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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Microscopic Measurement: Need for Nuclear Material Sample Specimen Characterization Capability

The Surveillance, Fabrication, and Off-Site Operations team at Lawrence Livermore National Laboratory is beginning an update to the nuclear material machining lab in Superblock. Plutonium and other nuclear materials tend to accelerate the aging process for equipment and machines that would otherwise be maintainable for long lives. They have their lifespans shortened from deteriorated seals, embrittled polymer components, accelerated corrosion, and damage to electronics from exposure to radioactive materials. The cost of installation of equipment into a glove box (GB) tends to outstrip the cost of the equipment itself. Due to the magnification of cost, the historical approach to equipment installs has been to purchase and install the highest-quality and most robust equipment available to maximize time between failures and updates. To make room for the installation of a new lathe, the inspection GB is being moved to a different location within the machining lab. As part of the overall effort, the equipment within the inspection GB is being revisited. Current measurement capabilities are antiquated and starting to become problematic due to age. Advances in metrology are sought for more comprehensive characterization of scientific samples. This document aims to identify several options for the replacement of current measurement equipment and identify a system for purchase and eventual installation. The intention is not to select the cheapest system, but rather to identify a system that best meets the needs of both the operators and principal investigators (PI). Following the convention of the SYSM-5620 Design Thinking and System Engineering, it was determined that a laser confocal measurement system from Keyence is the most suitable option for our programmatic need. Form factor, capability, and maintainability were considered. Along with stakeholder input, to ensure the best decision for the Nuclear Material Technology Program.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes

Hydrogen bonded electrolytes that exhibit accelerated proton transport via sequential reactive hops have drawn interest for their promise in clean energy applications. Molecular dynamics simulations of these electrolytes offer the opportunity to uncover microscopic mechanistic details that could be used to design and tune the properties of candidate electrolyte technologies. However, accurately modeling the proton transfer reactions and transport properties that give rise to high charge conductivites in these electrolytes proves computationally challenging because of the need to perform lengthy condensed phase simulations, treating both the electronic and nuclear degrees of freedom quantum mechanically. In this paper, we demonstrate that such a modeling task can be efficiently achieved with the use of density functional theory (DFT)-trained machine learning potentials (MLP) to accelerate path integral molecular dynamics (PIMD) simulations. We highlight the practical utility of this approach by using it to benchmark how closely PIMD simulations employing different DFT exchange–correlation functionals reproduce the composition-dependent densities, diffusion coefficients, and electrical conductivities of mixtures consisting of imidazole and levulinic acid. Even with the speedup afforded by our MLPs, PIMD simulations remain quite expensive. Furthermore, in order to render PIMD more computationally tractable, we introduce and benchmark the accuracy of a ring polymer contraction approach that leverages a computationally efficient short-range MLP to accelerate our PIMD simulations by an additional factor of four.

Chemical bonding↗
DOE OSTI2025

Microscopic Theory of Pair Density Waves in Spin-Orbit Coupled Kondo Lattice

We demonstrate that the discommensuration between the Fermi surfaces of a conduction sea and an underlying spin liquid provides a natural mechanism for the spontaneous formation of pair density waves. Using a recent formulation of the Kondo lattice model that incorporates a Yao Lee spin liquid proposed by the authors, we demonstrate that doping away from half filling induces finite-momentum electron-Majorana pair condensation, resulting in amplitude-modulated pair density waves (PDWs). Our approach provides a precise, analytically tractable pathway for understanding the spontaneous formation of PDWs in higher dimensions and offers a natural mechanism for PDW formation in the absence of Zeeman splitting.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Binary pseudo-random array standard for extreme ultraviolet lithography tool characterization

