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At least 307 records · Page 17

STEM Imaging of Materials: Final Report for DE-FG02-08ER46547

This project supported research advancing the state of the art in scanning transmission electron microscopy (STEM) imaging and characterization of materials, especially electronic materials. The project began with studies of point defects in materials using high-resolution Z-contrast STEM, then evolved to including methods in four-dimensional (4D) STEM and machine learning. Highlights include: (1) the discovery of stable, p-type ZnO via Sb doping, (2) demonstration that the high performance of InGaN LEDs is not due to In composition fluctuations as previously proposed, (3) the demonstration of the first sub-pm precision high-resolution STEM images using non-rigid registration of a series of STEM images, (4) the extension of high-precision STEM to low dose imaging and spectrum imaging, (5) discovery of a synthesis method for twisted spiral growth of transition-metal dichalcogenide materials via chemical vapor deposition, and (6) development of machine-learning methods for analysis and denoising of enormous 4D STEM data sets.

36 MATERIALS SCIENCE↗

Atomic Resolution Cryogenic 4D-STEM Imaging via Robust Distortion Correction

Cryogenic four-dimensional scanning transmission electron microscopy (4D-STEM) imaging is a useful technique for studying quantum materials and their interfaces by simultaneously probing charge, lattice, spin, and chemistry on the atomic scale with the sample held at temperatures ranging from room to cryogenic. However, its applications are currently limited by the instabilities of cryo-stages and electronics. To overcome this challenge, we develop an algorithm to effectively correct the complex distortions present in atomic resolution cryogenic 4D-STEM data sets. This method uses nonrigid registration to identify localized distortions in a 4D-STEM and relate them to an undistorted experimental STEM image, followed by a series of affine transformations for distortion corrections. This method allows a minimum loss of information in both reciprocal and real spaces, enabling the reconstruction of sample information from 4D-STEM data sets. This method is computationally cheap, fast, and applicable for on-the-fly data analysis in future in situ cryogenic 4D-STEM experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improved reduced-resolution satellite imagery

The resolution of satellite imagery is often traded-off to satisfy transmission time and bandwidth, memory, and display limitations. Although there are many ways to achieve the same reduction in resolution, algorithms vary in their ability to preserve the visual quality of the original imagery. These issues are investigated in the context of the Landsat browse system, which permits the user to preview a reduced resolution version of a Landsat image. Wavelets-based techniques for resolution reduction are proposed as alternatives to subsampling used in the current system. Experts judged imagery generated by the wavelets-based methods visually superior, confirming initial quantitative results. In particular, compared to subsampling, the wavelets-based techniques were much less likely to obscure roads, transmission lines, and other linear features present in the original image, introduce artifacts and noise, and otherwise reduce the usefulness of the image. The wavelets-based techniques afford multiple levels of resolution reduction and computational speed. This study is applicable to a wide range of reduced resolution applications in satellite imaging systems, including low resolution display, spaceborne browse, emergency image transmission, and real-time video downlinking.

Ellison, James↗

Stereo Imaging Miniature Endoscope with Single Imaging Chip and Conjugated Multi-Bandpass Filters

A dual objective endoscope for insertion into a cavity of a body for providing a stereoscopic image of a region of interest inside of the body including an imaging device at the distal end for obtaining optical images of the region of interest (ROI), and processing the optical images for forming video signals for wired and/or wireless transmission and display of 3D images on a rendering device. The imaging device includes a focal plane detector array (FPA) for obtaining the optical images of the ROI, and processing circuits behind the FPA. The processing circuits convert the optical images into the video signals. The imaging device includes right and left pupil for receiving a right and left images through a right and left conjugated multi-band pass filters. Illuminators illuminate the ROI through a multi-band pass filter having three right and three left pass bands that are matched to the right and left conjugated multi-band pass filters. A full color image is collected after three or six sequential illuminations with the red, green and blue lights.

Shahinian, Hrayr Karnig↗

Massive all-atom analysis of 2D materials with quantum properties (Final report)

Improvements in microscopy have enabled the acquisition of data at a scale that is difficult to process manually, making automated machine learning approaches to analyzing experimental images essential. In this project, we developed and applied machine learning (ML) workflows for atomic resolution scanning transmission electron microscopy (STEM) images. This development included improving both methodology as well as generating user-friendly codes. We developed machine learning architectures which, after training, automatically identify the location and types of defects throughout a material. We used these data to produce class-averaged images of 2D atomic coordinates with up to 0.3 pm precision, uncovering the structure and oscillations of long-range strain fields around point defects in WSe 2-2x Te 2x . We also resolved a long-standing problem in this field in the training of ML models, a lack of labeled experimental data, by developing a cycle-GAN that transformed simulated-generated labeled data into labeled data indistinguishable from experiment and therefore suitable for training. This removed the remaining parts of the ML data processing workflow where human intervention was still critical and therefore a bottleneck to working at scale. Codes have been developed and released for this full machine learning workflow. ML approaches to partially automate STEM acquisition were also developed. Finally we applied ML and other advanced data processing methods to several materials science problems in two-dimensional materials, including studying the evolution of hyperuniformity with defect concentration in WSe2, understanding phase transformations in transition metal dichalcogenides during in-situ heating in the STEM, and exploring how 2D interfaces transform from twisted into aligned structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Electron image contrast analysis of mosaicity in rutile nanocrystals using direct electron detection

