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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Large-Angle Rocking Beam Electron Diffraction of Large Unit Cell Crystals Using Direct Electron Detector

We report a large-angle rocking beam electron diffraction (LARBED) technique for electron diffraction analysis. Diffraction patterns are recorded in a scanning transmission electron microscope (STEM) using a direct electron detector with large dynamical range and fast readout. We use a nanobeam for diffraction and perform the beam double rocking by synchronizing the detector with the STEM scan coils for the recording. Using this approach, large-angle convergent beam electron diffraction (LACBED) patterns of different reflections are obtained simultaneously. By using a nanobeam, instead of a focused beam, the LARBED technique can be applied to beam-sensitive crystals as well as crystals with large unit cells. Here, this paper describes the implementation of LARBED and evaluates the performance using silicon and gadolinium gallium garnet crystals as test samples. We demonstrate that our method provides an effective and robust way for recording LARBED patterns and paves the way for quantitative electron diffraction of large unit cell and beam-sensitive crystals.

4DSTEM↗
DOE OSTI2023

An Alternating, Current-Induced Electromagnetic Field for Membrane Fouling and Scaling Control during Desalination of Secondary Effluent from Municipal Wastewater

Membrane treatment of secondary effluent for reuse applications is a promising approach to expand water supplies and provide flexibility to water resources management. However, effective control of membrane fouling and scaling is crucial for cost-effective treatment and system resilience. This study compared the performance of antiscalants to an alternating, current-induced electromagnetic field (EMF) as an alternative pretreatment method to reverse osmosis. Compared to the no-EMF control experiments, the EMF device resulted in 13% higher water recovery and 366% lower flux decline at 60% of water recovery, along with 2–8 times lower precipitation of fouling and scaling, as evidenced by scanning electron microscope, energy dispersive X-ray spectroscopy, and chemical extraction analysis. The combination of the EMF with antiscalant was more effective for reducing membrane fouling and scaling, increasing water recoveries up to 89.3%, as compared to the EMF (67.5%) and antiscalant-only (73.6%) configurations. This is the first study to demonstrate synergistic effects of using an EMF in combination with antiscalants and could lead to lower pretreatment costs. Additional research is required to quantify the economics of this approach and to fully understand the fundamental mechanisms governing fouling and scaling control by an EMF.

42 ENGINEERING↗
DOE OSTI2026

Characterizing skyrmion flow phases with principal component analysis

Principal component analysis (PCA) is a powerful method that can identify patterns in large, complex data sets by constructing low-dimensional order parameters from higher-dimensional feature vectors. There are increasing efforts to use space-and-time-dependent PCA to detect transitions in nonequilibrium systems that are difficult to characterize with equilibrium methods. Here, we demonstrate that feature vectors incorporating the position and velocity information of driven skyrmions moving through random disorder permit PCA to resolve different types of disordered skyrmion motion as a function of driving force and the ratio of the Magnus force to the dissipation. Since the Magnus force creates gyroscopic motion and a finite Hall angle, skyrmions can exhibit a greater range of flow phases than what is observed in overdamped driven systems with quenched disorder. We show that in addition to identifying previously known skyrmion flow phases, PCA detects several additional phases, including different types of channel flow, moving fluids, and partially ordered states. Guided by the PCA analysis, we further characterize the disordered flow phases to elucidate the different microscopic dynamics and show that the changes in the PCA-derived order parameters can be connected to features in bulk transport measures, including the transverse and longitudinal velocity-force curves, differential conductivity, topological defect density, and changes in the skyrmion Hall angle as a function of drive. We discuss how asymmetric feature vectors can be used to improve the resolution of the PCA analysis, and how this technique can be extended to find disordered phases in other nonequilibrium systems with time-dependent dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

An insight into microscopy and analytical techniques for morphological, structural, chemical, and thermal characterization of cellulose

Cellulose obtained from plants is a bio-polysaccharide and the most abundant organic polymer on earth that has immense household and industrial applications. Hence, the characterization of cellulose is important for determining its appropriate applications. In this article, we review the characterization of cellulose morphology, surface topography using microscopic techniques including optical microscopy, transmission electron microscopy, scanning electron microscopy, and atomic force microscopy. Additionally, other physicochemical characteristics like crystallinity, chemical composition, and thermal properties are studied using techniques including X-ray diffraction, Fourier transform infrared, Raman spectroscopy, nuclear magnetic resonance, differential scanning calorimetry, and thermogravimetric analysis. This review may contribute to the development of using cellulose as a low-cost raw material with anticipated physicochemical properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Thermodynamics of optical Bloch equations

