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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 721 records · Page 40

Quantitative Analysis of Charge Injection and Discharging of Si Nanocrystals and Arrays by Electrostatic Force Microscopy

NASA requirements for computing and memory for microspacecraft emphasize high density, low power, small size, and radiation hardness. The distributed nature of storage elements in nanocrystal floating-gate memories leads to intrinsic fault tolerance and radiation hardness. Conventional floating-gate non-volatile memories are more susceptible to radiation damage. Nanocrystal-based memories also offer the possibility of faster, lower power operation. In the pursuit of filling these requirements, the following tasks have been accomplished: (1) Si nanocrystal charging has been accomplished with conducting-tip AFM; (2) Both individual nanocrystals on an oxide surface and nanocrystals formed by implantation have been charged; (3) Discharging is consistent with tunneling through a field-lowered oxide barrier; (4) Modeling of the response of the AFM to trapped charge has allowed estimation of the quantity of trapped charge; and (5) Initial attempts to fabricate competitive nanocrystal non-volatile memories have been extremely successful.

Bell, L. D.↗

Quantitative analysis of charge injection and discharging of Si nanocrystals and arrays by electrostatic force microscopy

NASA requirements for computing and memory for microspacecraft emphasizes high density, low power, small size, and radiation hardness. The distributed nature of a storage elements in nanocrystal floating-gate memories leads to instrinsic fault tolerance and radiation-hardness. Nanocrystal-based memories also offer the possibility of a faster, lower power operation.

atomic↗

Impact of metal diffusion, lattice distortions, native defects, and ambient on dielectric breakdown in Ni–Ga 2 O 3 Schottky diodes

Ga 2 O 3 unipolar devices are of high interest due to their ~8 MV/cm predicted breakdown fields, which have not yet been achieved due to premature device failure. Pre- and post-failure defect analysis of Ni–Ga 2 O 3 Schottky diodes in ultrahigh vacuum (UHV) and air were performed using depth-resolved cathodoluminescence, high angle annular dark field scanning transmission electron microscopy, and energy dispersive x-ray analysis to understand the physical mechanisms that precede premature breakdown. The breakdown voltage in UHV was dramatically reduced by nearly 40% compared with the breakdown in air. This reduction in the breakdown voltage correlated with post-breakdown differences in Ni distribution, indicating that the coordination and bonding of Ni contribute strongly to electrical behavior in Ni–Ga 2 O 3 Schottky diodes. Breakdown studies in UHV revealed that Ni diffuses away more from the metal–semiconductor interface than with air breakdown, where Ni localizes more near the interface, indicative of the preferential formation of a Ni oxide under O-poor conditions. These measurements also identified the formation of divacancy-interstitial complexes and their characteristic luminescence signature ~150 nm from the interface, the densities of which correlated with breakdown fields. These findings show that electric-field-induced degradation occurs via the rearrangement of native point defects, which act as an additional precursor to device failure. Macroscopically, they show the impact of both vacuum conditions and metal reactivity on Ga 2 O 3 device fabrication.

36 MATERIALS SCIENCE↗

Applications of analytical electron microscopy to guide the design of boron carbide

Compositional analysis of boron carbide on nanometer length scales to examine or interpret atomic mechanisms, for example, solid-state amorphization or grain-boundary segregation, is challenging. This work reviews advancements in high-resolution microanalysis to characterize multiple generations of boron carbide. First, ζ-factor microanalysis will be introduced as a powerful (scanning) transmission electron microscopy ((S)TEM) analytical framework to accurately characterize boron carbide. Three case studies involving the application of ζ-factor microanalysis will then be presented: (1) accurate stoichiometry determination of B-doped boron carbide using ζ-factor microanalysis and electron energy loss spectroscopy, (2) normalized quantification of silicon grain-boundary segregation in Si-doped boron carbide, and (3) calibration of a scanning electron microscope X-ray energy-dispersive spectroscopy (XEDS) system to measure compositional homogeneity differences of B/Si-doped arc-melted boron carbides in the as-melted and annealed conditions. Overall, the improvement and application of advanced analytical tools have helped better understand processing–microstructure–property relationships and successfully manufacture high-performance ceramics.

36 MATERIALS SCIENCE↗

Evaluating Cryo–TEM Reconstruction Accuracy of Self–Assembled Polymer Nanostructures

Cryogenic transmission electron microscopy (cryo–TEM) combined with single particle analysis (SPA) is an emerging imaging approach for soft materials. However, the accuracy of SPA–reconstructed nanostructures, particularly those formed by synthetic polymers, remains uncertain due to potential packing heterogeneity of the nanostructures. In this study, the combination of molecular dynamics (MD) simulations and image simulations is utilized to validate the accuracy of cryo–TEM 3D reconstructions of self–assembled polypeptoid fibril nanostructures. Using CryoSPARC software, image simulations, 2D classifications, ab initio reconstructions, and homogenous refinements are performed. By comparing the results with atomic models, the recovery of molecular details is assessed, heterogeneous structures are identified, and the influence of extraction location on the reconstructions is evaluated. In conclusion, these findings confirm the fidelity of single particle analysis in accurately resolving complex structural characteristics and heterogeneous structures, exhibiting its potential as a valuable tool for detailed structural analysis of synthetic polymers and soft materials.