Direct electron detection provides high detective quantum efficiency, significantly improved point spread function and fast read-out which have revolutionized the field of cryogenic electron microscopy. However, these benefits for high-resolution electron microscopy (HREM) are much less exploited, especially for in situ study where major impacts on crystallographic structural studies could be made. By using direct detection in electron counting mode, rutile nanocrystals have been imaged at high temperature inside an environmental transmission electron microscope. The improvements in image contrast are quantified by comparison with a charge-coupled device (CCD) camera and by image matching with simulations using an automated approach based on template matching. Together, these approaches enable a direct measurement of 3D shape and mosaicity (~1°) of a vacuum-reduced TiO 2 nanocrystal about 50 nm in size. Thus, this work demonstrates the possibility of quantitative HREM image analysis based on direct electron detection.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the Influence of Receptive Field and Network Complexity in Neural Network-Guided TEM Image Analysis

Abstract Trained neural networks are promising tools to analyze the ever-increasing amount of scientific image data, but it is unclear how to best customize these networks for the unique features in transmission electron micrographs. Here, we systematically examine how neural network architecture choices affect how neural networks segment, or pixel-wise separate, crystalline nanoparticles from amorphous background in transmission electron microscopy (TEM) images. We focus on decoupling the influence of receptive field, or the area of the input image that contributes to the output decision, from network complexity, which dictates the number of trainable parameters. For low-resolution TEM images which rely on amplitude contrast to distinguish nanoparticles from background, we find that the receptive field does not significantly influence segmentation performance. On the other hand, for high-resolution TEM images which rely on both amplitude and phase-contrast changes to identify nanoparticles, receptive field is an important parameter for increased performance, especially in images with minimal amplitude contrast. Rather than depending on atom or nanoparticle size, the ideal receptive field seems to be inversely correlated to the degree of nanoparticle contrast in the image. Our results provide insight and guidance as to how to adapt neural networks for applications with TEM datasets.

42 ENGINEERING↗

A preliminary investigation of communication techniques for local and remote access to image databases

A software technique which allows users to examine images remotely while minimizing transmission time, is discussed. The technique provides a browsing capability, making it possible to roam over larger images, to zoom to various resolution levels, and to specify subregions of interest in the image to display at full resolution. The software permits analysts to remotely submit images for processing and to review the processing result. The capabilities of the technique under varying conditions and the speed at which imagery can be displayed over direct connect serial lines are discussed and examples of the imagery at various levels of resolution are presented.

Ma, Mathias↗

Detection of defects in atomic-resolution images of materials using cycle analysis

The automated detection of defects in high-angle annular dark-field Z-contrast (HAADF) scanning-transmission-electron microscopy (STEM) images has been a major challenge. Here, we report an approach for the automated detection and categorization of structural defects based on changes in the material’s local atomic geometry. The approach applies geometric graph theory to the already-found positions of atomic-column centers and is capable of detecting and categorizing any defect in thin diperiodic structures (i.e., “2D materials”) and a large subset of defects in thick diperiodic structures (i.e., 3D or bulk-like materials). Despite the somewhat limited applicability of the approach in detecting and categorizing defects in thicker bulk-like materials, it provides potentially informative insights into the presence of defects. The categorization of defects can be used to screen large quantities of data and to provide statistical data about the distribution of defects within a material. This methodology is applicable to atomic column locations extracted from any type of high-resolution image, but here we demonstrate it for HAADF STEM images.

36 MATERIALS SCIENCE↗

The Effects of Radiation on Imagery Sensors in Space

Recent experience using high definition video on the International Space Station reveals camera pixel degradation due to particle radiation to be a much more significant problem with high definition cameras than with standard definition video. Although it may at first appear that increased pixel density on the imager is the logical explanation for this, the ISS implementations of high definition suggest a more complex causal and mediating factor mix. The degree of damage seems to vary from one type of camera to another, and this variation prompts a reconsideration of the possible factors in pixel loss, such as imager size, number of pixels, pixel aperture ratio, imager type (CCD or CMOS), method of error correction/concealment, and the method of compression used for recording or transmission. The problem of imager pixel loss due to particle radiation is not limited to out-of-atmosphere applications. Since particle radiation increases with altitude, it is not surprising to find anecdotal evidence that video cameras subject to many hours of airline travel show an increased incidence of pixel loss. This is even evident in some standard definition video applications, and pixel loss due to particle radiation only stands to become a more salient issue considering the continued diffusion of high definition video cameras in the marketplace.

