arXiv subjects

Qing Rao

Publications and source records attributed to Qing Rao.

5 recordsLinked to original sources

arXiv2023

Landau-level spectrum and the effect of spin-orbit coupling in monolayer graphene on transition metal dichalcogenides

In graphene on transition metal dichalcogenides, proximity-induced Rashba and spin-valley Zeeman SOCs can coexist that modify graphene's electronic band differently. Here, we show that the Landau levels (LLs) are also affected by these SOCs distinctively enough to estimate their relative strengths from the Landau fan diagram. Using a simple theoretical model, we calculated the LL spectrums of graphene for different SOC strengths, and found that when the total SOC is strong enough (i.e., when it is comparable to the half of the energy gap between the LLs of an intrinsic graphene), the corresponding LLs will split and cross with others depending sensitively on the relative strengths of the SOC terms. To demonstrate how one can use it to estimate the relative SOC strengths, we first identified the four key features that are well separated from the complex background and can be compared with experiment directly, and used them to show that in our sample, the Rashba SOC is stronger than the spin-valley Zeeman SOC that is consistent with other spectroscopic measurements. Our study therefore provides a simple and practical strategy to analyze the LL spectrum in graphene with SOC before carrying out more in-depth measurements.

cond-mat.mes-hall↗

arXiv2023

Scratching lithography, manipulation, and soldering of 2D materials using microneedle probes

We demonstrate a facile technique to scratch, manipulate, and solder exfoliated flakes of layered 2D materials using a microneedle probe attached to the precision xyz manipulators under an optical microscope. We show that the probe can be used to scratch the flakes into a designated shape with a precision at micrometer scales, move, rotate, roll-up, and exfoliate the flakes to help building various types of heterostructures, and form electric contacts by directly drawing/placing thin metal wires over the flake. All these can be done without lithography and etching steps that often take long processing time and involve harmful chemicals. Moreover, the setup can be easily integrated into any van der Waals assembly systems such as those in a glove box for handling air/chemical-sensitive materials. The microneedle technique demonstrated in this study therefore enables quick fabrications of devices from diverse 2D materials for testing their properties at an early stage of research before conducting more advanced studies and helps to build different types of van der Waals heterostructures.

physics.app-ph↗

arXiv2023

Ballistic transport spectroscopy of spin-orbit-coupled bands in monolayer graphene on WSe$_2$

Van der Waals interactions with transition metal dichalcogenides was shown to induce strong spin-orbit coupling (SOC) in graphene, offering great promises to combine large experimental flexibility of graphene with unique tuning capabilities of the SOC that can rotate spin by moving electrons or vice versa. Here, we probe SOC-driven band splitting and electron dynamics in graphene on WSe$_2$ by measuring ballistic transverse magnetic focusing. We found a clear splitting in the first focusing peak whose evolution in charge density and magnetic field is well reproduced by calculations using SOC strength of ~13 meV and no splitting in the second peak that indicates stronger Rashba SOC. A possible suppression of electron-electron scatterings was also found in temperature dependence measurement. Further, we found that Shubnikov-de Haas oscillations exhibit SOC strength of ~3.4 meV, suggesting that it probes different electron dynamics, calling for new theory. Our study demonstrates an interesting possibility to exploit ballistic electron motion pronounced in graphene for emerging spin-orbitronics.

cond-mat.mes-hall↗

arXiv2021

ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging

In this paper, we present an attention-guided deformable convolutional network for hand-held multi-frame high dynamic range (HDR) imaging, namely ADNet. This problem comprises two intractable challenges of how to handle saturation and noise properly and how to tackle misalignments caused by object motion or camera jittering. To address the former, we adopt a spatial attention module to adaptively select the most appropriate regions of various exposure low dynamic range (LDR) images for fusion. For the latter one, we propose to align the gamma-corrected images in the feature-level with a Pyramid, Cascading and Deformable (PCD) alignment module. The proposed ADNet shows state-of-the-art performance compared with previous methods, achieving a PSNR-$l$ of 39.4471 and a PSNR-$μ$ of 37.6359 in NTIRE 2021 Multi-Frame HDR Challenge.

cs.CV↗

arXiv2019

LiDAR-Flow: Dense Scene Flow Estimation from Sparse LiDAR and Stereo Images

We propose a new approach called LiDAR-Flow to robustly estimate a dense scene flow by fusing a sparse LiDAR with stereo images. We take the advantage of the high accuracy of LiDAR to resolve the lack of information in some regions of stereo images due to textureless objects, shadows, ill-conditioned light environment and many more. Additionally, this fusion can overcome the difficulty of matching unstructured 3D points between LiDAR-only scans. Our LiDAR-Flow approach consists of three main steps; each of them exploits LiDAR measurements. First, we build strong seeds from LiDAR to enhance the robustness of matches between stereo images. The imagery part seeks the motion matches and increases the density of scene flow estimation. Then, a consistency check employs LiDAR seeds to remove the possible mismatches. Finally, LiDAR measurements constraint the edge-preserving interpolation method to fill the remaining gaps. In our evaluation we investigate the individual processing steps of our LiDAR-Flow approach and demonstrate the superior performance compared to image-only approach.

cs.CV↗