Low-noise smart sensor based on silicon nanowire for MEMS resistive microphone

Nebhen, Jamel; Rahajandraibe, W.; Dufaza, C.; Meillere, S.; Kussener, Edith; Barthélémy, H.; Czarny, Jaroslaw; Walther, Arnaud

doi:10.1109/icsens.2013.6688605

Cited by 7 publications

(5 citation statements)

References 7 publications

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“…In [8], nanowire microphones of an artificial cochlea exploit piezo resistivity to capture an acoustic vibration and transduces it to an electrical signal of a few millivolts amplitude in the frequency range from 20 Hz to 20 kHz. Traditionally, cochlea circuitry includes an analog front end [9] and multibit DR modulators in order to analog-todigital convert the transduced audio signal.…”

Section: Introductionmentioning

confidence: 99%

Neuromorphic analog spiking-modulator for audio signal processing

Ferreira

Nebhen

Klisnick

et al. 2020

Analog Integr Circ Sig Process

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While CMOS scaling is currently reaching its limits in power dissipation and circuit density, the analogy between biology and silicon is emerging as a solution to ultra-low-power signal processing. Urgent applications involving artificial vision and audition, including intelligent sensing, appeal original energy efficient and ultra-miniaturized silicon-based solutions. While state-of-the-art is focusing on digital-oriented solutions, this paper proposes a neuromorphic analog signal processor using Izhikevich-based artificial neurons in an analog spiking modulator. A varicap-based artificial neuron is explored reducing the silicon area to 98:6 lm 2 and the substrate leakage to a 1:95 fJ=spike efficiency. Post-layout simulation results are presented to investigate the high-resolution, high-speed, and full-scale dynamic range for audio signal processing applications. The proposal demonstrates a 9 bits spiking-modulator resolution, a maximum of 8 fJ=conv efficiency, and a root-mean-square error of 0:63 mV RMS .

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Section: Introductionmentioning

confidence: 99%

Neuromorphic analog spiking-modulator for audio signal processing

Ferreira

Nebhen

Klisnick

et al. 2020

Analog Integr Circ Sig Process

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“…Horizontally grown SiNW arrays on cantilevers have been tested for piezoresistive strain sensing [166]. SiNW strain gauges used in place of input resistors of delta modulator in a MEMS microphone help reduce noise [167]. SiNW-based strain gauges are also part of 3D magnetometers [168].…”

Section: Resonators and Strain Gaugesmentioning

confidence: 99%

Silicon nanowire piezoresistor and its applications: a review

Raman,

K V,

et al. 2024

Nanotechnology

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Monocrystalline bulk silicon with doped impurities has been the widely preferred piezoresistive material for the last few decades to realize micro-electromechanical system (MEMS) sensors. However, there has been a growing interest among researchers in the recent past to explore other piezoresistive materials with varied advantages in order to realize ultra-miniature high-sensitivity sensors for area-constrained applications. Of the various alternative piezoresistive materials, silicon nanowires (SiNWs) are an attractive choice due to their benefits of nanometre range dimensions, giant piezoresistive coefficients, and compatibility with the integrated circuit (IC) fabrication processes. This review article elucidates the fundamentals of piezoresistance and its existence in various materials, including silicon. It comprehends the piezoresistance effect in SiNWs based on two different biasing techniques, viz., (i) ungated and (ii) gated SiNWs. In addition, it presents the application of piezoresistive SiNWs in MEMS-based pressure sensors, acceleration sensors, flow sensors, resonators, and strain gauges.

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“…As a result, a noise density of 7 nV Hz À1/2 in the frequency range from 10 Hz to 10 kHz is achieved. [133,137] To increase the resolution to 95 nV bits À1 , a 65 nm CMOS integrated circuit is also used. [138] The device is recently investigated for its potential in IoT applications, [139] where a power consumption of 0.4 mW is achieved with an SNR of 77 dB and a bandwidth of 20 kHz.…”

Section: Microphonesmentioning

confidence: 99%

Silicon Nanowires Driving Miniaturization of Microelectromechanical Systems Physical Sensors: A Review

et al. 2023

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The miniaturization of microelectromechanical systems (MEMS) physical sensors is driven by global connectivity needs and is closely linked to emerging digital technologies and the Internet of Things. Strong technical advantages of miniaturization such as improved sensitivity, functionality, and power consumption are accompanied by significant economic benefits due to semiconductor manufacturing. Hence, the trend to produce smaller sensors and their driving force resemble very much those of the miniaturization of integrated circuits (ICs) as described by Moore's law. In this respect, with its IC‐, and MEMS‐compatibility, and scalability, the silicon nanowire is frequently employed in frontier research as the sensor building block replacing conventional sensors. The integration of the silicon nanowire with MEMS has thus generated a multiscale hybrid architecture, where the silicon nanowire serves as the piezoresistive transducer and MEMS provide an interface with external forces, such as inertial or magnetic. This approach has been reported for almost all physical sensor types over the last decade. These sensors are reviewed here with detailed classification. In each case, associated technological challenges and comparisons with conventional counterparts are provided. Future directions and opportunities are highlighted.

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Low-noise smart sensor based on silicon nanowire for MEMS resistive microphone

Cited by 7 publications

References 7 publications

Neuromorphic analog spiking-modulator for audio signal processing

Neuromorphic analog spiking-modulator for audio signal processing

Silicon nanowire piezoresistor and its applications: a review

Silicon Nanowires Driving Miniaturization of Microelectromechanical Systems Physical Sensors: A Review

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