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 & Computer science. The organization has 31149 authors who have published 27940 publications receiving 276787 citations. The organization is also known as: HEU.

γ-Fe2O3–MWNT/poly(p-phenylenebenzobisoxazole) composites with excellent microwave absorption performance and thermal stability

Abstract: Ferromagnetic γ-Fe2O3 nanoparticles were successfully loaded into multi-walled carbon nanotubes (MWNTs) as probed by transmission electron microscopy. Upon incorporation of the γ-Fe2O3–MWNTs into poly(p-phenylenebenzobisoxazole) (PBO), a conjugated polymer with high mechanical strength and outstanding thermal and oxidative stability, microwave absorbing materials were obtained. Attributed to the special structure of the γ-Fe2O3–MWNTs, synergistic effects on dielectric loss and magnetic loss, and a better matched characteristic impedance of the composites were achieved. The optimal minimum reflection loss reached −32.7 dB at 12.09 GHz on a composite containing 12 wt% γ-Fe2O3–MWNTs with a thickness of 2.7 mm, and the corresponding bandwidth below −5 dB was 6.2 GHz. This demonstrated its potential applications as a low-density microwave absorbing material operating under extreme environments.

Multifunctional Bismuth Ferrite Nanocatalysts with Optical and Magnetic Functions for Ultrasound-Enhanced Tumor Theranostics.

Abstract: Ultrasound (US)-assisted oncotherapy has aroused extensive attention due to its capacities to conquer significant restrictions covering short tissue penetration depth and high phototoxicity in photoinduced therapy. We herein developed a class of pure-phase perovskite-type bimetallic oxide, namely, bismuth ferrite nanocatalysts (BFO NCs), for multimodality imaging-guided and US-enhanced chemodynamic therapy (CDT) against malignant tumors. As-prepared BFO nanoparticles with poly(ethylene glycol)-grafted phosphorylated serine (pS-PEG) modification exhibit satisfactory physiological stability and biocompatibility. The BFO NCs also present high fluorescence emission within the second near-infrared region when irradiated with an 808 nm laser. Intriguingly, the BFO NCs demonstrate highly efficient US-enhanced generation of hydroxyl free radicals, as the cavitation bubbles produced by US trigger partial grievous turbulence and promote the transfer rate of the Fenton reagents. Thus, the BFO NCs enable effective inhibition of tumor growth assisted by external US, and the treatment efficacy can be monitored by computer tomography, magnetic resonance, and fluorescence imaging. Meanwhile, H2O2 and US, as a double logic gate, activate the BFO NCs to trigger the iron-catalyzed and US-enhanced CDT with high specificity and treatment efficiency. Therefore, the BFO NCs as a theranostic agent with an enhanced chemodynamic therapeutic effect assisted by external US and a multimodality imaging capacity are put forward, which show a promising prospect for noninvasive chemodynamic oncotherapy.

High gas sensing performance of one-step-synthesized Pd-ZnO nanoflowers due to surface reactions and modifications.

Abstract: Pd-ZnO nanoflowers with high uniformity were prepared via a novel one-step hydrothermal route. High sensitivity, fast response, high selectivity and low work temperature are obtained from Pd-ZnO nanoflower sensors. The sensitivity upon exposure to 300 ppm ethanol is up to 168 at 300 °C and maintains 2.6 at 120 °C. Such behaviors can be attributed to Schottky contact at the Pd/ZnO interface and catalytic activity of Pd nanoparticles. The present results open a way for uniform surface modification of one-dimensional nanostructures with Pd nanoparticles and further enhancing their gas sensing performance.

A Novel Kullback–Leibler Divergence Minimization-Based Adaptive Student's t-Filter

Abstract: In this paper, in order to improve the Student's t-matching accuracy, a novel Kullback-Leibler divergence (KLD) minimization-based matching method is firstly proposed by minimizing the upper bound of the KLD between the true Student's t-density and the approximate Student's t-density. To improve the Student's t-modelling accuracy, a novel KLD minimization-based adaptive method is then proposed to estimate the scale matrices of Student's t-distributions, in which the modified evidence lower bound is maximized. A novel KLD minimization-based adaptive Student's t-filter is derived via combining the proposed Student's t-matching technique and the adaptive method. A manoeuvring target tracking example is provided to demonstrate the effectiveness and potential of the proposed filter.