36 MATERIALS SCIENCE↗

BraggNN : fast X-ray Bragg peak analysis using deep learning

X-ray diffraction based microscopy techniques such as high-energy diffraction microscopy (HEDM) rely on knowledge of the position of diffraction peaks with high precision. These positions are typically computed by fitting the observed intensities in detector data to a theoretical peak shape such as pseudo-Voigt. As experiments become more complex and detector technologies evolve, the computational cost of such peak-shape fitting becomes the biggest hurdle to the rapid analysis required for real-time feedback in experiments. To this end, we propose BraggNN, a deep-learning based method that can determine peak positions much more rapidly than conventional pseudo-Voigt peak fitting. When applied to a test dataset, peak center-of-mass positions obtained from BraggNN deviate less than 0.29 and 0.57 pixels for 75 and 95% of the peaks, respectively, from positions obtained using conventional pseudo-Voigt fitting (Euclidean distance). When applied to a real experimental dataset and using grain positions from near-field HEDM reconstruction as ground-truth, grain positions using BraggNN result in 15% smaller errors compared with those calculated using pseudo-Voigt. Recent advances in deep-learning method implementations and special-purpose model inference accelerators allow BraggNN to deliver enormous performance improvements relative to the conventional method, running, for example, more than 200 times faster on a consumer-class GPU card with out-of-the-box software.

36 MATERIALS SCIENCE↗

Otoconial formation in the fetal rat

Otoconial formation in the fetal rat is examined by scanning and transmission electron microscopy, and by X-ray elemental analysis. The primitive otoconia appear highly organic, but are trigonal in cross section, indicating that they already possess a three-fold axis of symmetry and a complement of calcite. These otoconia develop into spindle-shaped and, subsequently, dumbbell-shaped units. Transmission electron microscopy of dumbbell-shaped otoconia not exposed to fluids during embedment showed that calcite deposits mimicked the arrangement of the organic material. X-ray elemental analysis demonstrated that calcium was present in lower quantities in the central core than peripherally. It is concluded that organic material is essential to otoconial seeding and directs otoconial growth.

Salamat, M. S.↗

Multi-technique characterization of spray coated and roll-to-roll coated gas diffusion fuel cell electrodes

Here this work reports the characterization of catalyst layer (CL) structure and composition for a set of gas-diffusion electrodes (GDEs) fabricated by different coating methods with the goal of developing a better understanding of CL processing-structure-property-performance relationships. The CL coating techniques used in this study were ultrasonic spray coating, and two roll-to-roll (R2R) methods - gravure and slot die. Scanning transmission electron microscopy (STEM) coupled with X-ray energy dispersive spectroscopy (EDS) analysis of GDE cross-sections provided bulk information, while scanning electron microscopy (SEM) with EDS and X-ray photoelectron spectroscopy (XPS) were used to investigate the near surface and surface composition of the CLs that will be in direct contact with the membrane once the membrane electrode assembly (MEA) is constructed. This study demonstrates that common quantification parameters, namely the F:Pt ratio extracted from cross-sectional STEM-EDS maps and top-down CL measurements with SEM and XPS, along with roughness parameters quantified from SEM micrographs are useful parameters in explaining and potentially predicting performance trends. Additionally, it highlights the importance of understanding key CL surface properties for advancing the manufacturability of high-performance components for polymer electrolyte membrane (PEM) technologies.

30 DIRECT ENERGY CONVERSION↗

Quantitative Electron Beam‐Single Atom Interactions Enabled by Sub‐20‐pm Precision Targeting

The ability to probe and control matter at the picometer scale is essential for advancing quantum and energy technologies. Scanning transmission electron microscopy offers powerful capabilities for materials analysis and modification, but sample damage, drift, and scan distortions hinder single atom analysis and deterministic manipulation. Materials analysis and modification via electron–solid interactions can be transformed by precise delivery of electrons to a specified atomic location, maintaining the beam position despite drift, and minimizing collateral dose. Here a fast, low-dose, sub-20-pm precision electron beam positioning technique is developed, “atomic lock-on,” (ALO), which offers the ability to position the beam on a specific atomic column without previously irradiating that column. This technique is used to lock onto a single selected atomic location to repeatedly measure its weak electron energy loss signal despite sample drift. Moreover, electron beam-matter interactions in single atomic events are measured with μ s time resolution. This enables observation of single-atom dynamics, such as atomic bistability, revealing partially bonded atomic configurations and recapture phenomena. This opens prospects for using electron microscopy for high-precision measurements and deterministic control of matter for quantum technologies.

