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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

N - V –Diamond Magnetic Microscopy Using a Double Quantum 4-Ramsey Protocol

We introduce a double quantum (DQ) 4-Ramsey measurement protocol that enables wide-field magnetic imaging using nitrogen-vacancy (N-V) centers in diamond, with enhanced homogeneity of the magnetic sensitivity relative to conventional single quantum (SQ) techniques. The DQ 4-Ramsey protocol employs microwave-phase alternation across four consecutive Ramsey (4-Ramsey) measurements to isolate the desired DQ magnetic signal from any residual SQ signal induced by microwave pulse errors. In a demonstration experiment employing a 1-μm-thick N-V layer in a macroscopic diamond chip, the DQ 4-Ramsey protocol provides a volume-normalized dc magnetic sensitivity of η V = 34nTHz –1/2 μm 3/2 across a 125 μm × 125 μm field of view, with about 5× less spatial variation in sensitivity across the field of view compared to a SQ measurement. Furthermore, the improved robustness and magnetic sensitivity homogeneity of the DQ 4-Ramsey protocol enables imaging of dynamic broadband magnetic sources such as integrated circuits and electrically active cells.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Phase-resolving spin-wave microscopy using infrared strobe light

The need for sensitively and reliably probing magnetization dynamics has been increasing in various contexts such as studying novel hybrid magnonic systems, in which the spin dynamics strongly and coherently couple to other excitations, including microwave photons, light photons, or phonons. Recent advances in quantum magnonics also highlight the need for employing the magnon phase as quantum state variable, which is to be detected and mapped out with high precision in on-chip micro- and nanoscale magnonic devices. Here, in this study, we demonstrate a facile optical technique that can directly perform concurrent spectroscopic and imaging functionalities with spatial and phase resolutions, using infrared strobe light operating at 1550-nm wavelength. To showcase the methodology, we spectroscopically studied the phaseresolved spin dynamics in a bilayer of Permalloy and yttrium iron garnet Y 3 Fe 5 O 12 (YIG), and spatially imaged the backward-volume spin-wave modes of YIG in the dipolar spin-wave regime. Using the strobe light probe, the detected precessional phase contrast can be directly used to construct the map of the spin wave's wave front, in the continuous-wave regime of spin-wave propagation and in the stationary state, without needing any optical reference path. By selecting the applied field, frequency, and detection phase, the spin-wave images can be made sensitive to the precession amplitude and phase. Our results demonstrate that infrared optical strobe light can serve as a versatile platform for magneto-optical probing of magnetization dynamics, with potential implications in investigating hybrid magnonic systems.

Xiong, Yuzan [University of North Carolina, Chapel↗
DOE OSTI2020

Twofold symmetry of proximity-induced superconductivity in Bi 2 Te 3 / Bi 2 Sr 2 CaCu 2 O 8 + δ heterostructures revealed by scanning tunneling microscopy

We observe proximity-induced superconductivity in in situ prepared heterostructures constructed by topological insulator Bi 2 Te 3 thin films and high-temperature cuprate superconductors Bi 2 Sr 2 CaCu 2 O 8+δ . The superconducting gap maximum is about 7.6 meV on the surface of Bi 2 Te 3 thin films with a thickness of two quintuple layers, and the gap value decreases with an increase in the film thickness. Moreover, the quasiparticle interference data show clear evidence of a twofold symmetric superconducting gap with gap minima along one pair of the principal crystalline axes of Bi 2 Te 3 . This gap form is consistent with the Δ 4y notation of the topological superconductivity proposed in such systems. Our results provide fruitful information on the possible topological superconductivity induced by the proximity effect in high-temperature superconducting cuprates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Towards scanning nanostructure X-ray microscopy

This article demonstrates spatial mapping of the local and nanoscale structure of thin film objects using spatially resolved pair distribution function (PDF) analysis of synchrotron X-ray diffraction data. This is exemplified in a lab-on-chip combinatorial array of sample spots containing catalytically interesting nanoparticles deposited from liquid precursors using an ink-jet liquid-handling system. A software implementation is presented of the whole protocol, including an approach for automated data acquisition and analysis using the atomic PDF method. The protocol software can handle semi-automated data reduction, normalization and modeling, with user-defined recipes generating a comprehensive collection of metadata and analysis results. By slicing the collection using included functions, it is possible to build images of different contrast features chosen by the user, giving insights into different aspects of the local structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Versatile compact heater design for in situ nano-tomography by transmission X-ray microscopy

