arXiv subjects

Silu Guo

Publications and source records attributed to Silu Guo.

4 recordsLinked to original sources

arXiv2026

Electron Beam Radiolysis-Assisted Growth of Rutile TiO2 Thin Films

A new approach for growing crystalline thin films is developed that takes advantage of electron beam radiolysis being a constructive force to rearrange atoms into a crystalline structure. It is demonstrated that by irradiating the surface of a TiO2 film by an electron beam supplied by a reflection high energy electron diffraction (RHEED) gun inside the MBE chamber during growth, a crystalline film can be grown at much lower substrate temperatures, where deposited films typically appear amorphous. Here, rutile TiO2 films were grown using hybrid molecular beam epitaxy (MBE) allowing atomic level control of growth as well as an observation of radiolysis-driven crystallization. Analysis was carried out using a combination of SEM and atomic-resolution STEM imaging. It is also shown that by tuning the temperature of the substrate and the dose of the electron beam, the degree of crystallinity of the film can be controlled.

cond-mat.mtrl-sci↗

arXiv2024

Deep-ultraviolet transparent conducting SrSnO3 via heterostructure design

Exploration and advancements in ultra-wide bandgap (UWBG) semiconductors are pivotal for next-generation high-power electronics and deep-ultraviolet (DUV) optoelectronics. A critical challenge lies in finding a semiconductor that is highly transparent to DUV wavelengths yet conductive with high mobility at room temperature. Here, we achieved both high transparency and high conductivity by employing a thin heterostructure design. The heterostructure facilitated high conductivity by screening phonons using free carriers, while the atomically thin films ensured high transparency. We utilized a heterostructure comprising SrSnO3/La:SrSnO3/GdScO3 (110) and applied electrostatic gating to effectively separate electrons from their dopant atoms. This led to a modulation of carrier density from 1018 cm-3 to 1020 cm-3, with room temperature mobilities ranging from 40 to 140 cm2V-1s-1. The phonon-limited mobility, calculated from first principles, closely matched experimental results, suggesting that room-temperature mobility could be further increased with higher electron density. Additionally, the sample exhibited 85% optical transparency at a 300 nm wavelength. These findings highlight the potential of heterostructure design for transparent UWBG semiconductor applications, especially in deep-ultraviolet regime.

cond-mat.mtrl-sci↗

arXiv2023

Mending Cracks in Rutile TiO$_{2}$ with Electron Beam

Restructuring of rutile TiO$_{2}$ under electron beam irradiation driven by radiolysis was observed and analyzed using a combination of atomic-resolution imaging and electron energy loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM). It was determined that a high-energy (80-300 keV) electron beam at high doses ($\gtrapprox 10^7 \ e/nm^2$) can constructively restructure rutile TiO$_{2}$ with an efficiency of $6\times 10^{-6}$. These observations were realized using rutile TiO$_{2}$ samples with atomically sharp nanometer-wide cracks. Based on atomic-resolution STEM imaging and quantitative EELS analysis, we propose a $"$ 2-step $"$ rolling model of the octahedral building blocks of the crystal to account for observed radiolysis-driven atomic migration.

cond-mat.mtrl-sci↗

arXiv2020

3D Object Detection and Tracking Based on Streaming Data

Recent approaches for 3D object detection have made tremendous progresses due to the development of deep learning. However, previous researches are mostly based on individual frames, leading to limited exploitation of information between frames. In this paper, we attempt to leverage the temporal information in streaming data and explore 3D streaming based object detection as well as tracking. Toward this goal, we set up a dual-way network for 3D object detection based on keyframes, and then propagate predictions to non-key frames through a motion based interpolation algorithm guided by temporal information. Our framework is not only shown to have significant improvements on object detection compared with frame-by-frame paradigm, but also proven to produce competitive results on KITTI Object Tracking Benchmark, with 76.68% in MOTA and 81.65% in MOTP respectively.

cs.CV↗