Abstract Optical Bloch equations (OBE) describe the coherent exchange of energy between a quantum bit (qubit) and a quasi-resonant driving field in the presence of a thermal bath. Despite it being an ubiquitous process in quantum technologies, a sound thermodynamic analysis is still missing. We hereby provide such an analysis, by deriving the relevant framework from first principles. We start from a complete microscopic description of the qubit-bath system where definitions of heat, work and entropy production are unambiguous. We trace out the bath and coarse-grain the resulting expressions in time, using a methodology similar to the derivation of the dynamical master equation, to derive closed expressions for the first and second law in terms of system properties. Long coarse graining times yield the Floquet Master equation and its already known thermodynamic description. Short coarse-graining times yield instead the OBE and a novel thermodynamic framework which explicitly depends on quantum coherences in the qubit’s energy basis which produce quantum signatures in the heat and entropy production flows. This allows us to characterize a genuinely quantum non-equilibrium situation, where the coherences created by the driving field are continuously erased by the bath. Our findings can be readily extended to larger open quantum systems. They carry the seeds for future thermodynamic analyses of quantum gates and the design of quantum engines in the strong coherent driving regime.

Elouard, Cyril↗
DOE OSTI2025

Reduced-order modeling for efficient cross section library development in high-temperature gas reactor pebble-bed depletion analysis

Accurate modeling of running-in and equilibrium conditions in pebble-bed reactors (PBRs) requires precise microscopic multigroup neutron cross sections. In Griffin, deterministic neutronics calculations rely on multivariate interpolation over large cross section libraries, resulting in significant memory usage and performance bottlenecks. This work, together with a companion paper on Griffin integration, explores reduced-order models (ROMs) to replace interpolation with lightweight surrogates. Several ROM techniques are benchmarked, with deep neural networks (DNNs) demonstrating superior memory efficiency, scalability, and predictive accuracy. A total of 295 DNNs were trained to build a comprehensive isotope library, integrated into Griffin through a custom LibTorch interface for depletion analysis. Initial results demonstrate that DNN-based ROMs drastically reduce memory demands while preserving accuracy, enabling finer tabulations and additional state variables without overhead. In conclusion, the framework also supports online cross section generation and real-time DNN updates through transfer learning, improving fidelity by capturing self-shielding and evolving nuclide compositions during burnup.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Design of a graphical user interface for few-shot machine learning classification of electron microscopy data

The recent growth in data generation by modern electron microscopes requires rapid, scalable, and flexible approaches to image segmentation and analysis. Few-shot machine learning, which can richly classify images from a handful of user-provided examples, is a promising route to high-throughput analysis. However, current command-line implementations of such approaches can be slow and unintuitive to use, lacking the real-time feedback necessary to perform effective classification. Here we report on the development of a Python-based graphical user interface that enables end users to easily conduct and visualize the output of few-shot learning models. This interface is portable and can be hosted locally or on the web, providing the opportunity to reproducibly conduct, share, and crowd-source few-shot analyses.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Ion irradiation effects on Cr-coated zircaloy-4 surface wettability and pool boiling critical heat flux.

