The potential diagram for field-effect transistors used to detect charged biological macromolecules in an electrolyte is presented for the case where an insulating cover layer is used over a conventional eletrolyte-insulator metal-oxide-semiconductor (EIMOS) structure to tether or bind the biological molecules to a floating gate. The layer of macromolecules is modeled using the Poisson-Boltzmann equation for an ion-permeable membrane. Expressions are derived for the charges and potentials in the EIMOS and electrolyte-insulator-semiconductor structures, including the membrane and electrolyte. Exact solutions for the potentials and charges are calculated using numerical algorithms. Simple expressions for the response are presented for low solution potentials when the Donnan potential is approached in the bulk of the membrane. The implications of the model for the small-signal equivalent circuit and the noise analysis of these structures are discussed.

Field-effect sensors used to detect and identify biological species have been proposed as alternatives to other methods such as fluorescence deoxyribonucleic acid (DNA) microarrays. Sensors fabricated using commercial complementary metal-oxide-semiconductor technology would enable low-cost and highly integrated biological detection systems. In this paper, the small-signal and noise modeling of biosensors implemented with electrolyte-insulator-semiconductor structures is studied, with emphasis on design guidelines for low-noise performance. In doing so, a modified form of the general charge sheet metal-oxide-semiconductor field-effect transistor model that better fits the electrolyte-insulator-semiconductor structure is used. It is discussed how if the reference electrode and the insulator-electrolyte generate no noise associated with charge transport, then the main noise mechanisms are the resistive losses of the electrolyte and the low-frequency noise of the field-effect transistor. It is also found that for realistic sensor geometries and high electrolyte concentrations, the noise from the field-effect transistor (FET) dominates the thermal noise from the electrolyte resistance, and the optimal biasing point for the FET for minimum noise is found to be around moderate inversion.

No abstract

No abstract

No abstract

No abstract

No abstract

Articles you may be interested inHigh frequency and noise model of gate-all-around metal-oxide-semiconductor field-effect transistors J. Appl. Phys. 105, 074505 (2009); 10.1063/1.3093884 Parasitics-aware layout design of a low-power fully integrated complementary metal-oxide semiconductor power amplifier J. Vac. Sci. Technol. A 24, 835 (2006); 10.1116/1.2180269Scaling considerations for high performance 25 nm metal-oxide-semiconductor field effect transistors Broadband amplifiers implemented in complementary metal-oxide semiconductor technology offer a low-cost solution as gain elements for wideband communication systems. These components must maintain an acceptable target performance for a wide range of temperatures. We present experimental results for the gain, reflection coefficients, and group delay of a broadband amplifier operating from 2 to 14 GHz in the temperature range of 25-125°C. The high-frequency power gain drops by approximately 0.37 dB every 10°C of temperature increase, the maximum input and output refection coefficients change by less than 0.1 dB/ 10°C, and the change in the input-to-output group delay is negligible over the measured temperature range. The amplifier was simulated using temperature-dependent measurement-based models for the transistors, capacitors, and resistors and a single-temperature electromagnetic-simulation-based model for the inductors and interconnections. Simulated gain degradation is 0.22 dB/ 10°C, which suggests that the temperature effects on the inductors and interconnections lines are very important; however, temperature-dependent simulation is not a standard feature of electromagnetic ͑EM͒ simulators. It is thus important to include temperature effects when developing models based on EM simulations. Our results suggest that the key element to be considered is the conductor's resistivity increase with temperature.