Extreme ultraviolet (EUV) imaging tools play a crucial role in EUV lithography. Achieving high accuracy in EUV metrology is essential for advanced semiconductor manufacturing. A thorough characterization of the instrumentation in use is required. Binary pseudo-random arrays (BPRAs) are an established standard for calibrating and characterizing optical instruments in the frequency domain. Here, we expand the BPRA standard to applications in EUV imaging. To extend the technology to the EUV spectral range, a high-resolution BPRA target with the smallest feature size of 40 nm is developed. The EUV BPRA target establishes an in situ and portable calibration and alignment standard for EUV imaging. The target is patterned by means of electron-beam lithography, using a nickel absorber with a thickness of 39 nm. The substrate is a 4″ silicon wafer with a molybdenum/silicon multilayer coating. To demonstrate the efficacy of the target and develop the instrument calibration protocol, the target is imaged on the Sharp Hyper-NA Actinic Reticle Review Project EUV mask microscope. Power spectral density (PSD) data are presented. The characteristics of the imaging system are imprinted on the PSD. The modulation transfer function is extracted from the PSD data. A partially coherent imaging model is used as a reference to the experimental results.

BPRA↗
DOE OSTI2025

Bridging multimodal microscopy for advanced characterization on nuclear fuel using machine learning

Uranium dioxide (UO 2 ), widely used as driver fuel in light water reactors, experiences microstructure and property change by nuclear fission reactions. This paper bridges the characterization of fresh UO 2 fuel at different length scales, serving as a baseline for future post irradiation examination of irradiated UO 2 fuel. To characterize the microstructural change of nuclear fuel, modern approaches cover a wide range of length scales through different characterization techniques, such as mm scale for Synchrotron-based X-ray computed tomography (SXCT) and microscale for focused ion beam (FIB) and scanning electron microscopy (SEM). It is challenging to bridge the data and knowledge of the same sample in different length scales. This paper proposed a deep learning framework leveraging transfer learning to detect microstructural defects, trained from a sparse FIB, SEM, and SXCT images. The proposed model achieved superior performance in defect segmentation on multiscale microscopic data compared to four of the latest deep learning models.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Identification and correction of temporal and spatial distortions in scanning transmission electron microscopy

Scanning transmission electron microscopy (STEM) has become the technique of choice for quantitative characterization of atomic structure of materials, where the minute displacements of atomic columns from high-symmetry positions can be used to map strain, polarization, octahedra tilts, and other physical and chemical order parameter fields. The latter can be used as inputs into mesoscopic and atomistic models, providing insight into the correlative relationships and generative physics of materials on the atomic level. However, these quantitative applications of STEM necessitate understanding the microscope induced image distortions and developing the pathways to compensate them both as part of a rapid calibration procedure for in situ imaging, and the post-experimental data analysis stage. Here, we explore the spatiotemporal structure of the microscopic distortions in STEM using multivariate analysis of the atomic trajectories in the image stacks. Based on the behavior of principal component analysis (PCA), we develop the Gaussian process (GP)-based regression method for quantification of the distortion function. The limitations of such an approach and possible strategies for implementation as a part of in-line data acquisition in STEM are discussed. Here, the analysis workflow is summarized in a Jupyter notebook that can be used to retrace the analysis and analyze the reader's data.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Toward Optimizing Electrospun Nanofiber Fuel Cell Catalyst Layers: Microstructure and Pt Accessibility

This work investigates how local ionomer/platinum (Pt) interactions and ionomer distribution in electrospun Pt/Vulcan nanofiber electrodes impact ionomer coverage, proton accessibility, and oxygen reduction reaction (ORR) performance in proton-exchange membrane fuel cells. Insights from various in situ electrochemical diagnostics were utilized in conjunction with ex situ microscopic characterization to understand how the electrode microstructure—both at the aggregate level and near the ionomer/platinum interface—is affected by electrospinning in comparison to ultrasonic spraying. The effect of the carrier polymer poly(acrylic acid) (PAA) concentration from 5–20 wt % (with respect to total ink solids) on the resulting nanofiber morphology is discussed. Electron microscopy observations and CO displacement measurements indicated that Pt/Vulcan nanofibers prepared with a higher PAA concentration (15 wt %) were conformally coated with a film of ionomer on the exterior of the fiber, which resulted in an overall lower ionomer coverage on both Pt and carbon throughout the fiber diameter. In contrast, 10 wt % PAA leads to a uniform intrafiber distribution of the ionomer within the fibers, increasing the overall ionomer coverage and proton accessibility under both wet and dry conditions. These differences in the local ionomer coverage on Pt between 10 and 15 wt % PAA were also attributed to differences in the adsorption/interaction affinities between PAA and the ionomer onto the catalyst surface in the ink using zeta potential measurements. Additional fuel cell electrochemical tests on the electrospun electrodes show improvements in ORR kinetics and high-current-density H 2 /air performance compared to the ultrasonically sprayed electrodes.

