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At least 19 records

A bi-channel aided stitching of atomic force microscopy images

Microscopy is an essential tool in scientific research, enabling the visualization of structures at micro- and nanoscale resolutions. However, the field of microscopy often encounters limitations in field-of-view (FOV), restricting the amount of sample that can be imaged in a single capture. To overcome this limitation, image stitching techniques have been developed to seamlessly merge multiple overlapping images into a single, high-resolution composite. The images collected from microscope need to be optimally stitched before accurate physical information can be extracted from post analysis. However, the existing stitching tools either struggle to stitch images together when the microscopy images are feature sparse or cannot address all the transformations of images when performing image stitching. To address these issues, we propose a bi-channel aided feature-based image stitching method and demonstrate its use on Atomic Force Microscopy (AFM) generated Pantoea sp. YR343 biofilm and PTO thin film sample images as experimental data. The topographical channel image of AFM data captures the morphological details of the sample, and a stitched topographical image is desired for researchers. We utilize the amplitude and phase channels of AFM data to maximize the matching features and to estimate the position of the original topographical images and show that the proposed bi-channel aided stitching method outperforms the traditional direct stitching approach in AFM topographical image stitching task. Here, we demonstrated the application on AFM, but similar approaches could be employed of optical microscopy with brightfield and fluorescence channels. We believe this proposed workflow can serve as a valuable augmentation strategy for microscopy image stitching tasks and will benefit the experimentalist to avoid erroneous analysis and discovery due to incorrect stitching.

Atomic force microscopy

Backbone Stitching in Bottlebrush Copolymer Mesodomains and the Impact of Side Chain Crystallization

We synthesized bottlebrush statistical copolymers (BSCPs) having poly­(ethylene oxide) (PEO) and poly­(dimethylsiloxane) (PDMS) side chains attached to a polynorbornene backbone. Small-angle X-ray scattering analysis showed that for densely grafted BSCPs, the scattering length density gradually transitions between the PEO and PDMS domains. For loosely grafted BSCPs, the polymer backbone formed a distinct mesodomain, with a lower electron and mass density than both the PEO and PDMS domains. The bottlebrush backbone essentially “stitches” the PEO and PDMS side chains, looping back and forth from the PEO to PDMS domains with the backbone segments oriented normal to the domain interfaces. Self-consistent field theory (SCFT) calculations validated the stitching of the backbone driven by the microphase separation of PEO and PDMS, along with a strong segmental order of the side chains in the melt. The reduced birefringence upon PEO crystallization suggests the disruption of the strong segmental order by the crystallization. Both the static intrinsic and the form birefringences of the BSCPs decreased upon PEO crystallization. Solid-state NMR confirmed the rigidity of PEO crystallites and the bottlebrush backbone. Self-assembly of BSCPs containing polyhedral oligomeric silsesquioxane (POSS) pendent groups was also evaluated by X-ray scattering, showing the formation of lamellar microdomains that inhibited POSS crystallization.

Hu, Mingqiu

Defining Probe Closure Offset and Scan Stitching Methodology for Element Contact Profilometry in the Hot Fuel Examination Facility

The Element Contact Profilometer (ECP) is a non-destructive post-irradiation examination (PIE) method established in the Materials and Fuels Complex (MFC) Hot Fuel Examination Facility (HFEF). The ECP suspends a fuel rod with a standard end-fitting in a vertical orientation and draws it between two opposed Sony probes with sapphire rod tips, which measure the diameter directly as a function of vertical stage position through contact profilometry. The ECP is equipped with concave rollers, which pinch the rod to maintain a consist position between these sapphire probe tips. A schematic of the analysis head is shown in Figure 1. The gripper that suspends the rod end-fitting is able to rotate to allow measuring of any azimuthal angle around the rod. This system is used to characterize the diameter of full-length light water reactor (LWR) irradiated fuel rods at multiple azimuthal angles in support of the Advanced Fuels Campaign (AFC).

22 - GENERAL STUDIES OF NUCLEAR REACTORS

Abbreviated Report for 25-FS-011: Switch and Stitch Similar Subgraph Synthesizer

Government institutions utilize software from a wide array of development sources, including those written by large software companies, government contractors, and open-source repositories. Avoiding installation of malicious software components is an important national security endeavor. Automated analysis of previously unseen software is an active research area, and there is much research in the design of systems that compare new software artifacts to a large set of previously seen software records organized by various behaviors they contain. One attractive approach is to turn each compiled software binary into a graph representation and apply a graph similarity model that scores pairs of binaries by their relative similarity. When a pair is deemed similar, it is useful to know why, in the sense of providing explanations to security analysts regarding which portions of the software they should look into further.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF

Trident Smyth: Near Real Time Sensor Fusion and Track Stitching Application

Sandia’s Sensor Data Fusion application is a NGA sponsored project that fuses tracks from different sensors to provide more accuracy than any single track. The application serves as the unclassified architecture for data ingestion, processing, and near real-time sensor fusion.

