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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 415 records · Page 23

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↗

Atomic force microscopy monitoring of subcritical slow crack growth in soda lime silicate glass

Prediction of brittle fracture in silicate glasses requires a fundamental understanding of slow crack growth rates, far below the critical stress intensity (K IC ) of the material. Here, in this study, atomic force microscopy (AFM) was used to characterize slow crack propagation in soda lime silicate glasses. Using large-sample AFM systems with specialized tips and scanners, fractures less than 20 nm wide were measured as a function of relative humidity (RH). The results were found to be sensitive to the type of AFM tip used and to the dryness of the surface. Continuous scanning and image capture over several days allowed the determination of the crack tip velocity. The dependance of crack tip velocity on RH was measured by enclosing the sample and AFM head in a humidity-controlled chamber. The crack tip velocity was measured as low 4.0×10 -12 m/s at 15 % RH and as high as 3.7×10 -10 m/s at 40 % RH. Overall crack growth was smooth during the AFM scan. Additionally, recession of the crack tip was noted as the sample dried, indicating crack tip closure may be occurring. Further studies on alternative compositions will provide details on subcritical fracture processes in a range of different environmental conditions.

Atomic force microscopy↗

Transmission electron microscopy investigation of phase transformation and fuel constituent redistribution in neutron irradiated U-10wt.%Zr fuel

Uranium-10wt.%zirconium (U-10wt.%Zr) is a primary candidate for fast reactor nuclear fuels. However, there is a lack of data characterizing neutron irradiated crystallographic phases and chemistry. In the current study, the microstructural evolution of a U-10wt.%Zr fuel neutron irradiated to a burnup of 5.7 at.% was investigated by scanning transmission electron microscopy, energy dispersive spectroscopy, and selected area electron diffraction to determine the major phases, alterations in microstructure, and variations in local chemical composition at different localities of a fuel cross-section. The current study revealed that the irradiated U-10wt.%Zr fuel was comprised of various major phases, including a-U, ß-U, and d-UZr2, as well as amorphous and crystalline solid fission product (FP) precipitates within different regions of the fuel cross-section. Regions A and A/B in the center of the fuel were comprised of U-rich, U-intermediate, and U-lean localities with a-U and d-UZr 2 composing the major phases. Regions B and C in the intermediate and peripheral fuel localities, respectively, were comprised of a-U grains, U-rich (ß-U) grains with Zr-rich precipitates, U-intermediate grains (d-UZr2), and solid FP precipitates. The major phases identified were associated with the nanoscopic chemical concentrations, the phase diagram, and the as-characterized specimen temperature, with the exception of the non-equilibrium ß-U phase identified in region B. The U-lean localities in regions A, A/B, B, and C were Zr-enriched pathways along subgrain/grain boundaries. This phenomenon suggests that Zr is susceptible to radiation-induced segregation in U-Zr fuels and indicates a new mechanism for constituent redistribution.

36 MATERIALS SCIENCE↗

Transmission Electron Microscopy Characterization of Fuel Cladding Chemical Interaction between Minor Actinides bearing U-Pu-Zr Fuel and AIM1 Cladding

Minor actinides (MA) significantly contribute to the long-term radiotoxicity of spent nuclear fuel (SNF). Separating MA from SNF and incorporating it into metallic fuels for fast reactor transmutation is a potential method to reduce this radiotoxicity. Here, this study focuses on transmission electron microscopy characterization of two samples from the fuel cladding chemical interaction (FCCI) region of an americium (Am) and neptunium (Np)-bearing (MA-bearing) uranium-plutonium-zirconium (U-Pu-Zr) fuel irradiated in the Phenix fast reactor to 9.5 % FIMA burnup at approximately 550 °C cladding temperature. The results show that despite the complex chemical interactions between MA and AIM1 cladding elements, excessive FCCI was not induced, and Am penetration depth in the cladding limited to less than 4 µm. Np remained mostly inside fuel. The Zr-rich compounds layer effectively limited the accumulation of lanthanide on the inner cladding surface. Overall, the FCCI behavior between investigated MA-bearing U-Pu-Zr fuel and AIM1 cladding is benign.

