<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">F.Menacer</style></author><author><style face="normal" font="default" size="100%">Dibi Zohir</style></author><author><style face="normal" font="default" size="100%">A.Kadri</style></author><author><style face="normal" font="default" size="100%">DJEFFAL Fayçal</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A new smart nanoforce sensor based on suspended gate SOIMOSFET using carbon nanotube ISSN / e-ISSN 0263-2241 / 1873- 412X</style></title><secondary-title><style face="normal" font="default" size="100%">MeasurementMeasurement</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">Volume 125</style></volume><pages><style face="normal" font="default" size="100%">Pages 232-242</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper presents a new nanoforce sensor based on a suspended carbon&amp;nbsp;nanotube&amp;nbsp;gate&amp;nbsp;field-effect transistor. To do so, a numerical investigation of Suspended Gate&amp;nbsp;Silicon-on-Insulator&amp;nbsp;MOSFET&amp;nbsp;(SG-SOIMOSFET) is carried out using ATLAS 2D simulator. Based on the relationship between the nanotube’s deflection and the applied force, a comprehensive study of the proposed nanoforce sensor behavior is performed. Moreover, we describe the evolution of the drain current characteristics as a function of the applied force while examining the influence of capacity variation of the insulating gate on the drain current in the&amp;nbsp;saturation region. It is found that the sensor has a good sensitivity of 230.68 ln(A)/pN. Our second contribution in this paper is to develop a model based on&amp;nbsp;artificial neural networks&amp;nbsp;(ANNs). We successfully integrate our&amp;nbsp;neural model&amp;nbsp;of nanoforce sensor as a new component in the ORCAD-PSPICE electric simulator library; this component must accurately express the behavior of the sensor. A second model based on&amp;nbsp;neural networks, which deals with correction and&amp;nbsp;linearization&amp;nbsp;of the sensor output signal, is designed and implemented into the same simulator. The proposed device can be considered as a potential alternative for CMOS-based nanoforce sensing.</style></abstract></record></records></xml>