The concept of coating the currently used nuclear fuel cladding (zirconium-based alloy, typically Zircaloy-4 or Zirc-4) with an oxidation preventive layer is a progressing Accident tolerant Fuel (ATF) candidate alloys. The coated Zirc-4-based alloys could be a solution to suppress undesirable fast reaction kinetics with high-temperature steam. Zirc-4 has been the most preferred cladding material in pressurized water reactors (PWRs). Chromium (Cr) based alloys as a coating material provides excellent corrosion protection and good strength and wear resistance. In this paper, we present the surface wettability measurements and pool boiling Critical Heat Flux (CHF) for Cr-coated Zirc-4 claddings pre- and post-exposure to an ion irradiation environment. The wettability measurements, including static contact angle (contact angle, θ) and average surface roughness (surface roughness, Ra), are introduced for samples of different coating thicknesses (5–30 μm thick). The coatings fabricated by the cold spray of Cr-Al particles to 10 mm × 10 mm × 1.95 mm Zirc-4 substrates. Post fabrication, a Pilgering (cold rolling) process, was applied to finalize the coating thickness and resulted in a significant reduction in surface roughness of initially fabricated rough surfaces. The process produced three distinguished samples 5-μm unpolished (as machined), 5-μm, and 30-μm polished (cold rolled). The measurements are presented for the three surfaces and bare Zirc-4 as a baseline surface. The contact angle analyses were implemented in theoretical models from the literature to predict pool boiling CHF. Pool boiling experiments were conducted to measure the pool boiling CHF values and compare them to the predicted values. Scanning Electron Microscope (SEM) images and Energy Dispersive X-ray Spectroscopy (EDS) analysis was performed to characterize the surfaces for better understanding and interpreting the results. The SEM images showed localized surface damage due to ion irradiation. No recognized change in the measured surface roughness due to ion irradiation. The contact angles of irradiated Cr-coated surfaces are consistently higher (10°) than pre-irradiated surfaces. Decreasing the Cr-coating layer thickness resulted in lower contact angle pre- and post- ion irradiation. The predicted pool boiling CHF using the Kandlikar model is in good agreement with the experimentally measured CHF values within ±12% for all samples.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Atomic Force Microscopy and Infrared Nanospectroscopy of COVID-19 Spike Protein for the Quantification of Adhesion to Common Surfaces

The COVID-19 pandemic has claimed millions of lives worldwide, sickened many more, and has resulted in severe socio-economic consequences. As society returns to normal, understanding the spread and persistence of SARS CoV-2 on commonplace surfaces can help to mitigate future outbreaks of coronaviruses and other pathogens. We hypothesize that such an understanding can be aided from studying the binding and interaction of viral proteins with non-biological surfaces. Here, we propose a methodology for investigating the adhesion of the SARS CoV-2 spike glycoprotein on common inorganic surfaces such as aluminum-, copper-, iron-, silica-, and ceria-oxides as well as metallic gold. Quantitative adhesion was obtained from the analysis of measured forces at the nanoscale using an atomic force microscope operated under ambient conditions. Without imposing further constraints on the measurement conditions, our preliminary findings suggest that spike glycoproteins interact with similar adhesion forces across the majority of the metal oxides tested with the exception to gold, for which attraction forces ~10 times stronger than all other materials studied were observed. Ferritin, which was used as a reference protein, was found to exhibit similar adhesion forces as SARS CoV-2 spike protein. Further, this study results show that glycoprotein adhesion forces for similar ambient humidity, tip shape, and contact surface are non-specific to the properties of metal oxide surfaces, which are expected to be covered by a thin water film. The findings suggest that at ambient conditions glycoprotein adhesion to metal oxides is primarily controlled by the water capillary forces and they depend on the surface tension of the liquid (water). We discuss further strategies warranted to decipher the intricate nanoscale forces for improved quantification of the adhesion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Enabling discovery data science through cross-facility workflows

Experimental and observational instruments for scientific research (such as light sources, genome sequencers, accelerators, telescopes and electron microscopes) increasingly require High Performance Computing (HPC) scale capabilities for data analysis and workflow processing. Next-generation instruments are being deployed with higher resolutions and faster data capture rates, creating a big data crunch that cannot be handled by modest institutional computing resources. Often these big data analysis pipelines also require near real-time computing and have higher resilience requirements than the simulation and modeling workloads more traditionally seen at HPC centers. While some facilities have enabled workflows to run at a single HPC facility, there is a growing need to integrate capabilities across HPC facilities to enable cross-facility workflows, either to provide resilience to an experiment, increase analysis throughput capabilities, or to better match a workflow to a particular architecture. In this paper we describe the barriers to executing complex data analysis workflows across HPC facilities and propose an architectural design pattern for enabling scientific discovery using cross-facility workflows that includes orchestration services, application programming interfaces (APIs), data access and co-scheduling.