A versatile, compact heater designed at National Synchrotron Light Source-II for in situ X-ray nano-imaging in a full-field transmission X-ray microscope is presented. Heater design for nano-imaging is challenging, combining tight spatial constraints with stringent design requirements for the temperature range and stability. Finite-element modeling and analytical calculations were used to determine the heater design parameters. Performance tests demonstrated reliable and stable performance, including maintaining the exterior casing close to room temperature while the heater is operating at above 1100°C, a homogenous heating zone and small temperature fluctuations. Two scientific experiments are presented to demonstrate the heater capabilities: (i) in situ 3D nano-tomography including a study of metal dealloying in a liquid molten salt extreme environment, and (ii) a study of pore formation in icosahedral quasicrystals. The progression of structural changes in both studies were clearly resolved in 3D, showing that the new heater enables powerful capabilities to directly visualize and quantify 3D morphological evolution of materials under real conditions by X-ray nano-imaging at elevated temperature during synthesis, fabrication and operation processes. This heater design concept can be applied to other applications where a precise, compact heater design is required.

36 MATERIALS SCIENCE↗
DOE OSTI2022

TXM-Sandbox : an open-source software for transmission X-ray microscopy data analysis

A transmission X-ray microscope (TXM) can investigate morphological and chemical information of a tens to hundred micrometre-thick specimen on a length scale of tens to hundreds of nanometres. It has broad applications in material sciences and battery research. TXM data processing is composed of multiple steps. A workflow software has been developed that integrates all the tools required for general TXM data processing and visualization. The software is written in Python and has a graphic user interface in Jupyter Notebook . Users have access to the intermediate analysis results within Jupyter Notebook and have options to insert extra data processing steps in addition to those that are integrated in the software. The software seamlessly integrates ImageJ as its primary image viewer, providing rich image visualization and processing routines. As a guide for users, several TXM specific data analysis issues and examples are also presented.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Image registration for accurate electrode deformation analysis in operando microscopy of battery materials

Operando imaging techniques have become increasingly valuable in both battery research and manufacturing. However, the reliability of these methods can be compromised by instabilities in the imaging setup and operando cells, particularly when utilizing high-resolution imaging systems. The acquired imaging data often include features arising from both undesirable system vibrations and drift, as well as the scientifically relevant deformations occurring in the battery sample during cell operation. For meaningful analysis, it is crucial to distinguish and separately evaluate these two factors. To address these challenges, we employ a suite of advanced image-processing techniques. These include fast Fourier transform analysis in the frequency domain, power spectrum-based assessments for image quality, as well as rigid and non-rigid image-registration methods. These techniques allow us to identify and exclude blurred images, correct for displacements caused by motor vibrations and sample holder drift and, thus, prevent unwanted image artifacts from affecting subsequent analyses and interpretations. Additionally, we apply optical flow analysis to track the dynamic deformation of battery electrode materials during electrochemical cycling. This enables us to observe and quantify the evolving mechanical responses of the electrodes, offering deeper insights into battery degradation. Together, these methods ensure more accurate image analysis and enhance our understanding of the chemomechanical interplay in battery performance and longevity.

Sun, Tianxiao↗
DOE OSTI2025

Active Learning Surrogates for Integrating Electron Microscopy and Computational Insights from Simulations in Autonomous Experiments

Artificial Intelligence (AI) combined with simulations and experiments has great potential to accelerate scientific discovery across technology and pharmaceuticals. However, the gap between simulations and experiments is challenging due to disparities in time and scale, making it difficult to estimate properties like energy and electronic states from experiments, and to provide feedback based on theoretical insights.Our research addresses the challenge by developing unique deep kernel based surrogate models that learns from microscopic images, mapping structural features to energy differences from defect formation. We start with full-training using simulated images to determine optimal settings, establishing a baseline for active learning. Using these settings from the baseline, active learning is trained, and predicts structures along simulation trajectories based on uncertainty and energetic stability, thus reducing data requirements, simulation time and computational costs. The results demonstrate that the model achieves a low average error margin of approximately 0.03 meV, indicating good performance. To enhance feature extraction and reconstruction capabilities, we developed an autoencoder-decoder as additional surrogate to create latent space to capture essential features, enabling precise comparisons between simulations and experiments. The results from this model achieved a reconstruction loss of around 0.2 and accurately reconstructed molecular structures.Overall, this work advances the steering of experiments through computational simulations by employing a surrogate models that actively predicts the trajectories of structural evolution, achieving time-to-solution comparable to experimental measurements.

Saranathan, Gayathri [Hewlett-Packard]↗