Chemical interaction↗

An algorithm for resolving intragranular orientation fields using coupled far-field and near-field high energy $\mathrm{X}$-ray diffraction microscopy

Here, we present a novel algorithm for reconstructing spatial intragranular lattice orientation fields using both far-field and near-field high energy X-ray diffraction microscopy (HEDM) measurements. An established far-field indexing algorithm is modified to include lattice orientation distribution information (grain orientation envelopes) in addition to average grain orientations. The near-field data reduction algorithm utilizes this enriched far-field orientation data as a seed for reconstructing intragranular spatial maps of lattice orientation from the diffraction images. The primary benefit of the new algorithm is a significant decrease in the number of trial calculations that must be performed in the reconstruction process compared to existing methodologies while maintaining scalability. The resulting gains in efficiency facilitate the use of relatively modest computational resources and improve throughput at the point of measurement. We provide two example applications: volumetric orientation field reconstructions for a Ti-Al alloy both before and after the application of 3% uniaxial strain. The results showcase the efficiency of the new method and the ability to resolve subtle changes in microstructure, which are associated with incipient plastic deformation.

36 MATERIALS SCIENCE↗

Super-resolution model for overlapping peak detection and improved spatial resolution in high-energy diffraction microscopy

Reconstruction quality in Far-field High-Energy Diffraction Microscopy (FF-HEDM) is limited by the spatial resolution of area detectors and the frequent occurrence of overlapping diffraction spots. To address these challenges, we developed a super-resolution (SR) framework using convolutional neural networks (CNNs) to recreate 2D diffraction peaks at up to ×8 resolution from raw detector data. A specialized simulation tool was created to generate synthetic training datasets with varying degrees of peak overlap. Integrated into the Microstructural Imaging using Diffraction Analysis Software (MIDAS), the SR model improves the spatial accuracy and precision of 3D grain reconstruction by an order of magnitude. This approach provides a robust solution for investigation of complex micromechanical states and material classes where the analysis is limited by the presence of overlapping peaks. Furthermore, the methodology developed here can potentially be extended to other techniques that require sub-pixel accuracy for high-fidelity data analysis.

High-energy diffraction microscopy↗

Persistent hot carrier diffusion in boron arsenide single crystals imaged by ultrafast electron microscopy

Cubic boron arsenide (BAs) is promising for microelectronics thermal management because of its high thermal conductivity. Recently, its potential as an optoelectronic material is also being explored. However, it remains challenging to measure its photocarrier transport properties because of small sizes of available high-quality crystals. Here, we use scanning ultrafast electron microscopy (SUEM) to directly visualize the diffusion of photocarriers in BAs single crystals. Surprisingly, we observed ambipolar diffusion at low optical fluence with persistent hot carrier dynamics for above 200 ps, which can likely be attributed to the large frequency gap between acoustic and optical phonons, the same feature that is responsible for the high thermal conductivity. At higher optical fluence, we observed spontaneous electron-hole separation. Our results show BAs is an attractive optoelectronic material combining high thermal conductivity and excellent photocarrier transport properties. Finally, our study also demonstrates the capability of SUEM to probe photocarrier transport in emerging materials.

36 MATERIALS SCIENCE↗

An artificial intelligence’s interpretation of complex high-resolution in situ transmission electron microscopy data

Complicated nano- and atomic-scale processes with sub-angstrom spatial resolution and millisecond time resolution visualized by in situ transmission electron microscopy (TEM) are often highly dynamical and time consuming to analyze and interpret. Here, we report how variational autoencoders (VAEs) can provide an artificial intelligence’s interpretation of high-resolution in situ TEM data by condensing and deconvoluting complicated atomic-scale dynamics into a latent space with reduced dimensionality. We designed a VAE model with high latent dimensions capable of deconvoluting information from complex high-resolution TEM data. We demonstrate how this model, with high latent dimensions trained on atomically resolved TEM images of lead sulfide (PbS) nanocrystals, is able to capture movements and perturbations of periodic lattices in both simulated and real in situ TEM data. Importantly, the VAE model shows the capability of detecting and deconvoluting dynamical nanoscale physical processes, such as the rotation of crystal lattices and intra-particle ripening during the annealing of semiconductor nanocrystals.