Mathis, Dylan↗

X Ray, Far, and Extreme Ultraviolet Coatings for Space Applications

The idea of utilizing imaging mirrors as narrow band filters constitutes the basis of the design of extreme ultraviolet imagers operating at 58.4 nm and 83.4 nm. The net throughput of both imaging-filtering systems is better than 20 percent. The superiority of the EUV self-filtering camera/telescope becomes apparent when compared to previously theoretically designed 83.4-nm filtering-imaging systems, which yielded transmissions of less than a few percent and therefore less than 0.1 percent throughput when combined with at least two imaging mirrors. Utilizing the self-filtering approach, instruments with similar performances are possible for imaging at other EUV wavelengths, such as 30.4 nm. The self-filtering concept is extended to the X-ray region where its application can result in the new generation of X-ray telescopes, which could replace current designs based on large and heavy collimators.

Zukic, M.↗

A Compact 600 GHz Electronically Tunable Vector Measurement System for Submillimeter Wave Imaging

A compact submillimeter wave transmission / reflection measurement system has been demonstrated at 560-635 GHz, with electronic tuning over the entire band. Maximum dynamic range measured at a single frequency is 90 dB (60 dB typical), and phase noise is less than +/- 2(deg). By using a frequency steerable lens at the source output and mixer input, the frequency agility of the system can be used to scan the source and receive beams, resulting in near real-time imaging capability using only a single pixel.

submillimeter wave imaging↗

Automation of Laser Plasma Focused Ion Beam Microscopy for Next-Gen Energy Materials

Automation can revolutionize the use of ultrafast laser ablation and plasma-focused ion beam (PFIB) techniques for high-throughput, reproducible cross-sectioning and various sample preparation in materials characterization. As these methods become essential for analyzing complex energy materials and next-generation devices, efficient, standardized workflows are needed to minimize variability and enhance precision. This work highlights our advancements in developing automated processes for sample preparation that integrates machine learning, workflow optimization, and large-scale data acquisition to improve efficiency and scalability in applications such as electrolyzers, photovoltaic cells, and microelectronics. To streamline cross-sectioning and lamella fabrication, we have implemented fully automated workflows that standardize laser ablation and PFIB milling sequences. These workflows incorporate pre-programmed protocols for material removal, alignment, and thinning, reducing user intervention and ensuring consistency across different sample types. Machine learning algorithms further enhance automation by predicting optimal milling strategies and adapting parameters based on material properties and sectioning requirements. This approach significantly improves throughput while maintaining the structural integrity of prepared samples for high-resolution imaging and analysis, including transmission electron microscopy. Beyond sample preparation, our automation platform enables the acquisition of large, high-resolution datasets through serial sectioning, image alignment, and 3D reconstruction. These automated routines facilitate multi-scale characterization, capturing structural and compositional details from the nanoscale to the device level. By reducing variability and increasing efficiency, our automated approach enhances defect analysis, failure diagnostics, and process optimization, accelerating advancements in materials research and device engineering.

36 MATERIALS SCIENCE↗

Multimode-Optical-Fiber Imaging Probe

Currently, endoscopic surgery uses single-mode fiber-bundles to obtain in vivo image information inside orifices of the body. This limits their use to the larger natural bodily orifices and to surgical procedures where there is plenty of room for manipulation. The knee joint, for example can be easily viewed with a fiber optic viewer, but joints in the finger cannot. However, there are a host of smaller orifices where fiber endoscopy would play an important role if a cost effective fiber probe were developed with small enough dimensions (< 250 microns). Examples of beneficiaries of micro-endoscopes are the treatment of the Eustatian tube of the middle ear, the breast ducts, tear ducts, coronary arteries, fallopian tubes, as well as the treatment of salivary duct parotid disease, and the neuro endoscopy of the ventricles and spinal canal. To solve this problem, this work describes an approach for recovering images from. tightly confined spaces using multimode fibers and analytically demonstrates that the concept is sound. The proof of concept draws upon earlier works that concentrated on image recovery after two-way transmission through a multimode fiber as well as work that demonstrated the recovery of images after one-way transmission through a multimode fiber. Both relied on generating a phase conjugated wavefront which was predistorted with the characteristics of the fiber. The described approach also relies on generating a phase conjugated wavefront, but utilizes two fibers to capture the image at some intermediate point (accessible by the fibers, but which is otherwise visually unaccessible).

