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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 469 records · Page 26

Soot Nanostructure: Using Fringe Analysis Software on High Resolution Transmission Electron Microscopy of Carbon Soot

Using high resolution transmission electron images of carbon nanotubes and carbon particles, we are able to use image analysis program to determine several carbon fringe properties, including length, separation, curvature and orientation. Results are shown in the form of histograms for each of those quantities. The combination of those measurements can give a better indication of the graphic structure within nanotubes and particles of carbon and can distinguish carbons based upon fringe properties. Carbon with longer, straighter and closer spaced fringes are considered graphite, while amorphous carbon contain shorter, less structured fringes.

King, James D.↗

Insights into Heterogeneous Catalysts under Reaction Conditions by In Situ/Operando Electron Microscopy

The advancement of clean energy and environment depends strongly on the development of efficient catalysts in a wide range of heterogeneous catalytic reactions, which has benefited from transmission electron microscopic techniques in determining the atomic-scale morphologies and structures. However, it is the morphology and structure under the catalytic reaction conditions that determine the performance of the catalyst, which has captured a surge of interest in developing and applying in situ/operando transmission electron microscopic techniques in heterogeneous catalysis. The major theme of this review is to highlight some of the most recent insights into heterogeneous catalysts under the relevant reaction conditions using in situ/operando transmission electron microscopic techniques. Rather than a comprehensive overview of the basic principles of in situ/operando techniques, this review focuses on the insights into the atomic-scale/nanoscale details of various catalysts ranging from single-component to multicomponent catalysts under heterogeneous catalytic, electrocatalytic, and photocatalytic reaction conditions involving both gas–solid and liquid–solid interfaces. Here, this focus is coupled with discussions of the correlation of the atomic, molecular, and nanoscale morphology, composition, and structure with the catalytic properties under the reaction conditions, shining light on the challenges and opportunities in design of nanostructured catalysts for clean and sustainable energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reconstruction of simulated electrostatic potentials by automatic differentiation-based phase retrieval in electron microscopy imaging

Measuring interfacial electrostatic potentials is vital to understanding many fundamental materials properties. A variety of TEM methods exist for measuring electric potentials from the phase shift produced on an electron wave as it passes through a sample. However, most are either experimentally challenging or poorly suited to resolving nanoscale features. Here, we demonstrate the viability of a simple, automatic differentiation-based exit wave reconstruction from a focal series of images to accurately measure nanoscale electric potentials. Here, the analysis suggests that under optimal measurement conditions, electric potentials can be resolved to less than 0.06 V in magnitude and less than 1 nm in spatial extent.

36 MATERIALS SCIENCE↗

Physics Discovery in Nanoplasmonic Systems via Autonomous Experiments in Scanning Transmission Electron Microscopy

Abstract Physics‐driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here, this work develops and experimentally implements a deep kernel learning (DKL) workflow combining the correlative prediction of the target functional response and its uncertainty from the structure, and physics‐based selection of acquisition function, which autonomously guides the navigation of the image space. Compared to classical Bayesian optimization (BO) methods, this approach allows to capture the complex spatial features present in the images of realistic materials, and dynamically learn structure–property relationships. In combination with the flexible scalarizer function that allows to ascribe the degree of physical interest to predicted spectra, this enables physical discovery in automated experiment. Here, this approach is illustrated for nanoplasmonic studies of nanoparticles and experimentally implemented in a truly autonomous fashion for bulk‐ and edge plasmon discovery in MnPS 3 , a lesser‐known beam‐sensitive layered 2D material. This approach is universal, can be directly used as‐is with any specimen, and is expected to be applicable to any probe‐based microscopic techniques including other STEM modalities, scanning probe microscopies, chemical, and optical imaging.

42 ENGINEERING↗

Learning and Controlling Silicon Dopant Transitions in Graphene Using Scanning Transmission Electron Microscopy

A machine learning approach is introduced to determine the transition dynamics of silicon atoms on a single layer of carbon atoms, when stimulated by the electron beam of a scanning transmission electron microscope (STEM). This method is data-centric, leveraging data collected on a STEM. The data samples are processed and filtered to produce symbolic representations, which is used to train a neural network to predict transition probabilities. These learned transition dynamics are then leveraged to guide a single silicon atom throughout the lattice to pre-determined target destinations. Empirical analyses are presented that demonstrate the efficacy and generality of the approach.

36 MATERIALS SCIENCE↗

3D Nanotomography of calcium silicate hydrates by transmission electron microscopy

Calcium silicate hydrate (C-S-H), is the principal hydration product of Portland cement that mainly contributes to the physical and mechanical properties of concrete. This paper aims to investigate the three-dimensional structure of C-S-H with Ca/Si ratios of 1.0 and 1.6 at the nanoscale using electron tomography. The 3D reconstructions and selected region of interest analysis confirm that the morphology of both C-S-H materials are foil-like structures. Additionally, the difference between the two materials is the density of elongated structures. C-S-H with Ca/Si ratio 1.6 is clearly composed of denser particles compared to the other C-S-H material due to overlapping of the foil-like structure. Pore analysis shows that C-S-H 1.0 and C-S-H 1.6 have porosities 69.2% and 49.8% respectively. Pore size distribution also reveals that C-S-H 1.0 has pore size range between 0-250 nm and C-S-H 1.6 between 0-100 nm. The pore network's size of C-S-H 1.0 is significantly larger than 1.6. This study illustrates the capability of using electron tomography to determine the 3D nanoscale structure of cementitious products and to distinguish between C-S-H 1.0 and 1.6.

42 ENGINEERING↗

An In Situ transmission electron microscopy study on the synergistic effects of Au-ion irradiation and high temperature on nuclear graphite microstructure

Abstract The combined effects of high-temperature and heavy-ion irradiation on Mrozowski cracks (MC) and nuclear graphite crystallographic dimensions have been studied using in situ heating and in situ ion-irradiation in the transmission electron microscope (TEM). Electron transparent lamella of nuclear graphite, IG-110, was irradiated using a 2.8 MeV Au beam at an ion flux of 3.991 ×10 10 ion cm −2 s −1 for 70 min at 800 °C. Upon high-temperature irradiation, Mrozowski crack closure was studied quantitatively. The analysis showed linear, positive expansion of nuclear graphite which is significantly different from the dimensional changes previously reported for low-dose neutron irradiation of nuclear graphite in which the material undergoes negative to positive expansion via a turnaround radiation dose. The trend of the thermal expansion coefficient (CTE) of pristine IG-110 in this study is consistent with previous reports in the 100 °C–800 °C temperature region in which the dimensional change ranges from negative to positive values.

36 MATERIALS SCIENCE↗