Harbin Institute of Technology

About: Harbin Institute of Technology is a education organization based out in Harbin, China. It is known for research contribution in the topics: Microstructure & Control theory. The organization has 88259 authors who have published 109297 publications receiving 1603393 citations. The organization is also known as: HIT.

Synergistic effects from graphene and carbon nanotubes enable flexible and robust electrodes for high-performance supercapacitors.

Abstract: Flexible and lightweight energy storage systems have received tremendous interest recently due to their potential applications in wearable electronics, roll-up displays, and other devices. To manufacture such systems, flexible electrodes with desired mechanical and electrochemical properties are critical. Herein we present a novel method to fabricate conductive, highly flexible, and robust film supercapacitor electrodes based on graphene/MnO2/CNTs nanocomposites. The synergistic effects from graphene, CNTs, and MnO2 deliver outstanding mechanical properties (tensile strength of 48 MPa) and superior electrochemical activity that were not achieved by any of these components alone. These flexible electrodes allow highly active material loading (71 wt % MnO2), areal density (8.80 mg/cm2), and high specific capacitance (372 F/g) with excellent rate capability for supercapacitors without the need of current collectors and binders. The film can also be wound around 0.5 mm diameter rods for fabricating full cells...

Lightweight, Superelastic, and Mechanically Flexible Graphene/Polyimide Nanocomposite Foam for Strain Sensor Application.

Abstract: The creation of superelastic, flexible three-dimensional (3D) graphene-based architectures is still a great challenge due to structure collapse or significant plastic deformation. Herein, we report a facile approach of transforming the mechanically fragile reduced graphene oxide (rGO) aerogel into superflexible 3D architectures by introducing water-soluble polyimide (PI). The rGO/PI nanocomposites are fabricated using strategies of freeze casting and thermal annealing. The resulting monoliths exhibit low density, excellent flexibility, superelasticity with high recovery rate, and extraordinary reversible compressibility. The synergistic effect between rGO and PI endows the elastomer with desirable electrical conductivity, remarkable compression sensitivity, and excellent durable stability. The rGO/PI nanocomposites show potential applications in multifunctional strain sensors under the deformations of compression, bending, stretching, and torsion.

Oxidative Stress and the Pathogenesis of Alzheimer's Disease

Abstract: Alzheimer's disease (AD) is the most common neurodegenerative disease that causes dementia in the elderly. Patients with AD suffer a gradual deterioration of memory and other cognitive functions, which eventually leads to a complete incapacity and death. A complicated array of molecular events has been implicated in the pathogenesis of AD. The major pathological characteristics of AD brains are the presence of senile plaques, neurofibrillary tangles, and neuronal loss. Growing evidence has demonstrated that oxidative stress is an important factor contributing to the initiation and progression of AD. However, the mechanisms that lead to the disruption of redox balance and the sources of free radicals remain elusive. The excessive reactive oxygen species may be generated from mechanisms such as mitochondria dysfunction and/or aberrant accumulation of transition metals, while the abnormal accumulation of Abeta and tau proteins appears to promote the redox imbalance. The resulted oxidative stress has been implicated in Abeta- or tau-induced neurotoxicity. In addition, evidence has suggested that oxidative stress may augment the production and aggregation of Abeta and facilitate the phosphorylation and polymerization of tau, thus forming a vicious cycle that promotes the initiation and progression of AD.

Histogram of Gabor Phase Patterns (HGPP): A Novel Object Representation Approach for Face Recognition

Abstract: A novel object descriptor, histogram of Gabor phase pattern (HGPP), is proposed for robust face recognition. In HGPP, the quadrant-bit codes are first extracted from faces based on the Gabor transformation. Global Gabor phase pattern (GGPP) and local Gabor phase pattern (LGPP) are then proposed to encode the phase variations. GGPP captures the variations derived from the orientation changing of Gabor wavelet at a given scale (frequency), while LGPP encodes the local neighborhood variations by using a novel local XOR pattern (LXP) operator. They are both divided into the nonoverlapping rectangular regions, from which spatial histograms are extracted and concatenated into an extended histogram feature to represent the original image. Finally, the recognition is performed by using the nearest-neighbor classifier with histogram intersection as the similarity measurement. The features of HGPP lie in two aspects: 1) HGPP can describe the general face images robustly without the training procedure; 2) HGPP encodes the Gabor phase information, while most previous face recognition methods exploit the Gabor magnitude information. In addition, Fisher separation criterion is further used to improve the performance of HGPP by weighing the subregions of the image according to their discriminative powers. The proposed methods are successfully applied to face recognition, and the experiment results on the large-scale FERET and CAS-PEAL databases show that the proposed algorithms significantly outperform other well-known systems in terms of recognition rate