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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Adapting confocal Raman microscopy for in situ studies of redox transformations at electrode-electrolyte interfaces

Confocal Raman microscopy was applied to quantify redox species present within the diffusion layer adjacent to an electrode surface under potentiostatic control. A glass microscope coverslip with a thin indium tin oxide (ITO) coating served as both the working electrode and optical window for a microscope-stage mountable spectroelectrochemical cell. A high numerical aperture objective mounted in an inverted microscope frame just below the stage brought excitation radiation through the coverslip window and to a tight focus a few micrometers above the ITO film surface. Species diffusing into the confocal probe volume defined by the excitation beam focus and the collected light region were detected, identified and quantified based on their Raman scattering frequencies and intensities. Here, in measurements that interrogated the interconversion of ferrocyanide and ferricyanide ions as a function of applied voltage, least-squares regression analysis of spectral datasets predicted the formal potential and relative surface concentrations of the ions in good agreement with the expected Nernstian response. Preliminary studies of methyl viologen reduction at an ITO film/Nafion membrane interface were conducted and show the possibility for estimation of mass transport coefficients of redox species within ionic polymer materials.

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

Suppression of Helium Induced Cracking in Laser Repair Welding of Highly Irradiated Stainless Steels

Welding repair of irradiated nuclear reactor materials such as austenitic stainless steels used for the reactor internals has been challenging due to irradiation generated helium in the material matrix over an extended period of time. In this study, improved laser welding techniques, including the novel Auxiliary Beam Stress Improved (ABSI) technique that proactively manages the stresses during laser repair welding is investigated to substantially reduce or avoid the occurrence of intergranular helium-induced cracking (HeIC). Here, laser weld cladding, with and without ABSI technique, was applied to deposit weld metal on irradiated stainless steel (Type 304 L) blocks with various helium concentrations up to approximately 20 atomic parts per million (appm). Welded samples were cross-sectioned and analyzed using optical and electron microscopes. It was found that, with the improved laser welding techniques, no macroscopic (millimeter-sized) cracks were observed in any of the samples. Microscopic (less than 50 μm) cracks were present in the heat affected zone. Statistical analysis on the sample with the highest helium concentration (~20 appm) reveals that the ABSI technique could effectively reduce the size and amounts of microscopic cracks.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Investigating microstructural evolution in SolidStir™ extruded oxide dispersion strengthened 14YWT alloy fuel cladding tube

Structural components for extreme environments require advanced materials and manufacturing processes. One such advanced material is oxide dispersion strengthened (ODS) Fe–14 wt.%Cr–3W–0.4Ti–0.3Y 2 O 3 (14YWT), which is developed for components to be used in Gen IV and fusion nuclear reactors. However, the conventional manufacturing processes to produce components, such as fuel cladding tubes, either do not retain the desired microstructural attributes or are costly and less efficient. As a result, a more attractive option is a novel manufacturing process developed on the principle of friction stir welding or processing (FSW/P) and commercially referred to as SolidStir™ Extrusion (SSE). Here this study used the SSE technique to study the manufacturing and microstructural evolution of a fuel cladding tube made of ODS 14YWT alloy. The cladding extrusion by the SSE technique involved the use of ball-milled 14YWT powders with Y, Ti, and O in the solid solution and the use of a specially designed W-25Re-Hf tool for consolidation and extrusion of the powders. A scanning electron microscope (SEM), electron backscattered diffraction (EBSD), and transmission electron microscope (TEM) were utilized for microstructural characterization. A Keyence microscope captured macrostructural photographs of the extruded tube. EBSD examination of the extruded tube on both transverse and longitudinal cross-sections showed the presence of dynamically recrystallized grains and revealed that the average grain size of the transverse cross-section was smaller than that of the longitudinal cross-section. The texture was weak and consisted of some amount of shear texture. The presence of nano-oxide clusters or precipitates of Y, Ti, and O (pyrochlores) in the extruded tube was determined by TEM. Aging heat treatment caused the average precipitate size to decrease and the density to increase compared to the as-processed condition. The results indicated that SSE is a viable tool for manufacturing fuel cladding tubes with the desired microstructural attributes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
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 OSTI2021

