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Register a new userEvent driven 4D STEM acquisition with a Timepix3 detector: microsecond dwell time and faster scans for high precision and low dose applications
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Four dimensional scanning transmission electron microscopy (4D STEM) records the scattering of electrons in a material in great detail. The benefits offered by 4D STEM are substantial, with the wealth of data it provides facilitating for instance high precision, high electron dose efficiency phase imaging via center of mass or ptychography based analysis. However the requirement for a 2D image of the scattering to be recorded at each probe position has long placed a severe bottleneck on the speed at which 4D STEM can be performed. Recent advances in camera technology have greatly reduced this bottleneck, with the detection efficiency of direct electron detectors being especially well suited to the technique. However even the fastest frame driven pixelated detectors still significantly limit the scan speed which can be used in 4D STEM, making the resulting data susceptible to drift and hampering its use for low dose beam sensitive applications. Here we report the development of the use of an event driven Timepix3 direct electron camera that allows us to overcome this bottleneck and achieve 4D STEM dwell times down to 100~ns; orders of magnitude faster than what has been possible with frame based readout. We characterise the detector for different acceleration voltages and show that the method is especially well suited for low dose imaging and promises rich datasets without compromising dwell time when compared to conventional STEM imaging.
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4D-STEM, in which the 2D diffraction plane is captured for each 2D scan position in the scanning transmission electron microscope (STEM) using a pixelated detector, is complementing and increasingly replacing existing imaging approaches. However, at present the speed of those detectors, although having drastically improved in the recent years, is still 100 to 1,000 times slower than the current PMT technology operators are used to. Regrettably, this means environmental scanning-distortion often limits the overall performance of the recorded 4D data. Here we present an extension of existing STEM distortion correction techniques for the treatment of 4D-data series. Although applicable to 4D-data in general, we use electron ptychography and electric-field mapping as model cases and demonstrate an improvement in spatial-fidelity, signal-to-noise ratio (SNR), phase-precision and spatial-resolution.
The recent development of electron sensitive and pixelated detectors has attracted the use of four-dimensional scanning transmission electron microscopy (4D-STEM). Here, we present a precession electron diffraction assisted 4D-STEM technique for automated orientation mapping using diffraction spot patterns directly captured by an in-column scintillator based complementary metal-oxide-semiconductor (CMOS) detector. We compare the results to a conventional approach, which utilizes a fluorescent screen filmed by an external CCD camera. The high dynamic range and signal-to-noise characteristics of the detector largely improve the image quality of the diffraction patterns, especially the visibility of diffraction spots at high scattering angles. In the orientation maps reconstructed via the template matching process, the CMOS data yields a significant reduction of false indexing and higher reliability compared to the conventional approach. The angular resolution of misorientation measurement could also be improved by masking reflections close to the direct beam. This is because the orientation sensitive, weak and small diffraction spots at high scattering angle are more significant. The results show that fine details such as nanograins, nanotwins and sub-grain boundaries can be resolved with a sub-degree angular resolution which is comparable to orientation mapping using Kikuchi diffraction patterns.
With the next-generation Timepix3 hybrid pixel detector, new possibilities and challenges have arisen. The Timepix3 segments active sensor area of 1.98 $cm^2$ into a square matrix of 256 x 256 pixels. In each pixel, the Time of Arrival (ToA, with a time binning of 1.56 $ns$) and Time over Threshold (ToT, energy) are measured simultaneously in a data-driven, i.e. self-triggered, read-out scheme. This contribution presents a framework for data acquisition, real-time clustering, visualization, classification and data saving. All of these tasks can be performed online, directly from multiple readouts through UDP protocol. Clusters are reconstructed on a pixel-by-pixel decision from the stream of not-necessarily chronologically sorted pixel data. To achieve quick spatial pixel-to-cluster matching, non-trivial data structures (quadtree) are utilized. Furthermore, parallelism (i.e multi-threaded architecture) is used to further improve the performance of the framework. Such real-time clustering offers the advantages of online filtering and classification of events. Versatility of the software is ensured by supporting all major operating systems (macOS, Windows and Linux) with both graphical and command-line interfaces. The performance of the real-time clustering and applied filtration methods are demonstrated using data from the Timepix3 network installed in the ATLAS and MoEDAL experiments at CERN.
As part of an experiment to measure the spectrum of photons emitted in beta-decay of the free neutron, we developed and operated a detector consisting of 12 bismuth germanate (BGO) crystals coupled to avalanche photodiodes (APDs). The detector was operated near liquid nitrogen temperature in the bore of a superconducting magnet and registered photons with energies from 5 keV to 1000 keV. To enlarge the detection range, we also directly detected soft X-rays with energies between 0.2 keV and 20 keV with three large area APDs. The construction and operation of the detector is presented, as well as information on operation of APDs at cryogenic temperatures.
We present the design and characterization of a large-area Cryogenic PhotoDetector (CPD) designed for active particle identification in rare event searches, such as neutrinoless double beta decay and dark matter experiments. The detector consists of a $45.6$ $mathrm{cm}^2$ surface area by 1-mm-thick $10.6$ $mathrm{g}$ Si wafer. It is instrumented with a distributed network of Quasiparticle-trap-assisted Electrothermal feedback Transition-edge sensors (QETs) with superconducting critical temperature $T_c=41.5$ $mathrm{mK}$ to measure athermal phonons released from interactions with photons. The detector is characterized and calibrated with a collimated $^{55}$Fe X-ray source incident on the center of the detector. The noise equivalent power is measured to be $1times 10^{-17}$ $mathrm{W}/sqrt{mathrm{Hz}}$ in a bandwidth of $2.7$ $mathrm{kHz}$. The baseline energy resolution is measured to be $sigma_E = 3.86 pm 0.04$ $(mathrm{stat.})^{+0.23}_{-0.00}$ $(mathrm{syst.})$ $mathrm{eV}$ (RMS). The detector also has an expected timing resolution of $sigma_t = 2.3$ $mumathrm{s}$ for $5$ $sigma_E$ events.
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