Jackson, Deborah↗

Inactivation of Fluorescent Lipid Bilayers by Irradiation With 300 keV Electrons Using Liquid Cell Transmission Electron Microscopy

Liquid cell transmission electron microscopy allows for imaging of samples in a fully hydrated state at high resolution and has the potential for visualizing static or dynamic biological structures. However, the ionizing nature of the electron beam makes it difficult to discern real physiological dynamics from radiation induced artifacts within liquid cell samples. Electron flux thresholds for achieving high resolution structures from biological samples frozen in ice have been described extensively by the cryo-electron microscopy field, while electron flux thresholds which do not result in a functional change for biological samples within the hydrated environment of a transmission electron microscope liquid cell is less clear. Establishing these functional thresholds for biologically relevant samples is important for accurate interpretation of results from liquid cell experiments. Here we demonstrate the electron damage threshold of fluorescently tagged lipid bilayers by quantifying the change in fluorescence before and after electron exposure. We observe the reduction of fluorescent signal in bilayers by 25% after only 0.0005 e − /Å 2 and a reduction of over 90% after 0.01 e − /Å 2 . These results indicate that the loss of function occurs at irradiation thresholds far below a typical single high resolution (scanning) transmission electron microscopy image and orders of magnitude below fluxes used for preserving structural features with cryo-electron microscopy.

Moser, Trevor↗

Multimode-Optical-Fiber Imaging Probe

Currently, endoscopic surgery uses single-mode fiber-bundles to obtain in vivo image information inside the orifices of the body. This limits their use to the larger natural orifices and to surgical procedures where there is plenty of room for manipulation. The knee joint, for example, can be easily viewed with a fiber optic viewer, but joints in the finger cannot. However, there are a host of smaller orifices where fiber endoscopy would play an important role if a cost effective fiber probe were developed with small enough dimensions (less than or equal to 250 microns). Examples of beneficiaries of micro-endoscopes are the treatment of the Eustatian tube of the middle ear, the breast ducts, tear ducts, coronary arteries, fallopian tubes, as well as the treatment of salivary duct parotid disease, and the neuro endoscopy of the ventricles and spinal canal. This work describes an approach for recovering images from tightly confined spaces using multimode. The concept draws upon earlier works that concentrated on image recovery after two-way transmission through a multimode fiber as well as work that demonstrated the recovery of images after one-way transmission through a multimode fiber. Both relied on generating a phase conjugated wavefront, which was predistorted with the characteristics of the fiber. The approach described here also relies on generating a phase conjugated wavefront, but utilizes two fibers to capture the image at some intermediate point (accessible by the fibers, but which is otherwise visually inaccessible).

Jackson, Deborah↗

All-optical image denoising using a diffractive visual processor

Abstract Image denoising, one of the essential inverse problems, targets to remove noise/artifacts from input images. In general, digital image denoising algorithms, executed on computers, present latency due to several iterations implemented in, e.g., graphics processing units (GPUs). While deep learning-enabled methods can operate non-iteratively, they also introduce latency and impose a significant computational burden, leading to increased power consumption. Here, we introduce an analog diffractive image denoiser to all-optically and non-iteratively clean various forms of noise and artifacts from input images – implemented at the speed of light propagation within a thin diffractive visual processor that axially spans <250 × λ, where λ is the wavelength of light. This all-optical image denoiser comprises passive transmissive layers optimized using deep learning to physically scatter the optical modes that represent various noise features, causing them to miss the output image Field-of-View (FoV) while retaining the object features of interest. Our results show that these diffractive denoisers can efficiently remove salt and pepper noise and image rendering-related spatial artifacts from input phase or intensity images while achieving an output power efficiency of ~30–40%. We experimentally demonstrated the effectiveness of this analog denoiser architecture using a 3D-printed diffractive visual processor operating at the terahertz spectrum. Owing to their speed, power-efficiency, and minimal computational overhead, all-optical diffractive denoisers can be transformative for various image display and projection systems, including, e.g., holographic displays.

36 MATERIALS SCIENCE↗

Low Resolution Picture Transmission (LRPT) Demonstration System

Low-Resolution Picture Transmission (LRPT) is a proposed standard for direct broadcast transmission of satellite weather images. This standard is a joint effort by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and NOAA. As a digital transmission scheme, its purpose is to replace the current analog Automatic Picture Transmission (APT) system for use in the Meteorological Operational (METOP) satellites. GSFC has been tasked to build an LRPT Demonstration System (LDS). Its main objective is to develop or demonstrate the feasibility of a low-cost receiver utilizing a PC as the primary processing component and determine the performance of the protocol in the simulated Radio Frequency (RF) environment. The approach would consist of two phases.

Fong, Wai↗