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Mechanical Nanosensors
Published in Vinod Kumar Khanna, Nanosensors, 2021
where W0 and ΔW0 are the mechanical energy accumulated and dissipated, respectively, in the device per vibration cycle. As the Q-factor critically controls both the resonance behavior of any microcantilever and its off-resonance thermal noise, it is an important parameter characterizing MEMS/NEMS sensors operating in resonance as well as in static regimes. Thermal noise is the noise generated by thermal agitation of electrons in a conductor. The noise power, P, in watts, is given by P = kBTΔf, where kB is Boltzmann’s constant in joules per Kelvin, T is the conductor temperature in Kelvin, and Δf is the bandwidth in hertz. Thermal noise power, per hertz, is equal throughout the frequency spectrum, depending only on kB and T.
CMOS Circuits
Published in Michael Olorunfunmi Kolawole, Electronics, 2020
Thermal noise is caused by the thermal agitation of charge carriers (electrons or holes) in a conductor and can be modeled as voltage or current. This noise is present in all passive resistive elements even without a current flowing in the resistive medium. Spectrum describes the frequency content of noise, which allows its density being used to specify noise parameters. S(f) denotes the power spectral density of a noise waveform. For a series voltage source (as modeled in Figure 6.1a), the thermal noise of resistive conductor is expressed as Stnv(f)=Vtn−r2¯=∫(4kTR)df
Measurement
Published in David M. Scott, Industrial Process Sensors, 2018
Mechanical vibrations and electrical ground loops contribute stochastic noise to the process measurement, but it often happens that such noise is dominated by a few component frequencies. Truly random electrical noise is caused by loose or corroded electrical connections and electronic amplification. When an electrical connection becomes loose or corroded, a slight voltage difference may develop across the junction. This voltage is not well defined because the junction resistance is not well defined, and the fluctuating voltage affects the sensor output in an unpredictable manner. Other sources of random electrical noise include shot noise and thermal noise (see for example Fraden 1996, pp. 212ff). Shot noise is caused by the fact that electrical current is conducted by electrons; the current appears to be continuous, but it is in reality a rapid and random succession of charge transfer events. Thermal noise is due to the random motion of electrons in a conductor; this motion is dependent on the temperature of the conductor, so an increase in temperature produces an increase in thermal noise.
Imaging resolution and properties analysis of super resolution microscopy with parallel detection under different noise, detector and image restoration conditions
Published in Journal of Modern Optics, 2018
Zhongzhi Yu, Shaocong Liu, Shiyi Sun, Cuifang Kuang, Xu Liu
The noise in PMT is extremely low and almost can be neglectable (21) so that the shot noise and background noise from the imaging process are the main noise considered. Noise in APD and SPAD majorly contains quantum noise, multiplication noise, noise caused by dark current and thermal noise (22–25). The quantum noise and dark current noise are all shot noise which follows the Poisson distribution, and the thermal noise is caused by the electron’s Brown motion that can be simulated by Gaussian white noise. Specifically, multiplication noise is actually a multiplicative correction applied to the noise that describes the increase in the statistical noise, specifically Poisson noise, due to the multiplication process. Therefore, the multiplication noise can also be simply expressed as the amplified Poisson noise. CCD has dark current noise, shot noise and read noise (26). Among them, the read noise can be stimulated as random noise because the read noise is caused by the incomplete electron transfer which is mostly a random process in CCD. Noise in CMOS includes thermal noise which is discussed before, and flicker noise (27,28) which is the noise that appears in the low frequency region. Therefore, we used the Gaussian noise to simulate flicker noise and use low and high cut-off frequency to limit the frequency region flicker noise affects.
A Novel Technique Applying Spectral Estimation to Johnson Noise Thermometry
Published in Nuclear Technology, 2018
N. Dianne Bull Ezell, Chuck Britton, Nance Ericson, David Holcomb, M. J. Roberts, Seddik Djouadi, Richard Wood
There are several sources of EMI in and around nuclear reactor facilities that may corrupt temperature measurements. Mechanical vibrations, pumps, and other equipment are EMI contributors.3 For this reason, the front-end electronics must be very low noise and shielding is required. ORNL studied two types of EMI: transient and periodic. Spectral estimation is a key component in the signal processing algorithm used for EMI removal and temperature calculation. Applying spectral estimation requires the addition of specialized electronics and signal processing to existing resistive thermometers. The electronics are composed of a dual-mode resistance and Johnson noise thermometer in a rugged, integrated prototype form.3 The resistance measurement serves the dual purpose of providing a real-time fast temperature measurement and providing an independent measurement for Nyquist equation computation. The Nyquist equation describes the voltage produced by the motion of electrons within a resistor at a given temperature. The most valuable contribution of the research is the addition of the signal processing using spectral estimation techniques. Because thermal noise in any conductive material is Brownian motion of electrons due to ambient temperature, the measurement is simply the observation of random motion.2 Therefore, any nonrandom or periodic EMI can be detected in the frequency domain as a spike and removed leaving only the random transient EMI. Transient EMI is removed by detecting outliers in the time-domain signals.
Single-ion, transportable optical atomic clocks
Published in Journal of Modern Optics, 2018
Marion Delehaye, Clément Lacroûte
The ultimate performance of a FP resonator is limited by its length fluctuations at a finite temperature T, characterized by the thermal noise [77,78]. The thermal noise can be lowered by working at low temperatures and/or by using materials with low mechanical losses, such as fused silica or single-crystal silicon. Crystalline highly reflective coatings, which have a higher mechanical quality factor than traditional dielectric coatings, have also proved to reduce the thermal noise while still achieving high finesses [79].