Sorroche, Joseph John [Sandia National Laboratorie

Nonlocal Metasurfaces and Their High Q‐Factors in Fano Resonances

Herein nonlocal metasurfaces of parallel bars stitched to cubic rectangles containing structural and symmetry perturbations with a coupling of localized Mie resonance in meta‐atoms and Bragg modes in photonic crystals are reported. Two Fano resonances have been identified that maintain ultrahigh Q‐factors at incident angles of light up to 5°. Increasing the symmetry of the meta‐atoms results in Fano resonances with Q‐factors increased by a factor of 26, compared with the metasurfaces with a single bar stitched to a cubic rectangle at the incident angle of 5°. Due to nonlocal coupling of Bragg scattering and Mie resonance, the Q‐factor maintains almost a constant at 5° of incidence, while it varies with structural or symmetrical perturbations at 0°.

77 NANOSCIENCE AND NANOTECHNOLOGY

Binary pseudo-random array standards for calibration of 3D optical surface profilers used for metrology with significantly curved x-ray optics

High-accuracy metrology is vitally important in manufacturing ultra-high-quality free-form mirrors designed to manipulate X-ray light with nanometer-scale wavelengths. The current capabilities and possibility for improvements in X-ray mirror manufacturing are limited by inherent imperfections of the integrated metrology tools. In the case of Fizeau interferometry, metrology tools are currently calibrated with super-polished flat test-standard/reference mirrors. This is acceptable for measuring slightly curved X-ray optics. However, for even moderately curved aspherical X-ray mirrors the flat-reference calibration is not sufficiently accurate and stitching Fizeau interferometer-based surface metrology is used to mitigate the problem. But still, the retrace and aberration errors, as well as the limited spatial resolution, described with the instrument transfer function (ITF), can be transferred into the optical surface topography of X-ray mirrors obtained in stitching metrology. For ITF calibration, we have developed an original technique, based on test standards structured as two-dimensional (2D) highly-randomized (HR) binary pseudo-random arrays (BPRAs). The technique employs the unique properties of the HR BPRA patterns in the spatial frequency domain., i.e. the inherent 2D power spectral density of the HR BPRA pattern has a deterministic white-noise-like character that allows direct determination of the ITF with uniform sensitivity over the entire spatial frequency range and field-of-view of an instrument. Here, we explore technological, metrological, and analytical aspects essential for calibration of the retrace and aberration errors of Fizeau interferometers using different types of tilted test samples, including a super-polished reference mirror for the re-trace calibration and the uniformly redundant array (URA) BPRA standards for the geometrical distortion (aberration) calibration. While the first method was previously demonstrated by researchers at DIAMOND Light Source, a method based on the URA BPRA is described and demonstrated here for the first time. We outline the design and fabrication process used in fabrication of URA BPRA test standards, and present the results of application of the URA BPRA standards demonstrating the high efficacy of our approach to geometrical distortion calibration of Fizeau interferometers. We also discuss the possible sources of unexpected peculiarities of the systematic errors, including an astigmatic character of the retrace error, observed with Fizeau interferometers at the Advanced Light Source X-Ray Optics Laboratory.

Munechika, Keiko

Convergence of Emerging Technologies - Blickfeld Test Results

The Blickfeld Cube 1 Lidar is an inexpensive flash lidar being developed for autonomous navigation with an advertised maximum range of 75 meters that uses a Class 1 eye-safe laser. Figure 1 shows an example of the installation of the Cube 1 lidar and Figure 2 shows an example of the point cloud generated, with the red circle indicating an intruder. The Cube 1 lidar has a software adjustable field of view and as many as 5 lidars can be stitched together. (Figure 2 shows two Cube 1 lidars stitched together.)

47 OTHER INSTRUMENTATION

Flavor Classification in ICARUS Using Convolutional Visual Networks

In this work, we adapt the Convolutional Visual Network (CVN) approach [1] to the ICARUS detector by incorporating TPC stitching methods inspired by NuGraph[8]. The stitching technique used here is unique to ICARUS, designed specifically to handle its distinct detector segmentations. We then retrain the network using ICARUS-specific data. This study underscores the flexibility of deep learning models in high-energy physics and the importance of accounting for detector-specific features when transferring machine learning techniques between experiments. This poster presents the methods, classification performance, and insights gained from applying CVN to ICARUS data.

