Statistics-Based Gas Sensor

Khan, Shakir-ul Haque; Banerjee, Aishwaryadev; Broadbent, S.; Bulbul, Ashrafuzzaman; Simmons, Michelle Camilla; Kim, Kyeong Heon; Mastrangelo, Carlos H.; Looper, Ryan; Kim, Hanseup

doi:10.1109/memsys.2019.8870821

Cited by 7 publications

(4 citation statements)

References 5 publications

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“…These results suggest a highly selective sensor action against most commonly found VOCs. More details regarding these devices can be found here [57][58][59][60][61][62][63][64][65][66][67].…”

Section: Sensor Actionmentioning

confidence: 99%

Resurgence of Electron Quantum Tunneling Sensors

Banerjee

Mastrangelo

2022

Micro

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Quantum tunneling sensors are typically ultra-sensitive devices that have been specifically designed to convert a stimulus into an electronic signal using the wondrous principles of quantum mechanical tunneling. In the early 1990s, William Kaiser developed one of the first micromachined quantum tunneling sensors as part of his work with the NASA Jet Propulsion Laboratory. Since then, there have been scattered attempts at utilizing this phenomenon for the development of a variety of physical and chemical sensors. Although these devices demonstrate unique characteristics, such as high sensitivity, the principle of quantum tunneling often acts as a double-edged sword and is responsible for certain drawbacks of this sensor family. In this review, we briefly explain the underlying working principles of quantum tunneling and how they are used to design miniaturized quantum tunneling sensors. We then proceed to describe an overview of the various attempts at developing such sensors. Next, we discuss their current necessity and recent resurgence. Finally, we describe various advantages and shortcomings of these sensors and end this review with an insight into the potential of this technology and prospects.

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Section: Sensor Actionmentioning

confidence: 99%

Resurgence of Electron Quantum Tunneling Sensors

Banerjee

Mastrangelo

2022

Micro

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“…Garulli et al described a smart temperature-sensor design based on the architecture of CMOS 65 nm technology for use in the IoT network [ 197 ]. Kim et al have recently developed a novel sensing technique for highly sensitive biosensing based on the quantum-tunneling effect using nanogap break-junctions [ 198 , 199 , 200 , 201 , 202 , 203 , 204 , 205 , 206 ]. Furthermore, Mastrangelo et al have also been responsible for developing zero-power and highly sensitive polymeric sensors for VOC detection [ 207 , 208 , 209 , 210 , 211 , 212 , 213 ].…”

Section: Nano-biosensors For Cancer Detection and Future Prospectimentioning

confidence: 99%

Nanostructures for Biosensing, with a Brief Overview on Cancer Detection, IoT, and the Role of Machine Learning in Smart Biosensors

Banerjee

Maity

Mastrangelo

2021

Sensors

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Biosensors are essential tools which have been traditionally used to monitor environmental pollution and detect the presence of toxic elements and biohazardous bacteria or virus in organic matter and biomolecules for clinical diagnostics. In the last couple of decades, the scientific community has witnessed their widespread application in the fields of military, health care, industrial process control, environmental monitoring, food-quality control, and microbiology. Biosensor technology has greatly evolved from in vitro studies based on the biosensing ability of organic beings to the highly sophisticated world of nanofabrication-enabled miniaturized biosensors. The incorporation of nanotechnology in the vast field of biosensing has led to the development of novel sensors and sensing mechanisms, as well as an increase in the sensitivity and performance of the existing biosensors. Additionally, the nanoscale dimension further assists the development of sensors for rapid and simple detection in vivo as well as the ability to probe single biomolecules and obtain critical information for their detection and analysis. However, the major drawbacks of this include, but are not limited to, potential toxicities associated with the unavoidable release of nanoparticles into the environment, miniaturization-induced unreliability, lack of automation, and difficulty of integrating the nanostructured-based biosensors, as well as unreliable transduction signals from these devices. Although the field of biosensors is vast, we intend to explore various nanotechnology-enabled biosensors as part of this review article and provide a brief description of their fundamental working principles and potential applications. The article aims to provide the reader a holistic overview of different nanostructures which have been used for biosensing purposes along with some specific applications in the field of cancer detection and the Internet of things (IoT), as well as a brief overview of machine-learning-based biosensing.

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“…As a method to minimize the device uncertainty, a statistical concept of percolation was previously suggested and validated with limited experimental results with array size variations [4]. However, it lacked a holistic modeling and any expansion to other parameters, failing to provide fundamental understanding on its applicability to device operation.…”

Section: Introductionmentioning

confidence: 99%

Theoretical and Experimental Validation on the Tuning Capability of a Percolation-Based Gas Sensor.

Sium,

ul,

Noh

et al. 2022

2022 Solid-State, Actuators, and Microsystems Workshop Technical Digest

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This paper reports the theoretical and experimental validation of the tuning capability of a novel sensor based on percolation as the operation principle. To enable the tuning capability, an array of both the commercial and the microfabricated MEMS gas sensors was constructed. The array size and the degrees of freedom (DOF) for current flows within the array were manipulated. Theoretical and experimental results validated (1) that the percolation-based sensor tuning was feasible; (2) that the tuning became more deterministic with increasing array sizes and (3) the tuning threshold became lower with increasing DOF for current movement.

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Statistics-Based Gas Sensor

Cited by 7 publications

References 5 publications

Resurgence of Electron Quantum Tunneling Sensors

Resurgence of Electron Quantum Tunneling Sensors

Nanostructures for Biosensing, with a Brief Overview on Cancer Detection, IoT, and the Role of Machine Learning in Smart Biosensors

Theoretical and Experimental Validation on the Tuning Capability of a Percolation-Based Gas Sensor.

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