Antypas, Katerina B.↗
DOE OSTI2024

Photoluminescence probing of light absorption centers at silica laser damage

We use photoluminescence (PL) imaging to study damage growth precursors within laser damage sites on the surface of silica. Damage site evolution is induced by multiple shots of UV nanosecond pulsed laser at various energy densities and monitored throughout the early stages of growth. Wide-field PL imaging rapidly locates microscopic light absorption centers within the silica damage site. Our quantitative analysis shows that damage sites with strong local PL intensity show a higher probability of growth upon subsequent laser pulses. Scanning electron microscopy (SEM) paired with a study of PL spectrum shows that the strong PL intensity appears from the subsurface fractures with high defect density, which provides a local light absorption center leading to significant damage growth. We believe that this result offers an efficient optical damage mitigation strategy by providing a rapid and non-destructive optical inspection approach.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A new paradigm in electron microscopy: Automated microstructure analysis utilizing a dynamic segmentation convolutional neutral network

Over the past half century, the transmission electron microscope enabled insight into the fundamental arrangements and structures of materials. State-of-the-art electron microscopes can acquire large image datasets across multiple imaging modalities. However, the manual annotation process for feature or defect quantification may not be feasible with the modern microscope. Convolutional neural networks emerged to characterize individual microstructural features from an image in a cost-effective, consistent manner. However, many of these neural network approaches rely on thousands to hundreds of thousands of manual annotations of each feature type across hundreds of images to train the network for adequate performance. This work focused on the development and application of a pixel-wise defect detection machine-learning dynamic segmentation convolutional neural network with associated automated acquisition and postprocessing to identify microstructural features rapidly and quantitatively from a small initial dataset incorporating multiple imaging modes. The approach was demonstrated for characterization of superalloy 718 from both single image acquisition on multiple detectors to in-situ evolution captured with a single detector on a standard desktop computer to demonstrate the low barrier to entry required for widespread adoption. Pixel-by-pixel class identification was excellent with strong identification of chemically distinct phases, structurally distinct phases, and defect structures, thus demonstrating the new paradigm of machine learning-assisted characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Damage-free Analysis of Biological Materials by Vibrational Spectroscopy in the EM

In summary, vibrational spectroscopy in the electron microscope promises to probe biological materials in a way that is similar to infrared spectroscopy, at a spatial resolution of about 30-50 nm, while circumventing radiation damage. Herein we are now focused on developing this technique fully, using a side-entry cryotransfer holder in a Nion HERMES electron microscope equipped with a fast and efficient EELS direct detector [10], and capable of 5 meV (and better) energy resolution. The results of these investigations will be reported at the meeting.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

In Situ X-ray Scattering Reveals Coarsening Rates of Superlattices Self-Assembled from Electrostatically Stabilized Metal Nanocrystals Depend Nonmonotonically on Driving Force

Self-assembly of colloidal nanocrystals (NCs) into superlattices (SLs) is an appealing strategy to design hierarchically organized materials with promising functionalities. Mechanistic studies are still needed to uncover the design principles for SL self-assembly, but such studies have been difficult to perform due to the fast time and short length scales of NC systems. To address this challenge, we developed an apparatus to directly measure the evolving phases in situ and in real time of an electrostatically stabilized Au NC solution before, during, and after it is quenched to form SLs using small-angle X-ray scattering. By developing a quantitative model, we fit the time-dependent scattering patterns to obtain the phase diagram of the system and the kinetics of the colloidal and SL phases as a function of varying quench conditions. The extracted phase diagram is consistent with particles whose interactions are short in range relative to their diameter. We find the degree of SL order is primarily determined by fast (subsecond) initial nucleation and growth kinetics, while coarsening at later times depends nonmonotonically on the driving force for self-assembly. We validate these results by direct comparison with simulations and use them to suggest dynamic design principles to optimize the crystallinity within a finite time window. The combination of this measurement methodology, quantitative analysis, and simulation should be generalizable to elucidate and better control the microscopic self-assembly pathways of a wide range of bottom-up assembled systems and architectures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Reconstruction and uncertainty quantification of lattice Hamiltonian model parameters from observations of microscopic degrees of freedom

The emergence of scanning probe and electron beam imaging techniques has allowed quantitative studies of atomic structure and minute details of electronic and vibrational structure on the level of individual atomic units. These microscopic descriptors, in turn, can be associated with local symmetry breaking phenomena, representing the stochastic manifestation of the underpinning generative physical model. In this work, we explore the reconstruction of exchange integrals in the Hamiltonian for a lattice model with two competing interactions from observations of microscopic degrees of freedom and establish the uncertainties and reliability of such analysis in a broad parameter-temperature space. In contrast to other approaches, we specifically specify a loss function inherent to thermodynamic systems and utilize it to estimate uncertainty in simulated realizations of different models. As an ancillary task, we develop a machine learning approach based on histogram clustering to predict phase diagrams efficiently using a reduced descriptor space. We further demonstrate that reconstruction is possible well above the phase transition and in the regions of parameter space when the macroscopic ground state of the system is poorly defined due to frustrated interactions. This suggests that this approach can be applied to the traditionally complex problems of condensed matter physics such as ferroelectric relaxors and morphotropic phase boundary systems, spin and cluster glasses, and quantum systems once the local descriptors linked to the relevant physical behaviors are known.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Conductivity space isotherm behavior in quantum anomalous Hall devices