Development of a Reference Database for Beta-Delayed Neutron Emission

Beta-delayed neutron emission is important for nuclear structure and astrophysics as well as for reactor applications. Significant advances in nuclear experimental techniques in the past two decades have led to a wealth of new measurements that remain to be incorporated in the databases. In this work, we report on a coordinated effort to compile and evaluate all the available β-delayed neutron emission data. The different measurement techniques have been assessed and the data have been compared with semi-microscopic and microscopic-macroscopic models. The new microscopic database has been tested against aggregate total delayed neutron yields, time-dependent group parameters in 6-and 8-group re-presentation, and aggregate delayed neutron spectra. New recommendations of macroscopic delayed-neutron data for fissile materials of interest to applications are also presented. The new Reference Database for Beta-Delayed Neutron Emission Data is available online.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Hybrid electric buses fuel consumption prediction based on real-world driving data

Estimating fuel consumption by hybrid diesel buses is challenging due to its diversified operations and driving cycles. Here, long-term transit bus monitoring data were utilized to empirically compare fuel consumption of diesel and hybrid buses under various driving conditions. Artificial neural network (ANN) based high-fidelity microscopic (1 Hz) and mesoscopic (5–60 min) fuel consumption models were developed for hybrid buses. The microscopic model contained 1 Hz driving, grade, and environment variables. The mesoscopic model aggregated 1 Hz data into 5 to 60-minute traffic pattern factors and predicted average fuel consumption over its duration. The prediction results show mean absolute percentage errors of 1–2% for microscopic models and 5–8% for mesoscopic models. The data were partitioned by different driving speeds, vehicle engine demand, and road grade to investigate their impacts on prediction performance.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Advanced Characterization of Fuel-cladding Chemical Interaction between U-10Zr Fuel and HT9 Cladding Tested in Fast Flux Test Facility

Fuel cladding chemical interaction (FCCI) can greatly accelerate the cladding failure. However, due to the limited space in a fuel cladding assembly, it is historically challenging to gain an mechanistical understanding of the formation mechanism of FCCI and its influence on fuel and cladding performance. With the imminent need to qualify U-10Zr based metallic fuel cladded by HT-9 for advanced reactors demonstration project, it is of vital importance to use advanced characterization method to study FCCI in a unprecedent detailed manner and gain better mechanism understanding of FCCI. Mechanistic Fuel Failure (MFF) series of prototypic fuel elements irradiated in FFTF [1, 2] provides the best samples to study FCCI since the MFF-series assemblies had an axial fuel height the same as proposed length by industry partners. Jason et al. [3] has performed preliminary post-irradiation examination on a MFF fuel pin sample, which was extracted from the HT9 cladded U-10at.%Zr MFF-3 pin MFF-3 pin (#193045) at an axial location of X/L = 0.98. This sample has a peak burnup of 5.7 at.% and peak inner cladding temperature (PICT) of around 615 °C during in-core testing. Scanning electron microscope examination has identified visible FCCI region on more than half of the HT9 circumference [3]. The most striking feature are grain boundary attacking by apparently lanthanides (Lns) rich phase. However, SEM cannot provide accurate assessment of phase and concentration of grain boundary phases and prevented a better understanding of the formation mechanism of such attach. This study, by pairing transmission electron microscope (TEM) characterization and atom probe tomography (APT) techniques with in-situ micro-tensile testing in scanning electron microscope (SEM), aims at gaining in-depth understanding on the formed FCCI region. The identified FCCI region roughly consists of multilayers as illustrated in Figure 1 (c). The main findings are: (1) layer-B shows observable lanthanides (Lns) infiltration along grain boundaries and mechanical softening due to FCCI- and irradiation-induced microstructural and microchemistry changes, particularly the recovery of martensitic lath structure and dissolution of pre-existing M23C6 together with the formation of coarsened Laves phases, (Fe, Cr)2(Mo, W); (2) layer-C is Fe depleted but Lns significantly enriched, becoming very brittle; (3) layer-D is mainly composed of UFe2 and Lns; (4) three FCCI-induced intermetallic U-Fe-Zr phases, ? (Fe0.5Zr0.32U0.18), e (Fe0.3Zr0.4U0.3), ? (Fe0.06Zr0.23U0.71), were identified near layer-E; (5) the ? (Fe0.5Zr0.32U0.18) phase was characterized to be a face centered cubic (FCC) crystal structure. These results will help to better understanding the governing mechanism of FCCI and facilitating the development of theoretical model for assessing the performance of metallic fuel and cladding integrity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Nonlocal Effect of Percolated Particle Networks on Viscoelasticity of Polymer–Filler Nanocomposites: A Mesoscale Simulation Study

