Yifan Gao

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We have applied the perturbation theory for calculating the piezoelectric potential distribution in a nanowire (NW) as pushed by a lateral force at the tip. The analytical solution given under the first-order approximation produces a result that is within 6% from the full numerically calculated result using the finite element method. The calculation shows(More)
Using phosphorus-doped ZnO nanowire (NW) arrays grown on silicon substrate, energy conversion using the p-type ZnO NWs has been demonstrated for the first time. The p-type ZnO NWs produce positive output voltage pulses when scanned by a conductive atomic force microscope (AFM) in contact mode. The output voltage pulse is generated when the tip contacts the(More)
Using a two-end bonded ZnO piezoelectric-fine-wire (PFW) (nanowire, microwire) on a flexible polymer substrate, the strain-induced change in I-V transport characteristic from symmetric to diode-type has been observed. This phenomenon is attributed to the asymmetric change in Schottky-barrier heights at both source and drain electrodes as caused by the(More)
A novel approach converts nanoscale mechanical energy into electric energy for self-powering nanodevices.In our own work, we've used piezoelectric zinc-oxide nanowire (ZnO NW) arrays to demonstrate a novel approach for converting nanoscale mechanical energy into electric energy. Here, we review the fundamental principle behind the nanogenerator, present an(More)
We report an external force triggered field-effect transistor based on a free-standing piezoelectric fine wire (PFW). The device consists of an Ag source electrode and an Au drain electrode at two ends of a ZnO PFW, which were separated by an insulating polydimethylsiloxane (PDMS) thin layer. The working principle of the sensor is proposed based on the(More)
We demonstrate a mechanical-electrical trigger using a ZnO piezoelectric fine-wire (PFW) (microwire, nanowire). Once subjected to mechanical impact, a bent PFW creates a voltage drop across its width, with the tensile and compressive surfaces showing positive and negative voltages, respectively. The voltage and current created by the piezoelectric effect(More)
This paper proposes a multi-level feature learning framework for human action recognition using body-worn inertial sensors. The framework consists of three phases, respectively designed to analyze signal-based (low-level), components (mid-level) and semantic (high-level) information. Low-level features , extracted from raw signals, capture the time and(More)