Wieler, Felipe [Tech. Fed. Parana U.]

Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Neutrino Flavor Classification in ICARUS Experiment Using Convolutional Visual Networks

In this work, I adapt the Convolutional Visual Network (CVN) approach to the ICARUS detector by incorporating TPC stitching methods inspired by NuGraph. The stitching technique used here is unique to ICARUS, designed specifically to handle its distinct detector segmentation s. I then retrain the network using ICARUS-specific data. This study underscores the flexibility of deep learning models in high-energy physics and the importance of accounting for detector-specific features when transferring machine learning techniques between experiments. This dissertation presents the methods, classification performance, and insights gained from applying CVN to ICARUS data.

Wieler, Felipe Andre [Parana Tech. Fed. U., Toledo

Wide‐Field Bond Quality Evaluation Using Frequency Domain Thermoreflectance with Deep Neural Network Feature Reconstruction

Heterogeneous integration of microelectronic components provides a pathway to improve circuit/component performance; however, this comes with assembly challenges, in particular due to complex interfaces via subsurface bump bonds. The ability of these bonds to transmit electrical signals and conduct heat to the carrier substrate limits component performance. In this work, hyperspectral frequency‐domain thermoreflectance (FDTR) imaging is demonstrated as a robust technique for evaluating the quality of subsurface indium bump bonds in a surrogate microelectronic sample. By performing microscale FDTR imaging with coarse motion image stitching, thermal phase maps that cover a 4 mm by 4 mm field‐of‐view with subsurface feature sensitivity at depths greater than 50 µm are obtained. The resulting FDTR hyperspectral data contains more than three million pixels and reveal the quality of subsurface microbump arrays. Wide‐field analysis of bonded versus gap regions is enabled by deep neural network feature reconstruction, that after training, rapidly provides an interpretable representation of bond quality. Utility of noisy higher frequency FDTR phase maps, i.e., near the computationally predicted sensing depth limit, results in an average prediction error of 11%. Taken together, FDTR with neural network‐based analysis demonstrates subsurface bond monitoring at length scales relevant for heterogeneously integrated microelectronics.

FDTR

Directing Charge Carriers and Ferroelectric Domains at Lateral Interfaces in van der Waals Heterostructures

Emergent phenomena in traditional ferroelectrics are frequently observed at heterointerfaces. Accessing such functionalities in van der Waals ferroelectrics requires the formation of layered heterostructures, either vertically stacked (similar to oxide ferroelectrics) or laterally stitched (without equivalent in 3D-crystals). Here, we investigate lateral heterostructures of the ferroelectric van der Waals semiconductors SnSe and SnS. A two-step process produces ultrathin crystals comprising an SnSe core laterally joined to an SnS edge-band, as confirmed by Raman spectroscopy, transmission electron microscopy (TEM) imaging, and electron diffraction. TEM shows a moiré pattern across the SnSe core due to coverage by an ultrathin SnS layer. The ability of the lateral interface (IF) to direct excited carriers, probed by cathodoluminescence, shows electron transfer over 560 nm diffusion length from the SnS edge-band. Large, thin flakes supporting ferroelectricity allow investigating domains and domain wall interactions in uniform crystals and lateral heterostructures. Polarized optical microscopy of sub-20 nm flakes consistently shows ⟨110⟩ oriented stripe domains with mirror-twin domain walls. Heterostructures adopt two domain configurations, with domains either constrained to the SnSe core or propagating across the entire SnSe–SnS flakes. Furthermore, the combined results demonstrate multifunctional van der Waals heterostructures with high-quality IFs presenting extraordinary opportunities for manipulating carrier flows and ferroelectric domain patterns.

2D ferroelectrics

Substrate-Directed Underlayer Growth of Bilayer MoS 2 Revealed by Mo Isotope Labeling

Direct control over the vertical formation sequence and stacking registry in van der Waals (vdW) bilayers is essential for device performance and moiré engineering yet difficult to resolve unambiguously with conventional probes. Here, we use Mo isotope labeling in a two-step chemical vapor deposition process to synthesize bilayer MoS 2 and trace its vertical formation on common substrates. By combining site-selective laser thinning, Raman spectroscopy, time-of-flight secondary ion mass spectrometry, and atomic-resolution scanning transimission electron microscopy (STEM), we find a clear substrate dependence: on SiO 2 /Si, the second layer nucleates and grows beneath the first (underlayer), whereas on sapphire, it forms on top (overlayer). Density functional theory indicates that a larger equilibrium interfacial separation and weaker MoS 2 –substrate interactions on amorphous SiO 2 permit confined interfacial diffusion and underlayer nucleation, whereas stronger interactions and smaller separations on sapphire favor overlayer growth. On SiO 2 , confined epitaxy templates commensurate 2H, 3R, and mixed bilayers, as confirmed by second harmonic generation spectroscopy and STEM. During underlayer coalescence, embedded mirror-twin grain boundaries stitch atomically sharp 2H|3R junctions via alternating 4|8 ring motifs. Molecular-dynamics simulations reveal that these alternating 4|8 motifs accommodate interlayer vdW coupling and locally modulate the stacking registry. These results provide mechanistic insight into confined epitaxial growth and establish isotope labeling as a powerful probe of two-dimensional materials synthesis.