25 ENERGY STORAGE↗
DOE OSTI2022

Spin structure and dynamics of the topological semimetal Co 3 Sn 2-x In x S 2

The anomalous Hall effect (AHE), typically observed in ferromagnetic (FM) metals with broken time-reversal symmetry, depends on electronic and magnetic properties. In Co 3 Sn 2-x In x S 2 , a giant AHE has been attributed to Berry curvature associated with the FM Weyl semimetal phase, yet recent studies report complicated magnetism. We use neutron scattering to determine the spin dynamics and structures as a function of x and provide a microscopic understanding of the AHE and magnetism interplay. Spin gap and stiffness indicate a contribution from Weyl fermions consistent with the AHE. The magnetic structure evolves from c-axis ferromagnetism at x = 0 to a canted antiferromagnetic (AFM) structure with reduced c-axis moment and in-plane AFM order at x = 0.12 and further reduced c-axis FM moment at x = 0.3. Since noncollinear spins can induce non-zero Berry curvature in real space acting as a fictitious magnetic field, our results revealed another AHE contribution, establishing the impact of magnetism on transport.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Magnetic contribution of itinerant electrons to neutron diffraction in the topological antiferromagnet CeAlGe

We report a neutron diffraction study of the magnetic structure of CeAlGe, a candidate topological semimetal that hosts a noncollinear, multi-𝐤 magnetic phase. By measuring both low- and high-momentum-transfer magnetic Bragg peaks within a single experimental setup, we refine a magnetic structure model based solely on localized Ce moments. This model, which differs from that obtained using only high-𝑄 data, quantitatively reproduces the observed intensities, including the (000) zeroth-order magnetic satellites that are especially sensitive to subtle components of the modulation. While a contribution from itinerant electrons to the zeroth satellite cannot be definitively excluded, our analysis reveals no unambiguous evidence for such effects within experimental uncertainty. The refined magnetic structures exhibit topologically nontrivial winding patterns, derived from the fitted magnetic parameters, that support localized, particle-like spin textures with half-integer topological charges. These features provide a natural microscopic origin for the observed topological Hall effect, establishing CeAlGe as a model system where magnetism and topology are intimately linked.

Magnetic coupling↗
DOE OSTI2023

Microstructure development and properties of micro-alloyed copper, Cu-0.3Zr-0.15Ag, produced by electron beam additive manufacturing

A micro-alloyed copper powder, Cu-0.3Zr-0.15Ag wt.%, was produced using gas atomization reaction synthesis. Zirconium was added to copper to sequester the oxygen present as copper oxide surface films on the powder particles. The as-received powders, as well as the intentionally oxidized powders were used to fabricate solid test articles by electron beam powder bed fusion additive manufacturing. Dense samples fabricated from as-received powder demonstrated nominal UTS, yield, and elongation values at 260 MPa, 150 MPa, and 34%, respectively. The average electrical conductivity of these samples was measured at 95% of the international annealed copper standard (IACS). Samples fabricated from the oxidized powder exhibited nominal UTS, yield, and elongation of 241 MPa, 146 MPa, and 43%, respectively, with an electrical conductivity of 95 % IACS. During characterization, it was observed that, rather than forming nano-scale dispersoids, the Zirconia (ZrO 2 ) appeared as discontinuous stringers in the metallographic cross-sections that crossed grain and melt pool boundaries. This was rationalized by tracing the presence of the micro-alloying addition of elemental zirconium, which was found to react with surface oxides dissociated in the melt pool to form ZrO 2 , which then solidified on the surface of the melt pool through an allotropic transformation to monoclinic ZrO 2 in discontinuous films and spheroids ranging in size from nanometers to microns. This was confirmed by microscopic analysis of the tops of the melt pools. On subsequent melt passes, these ZrO 2 structures were displaced and redistributed within the melt pool.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Intricacies of frustrated magnetism in the Kondo metal YbAgGe

