Time-Resolved Charge Transport Sensing by Chemoreceptive Neuron MOS Transistors $({\rm C}\nu{\rm MOS})$ With Microfluidic Channels

Jacquot, Blake C.; Lee, Chungho; Shen, Ying‐Chun; Kan, Edwin C.

doi:10.1109/jsen.2007.904893

Cited by 10 publications

(4 citation statements)

References 32 publications

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“…The sensing transistor can thus be tuned to ensure maximum sensitivity. This principle is very similar to the chemoreceptive neuron MOS transistors 12 and the charge modulated FET sensors. 13 To further relate the sensing electrode potential V S with the experimentally accessible quality (i.e., the drain current I d ), we note that the general form of the I-V characteristics of a MOSFET can be expressed as I d = f(V gs ,V ds ) for sub-threshold, linear and saturated region, 14 where V gs equals the sensing electrode potential V S , and V ds is the drain voltage of the MOSFET.…”

Section: Device Principlementioning

confidence: 80%

Quantitative probing of surface charges at dielectric–electrolyte interfaces

et al. 2013

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The intrinsic charging status at the dielectric-electrolyte interface (DEI) plays a critical role for electrofluidic gating in microfluidics and nanofluidics, which offers opportunities for integration of wet ionics with dry electronics. A convenient approach to quantitatively probe the surface charges at the DEI for material pre-selection purpose has been lacking so far. We report here a low-cost, off-chip extended gate field effect transistor configuration for direct electrostatic probing the charging status at the DEI. Capacitive coupling between the surface charges and the floating extended gate is utilized for signal transducing. The relationship between the surface charge density and the experimentally accessible quantities is given by device modeling. The multiplexing ability makes measuring a local instead of a globally averaged surface charge possible.

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Section: Device Principlementioning

confidence: 80%

Quantitative probing of surface charges at dielectric–electrolyte interfaces

et al. 2013

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“…One of the unique features of the neuron transistors is the ultralow power dissipation during calculation due to the gate-level sum operation in a voltage mode. From then on, Si-based neuron transistors have attracted much attention for chemical and biological detection due to the easy adjustment of threshold voltage 16 17 18 19 20 . When an asymmetric gate capacitor structure is adopted, magnification of V th shift can be observed in the neuron transistor when the sensing gate experiences a load from electrolyte.…”

mentioning

confidence: 99%

Flexible Sensory Platform Based on Oxide-based Neuromorphic Transistors

Ning

Zhu

Feng

et al. 2015

Sci Rep

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Inspired by the dendritic integration and spiking operation of a biological neuron, flexible oxide-based neuromorphic transistors with multiple input gates are fabricated on flexible plastic substrates for pH sensor applications. When such device is operated in a quasi-static dual-gate synergic sensing mode, it shows a high pH sensitivity of ~105 mV/pH. Our results also demonstrate that single-spike dynamic mode can remarkably improve pH sensitivity and reduce response/recover time and power consumption. Moreover, we find that an appropriate negative bias applied on the sensing gate electrode can further enhance the pH sensitivity and reduce the power consumption. Our flexible neuromorphic transistors provide a new-concept sensory platform for biochemical detection with high sensitivity, rapid response and ultralow power consumption.

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“…Truman et al (2006) reported the use of silicon-based ISFETs for monitoring transport and chemical properties of liquids in microfluidic systems. Reliable, time-resolved ion, and molecular transport sensing in chemoreceptive neurons in microluidic channels using transistors has been demonstrated by Jacquot et al (2007). Tetraphenylborate derivatives have been used to modify ISFETs on polymeric microluidic devices for sensing cationic surfactants in dental rinses (Masadome et al 2006).…”

Section: Introductionmentioning

confidence: 99%