2D materials↗

Thermal Hysteresis and Ordering Behavior of Magnetic Skyrmion Lattices

The physics of phase transitions in two-dimensional (2D) systems underpins research in diverse fields including statistical mechanics, nanomagnetism, and soft condensed matter. However, many aspects of 2D phase transitions are still not well understood, including the effects of interparticle potential, polydispersity, and particle shape. Magnetic skyrmions are chiral spin-structure quasi-particles that form two-dimensional lattices. Here, in this study, we show, by real-space imaging using in situ cryo-Lorentz transmission electron microscopy coupled with machine learning image analysis, the ordering behavior of Néel skyrmion lattices in van der Waals Fe 3 GeTe 2 . We demonstrate a distinct change in the skyrmion size distribution during field-cooling, which leads to a loss of lattice order and an evolution of the skyrmion liquid phase. Remarkably, the lattice order is restored during field heating and demonstrates a thermal hysteresis. This behavior is explained by the skyrmion energy landscape and demonstrates the potential to control the lattice order in 2D phase transitions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Transfer of Methanolobus siciliae to the genus Methanosarcina, naming it Methanosarcina siciliae, and emendation of the genus Methanosarcina

A sequence analysis of the 16S rRNA of Methanolobus siciliae T4/M(T) (T = type strain) showed that this strain is closely related to members of the genus Methanosarcina, especially Methanosarcina acetivorans C2A(T). Methanolobus siciliae T4/M(T) and HI350 were morphologically more similar to members of the genus Methanosarcina than to members of the genus Methanolobus in that they both formed massive cell aggregates with pseudosarcinae. Thus, we propose that Methanolobus siciliae should be transferred to the genus Methanosarcina as Methanosarcina siciliae.

NASA Discipline Exobiology↗

spammR: an R package designed for analysis and integration of spatial multi-omic measurements

Spatial omics is a young and evolving field and as such shows rapid development of novel technologies and analysis methods to measure transcripts, proteins, metabolites, and post-translational modifications at high spatial resolution. These advances in technology have enabled the simultaneous generation of abundance profiles for multiple different omics types and associated microscopy imaging data, as well as their analysis in a spatial context. However, most analytical tools are designed for spatial transcriptomics platforms and are challenging to use in other contexts such as mass spectrometry-based measurements or metagenomics. To this end we present spammR (spatial analysis of multi-omics measurements in R), an R package that enables end-to-end analysis with a specific focus on mass-spectrometry derived spatial omics datasets with (1) smaller sample sizes and spatial sparsity of samples, (2) considerable missingness, and (3) no a-priori knowledge about proteins or genes of interest, relying on a fully data-driven approach.

spammR↗

Do We Really Need All That Data: From Data to Agency in Automated Microscopy

Microscopy is entering an era of automated laboratories and AI-enabled instruments, often justified by a simple narrative of automating experiments to collect more data and train better models. In this work, we argue that, for microscopy, this framing is incomplete and can be counterproductive.

97 MATHEMATICS AND COMPUTING↗

A Simple Approach for the Synthesis of Cellulose Nanofiber Reinforced Chitosan/PVP Bio Nanocomposite Film for Packaging

The development of chitosan-based food packaging film has been increasing due to its wider availability, biodegradability, low-cost, and renewability. The purpose of this study was to develop cellulose nanofibers (CNFs) reinforced Chitosan/PVP(CHP) green bio nanocomposite film by solvent casting method with enhanced barrier and mechanical property. CNFs of dimension 9–11 nm and 100–200 nm were extracted from jute fibers by directly treating it with HNO{sub 3}–NaNO{sub 2} mixture. Bio nanocomposite films were synthesized with various concentrations of CNFs and evaluated using SEM, TGA/DTG and XRD to analyze the morphology, thermal behavior and crystallinity of bio nanocomposite films. SEM analysis revealed the uniform dispersion of CNFs in CHP matrix. Thermal stability of prepared bio nanocomposite films was improved with the loading of 5 wt% of cellulose nanofibers. ATR(FT-IR) spectra shows physical interaction between all the components of bio nanocomposite film. The bio nanocomposite films were also characterized for physical property like thickness, mechanical testing and barrier properties. The addition of CNFs significantly enhanced the mechanical property of bio nanocomposite films. Furthermore, water and oxygen transmission rate of bio nanocomposite film decreased with the increase in CNFs concentration. Overall the performed studies confirmed, the use of CNFs in polymer matrix makes it possible to produce a flexible, transparent, thermally stable bio nanocomposite film with enhanced mechanical and barrier properties for food packaging applications.