The combination of localized magnetic moments, their frustration and interaction with itinerant electrons is a key challenge of condensed matter physics. Frustrated magnetic interactions promote degenerate ground states with enhanced fluctuations, a topic that is predominantly studied in magnetic insulators. The coupling between itinerant and localized electrons in metals add complexity to the problem, and is presently formulated only for extreme cases in which the itinerant electrons mediate exchange between localized spins (RKKY interaction) or suppress the formation of magnetic moments (Kondo screening). Here, we report an in-depth experimental study of the distorted Kagome metal YbAgGe, unravelling the open questions of how frustration, localized magnetism and itinerant electrons are intertwined in frustrated Kondo metals. We find that coupled itinerant and localized electrons give rise to dynamic magnetic correlations below T* ≈ 20 K. At lower temperature, frustrated magnetic interactions establish anisotropic magnetic short-range correlations that culminate into antiferromagnetic long-range order below T N = 0.68 K with a significantly reduced modulated magnetic moment. We show that local moment Hamiltonians can yield limited understanding of the microscopic behaviour in frustrated metals, and prompt the extension of more sophisticated model Hamiltonians incorporating itinerant effects.

Mazzone, Daniel G. [PSI Center for Neutron and Muo↗
DOE OSTI2025

Chiral population analysis: a real space visualization of X-ray circular dichroism

The microscopic understanding of probing and controlling molecular chirality is of considerable interest. Numerous spectroscopic techniques are capable of monitoring molecular asymmetry and its consequences, ranging from the infrared to the X-ray regime. Resonant X-rays have long been used to investigate local atomic sites within molecules thanks to the localized nature of core electronic transitions. These techniques can be used to determine the extent to which chirality is a local versus a delocalized property. However, how to systematically partition dichroic contributions from the point of view of electronic structure simulations remains an open question. Here, we introduce the concept of chiral population analysis that connects chirality to the atomic orbital picture. In analogy with Mulliken population analysis, which assigns charges to atomic orbitals, chiral populations allow the dichroic response to be distributed among the participating atomic orbitals. This decomposition can be further visualized in real space by representing it in terms of isosurface plots, providing an intuitive way to connect the dichroic response to its origins. Thus chiral population analysis can be particularly useful to assess the extent to which a given electronic transition is sensitive to chirality as a local or global feature of the molecular geometry.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Probe microscopy is all you need *

We pose that microscopy offers an ideal real-world experimental environment for the development and deployment of active Bayesian and reinforcement learning methods. Indeed, the tremendous progress achieved by machine learning (ML) and artificial intelligence over the last decade has been largely achieved via the utilization of static data sets, from the paradigmatic MNIST to the bespoke corpora of text and image data used to train large models such as GPT3, DALL·E and others. However, it is now recognized that continuous, minute improvements to state-of-the-art do not necessarily translate to advances in real-world applications. We argue that a promising pathway for the development of ML methods is via the route of domain-specific deployable algorithms in areas such as electron and scanning probe microscopy and chemical imaging. This will benefit both fundamental physical studies and serve as a test bed for more complex autonomous systems such as robotics and manufacturing. Favorable environment characteristics of scanning and electron microscopy include low risk, extensive availability of domain-specific priors and rewards, relatively small effects of exogenous variables, and often the presence of both upstream first principles as well as downstream learnable physical models for both statics and dynamics. Recent developments in programmable interfaces, edge computing, and access to application programming interfaces (APIs) facilitating microscope control, all render the deployment of ML codes on operational microscopes straightforward. We discuss these considerations and hope that these arguments will lead to create novel set of development targets for the ML community by accelerating both real world ML applications and scientific progress.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Exploring the Relationship of Microstructure and Conductivity in Metal Halide Perovskites via Active Learning-Driven Automated Scanning Probe Microscopy