47 OTHER INSTRUMENTATION↗

A machine-learning approach to measure 3D sample properties from 2D Transmission Electron Microscopy images

Transmission Electron Microscopy (TEM) is a powerful tool for the characterization of materials at the nanoscale; however, its inherent two-dimensional (2D) nature poses significant challenges to accurately measure three-dimensional (3D) properties. We introduce a supervised machine-learning model that predicts 3D structural information, such as sample thickness and curvature, from a series of conventional 2D TEM images. The model, a U-Net convolutional neural network, is trained on a large synthetic dataset generated from dynamical diffraction simulations that model TEM’s complex, nonlinear image formation, accounting for sample thickness and curvature. This physically realistic framework enables exploration of a broad parameter space impractical to sample experimentally. We demonstrate that the trained model has accurate predictions for experimental single-crystal silicon samples, achieving performance comparable to established measurement techniques. This work highlights the critical role of robust, simulation-based training in overcoming the limitations of real-world imaging artifacts and inconsistent sample geometries. By integrating machine learning with numerical simulations, we offer an efficient and scalable framework for quantitative TEM analysis, paving the way for more sophisticated 3D characterization of complex materials.

Dynamical diffraction↗

Biofouling of filtration membranes in wastewater reuse: In situ visualization with confocal laser scanning microscopy

The filtration membranes utilized in advanced treatment of municipal wastewater are prone to biological fouling. Permeability loss and water recovery limitations due to fouling necessitate additional pretreatment and membrane cleaning, which raise the cost of water reuse. Better fouling mitigation calls for a deeper understanding of biofilm behavior on water reuse membranes. This study uses confocal microscopy to monitor biofouling under realistic conditions. To simulate water reuse, a miniature flow cell with microfiltration and ultrafiltration membranes was operated under typical filtration conditions using secondary effluent from California's East Bay Municipal Utility District. The growing biofilms were stained for extracellular polymeric substances and live and dead cells, and they were monitored in situ under filtration conditions with a confocal laser scanning microscope to produce 2-D and 3-D images. In situ image series revealed biofilm growth and removal processes including internal and external fouling, extracellular polymeric substance production, wrinkling, delamination, and film re-deposition. Additionally, changes in biofilm morphology between in situ and ex situ images highlighted limitations of ex situ imaging. Here, these results provide insight into the physical and biological mechanisms of biofouling in hopes of informing the development of improved techniques for biofouling mitigation.

ultrafiltration↗

Measurement of G-phase volume fraction and number density in duplex stainless steels using transmission electron microscopy

Duplex stainless steels (DSS) have a high toughness and strength due the presence of both austenitic and ferritic phases. These alloys have had limited use in power production applications due to thermal embrittlement caused by spinodal decomposition and development of G-phase precipitates in the ferrite. Lean grade DSS alloys (e.g., 2101, 2003) may offer improved thermal stability due to the reduction of Cr- and Ni-equivalent elements when compared to standard grade compositions (e.g., 2205, 2209). The abundance of the G-phase was measured in five duplex stainless steels, three wrought alloys (2101, 2003, 2205) and their matching filler metals (2101-w, 2209-w), after aging at 427 °C for 1000 h and 10,000 h. The G-phase volume fraction, number density, size, and precipitate spacing were found using quantitative analysis of transmission electron microscopy dark field images and the composition of G-phase precipitates on other clusters were characterized with atom probe tomography (APT). In the welded alloys, the G-phase was found to develop rapidly, relative to the wrought material. A positive correlation was found between the nickel equivalent composition of the alloy and the G-phase volume fraction. The alloys 2205, 2209, and 2101-w, which are higher in Cr and Ni, all showed significant G-phase precipitation, further strengthening the hypothesis that lean grade DSS alloys are more thermally stable against precipitation in the ferrite. Electron diffraction showed a secondary phase present in the 2101 wrought alloy at 10,000 h, but it was not crystallographically consistent with the G-phase; APT showed the presence of nanoclusters rich in both nickel and copper for this alloy. In conclusion, no secondary phases or clusters were found in 2003 after 10,000 h of aging, so it may be a candidate alloy for applications that require long-life times at high operating temperatures.

36 MATERIALS SCIENCE↗

Lithium metal stripping mechanisms revealed through electrochemical liquid cell electron microscopy

An understanding of lithium stripping is as important as that of lithium plating to achieve significant advances in using lithium metal anodes for high-energy rechargeable batteries. However, there have been limited studies on lithium stripping compared to lithium plating. Here we report the lithium stripping mechanisms revealed through in-situ electrochemical liquid cell transmission electron microscopy (TEM). We directly observe and compare the stripping behavior of the in-situ grown lithium dendrites and lithium nanograins covered by a lithium fluoride-rich solid-electrolyte interphase (SEI). Furthermore, we find the sporadic lithium stripping behavior and three important modes that can describe the stripping of individual lithium deposits, regardless of their morphology: (i) symmetric stripping, (ii) surface-preferred asymmetric stripping, and (iii) interface-preferred asymmetric stripping. In addition, SEI chemical mapping with high spatial resolution shows a remarkable SEI loss at the end of the lithium metal stripping, which illustrates the importance of SEI protection in the subsequent cycles.

