Dynamic evolution mechanism of scanning moiré fringes.

Scanning moiré fringes (SMFs) in scanning transmission electron microscopy (STEM) have a broad application prospect owing to the low-magnification imaging and hereto the low electron irritation damage, especially in defects localization, strain analysis etc. However, the dynamic evolution mechanism of SMFs is still not clear. In this paper, we carry out in-depth study of SMFs with ferroelectric material GeSe as an example. With the help of combination of aberration-corrected STEM imaging and geometrical model, we discuss the evolution of SMFs with variation of scanning step (magnification), and explain its quasiperiodic behavior in the experiments. Our results will deepen the understanding of SMFs, and may widen their applications under the guidance of the new formation mechanism.

Hyperspectral Tensor Completion Using Low-Rank Modeling and Convex Functional Analysis.

Hyperspectral tensor completion (HTC) for remote sensing, critical for advancing space exploration and other satellite imaging technologies, has drawn considerable attention from recent machine learning community. Hyperspectral image (HSI) contains a wide range of narrowly spaced spectral bands hence forming unique electrical magnetic signatures for distinct materials, and thus plays an irreplaceable role in remote material identification. Nevertheless, remotely acquired HSIs are of low data purity and quite often incompletely observed or corrupted during transmission. Therefore, completing the 3-D hyperspectral tensor, involving two spatial dimensions and one spectral dimension, is a crucial signal processing task for facilitating the subsequent applications. Benchmark HTC methods rely on either supervised learning or nonconvex optimization. As reported in recent machine learning literature, John ellipsoid (JE) in functional analysis is a fundamental topology for effective hyperspectral analysis. We therefore attempt to adopt this key topology in this work, but this induces a dilemma that the computation of JE requires the complete information of the entire HSI tensor that is, however, unavailable under the HTC problem setting. We resolve the dilemma, decouple HTC into convex subproblems ensuring computational efficiency, and show state-of-the-art HTC performances of our algorithm. We also demonstrate that our method has improved the subsequent land cover classification accuracy on the recovered hyperspectral tensor.

Dual Topology of Dirac Electron Transport and Photogalvanic Effect in Low-Dimensional Topological Insulator Superlattices.

Dual topological insulators, simultaneously protected by time-reversal symmetry and crystalline symmetry, open great opportunities to explore different symmetry-protected metallic surface states. However, the conventional dual topological states located on different facets hinder integration into planar opto-electronic/spintronic devices. Here, dual topological superlattices (TSLs) Bi2 Se3 -(Bi2 /Bi2 Se3 )N with limited stacking layer number N are constructed. Angle-resolved photoelectron emission spectra of the TSLs identify the coexistence and adjustment of dual topological surface states on Bi2 Se3 facet. The existence and tunability of spin-polarized dual-topological bands with N on Bi2 Se3 facet result in an unconventionally weak antilocalization effect (WAL) with variable WAL coefficient α (maximum close to 3/2) from quantum transport experiments. Most importantly, it is identified that the spin-polarized surface electrons from dual topological bands exhibit circularly and linearly polarized photogalvanic effect (CPGE and LPGE). It is anticipated that the stacked dual-topology and stacking layer number controlled bands evolution provide a platform for realizing intrinsic CPGE and LPGE. The results show that the surface electronic structure of the dual TSLs is highly tunable and well-regulated for quantum transport and photoexcitation, which shed light on engineering for opto-electronic/spintronic applications.

Fast determination of sample thickness through scanning moiré fringes in scanning transmission electron microscopy.

Sample thickness is an important parameter in transmission electron microscopy (TEM) imaging for interpreting image contrast and understanding the relationship between properties and microstructure. In this study, we introduce a method for sample thickness determination in scanning TEM (STEM) mode based on scanning moiré fringes (SMFs). Focal-series SMF imaging is used and sample thickness can be determined in situ at a medium magnification range, with beam damage and contamination avoided to a large extent. It provides a fast and convenient approach for determining sample thickness in TEM imaging, which is particularly useful for beam-sensitive materials.