分类： 光学 >> 量子光学 提交时间： 2023-02-19
摘要： Halide perovskite materials raised tremendous interest in recent years since their cheap fabrication, superior performance in both solar cell and light emitting diode (LED). Due to the existence of layered quantum well structure, quasi two-dimensional(2D) halide perovskite has more intriguing spin related physics than its 3D counterpart. For instance, the detection and brightening of dark exciton (DX) in 2D halide perovskite attracts much attention since these species can be used in opto-spintronic and quantum computing devices. Here, we report the gradually brightened emission of the DX at 2.33 eV with the thickness decreases in (PEA)2PbI4 single crystalline nanoflake, which hitherto has not been reported. By coupling with in-plane (IP) magnetic field in Voigt configuration, the DX emission can be sharply enhanced, while for the out-of-plane (OP) magnetic field in Faraday configuration, the DX emission has no noticeable change, which can be reconciled with the theory interpretation of magnetic field dependent wave function mixing between the four exciton states fi1, fi2, fi3- , fi3+. The emission of DX fi2 at 2.335 eV and the fine splitting of all the four states are observed in static PL spectroscopy for the first time. Our work thus clarifies the debating questions regarding to previous research on DX behavior in 2D halide perovskite material and sheds light on the road of realizing opto-spintronic or quantum computing devices with these materials.
分类： 物理学 >> 核物理学 提交时间： 2024-03-08
摘要： Neutron radiography is a crucial nondestructive testing technology widely used in the aerospace, military, andnuclear industries. However, because of the physical limitations of neutron sources and collimators, the resultingneutron radiographic images inevitably exhibit multiple distortions, including noise, geometric unsharpness,and white spots. Furthermore, these distortions are particularly significant in compact neutron radiography systemswith low neutron fluxes. Therefore, in this study, we devised a multi-distortion suppression network thatemploys a modified generative adversarial network to improve the quality of degraded neutron radiographic images.Real neutron radiographic image datasets with various types and levels of distortion were built for the firsttime as multi-distortion suppression datasets. Thereafter, the coordinate attention mechanism was incorporatedinto the backbone network to augment the capability of the proposed network to learn the abstract relationshipbetween ideally clear and degraded images. Extensive experiments were performed; the results show that theproposed method can effectively suppress multiple distortions in real neutron radiographic images and achievestate-of-the-art perceptual visual quality, thus demonstrating its application potential in neutron radiography.
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