With nanoparticles (NPs) as fillers, polymer nanocomposites (PNCs) usually exhibit enhanced mechanical properties. However, a direct connection between the microscopic structural relaxation and macroscopic mechanical properties of PNCs remains to be established. To investigate the micro-to-macro connection, we develop a mesoscale model, in which the NPbridging polymer chains are represented by a dynamic bonded interaction between NPs, and the bulk polymer matrix is implicitly modeled by overdamped Langevin dynamics. Extensive equilibrium simulations are performed to quantify the microscopic dynamics of model PNCs. Systematic analyses of modified Rouse dynamics, dynamic structure factor, and relaxation modulus uncover that the microscopic relaxation dynamics of PNCs are significantly decelerated across different length scales because of nonlocal effects of percolated particle networks a phenomenon that has not been adequately captured in prior simulation studies. We find that NPvolume- fraction and NP-bonding-energy barrier are the two critical variables that affect bulk viscoelasticity the most. The proposed mesoscale model is versatile and provides a powerful framework for studying structure−property relations of different PNCs.

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

Deep generative learning of magnetic frustration in artificial spin ice from magnetic force microscopy images

Increasingly large datasets of microscopic images with nanoscale resolution facilitate the development of machine learning methods to identify and analyze subtle physical phenomena embedded within the images. In this work, microscopic images of honeycomb lattice spin-ice samples serve as datasets from which we automate the calculation of net magnetic moments and directional orientations of spin-ice configurations. In the first stage of our workflow, machine learning models are trained to accurately predict magnetic moments and directions within spin-ice structures. Variational Autoencoders (VAEs), an emergent unsupervised deep learning technique, are employed to generate high-quality synthetic magnetic force microscopy (MFM) images and extract latent feature representations, thereby reducing experimental and segmentation errors. The second stage of proposed methodology enables precise identification and prediction of frustrated vertices and nanomagnetic segments, effectively correlating structural and functional aspects of microscopic images. This facilitates the design of optimized spin-ice configurations with controlled frustration patterns, enabling potential on-demand synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optomechanical self-organization in a mesoscopic atom array

Increasing the number of particles in a system often leads to qualitative changes in its properties, such as breaking of symmetries and the appearance of phase transitions. This renders a macroscopic system fundamentally different from its individual microscopic constituents. Lying between these extremes, mesoscopic systems exhibit microscopic fluctuations that influence behaviour on longer length scales, leading to critical phenomena and dynamics. Therefore, tracing the properties of well-controlled mesoscopic systems can help bridge the gap between an exact description of few-body microscopic systems and the emergent description of many-body systems. Here we explore the mesoscopic signatures of an optomechanical self-organization phase transition using arrays of cold atoms inside an optical cavity. By precisely engineering atom–cavity interactions, we reveal how critical behaviour depends on the atom number, identify characteristic dynamical behaviours in the self-organized regime and observe a finite optomechanical susceptibility at the critical point. These findings advance our understanding of particle-number- and time-resolved properties of phase transitions in mesoscopic systems.

Atomic and molecular interactions with photons↗
DOE OSTI2020

$${\mathcal{P}}{\mathcal{T}}$$-Symmetric Effective Model for Nonequilibrium Phase Transitions in a Dissipative Fermionic Mott Insulator Chain

Nonequilibrium phase transitions in open dissipative systems can be described as instabilities in the spectra and wavefunctions of effective non-Hermitian Hamiltonians invariant under simultaneous parity (P) and time-reversal (T) transformations. The degree of non-Hermiticity reflects the strength of the external drive and dissipation, and the transition is described as a loss of the PT symmetry of the solutions corresponding to stationary low-drive dynamics. This approach has been successfully applied to spin, superconducting, and Mott insulator systems. However, the microscopic foundations for the employed phenomenological models are currently lacking. Here we propose a microscopic mechanism leading to the PT-symmetric effective model in the context of the nonequilibrium Mott transition in a dissipative Hubbard chain. Our model comprises a half-filled fermionic Hubbard chain subject to a constant electric field. The dissipation is introduced via the electron-phonon coupling. We obtain the explicit expressions for the non-Hermitian parameter in terms of the electron-phonon coupling strength and driving field. Analyzing the implications of microscopic model, we find a re-entrant Mott insulator with the increasing electric field for phonon density of states that increases slower than the square of the energy (such as in one or two dimensions), or varies non-monotonously with energy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Spatially co-registered wide-field nonlinear optical imaging of living and complex biosystems in a total internal reflection geometry