The quantum Hall effect (QHE) has enhanced accessibility to measure and disseminate electrical units, owed in part to the recently redefined International System of Units in 2019. Graphene remains one of the preferred options to realize the ohm despite the limitations of high magnetic fields to produce a robust QHE. Topological insulators, on the other hand, show promise in providing quantized resistance via the quantum anomalous Hall effect, a phenomenon that removes the need for magnetic fields during operation. To optimize future devices for metrological applications, it is important to gain a better understanding of magnetically doped topological insulators like Cr-doped bismuth antimony telluride. The application of differential conductivity space analyses offers a more sensitive way to analyze the data and distinguish between 2D and 3D transport behaviors. This is particularly important in thin films, where the transition between 2D and 3D behavior can be subtle. The ability to confidently determine the dimensionality of the transport is crucial for selecting appropriate theoretical models for future device optimization. Furthermore, this work identifies variable range hopping as the dominant transport mechanism in the 2D regime using a rigorous statistical analysis (via the Bayes factor). These elements assist in the understanding of microscopic processes that govern charge transport in these materials.

Tran, N. T. M. [National Inst. of Standards and Te↗
DOE OSTI2023

Colossal transverse magnetoresistance due to nematic superconducting phase fluctuations in a copper oxide

Electronic anisotropy (“nematicity”) has been detected in cuprate superconductors by various experimental techniques. Using angle-resolved transverse resistance (ARTR) measurements, a very sensitive and background-free technique that can detect 0.5% anisotropy in transport, we have observed it also in La 2-x Sr x CuO 4 (LSCO) for 0.02 ≤ x ≤ 0.25. A central enigma in LSCO is the rotation of the nematic director (orientation of the largest longitudinal resistance) with temperature; this has not been seen before in any material. Here, we address this puzzle by measuring the angle-resolved transverse magnetoresistance (ARTMR) in LSCO. We report the discovery of colossal transverse magnetoresistance (CTMR)—an order-of-magnitude drop in the transverse resistivity in the magnetic field of 6 T. We show that the apparent rotation of the nematic director is caused by anisotropic superconducting fluctuations, which are not aligned with the normal electron fluid, consistent with coexisting bond-aligned and diagonal nematic orders. We quantify this by modeling the (magneto-)conductivity as a sum of normal (Drude) and paraconducting (Aslamazov–Larkin) channels but extended to contain anisotropic Drude and Cooper-pair effective mass tensors. Strikingly, the anisotropy of Cooper-pair stiffness is much larger than that of the normal electrons. It grows dramatically on the underdoped side, where the fluctuations become quasi-one-dimensional. Our analysis is general rather than model dependent. Still, we discuss some candidate microscopic models, including coupled strongly-correlated ladders where the transverse (interladder) phase stiffness is low compared with the longitudinal intraladder stiffness, as well as the anisotropic superconducting fluctuations expected close to the transition to a pair-density wave state.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Nature of Symmetry Breaking at the Excitonic Insulator Transition: Ta 2 NiSe 5

Ta 2 NiSe 5 is one of the most promising materials for hosting an excitonic insulator ground state. While a number of experimental observations have been interpreted in this way, the precise nature of the symmetry breaking occurring in Ta 2 NiSe 5 , the electronic order parameter, and a realistic microscopic description of the transition mechanism are, however, missing. By a symmetry analysis based on first-principles calculations, we uncover the discrete lattice symmetries which are broken at the transition. We identify a purely electronic order parameter of excitonic nature that breaks these discrete crystal symmetries and contributes to the experimentally observed lattice distortion from an orthorombic to a monoclinic phase. Our results provide a theoretical framework to understand and analyze the excitonic transition in Ta 2 NiSe 5 and settle the fundamental questions about symmetry breaking governing the spontaneous formation of excitonic insulating phases in solid-state materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