MoS2

Alkali-Metal Interlocking of 2D V 4 O 10 Sheets Defines Discretized Interlayer Shear Relationships

Low-dimensional materials manifest structural anisotropy, quantum confinement, and tightly bound excitonic states, which make them attractive building blocks that can be assembled within three-dimensional laterally stitched heterostructures, stacked van der Waals solids, and complex moiré superlattices. Ion intercalation in the galleries between layered materials provides a means of modifying interlayer separation and coupling, but it is also known to drive the shearing of the layers. In this article, we explore the distinct ligand coordination environments afforded by vanadyl oxygens of singular [V 4 O 10 ] sheets and examine how the size, polarizability, and stoichiometry of Group I cations sandwiched between such layers determine the interlocking of the sheets in stacked structures. Based on the topochemical insertion of alkali-metal ions into the layered λ-V 2 O 5 , we identify seven types of guest ion coordination sites discretized into four distinct regimes of interlayer shear in units of half octahedral widths. The coordination preferences of intercalated cations govern how they interlock 2D [V 4 O 10 ] sheets and engender specific shear conformations. We present evidence that static and dynamic disorder in guest ion arrangement modulate the magnetic structure of the intercalated compounds based on electrostatic polarization, localization of charge and spin density, and lattice distortion. The results illustrate the use of topochemical ion insertion to modulate stacking relationships and magnetic transition characteristics.

36 MATERIALS SCIENCE

Grayscale projection two-photon lithography using sub-diffraction motifs for ultrafast and precise nanoscale 3D printing

Rapid and high-fidelity nanoscale 3D printing is highly desirable, but it is difficult due to the tradeoff between speed and accuracy. Although optical projection techniques can massively scale up printing, fidelity is compromised due to the difficulty in precisely controlling the light dosage over the entire field. This challenge is typically addressed by using multiple projections, but it slows down printing. Here, we present grayscale projection two-photon lithography to overcome this tradeoff. Despite using a binary mask, it enables projecting more than 15,000 focal spots, each with independently tunable intensity. It advantageously leverages constraints imposed by optical diffraction to achieve grayscale tuning over the entire field at once. By directly tuning the focal spot intensities, we demonstrate suppression of proximity effects, compensation of non-uniform illumination, compensation of stitching artefacts, and rapid 3D printing with a single femtosecond pulse per layer. We demonstrate printing of nanowires as thin as 55 nm and achieve rates of 1.7 billion voxels/s and 215 mm 3 /hr.

36 MATERIALS SCIENCE

Analysis of biofilm assembly by large area automated AFM

Biofilms are complex microbial communities critical in medical, industrial, and environmental contexts. Understanding their assembly, structure, genetic regulation, interspecies interactions, and environmental responses is key to developing effective control and mitigation strategies. While atomic force microscopy (AFM) offers critically important high-resolution insights on structural and functional properties at the cellular and even sub-cellular level, its limited scan range and labor-intensive nature restricts the ability to link these smaller scale features to the functional macroscale organization of the films. We begin to address this limitation by introducing an automated large area AFM approach capable of capturing high-resolution images over millimeter-scale areas, aided by machine learning for seamless image stitching, cell detection, and classification. Large area AFM is shown to provide a very detailed view of spatial heterogeneity and cellular morphology during the early stages of biofilm formation which were previously obscured. Using this approach, we examined the organization of Pantoea sp. YR343 on PFOTS-treated glass surfaces. Our findings reveal a preferred cellular orientation among surface-attached cells, forming a distinctive honeycomb pattern. Detailed mapping of flagella interactions suggests that flagellar coordination plays a role in biofilm assembly beyond initial attachment. Additionally, we use large-area AFM to characterize surface modifications on silicon substrates, observing a significant reduction in bacterial density. This highlights the potential of this method for studying surface modifications to better understand and control bacterial adhesion and biofilm formation.

59 BASIC BIOLOGICAL SCIENCES