Low-frequency 1/f γ noise
is ubiquitous, even in high-end electronic devices. Recently, it was
found that adsorbed O2 molecules provide the dominant contribution
to flux noise in superconducting quantum interference devices. To
clarify the basic principles of such adsorbate noise, we have investigated
low-frequency noise, while the mobility of surface adsorbates is varied
by temperature. We measured low-frequency current noise in suspended
monolayer graphene Corbino samples under the influence of adsorbed
Ne atoms. Owing to the extremely small intrinsic noise of suspended
graphene, we could resolve a combination of 1/f γ and Lorentzian noise induced by the presence of Ne.
We find that the 1/f γ noise
is caused by surface diffusion of Ne atoms and by temporary formation
of few-Ne-atom clusters. Our results support the idea that clustering
dynamics of defects is relevant for understanding of 1/f noise in metallic systems.
This paper proposes a driving method, the superimposed pulse driving method, that can make an ultrasonic motor run at a low speed. Although this method solves the periodic oscillation of speed in a traditional low-speed driving motor, it still has a small periodic fluctuation, which affects the stability of the speed. To reduce the fluctuation rate of the motor speed, the structure model and driving model of the motor are established, based on the theory of a beat traveling wave, and the motion characteristics of the particle point are analyzed in this paper. The simulation curve of the motor speed is obtained according to the stator and rotor contact model and the transfer model. The research shows that the driving method introduced in this paper causes the stator surface to generate a traveling beat wave, and the driving end of the stator generates an intermittent reciprocating vibration and drives the rotor rotation, which is the mechanism of low-speed operation when the driving method is used to drive the motor, as well as the reason for the periodic fluctuation of the motor speed. To improve the speed stability, this paper controlled the output performance of the motor by changing the two control variables—prepressure and frequency difference—and concluded that the variation trend of the average speed and speed volatility were consistent with the variation trend of the motor’s average speed determinant and the speed volatility determinant, respectively, which is verified by the velocity measurement experiment and the vibration measurement experiment. These insights lay the theoretical foundation for the velocity adjustment and stability optimization and, finally, the application of the new driving method is prospected.
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