25 ENERGY STORAGE↗

YOLO2U-Net: Detection-guided 3D instance segmentation for microscopy

Microscopy imaging techniques are instrumental for characterization and analysis of biological structures. As these techniques typically render 3D visualization of cells by stacking 2D projections, issues such as out-of-plane excitation and low resolution in the z-axis may pose challenges (even for human experts) to detect individual cells in 3D volumes as these non-overlapping cells may appear as overlapping. In this paper a comprehensive method for accurate 3D instance segmentation of cells in the brain tissue is introduced. The proposed method combines the 2D YOLO detection method with a multi-view fusion algorithm to construct a 3D localization of the cells. Next, the 3D bounding boxes along with the data volume are input to a 3D U-Net network that is designed to segment the primary cell in each 3D bounding box, and in turn, to carry out instance segmentation of cells in the entire volume. The promising performance of the proposed method is shown in comparison with current deep learning-based 3D instance segmentation methods.

3D instance segmentation↗

Explainability and human intervention in autonomous scanning probe microscopy

The broad adoption of machine learning (ML)-based autonomous experiments (AEs) in material characterization and synthesis requires strategies development for understanding and intervention in the experimental workflow. Here, we introduce and realize a post-experimental analysis strategy for deep kernel learning-based autonomous scanning probe microscopy. This approach yields real-time and post-experimental indicators for the progression of an active learning process interacting with an experimental system. We further illustrate how this approach can be applied to human-in-the-loop AEs, where human operators make high-level decisions at high latencies setting the policies for AEs, and the ML algorithm performs low-level, fast decisions. The proposed approach is universal and can be extended to other techniques and applications such as combinatorial library analysis.

47 OTHER INSTRUMENTATION↗

Characterization of Polyamide Thin Films by Atomic Force Microscopy

This study directly compares the mechanical behavior of novel molecular layer deposition (MLD) and analogous interfacial polymerization (IP) polyamide thin films in environments relevant to reverse osmosis (RO) membrane operation. The elastic modulus of the films was determined using atomic force microscopy (AFM) in dry, hydrated, and chlorinated states. Surface roughness characteristics were also obtained given their potential influence on AFM modulus measurements. The much smoother MLD films demonstrated a statistically higher modulus in all states as compared to their IP counterparts. The MLD films maintained a modulus ~3X and ~5X greater than that of IP films after hydration and chlorination, respectively. Such differences in behavior may be due to the higher density and correspondingly lower void content of the MLD films. Results from this study provide a rationale for future development of MLD for fabrication of polyamide films for incorporation in RO membranes.

atomic force microscopy↗

Optical super-resolution microscopy in polymer science

The advent of optical super-resolution microscopy (OSRM) over two decades ago has transformed light-mediated interrogation of systems down to the nanoscale. This innovative set of approaches to optics breaks the so-called diffraction limit of light (~200 nm), allowing for the first time to use optics in the far field to visualize behavior on nanoscopic length scales. While these visualization tools have rapidly found widespread use in biology and related fields, their implementation in materials and, more specifically, in polymer science has been far slower. To overcome possible barriers and highlight possible future directions, we present in this paper an introduction to OSRM for polymer scientists, beginning with an overview of relevant techniques and existing optical probes. We then show and examine the first examples of OSRM adaptation across major areas of polymer science, including: polymerization and structural characterization, self-assembly and solution behavior, bulk structure and behavior, crystallization, gel structure and behavior, phase transitions, and biofunctionality. We hope and anticipate that the discussions provided in this review will draw the attention of the polymer community to the capacities of these hitherto underexplored optical visualization techniques to further transform polymer science.

36 MATERIALS SCIENCE↗

Squeezing Noise in Microscopy with Quantum Light

Quantum-enhanced microscopes capable of probing classically inaccessible material properties have drawn increasing interest, but most proof-of-principle quantum microscopes have not surpassed classical limits. Here, we discuss the promise and obstacles associated with the use of quantum light with reduced noise (‘squeezed’ light) for quantum-enhanced atomic force microscopy, bioimaging, magneto-optical measurements, and Raman spectroscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