Dinar, Ahmed Musa (2020) Modeling and simulation of single and double gates ion sensitive field effect transistor for biomedical applications. Doctoral thesis, Universiti Teknikal Malaysia Melaka.
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Modeling And Simulation Of Single And Double Gates Ion Sensitive Field Effect Transistor For Biomedical Applications.pdf - Submitted Version Download (609kB) |
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Abstract
The modeling of Ion Sensitive Field Effect Transistor (ISFET) generally starts with its analogy to MOS devices and its threshold dependence on pH. Massobrio et al. proposed a macro-model plug in for SPICE. It was later modified to fit general SPICE based simulators without the need for a plug-in software. Then, different works followed the first modeling and simulation of ISFET by using widely available commercial CAD simulations. Unfortunately, the commercial TCAD is not supplied with model, material, and electrochemical packages to effectively manage the ISFET process and its operations. The main objective of this research is a comprehensive, accurate modeling and simulation of SG and DG ISFET devices. First, the adaptation of the Gouy-Chapman-Stern model mathematically and using TCAD to compensate for the roll-off non-ideality have been proposed. Performance analysis of conventional ISFET for six high-k materials as a Stern layer sensing membrane was also implemented. Moreover, a design and characterization of double-gate (DG) ISFET for SiO2 and Six high-k sensing membrane toward beyond Nernst limit sensitivity was done. Finally, a model for the geometrical parameter's impact on DG ISFET sensitivity was proposed. To achieve these objectives, the parameters of the silicon semiconductor material (that is, energy bandgap, permittivity, affinity, and density of states) are reconstructed in the electrolyte solution utilizing user-defined statement offered by Silvaco ATLAS. The electrostatic solution of the electrolyte area can also be investigated by constructing a numerical solution for the semiconductor equation in this area. The devices were virtually fabricated using ATHENA module of TCAD software. The materials used as a sensing membrane in devices were normal silicon dioxide (SiO2) and six high-k material (TiO2, Ta2O5, ZrO2, Al2O3, HfO2, and Si3N4). Then, the developed TCAD is used with the design of experiments (DOE) to investigate the effect of geometrical parameters on the performance of DG ISFETs and enhance the classical model. Three and five geometrical parameters, namely, buried oxide, silicon body, top oxide, channel length, and electrolyte thickness, are considered as independent factors in the DOE. Validation results revealed that the developed TCAD model has an acceptable agreement with experimental results and theoretical models in SG and DG ISFET in terms of sensitivity and ideal amplification ratio. On the other hand, silicon body thickness does not only affect the sensitivity toward the ultra-thin body but also can achieve an ultra-thin-body-buried oxide (Box). Channel length and electrolyte thickness as new investigated parameters also showed a clear impact on ISFET sensing properties. Furthermore, the developed TCAD and RSM mathematical models agreed with real experimental results in terms of average sensitivity and amplification ratio. The final design that depends on the control model resulted in a sensitivity ~1250 mV/pH that is ~21 times higher than the Nernst limit. To sum up, this study can open new directions for further analysis and optimization. Besides, the small sensing area and the FDSOI ISFET-based technology of the device can make the sensors ideal for the biomedical and IoT devices market.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | Transistors, Biomedical engineering, Biomedical applications |
| Subjects: | T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Library > Tesis > FKEKK |
| Depositing User: | F Haslinda Harun |
| Date Deposited: | 07 Dec 2021 13:56 |
| Last Modified: | 28 Jul 2023 15:15 |
| URI: | http://eprints.utem.edu.my/id/eprint/25424 |
| Statistic Details: | View Download Statistic |
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