36 MATERIALS SCIENCE↗

Unsupervised learning of ferroic variants from atomically resolved STEM images

An approach for the analysis of atomically resolved scanning transmission electron microscopy data with multiple ferroic variants in the presence of imaging non-idealities and chemical variabilities based on a rotationally invariant variational autoencoder (rVAE) is presented. We show that an optimal local descriptor for the analysis is a sub-image centered at specific atomic units, since materials and microscope distortions preclude the use of an ideal lattice as a reference point. The applicability of unsupervised clustering and dimensionality reduction methods is explored and is shown to produce clusters dominated by chemical and microscope effects, with a large number of classes required to establish the presence of rotational variants. Comparatively, the rVAE allows extraction of the angle corresponding to the orientation of ferroic variants explicitly, enabling straightforward identification of the ferroic variants as regions with constant or smoothly changing latent variables and sharp orientational changes. This approach allows further exploration of the chemical variability by separating the rotational degrees of freedom via rVAE and searching for remaining variability in the system. The code used in this article is available at https://github.com/saimani5/ferroelectric_domains_rVAE.

30 DIRECT ENERGY CONVERSION↗

Unsupervised machine learning discovery of structural units and transformation pathways from imaging data

We show that unsupervised machine learning can be used to learn chemical transformation pathways from observational Scanning Transmission Electron Microscopy (STEM) data. To enable this analysis, we assumed the existence of atoms, a discreteness of atomic classes, and the presence of an explicit relationship between the observed STEM contrast and the presence of atomic units. With only these postulates, we developed a machine learning method leveraging a rotationally invariant variational autoencoder (VAE) that can identify the existing molecular fragments observed within a material. The approach encodes the information contained in STEM image sequences using a small number of latent variables, allowing the exploration of chemical transformation pathways by tracing the evolution of atoms in the latent space of the system. The results suggest that atomically resolved STEM data can be used to derive fundamental physical and chemical mechanisms involved, by providing encodings of the observed structures that act as bottom-up equivalents of structural order parameters. The approach also demonstrates the potential of variational (i.e., Bayesian) methods in the physical sciences and will stimulate the development of more sophisticated ways to encode physical constraints in the encoder–decoder architectures and generative physical laws and causal relationships in the latent space of VAEs.

97 MATHEMATICS AND COMPUTING↗

Structure and Dynamics of Interfaces: Drops and Films

We aim to acquire measurements of the structure and dynamics of certain liquid-fluid interfaces using an ensemble of techniques in collaboration: (1) Total internal reflection (TIR) Surface light scattering spectroscopy (SLSS), (2) Brewster angle microscopy (BAM), and (3) Drop-shape analysis. SLSS and BAM can be done on a shared interfacial footprint. Results using a 50-50 mixture of pentane-isohexane, which extends the range of NASA's Confined Vapor Bubble (CVB) experiment, yield surface tension results that differ from the expected Langmuir Fit. These results were confirmed using both the SLSS and drop-shape analysis approaches.

pentane-isohexane mixture↗

Assessment of Proper Bonding Methods and Mechanical Characterization FPGA CQFPs

This presentation discusses fractured leads on field-programmable gate array (FPGA) during flight vibration. Actions taken to determine root cause and resolution of the failure include finite element analysis (FEA) and vibration testing and scanning electron microscopy (with X-ray microanalysis) and energy dispersive spectrometry (SEM/EDS) failure assessment. Bonding methods for surface mount parts is assessed, including critical analysis and assessment of random fatigue damage. Regarding ceramic quad flat pack (CQFP) lead fracture, after disassembling the attitude control electronics (ACE) configuration, photographs showed six leads cracked on FPGA RTSX72SU-1 CQ208B package located on the RWIC card. An identical package (FPGA RTSX32SU-1 CQ208B) mounted on the RWIC did not results in cracked pins due to vibration. FPGA lead failure theories include workmanship issues in the lead-forming, material defect in the leads of the FPGA packages, and the insecure mounting of the board in the card guides, among other theories. Studies were conducted using simple calculations to determine the response and fatigue life of the package. Shorter packages exhibited more response when loaded by out-of-plane displacement of PCB while taller packages exhibit more response when loaded by in-plane acceleration of PCB. Additionally, under-fill did not contribute to reducing stress in leads due to out-of-plane PCB loading or from component twisting, as much as corner bonding. The combination of corner bond and under-fill is best to address mechanical and thermal S/C environment. Test results of bonded parts showed reduced (dampened) amplitude and slightly shifted peaks at the un-bonded natural frequency and an additional response at the bonded frequency. Stress due to PCBB out-of-plane loading was decreased on in the corners when only a corner bond was used. Future work may address CQFP fatigue assessment, including the investigation of discrepancy in predicted fatigue damage, as well as comparing fatigue life and fatigue damage cycle ration computed using FEA and Miner's rule to results from a fatigue assessment software program.

Davis, Milton C.↗