GHz operation of a quantum point contact using stub-impedance matching circuit
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Crystalline materials used in technological applications are often complex assemblies composed of multiple phases and differently oriented grains. Robust identification of the phases and orientation relationships from these samples is crucial, but the information extracted from the diffraction condition probed by an electron beam is often incomplete. We have developed an automated crystal orientation mapping (ACOM) procedure which uses a converged electron probe to collect diffraction patterns from multiple locations across a complex sample. We provide an algorithm to determine the orientation of each diffraction pattern based on a fast sparse correlation method. We demonstrate the speed and accuracy of our method by indexing diffraction patterns generated using both kinematical and dynamical simulations. We have also measured orientation maps from an experimental dataset consisting of a complex polycrystalline twisted helical AuAgPd nanowire. From these maps we identify twin planes between adjacent grains, which may be responsible for the twisted helical structure. All of our methods are made freely available as open source code, including tutorials which can be easily adapted to perform ACOM measurements on diffraction pattern datasets.
Here, we present a novel machine learning (ML)-based scoring technique for determining the similarity between experimental and predicted infrared (IR) spectra for identification purposes. IR spectroscopy is a powerful technique used to identify the molecular structure and composition of a sample by measuring the unique vibrational frequency pattern of the molecule’s functional groups. Molecular identifications are often made by comparing experimental and reference spectra. However, the limited number of reference spectra available in spectral libraries can confound the identification process. Alternative identification procedures rely on in silico techniques to simulate spectra for a wide range of molecules. However, scoring spectral similarity between an experimental query and computationally predicted reference remains a significant challenge. Our proposed ML-based scoring technique overcomes these barriers by accurately and efficiently determining spectral similarity.
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Here, perovskite and organic semiconductors can be combined to make tandem solar cells but, to date, their efficiency has hovered around 20%. Now, researchers demonstrate a 23.6% tandem by reducing interfacial defects to improve the perovskite cell's voltage and developing an ultrathin interconnection layer.
Studying the effect of resin RI on print fidelity. Chemically modifying RI resins to demonstrate 3D structures print without height limitation resulting on ceramic and nonceramic print as tall as 2.5 mm with sub-micron features.
Photochromic radionuclide-based “claw machines” characterizedviaa combination of isothermal titration calorimetry and spectroscopic analysis unlock a pathway for on demand radionuclide capture and release.
We would like to correct an error affecting the horizontal scale of panels (c) and (d) of Fig. 4 in Ref. 1. A scale factor of k p was neglected when generating the plots. The correct figure is shown below. Further, the authors would like to thank Yujian Zhao for pointing out this issue. We would also like to correct a typo introduced during the preparation of the proofs and affecting Eq. (25); the correct equation reads. (Formula presented). All the conclusions of the paper are unaffected.
A number of improvements to the TJ toroidal tearing mode code [Fitzpatrick, Phys. Plasmas 31, 102507 (2024)] are documented. The TJ code is also successfully benchmarked against the STRIDE toroidal tearing mode code [Glasser and Koleman, Phys. Plasmas 25, 082502 (2018)]. Finally, the new capabilities of the TJ code are used to investigate the stability of tearing modes in tokamak plasmas as an ideal stability boundary, associated with either an external-kink or an internal-kink mode, is approached. All elements of the tearing stability matrix are found to tend to infinity as an ideal stability boundary is approached. Furthermore, as the stability boundary is approached, the eigenfunctions of the various tearing modes in the plasma, which are decoupled by sheared plasma rotation, are all found to morph into that of the marginally stable ideal mode. However, the growth-rates and real frequencies of the various “ideal-tearing-modes” are different from one another. Moreover, the growth-rate of the ideal-tearing-mode that reconnects magnetic flux at the rational surface that lies closest to the edge of the plasma is the one that tends to a very large value as the stability boundary is approached. A relatively simple test for ideal stability that is capable of detecting stability boundaries for external-kink and internal-kink modes, even in the presence of a very close-fitting ideal wall, is described and verified.