Harbin Engineering University

About: Harbin Engineering University is a education organization based out in Harbin, Heilongjiang, China. It is known for research contribution in the topics: Control theory & Microstructure. The organization has 31149 authors who have published 27940 publications receiving 276787 citations. The organization is also known as: HEU.

N-Doped TiO2 Nanobelts with Coexposed (001) and (101) Facets and Their Highly Efficient Visible-Light-Driven Photocatalytic Hydrogen Production.

Abstract: To narrow the band gap (3.2 eV) of TiO2 and extend its practical applicability under sunlight, the doping with nonmetal elements has been used to tune TiO2 electronic structure. However, the doping also brings new recombination centers among the photoinduced charge carriers, which results in a quantum efficiency loss accordingly. It has been proved that the {101} facets of anatase TiO2 are beneficial to generating and transmitting more reductive electrons to promote the H2-evolution in the photoreduction reaction, and the {001} facets exhibit a higher photoreactivity to accelerate the reaction involved of photogenerated hole. Thus, it was considered by us that using the surface heterojunction composed of both {001} and {101} facets may depress the disadvantage of N doping. Fortunately, we successfully synthesized anatase N-doped TiO2 nanobelts with a surface heterojunction of coexposed (101) and (001) facets. As expected, it realized the charge pairs’ spatial separation and showed higher photocatalytic ac...

Contour Stella Image and Deep Learning for Signal Recognition in the Physical Layer

Abstract: The rapid development of communication systems poses unprecedented challenges, e.g., handling exploding wireless signals in a real-time and fine-grained manner. Recent advances in data-driven machine learning algorithms, especially deep learning (DL), show great potential to address the challenges. However, waveforms in the physical layer may not be suitable for the prevalent classical DL models, such as convolution neural network (CNN) and recurrent neural network (RNN), which mainly accept formats of images, time series, and text data in the application layer. Therefore, it is of considerable interest to bridge the gap between signal waveforms to DL amenable data formats. In this article, we develop a framework to transform complex-valued signal waveforms into images with statistical significance, termed contour stellar image (CSI), which can convey deep level statistical information from the raw wireless signal waveforms while being represented in an image data format. In this article, we explore several potential application scenarios and present effective CSI-based solutions to address the signal recognition challenges. Our investigation validates that CSI is a promising method to bridge the gap between signal recognition and DL.

Enabling high-volumetric-energy-density supercapacitors: designing open, low-tortuosity heteroatom-doped porous carbon-tube bundle electrodes

Abstract: In our work, we successfully design boron (B) and nitrogen (N) co-doped porous carbon tube bundle (B/N-PCTB) electrode materials which are directly derived from the biomass of dandelion fluff. The low-tortuosity, and open and porous structures contribute to electron transport along the tube wall and unimpeded ion diffusion inside the carbon tubes. The incorporation of heteroatoms into PCTBs can bring extra pseudocapacitance and double layer capacitance to enhance the overall capacitance. Benefiting from the hollow and open microstructure and heteroatom doping, the optimized B/N-PCTB electrode (active materials: 2.6 mg cm−2) possesses an impressive specific capacitance of 355 F g−1 at 1 A g−1. Even with an ultrahigh loading mass of 40 mg cm−2, the electrode still has a relatively high specific capacity of 216 F g−1 at 1 A g−1. The assembled symmetric cell with an active material loading of 80 mg cm−2 (cathode: 40 mg cm−2; anode: 40 mg cm−2) shows a superior volumetric energy density of 12.15 W h L−1 at the power density of 699.84 W L−1. The facile yet high-performance porous carbon tube bundle is a promising material which can be applied in many other fields such as lithium ion batteries, hydrogen evolution reaction, and heavy metal ion adsorption.