Electronic transport and hysteresis in metal halide perovskites (MHPs) are key to the applications in photovoltaics, light emitting devices, and light and chemical sensors. These phenomena are strongly affected by the materials microstructure including grain boundaries, ferroic domain walls, and secondary phase inclusions. Here, we demonstrate an active machine learning framework for “driving” an automated scanning probe microscope (SPM) to discover the microstructures responsible for specific aspects of transport behavior in MHPs. In our setup, the microscope can discover the microstructural elements that maximize the onset of conduction, hysteresis, or any other characteristic that can be derived from a set of current–voltage spectra. Furthermore, this approach opens new opportunities for exploring the origins of materials functionality in complex materials by SPM and can be integrated with other characterization techniques either before (prior knowledge) or after (identification of locations of interest for detail studies) functional probing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

The Role of Defect Geometry in Localized Emission from Monolayer Tungsten Dichalcogenides

In two-dimensional transition metal dichalcogenides such as tungsten diselenide (WSe 2 ), single photon emission has been broadly attributed to exciton localization from atomic point defects, yet the precise microscopic origins are unclear. This work introduces an empirically grounded computational framework that explains the origins of facile single photon emission in WSe 2 . High-resolution microscopy identifies native defect geometries in monolayer WSe 2 lattices from which the model is built. Here, the qualitative effects of chalcogen type, defect geometry, and mechanical strain on the electronic structure are individually assessed using density functional theory, and a specific divacancy configuration emerges as the candidate for localized single-electron transitions that match observed spectral energies. Spectroscopy and photon correlation measurements further validate this model, establishing a self-consistent link between defect geometry, electronic structure, and quantum emission.

defect emission↗
DOE OSTI2020

mpfit: a robust method for fitting atomic resolution images with multiple Gaussian peaks

The standard technique for sub-pixel estimation of atom positions from atomic resolution scanning transmission electron microscopy images relies on fitting intensity maxima or minima with a two-dimensional Gaussian function. While this is a widespread method of measurement, it can be error prone in images with non-zero aberrations, strong intensity differences between adjacent atoms or in situations where the neighboring atom positions approach the resolution limit of the microscope. Here we demonstrate mpfit, an atom finding algorithm that iteratively calculates a series of overlapping two-dimensional Gaussian functions to fit the experimental dataset and then subsequently uses a subset of the calculated Gaussian functions to perform sub-pixel refinement of atom positions. Based on both simulated and experimental datasets presented in this work, this approach gives lower errors when compared to the commonly used single Gaussian peak fitting approach and demonstrates increased robustness over a wider range of experimental conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Imaging Quantum Interference in Stadium-Shaped Monolayer and Bilayer Graphene Quantum Dots

Experimental realizations of graphene-based stadium-shaped quantum dots (QDs) have been few and have been incompatible with scanned probe microscopy. Yet, the direct visualization of electronic states within these QDs is crucial for determining the existence of quantum chaos in these systems. Here we report the fabrication and characterization of electrostatically defined stadium-shaped QDs in heterostructure devices composed of monolayer graphene (MLG) and bilayer graphene (BLG). To realize a stadium-shaped QD, we utilized the tip of a scanning tunneling microscope to charge defects in a supporting hexagonal boron nitride flake. The stadium states visualized are consistent with tight-binding-based simulations but lack clear quantum chaos signatures. The absence of quantum chaos features in MLG-based stadium QDs is attributed to the leaky nature of the confinement potential due to Klein tunneling. In contrast, for BLG-based stadium QDs (which have stronger confinement) quantum chaos is precluded by the smooth confinement potential which reduces interference and mixing between states.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Competing magnetic phases and fluctuation-driven scalar spin chirality in the kagome metal YMn 6 Sn 6

Identification, understanding, and manipulation of novel magnetic textures are essential for the discovery of new quantum materials for future spin-based electronic devices. In particular, materials that manifest a large response to external stimuli such as a magnetic field are subject to intense investigation. Here, we study the kagome-net magnet YMn 6 Sn 6 by magnetometry, transport, and neutron diffraction measurements combined with first-principles calculations. We identify a number of nontrivial magnetic phases, explain their microscopic nature, and demonstrate that one of them hosts a large topological Hall effect (THE). We propose a previously unidentified fluctuation-driven mechanism, which leads to the THE at elevated temperatures. This interesting physics comes from parametrically frustrated interplanar exchange interactions that trigger strong magnetic fluctuations. Our results pave a path to chiral spin textures, promising for novel spintronics.

36 MATERIALS SCIENCE↗