Nonlinear optical microscopy that leverages an objective based total internal reflection (TIR) excitation scheme is an attractive means for rapid, wide-field imaging with enhanced surface sensitivity. Through select combinations of distinct modalities, one can, in principle, access complementary chemical and structural information for various chemical species near interfaces. Here, we report a successful implementation of such a wide-field nonlinear optical microscope system, which combines coherent anti-Stokes Raman scattering (CARS), two-photon fluorescence (TPF), second harmonic generation (SHG), and sum frequency generation (SFG) modalities on the same platform. The intense optical fields needed to drive these high order nonlinear optical processes are achieved through the use of femtosecond pulsed light in combination with the intrinsic field confinement induced by TIR over a large field of view. The performance of our multimodal microscope was first assessed through the experimental determination of its chemical fidelity, intensity and polarization dependences, and spatial resolution using a set of well-defined model systems. Subsequently, its unique capabilities were validated through imaging complex biological systems, including Hydrangea quercifolia pollen grains and Pantoea sp. YR343 bacterial cells. Specifically, the spatial distribution of different molecular groups in the former was visualized via vibrational contrast mechanisms of CARS, whereas co-registered TPF imaging allowed the identification of spatially localized intrinsic fluorophores. We further demonstrate the feasibility of our microscope for wide-field CARS imaging on live cells through independent characterization of cell viability using spatially co-registered TPF imaging. Overall, this approach to TIR enabled wide-field imaging is expected to provide new insights into bacterial strains and their interactions with other species in the rhizosphere in a time-resolved and chemically selective manner.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Probing growth of metal–organic frameworks with X-ray scattering and vibrational spectroscopy

Nucleation and crystallization arising from liquid to solid phase are involved in a multitude of processes in fields ranging from materials science to biology. Controlling the thermodynamics and kinetics of growth is advantageous to help tune the formation of complex morphologies. In this report, we harness wide-angle X-ray scattering and vibrational spectroscopy to elucidate the mechanism for crystallization and growth of the metal–organic framework Co-MOF-74 within microscopic volumes enclosed in a capillary and an attenuated total reflection microchip reactor. The experiments reveal molecular and structural details of the growth processes, while the results of plane wave density functional calculations allow identification of lattice and linker modes in the formed crystals. Synthesis of the metal–organic framework with microscopic volumes leads to monodisperse and micron-sized crystals, in contrast to those typically observed under bulk reaction conditions. Reduction in the volume of reagents within the microchip reactor was found to accelerate the reaction rate. The coupling of spectroscopy with scattering to probe reactions in microscopic volumes promises to be a useful tool in the synthetic chemist's kit to understand chemical bonding and has potential in designing complex materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Control over emergence and alignment of transient blisters in thermo-responsive gels using hierarchically patterned substrates

Surfaces with tunable microscale textures are vital in a large variety of technological applications, including heat transfer, antifouling and adhesion. To facilitate such broad-scale use, there is a need to create surfaces that undergo reconfigurable changes in topology and thus, enable switchable functionality. To date, there is a relative dearth of methods for engineering surfaces that can be actuated to change topography over a range of length scales, and hence, form tunable hierarchically structured layers. Combining modeling and experiments, we design a geometrically patterned, thermo-responsive poly (N-isopropylacrylamide) gel film that undergoes controllable hierarchical changes in topology with changes in temperature. At the bottom, the film is covalently bound to a solid, curved substrate; at the top, the film encompasses longitudinal rectangular ridges that are oriented perpendicular to the underlying cylindrical curves. At temperatures below lower critical solution temperature (LCST), the swollen gel exhibits 3D variations in polymer density and thickness defined by the gel's top and bottom topography. As the temperature rises above LCST, the interplay between the upper ridges and lower curves in the gel drives non-uniform, directional solvent transport, the nucleation and propagation of a phase-separated higher-density skin layer, and the resulting pressure buildup within the film. These different, interacting kinetic processes lead to an instability, which produces transient microscopic blisters in the film. Through simulations, we show how tuning the width of the ridges modifies the propagation of a skin layer and creates localized pressure build-up points, which enables control over the emergence, distribution, and alignment of the microscopic blisters. Futhermore, we provide a simple argument to predict the size of such microscopic features. Experiments confirm our predictions and further highlight how our computational model enables the rational design of topographical transitions in these tunable films. The development of actuatable, hierarchically structured films provides new routes for achieving switchable functionality in actuators, drug release systems and adhesives.

