University of Electronic Science and Technology of China

About: University of Electronic Science and Technology of China is a education organization based out in Chengdu, China. It is known for research contribution in the topics: Computer science & Antenna (radio). The organization has 50594 authors who have published 58502 publications receiving 711188 citations. The organization is also known as: UESTC.

Identification of Key Reversible Intermediates in Self-Reconstructed Nickel-Based Hybrid Electrocatalysts for Oxygen Evolution

Abstract: The oxygen evolution reaction (OER) has been explored extensively for reliable hydrogen supply to boost the energy conversion efficiency. The superior OER performance of newly developed non-noble metal electrocatalysts has concealed the identification of the real active species of the catalysts. Now, the critical active phase in nickel-based materials (represented by NiNPS) was directly identified by observing the dynamic surface reconstruction during the harsh OER process via combining in situ Raman tracking and ex situ microscopy and spectroscopy analyses. The irreversible phase transformation from NiNPS to α-Ni(OH)2 and reversible phase transition between α-Ni(OH)2 and γ-NiOOH prior to OER demonstrate γ-NiOOH as the key active species for OER. The hybrid catalyst exhibits 48-fold enhanced catalytic current at 300 mV and remarkably reduced Tafel slope to 46 mV dec-1 , indicating the greatly accelerated catalytic kinetics after surface evolution.

Emotion Recognition from EEG Signals Using Multidimensional Information in EMD Domain.

Abstract: This paper introduces a method for feature extraction and emotion recognition based on empirical mode decomposition (EMD). By using EMD, EEG signals are decomposed into Intrinsic Mode Functions (IMFs) automatically. Multidimensional information of IMF is utilized as features, the first difference of time series, the first difference of phase, and the normalized energy. The performance of the proposed method is verified on a publicly available emotional database. The results show that the three features are effective for emotion recognition. The role of each IMF is inquired and we find that high frequency component IMF1 has significant effect on different emotional states detection. The informative electrodes based on EMD strategy are analyzed. In addition, the classification accuracy of the proposed method is compared with several classical techniques, including fractal dimension (FD), sample entropy, differential entropy, and discrete wavelet transform (DWT). Experiment results on DEAP datasets demonstrate that our method can improve emotion recognition performance.

Optical trapping with structured light: a review

Abstract: Optical trapping describes the interaction between light and matter to manipulate micro-objects through momentum transfer. In the case of 3D trapping with a single beam, this is termed optical tweezers. Optical tweezers are a powerful and noninvasive tool for manipulating small objects, and have become indispensable in many fields, including physics, biology, soft condensed matter, among others. In the early days, optical trapping was typically accomplished with a single Gaussian beam. In recent years, we have witnessed rapid progress in the use of structured light beams with customized phase, amplitude, and polarization in optical trapping. Unusual beam properties, such as phase singularities on-axis and propagation invariant nature, have opened up novel capabilities to the study of micromanipulation in liquid, air, and vacuum. We summarize the recent advances in the field of optical trapping using structured light beams.