Ridge detection is a classical tool to extract curvilinear features in image processing. As such, it has great promise in applications to material science problems; specifically, for trend filtering relatively stable atom-shaped objects in image sequences, such as Transmission Electron Microscopy (TEM) videos. Standard analysis of TEM videos is limited to frame-by-frame object recognition. We instead harness temporal correlation across frames through simultaneous analysis of long image sequences, specified as a spatio-temporal image tensor. We define new ridge detection algorithms to non-parametrically estimate explicit trajectories of atomic-level object locations as a continuous function of time. Our approach is specially tailored to handle temporal analysis of objects that seemingly stochastically disappear and subsequently reappear throughout a sequence. We demonstrate that the proposed method is highly effective and efficient in simulation scenarios, and delivers notable performance improvements in TEM experiments compared to other material science benchmarks.

pdf/dynamic-atomic-column-detection-in-transmission-electron-3dqmsvti.pdf

Dynamic Atomic Column Detection in Transmission Electron Microscopy Videos via Ridge Estimation

Abstract. A photodetector that utilizes the phase-changing material Ge2Sb2Te5 (GST) integrated with a silicon on insulator (SOI) waveguide is designed and analyzed in the wavelength (λ) range of 1500 to 1600 nm for telecommunication and optical fiber communication. The analysis of simulated structure reveal that GST is a promising material for photodetection applications due to phase-change property on a nanoscale, excellent absorption (with an absorption coefficient of ∼106  cm  −  1), lower bandgap of 0.63 eV in the amorphous phase, and 0.53 eV in the crystalline phase, tunability, and high phase stability. The photodetector structure consists of an SOI substrate, silicon waveguide, GST layer as phase changing material, and gold (Au) to make contacts. The photodetector’s optical and electrical parameters, such as electric field distribution of carrier generation rate (G), absorbed power (Pabs), dark current (Idark), photocurrent (Iph), and responsivity (R), are analyzed for both the amorphous (a-GST) and crystalline (c-GST) phases. The results demonstrate the potential of GST material to design high-performance photodetectors for various applications. The highest resistivity of 2.29  A  /  W is achieved for a-GST at λ  =  1550  nm, with a bias voltage range of 0.5 to 2.5 V. The maximum absorption is observed in the amorphous phase as compared to the crystalline phase of GST. The calculated values of Iph and Idark are 0.24 mA and 78.54  μA for a-GST and 0.12 mA and 15.71  μA for c-GST, respectively. The optoelectrical behavior of GST-based photodetector on SOI waveguide demonstrates their potential application in photonic integrated circuits. Our work proposes an approach for using GST in photodetectors and analyzes both phases of GST that have not been explored before. Therefore, for the viability of the reported work, a detailed comparison is also presented with other simulated structures and found that the proposed device provided excellent results with low bias voltage.

Simulation of waveguide integrated Ge2Sb2Te5-based tunable photodetector

We propose a ﬂexible approach for the detection of features in images with ultra low signal-to-noise ratio using cubical persistent homology. Our main application is in the detection of atomic columns and other features in transmission electron microscopy (TEM) images. Cubical persistent homology is used to identify local minima in subregions in the frames of nanoparticle videos, which are hypothesized to correspond to relevant atomic features. We compare the performance of our algorithm to other employed methods for the detection of columns and their intensity. Additionally, Monte Carlo goodness-of-ﬁt testing using real-valued summaries of persistence diagrams—including the novel ALPS statistic—derived from smoothed images (generated from pixels residing in the vacuum region of an image) is developed and employed to identify whether or not the proposed atomic features generated by our algorithm are due to noise. Using these summaries derived from the generated persistence diagrams, one can produce univariate time series for the nanoparticle videos, thus providing a means for assessing ﬂuxional behavior. A guarantee on the false discovery rate for multiple Monte Carlo testing of identical hypotheses is also established.

Detection and hypothesis testing of features in extremely noisy image series using topological data analysis, with applications to nanoparticle videos

: A programmable hardware implementation of all-optical nonlinear activation functions for different scenarios and applications in all-optical neural networks is essential. We demonstrate a programmable, low-loss all-optical activation function device based on a silicon micro-ring resonator loaded with phase change materials. Four different nonlinear activation functions of Relu, ELU, Softplus and radial basis functions are implemented for incident signal light of the same wavelength. The maximum power consumption required to switch between the four different nonlinear activation functions in calculation is only 1.748 nJ. The simulation of classification of hand-written digit images also shows that they can perform well as alternative nonlinear activation functions. The device we design can serve as nonlinear units in photonic neural networks, while its nonlinear transfer function can be flexibly programmed to optimize the performance of different neuromorphic tasks.

Programmable low-power consumption all-optical nonlinear activation functions using a micro-ring resonator with phase-change materials

Manufacturing has undergone a greater change in recent years than it has over almost the entire past century. Due to the variety of products, shortening delivery times and changing customer habits, the COVID-19 pandemic has demanded greater flexibility from manufacturing companies than ever before. One of the fundamental parts of manufacturing flexibility is the design of manufacturing layouts, which has so far not followed automation and methodological developments with regard to technological areas of manufacturing. In this article, a new method for supporting traditional factory design methods with digital manufacturing tools is introduced.

Building a reusable data model to support systematic lay- out planning with discrete event simulation of flexible manufacturing systems

Strains and stresses in loaded and photoelastically coated structural members can be determined using the PhotoStress method. The quantitative values of variations in the principal strains (stresses) and their directions could be employed to get the strain or stress components field on the entire coated surface. In the PhotoStress experiment, isochromatic fringes give qualitative and quantitative information. It provides a source of information on the directions and magnitudes of principal strain and principal normal stress on the surface of photoelastic coated parts. This article reviews the principle of using PhotoStress analysis to measure the residual stress and provides the boundary condition of using this method.

Using the Photostress Method to Determine the Residual Stresses

: This supplemental document contains further details about the numerical simulations of the optical propagation, both in the linear and in the nonlinear regime. In accordance with the experiments, on the incident Gaussian beam a conical phase angle modulation is imparted by a spatial light modulator (SLM); the beam is then focused into the glass.

Manipulating geometric and optical properties of laser-inscribed nanogratings with a conical phase front: supplement

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