42 ENGINEERING↗
DOE OSTI2025

Ultracold cryogenic TEM with liquid helium and high stability

Cryogenic transmission electron microscopy has revolutionized structural biology and materials science. To image below liquid nitrogen temperatures, various liquid helium stages have been constructed but have proven to be complex and unstable, making high-resolution imaging challenging. This problem is even more pronounced in side-entry specimen holders common on modern transmission electron microscopes. Here, we introduce an ultracold liquid helium transmission electron microscope side-entry specimen holder, featuring continuous cryogen flow and vibration decoupling. This instrument is compatible with modern aberration-corrected microscopes and achieves sub-25 K base temperature, ±2 mK thermal stability over many hours, and atomic resolution—setting the stage for a new era of cryogenic electron microscopy.

42 ENGINEERING↗
DOE OSTI2020

Gibbs mixing of partially distinguishable photons with a polarising beamsplitter membrane

For a thought experiment concerning the mixing of two classical gases, Gibbs concluded that the work that can be extracted from mixing is determined by whether or not the gases can be distinguished by a semi-permeable membrane; that is, the mixing work is a discontinuous function of how similar the gases are. Here we describe an optomechanical setup that generalises Gibbs’ thought experiment to partially distinguishable quantum gases. Specifically, we model the interaction between a polarisation dependent beamsplitter, that plays the role of a semi-permeable membrane, and two photon gases of non-orthogonal polarisation. We find that the work arising from the mixing of the gases is related to the potential energy associated with the displacement of the microscopic membrane, and we derive a general quantum mixing work expression, valid for any two photon gases with the same number distribution. The quantum mixing work is found to change continuously with the distinguishability of the two polarised gases. In addition, fluctuations of the work on the microscopic membrane become important, which we calculate for Fock and thermal states of the photon gases. Our findings generalise Gibbs’ mixing to the quantum regime and open the door for new quantum thermodynamic (thought) experiments with quantum gases with non-orthogonal polarisations and microscopic pistons that can distinguish orthogonal polarisations.

distinguishability↗
DOE OSTI2025

Mic-hackathon 2024: hackathon on machine learning for electron and scanning probe microscopy

Microscopy is one of the primary sources of information on materials structure and functionality at the nanometer and atomic scales. The data generated through microscopy is often contained in well-structured datasets, enriched with extensive metadata and sample histories, although not always with the same level of detail or storage format. The broad incorporation of data management plans by major funding agencies ensures the preservation and accessibility of this data. However, deriving insights from these rich datasets remains challenging due to the lack of established code ecosystems, standardized benchmarks, and integration strategies. Correspondingly, the efficiency of data usage is very low, and time expenditures at the analysis stage are enormous. In addition to post-acquisition data analysis, the emergence of application programming interfaces by major microscope manufacturers now creates opportunities for real-time ML-based data analytics to enable automated decision making, and particularly ML-agent controlled real-time microscope operation. Despite these opportunities, there is a significant gap in integrating the ML community with the broader microscopy community, limiting the value that these methods bring to physics and materials discovery and materials optimization. Hackathons address these challenges by fostering collaboration between ML experts and microscopy professionals, encouraging the development of innovative solutions that leverage ML for microscopy and preparing the workforce of the future both for microscopy-intensive domains areas, instrument manufacturers, and ML scientists interested in real world applications for fundamental research, materials optimization, and manufacturing. The hackathon generated benchmark datasets and digital twins of microscopes that further contribute to the development of the field and establish data analysis ecosystems. All the codes can be found at GitHub(https://github.com/KalininGroup/Mic-hackathon-2024-codes-publication/tree/1.0.0.1) and Zenodo (https://zenodo.org/records/15579940).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Enabling the Acquisition of Electron Beam-Induced Current (EBIC) Images in Conventional SEM and STEM Instruments

Electron beam-induced current (EBIC) imaging is a well-established scanning electron microscope (SEM) technique used to analyze the behavior of microelectronic devices including solar cells. Recently, the application of EBIC imaging in an aberration-corrected scanning transmission electron microscope (STEM) has been demonstrated and offers great potential for the in situ study of electronic materials, correlating charge transport properties to atomic structural and elemental information. Here, this work presents two ways to implement EBIC imaging in conventional SEM and STEM systems: one relying on the instrument's inherent scanning and imaging electronics and the other involving third-party systems usually available in electron microscopes. The implementation of lock-in EBIC in systems equipped with a fast beam blanker is also described. In addition, this work shows and discusses the different mechanisms at play in EBIC imaging and their dependence on beam energy, sample impedance, and electrical measurement configuration, providing researchers with the basic information needed to apply the technique to their research.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