A5042335118- Force Microscopy Techniques and Applications
- Mechanical and Optical Resonators
- Catalytic Processes in Materials Science
- Nanomaterials for catalytic reactions
- Integrated Circuits and Semiconductor Failure Analysis
- Vibration and Dynamic Analysis
- Near-Field Optical Microscopy
- Piezoelectric Actuators and Control
- Bladed Disk Vibration Dynamics
- Fractional Differential Equations Solutions
- Catalysis and Oxidation Reactions
- Industrial Technology and Control Systems
- Sparse and Compressive Sensing Techniques
- Electrocatalysts for Energy Conversion
- Chaos control and synchronization
- Differential Equations and Numerical Methods
- Analytical Chemistry and Sensors
- Advanced Differential Equations and Dynamical Systems
- Image and Object Detection Techniques
- Catalysts for Methane Reforming
- Microfluidic and Capillary Electrophoresis Applications
- Domain Adaptation and Few-Shot Learning
- Fuel Cells and Related Materials
- Advanced Neural Network Applications
- Anomaly Detection Techniques and Applications
Southeast University
2025
Beihang University
1993-2024
China University of Geosciences
2024
University of Hong Kong
2021-2023
Donghua University
2019-2021
University of Shanghai for Science and Technology
2021
Michigan State University
2010-2016
East China University of Science and Technology
2011-2012
Taiyuan University of Technology
2009
Zhejiang Normal University
2004
The realization of room-temperature-operated, high-performance, miniaturized, low-power-consumption and Complementary Metal-Oxide-Semiconductor (CMOS)-compatible mid-infrared photodetectors is highly desirable for next-generation optoelectronic applications, but has thus far remained an outstanding challenge using conventional materials. Two-dimensional (2D) heterostructures provide alternative path toward this goal, yet despite continued efforts, their performance not matched that...
A<italic>para</italic>-aramid nonwoven fiber, composed of both microfibers and nanofibers, has been loaded with CuO–CeO<sub>2</sub>to remove solid gaseous pollutants.
We report on the synthesis and characterization of catalytic palladium nanoparticles (Pd NPs) their immobilization in microfluidic reactors fabricated from polydimethylsiloxane (PDMS). The Pd NPs were stabilized with D-biotin or 3-aminopropyltrimethoxysilane (APTMS) to promote inside reactors. homogeneous narrow size distributions between 2 4 nm, characterized by transmission electron microscopy (TEM), selected-area diffraction (SAED), x-ray (XRD). Biotinylated immobilized APTMS-modified...
A quartz tuning fork (QTF) has been widely used as a force sensor of the frequency modulation atomic microscope due to its ultrahigh stiffness, high quality factor and self-sensing nature. However, bulky structure exposed surface electrode arrangement, application is limited, especially in liquid imaging situ biological samples, ionic liquids, electrochemical reaction, etc. Although complication can be resolved by coating insulating materials on QTF then immersing whole into liquid, it would...
Using colloid-based methods to prepare supported catalytic metallic nanoparticles (NPs) often faces the challenge of removing stabilizer used during synthesis and activating catalyst without modifying particles or support. We explored three surface activation protocols (thermal oxidation at 150 ° C, thermal reduction 350 argon-protected calcination 650 C) activate ruthenium NPs on mesoporous silica (MSU-F), assessed their effects structural properties catalysts, activity by aqueous phase...
A novel deep neural network (DNN) architecture is proposed wherein the filtering and linear transform are realized solely with product quantization (PQ). This results in a natural implementation via content addressable memory (CAM), which transcends regular DNN layer operations requires only simple table lookup. Two schemes developed for end-to-end PQ prototype training, namely, through angle- distance-based similarities, differ their multiplicative additive natures different...
The tip motion of the dynamic atomic force microscope in liquids shows complex transient behaviors when using a low stiffness cantilever. second flexural mode cantilever is momentarily excited. Multiple impacts between and sample might occur one oscillation cycle. However, commonly used Fourier transform method cannot provide time-related information about these features. To overcome this limitation, we apply wavelet to perform time-frequency analysis liquids. momentary excitation phenomenon...
Recent results have revealed an interesting observation in a trained convolutional neural network (CNN), namely, the rank of feature map channel matrix remains surprisingly constant despite input images. This has led to effective rank-based pruning algorithm [23], yet phenomenon mysterious and unexplained. work aims at demystifying interpreting such behavior from frequency-domain perspective, which as bonus suggests extremely efficient Fast Fourier Transform (FFT)-based metric for measuring...
Learning convolutional neural networks (CNNs) with low bitwidth is challenging because performance may drop significantly after quantization. Prior arts often discretize the network weights by carefully tuning hyper-parameters of quantization (e.g. non-uniform stepsize and layer-wise bitwidths), which are complicated sub-optimal full-precision low-precision models have a large discrepancy. This work presents novel pipeline, Frequency-Aware Transformation (FAT), has several appealing...
Atomic force microscopy (AFM) has been an important tool for nanoscale imaging and characterization with atomic subatomic resolution. Theoretical investigations are getting highly the interpretation of AFM images. Researchers have used molecular simulation to examine mechanism. With a recent flurry researches applying machine learning AFM, images obtained from also as training data. However, is incredibly time consuming. In this paper, we apply super-resolution methods, including compressed...