60/LiF/hybrid perovskite interface are the primary source of degradation in these devices.

14 SOLAR ENERGY↗
DOE OSTI2021

Out of the Lab: 3D Printing on Non-Ideal Surfaces

In this work, coaxial direct ink writing is utilized to print sensitive or encapsulated materials onto heterogeneous and rough substrates. By enclosing the core fluid within a rigid ceramic shell, continuity is maintained even when printing on substrates traditionally considered challenging. This work presents the development of a coaxial ceramic direct ink writing system and investigates co-flow dynamics through microfluidic principles. A specially designed coaxial nozzle enables the co-extrusion of an alumina shell, with indium-tin-oxide inks serving as the core material. This approach allows the fabrication of core-shell ceramic structures suitable for future high-temperature applications on rough surfaces. The colloidal inks are tailored to achieve the necessary rheological properties and sintering performance. Additionally, flow simulations, guided by microfluidic co-flow principles, are employed to define the processing parameters for coaxial printing, ensuring precise control over the core-shell architectures. Physical modeling is further applied to study core deformation and eccentricity. These simulations are experimentally validated, supporting the successful deposition of coaxial ceramic features on heterogeneous, high-temperature ceramic substrates.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Time-Lapse Integration at FWU: Fluids, Rock Physics, Numerical Model Integration, and Field Data Comparison

We present the current status of time-lapse seismic integration at the Farnsworth (FWU) CO2 WAG (water-alternating-gas) EOR (Enhanced Oil Recovery) project at Ochiltree County, northwest Texas. As a potential carbon sequestration mechanism, CO2 WAG projects will be subject to some degree of monitoring and verification, either as a regulatory requirement or to qualify for economic incentives. In order to evaluate the viability of time-lapse seismic as a monitoring method the Southwest Partnership (SWP) has conducted time-lapse seismic monitoring at FWU using the 3D Vertical Seismic Profiling (VSP) method. The efficacy of seismic time-lapse depends on a number of key factors, which vary widely from one application to another. Most important among these are the thermophysical properties of the original fluid in place and the displacing fluid, followed by the petrophysical properties of the rock matrix, which together determine the effective elastic properties of the rock fluid system. We present systematic analysis of fluid thermodynamics and resulting thermophysical properties, petrophysics and rock frame elastic properties, and elastic property modeling through fluid substitution using data collected at FWU. These analyses will be framed in realistic scenarios presented by the FWU CO2 WAG development. The resulting fluid/rock physics models will be applied to output from the calibrated FWU compositional reservoir simulation model to forward model the time-lapse seismic response. Modeled results are compared with field time-lapse seismic measurements and strategies for numerical model feedback/update are discussed. While mechanical effects are neglected in the work presented here, complementary parallel studies are underway in which laboratory measurements are introduced to introduce stress dependence of matrix elastic moduli.

4D↗
DOE OSTI2026

Hidden Rotation Symmetry of the Jordan–Wigner Transformation and Its Application to Measurement in Quantum Computation

Using a global rotation by 𝜃 about the z-axis in the spin sector of the Jordan–Wigner transformation rotates Pauli matrices 𝑋̂ and 𝑌̂ in the 𝑥−𝑦 -plane, while it adds a global complex phase to fermionic quantum states that have a fixed number of particles. With the right choice of angles, this relates expectation values of Pauli strings containing products of 𝑋̂ and 𝑌̂ to different products, which can be employed to reduce the number of measurements needed when simulating fermionic systems on a quantum computer. Here, we derive this symmetry and show how it can be applied to systems in Physics and Chemistry that involve Hamiltonians with only single-particle (hopping) and two-particle (interaction) terms. We also discuss the consequences of this for finding efficient measurement circuits in variational ground state preparation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