The aim of this work is to model and analyze the behavior of a new smart nano force sensor.To do so,the carbon nanotube has been used as a suspended gate of a metal-oxide-semiconductor field-effect transistor(MOSFET)....The aim of this work is to model and analyze the behavior of a new smart nano force sensor.To do so,the carbon nanotube has been used as a suspended gate of a metal-oxide-semiconductor field-effect transistor(MOSFET).The variation of the applied force on the carbon nanotube(CNT)generates a variation of the capacity of the transistor oxide-gate and therefore the variation of the threshold voltage,which allows the MOSFET to become a capacitive nano force sensor.The sensitivity of the nano force sensor can reach 0.12431V/nN.This sensitivity is greater than results in the literature.We have found through this study that the response of the sensor depends strongly on the geometric and physical parameters of the CNT.From the results obtained in this study,it can be seen that the increase in the applied force increases the value of the MOSFET threshold voltage VTh.In this paper,we first used artificial neural networks to faithfully reproduce the response of the nano force sensor model.This neural model is called direct model.Then,secondly,we designed an inverse model called an intelligent sensor which allows linearization of the response of our developed force sensor.展开更多
This paper presents a compact analytical model for the organic field-effect transistors （OFETs）, which describes two main aspects, the first one is related to the behavior in above threshold regime, while the other ...This paper presents a compact analytical model for the organic field-effect transistors （OFETs）, which describes two main aspects, the first one is related to the behavior in above threshold regime, while the other corresponds to the below threshold regime. The total drain current in the OFET device is calculated as the sum of two components, with the inclusion of a smooth transition function in order to take into account both regions using a single expression. A genetic algorithm based approach （GA） is investigated as a parameter extraction tool in the case of the compact OFET model to find the parameters＇ values from experimental data such as： mobility enhancement factor % threshold voltage VTh, subthreshold swing S, channel length modulation A, and knee region sharpness m. The comparison of the developed current model with the experimental data shows a good agreement in terms of the transfer and the output characteristics. Therefore, the GA based approach can be considered as a competitive candidate compared to the direct method.展开更多
文摘The aim of this work is to model and analyze the behavior of a new smart nano force sensor.To do so,the carbon nanotube has been used as a suspended gate of a metal-oxide-semiconductor field-effect transistor(MOSFET).The variation of the applied force on the carbon nanotube(CNT)generates a variation of the capacity of the transistor oxide-gate and therefore the variation of the threshold voltage,which allows the MOSFET to become a capacitive nano force sensor.The sensitivity of the nano force sensor can reach 0.12431V/nN.This sensitivity is greater than results in the literature.We have found through this study that the response of the sensor depends strongly on the geometric and physical parameters of the CNT.From the results obtained in this study,it can be seen that the increase in the applied force increases the value of the MOSFET threshold voltage VTh.In this paper,we first used artificial neural networks to faithfully reproduce the response of the nano force sensor model.This neural model is called direct model.Then,secondly,we designed an inverse model called an intelligent sensor which allows linearization of the response of our developed force sensor.
文摘This paper presents a compact analytical model for the organic field-effect transistors （OFETs）, which describes two main aspects, the first one is related to the behavior in above threshold regime, while the other corresponds to the below threshold regime. The total drain current in the OFET device is calculated as the sum of two components, with the inclusion of a smooth transition function in order to take into account both regions using a single expression. A genetic algorithm based approach （GA） is investigated as a parameter extraction tool in the case of the compact OFET model to find the parameters＇ values from experimental data such as： mobility enhancement factor % threshold voltage VTh, subthreshold swing S, channel length modulation A, and knee region sharpness m. The comparison of the developed current model with the experimental data shows a good agreement in terms of the transfer and the output characteristics. Therefore, the GA based approach can be considered as a competitive candidate compared to the direct method.
