Showing posts with label field-effect transistor. Show all posts
Showing posts with label field-effect transistor. Show all posts

Sep 20, 2021

[paper] Compact Modeling of pH-Sensitive FETs Based on 2D Semiconductors

Tarek El Grour, Francisco Pasadas, Alberto Medina-Rull, Montassar Najari, Enrique G. Marin, Alejandro Toral-Lopez, Francisco G. Ruiz, Andrés Godoy, David Jiménez and Lassaad El-Mir
Compact Modeling of pH-Sensitive FETs Based on Two-Dimensional Semiconductors
arXiv:2109.06585 [physics.app-ph; submitted on 14 Sep 2021]
DOI: 10.1109/TED.2021.3112407
   
LAPHYMNE Laboratory, Gabes University, Gabes, Tunisia
PEARL Laboratory, Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, Spain
The Innovation and Entrepreneurship Centre, Jazan University, Jazan, Saudi Arabia.
Departament d’Enginyeria Electrònica, Escola d’Enginyeria, Universitat Autònoma de Barcelona, Spain

Abstract: We present a physics-based circuit-compatible model for pH-sensitive field-effect transistors based on two-dimensional (2D) materials. The electrostatics along the electrolyte-gated 2D-semiconductor stack is treated by solving the Poisson equation including the Site-Binding model and the Gouy-Chapman-Stern approach, while the carrier transport is described by the drift-diffusion theory. The proposed model is provided in an analytical form and then implemented in Verilog-A, making it compatible with standard technology computer-aided design tools employed for circuit simulation. The model is benchmarked against two experimental transition-metal-dichalcogenide (MoS2 and ReS2) based ion sensors, showing excellent agreement when predicting the drain current, threshold voltage shift, and current/voltage sensitivity measurements for different pH concentrations.
Fig: a) Schematic depiction of a 2D-ISFET b) its quivalent capacitive circuit

Acknowledgments: This work is supported in part by the Spanish Government under the projects TEC2017-89955-P, RTI2018-097876-B-C21 and PID2020-116518GB-I00 (MCIU/AEI/FEDER, UE); the FEDER/Junta de Andalucía under project BRNM-375-UGR18; EC under Horizon 2020 projects WASP No. 825213 and GrapheneCore3 No. 881603. E.G. Marin gratefully acknowledges Juan de la Cierva Incorporación IJCI-2017-32297. A. Toral-Lopez acknowledges the FPU program (FPU16/04043). F. Pasadas acknowledges funding from PAIDI 2020 and Andalusian ESF OP 2014-2020 (20804). F. Pasadas and D. Jiménez also acknowledge the partial funding from the ERDF allocated to the Programa Operatiu FEDER de Catalunya 2014-2020, with the support of the Secretaria d’Universitats i Recerca of the Departament d’Empresa i Coneixement of the Generalitat de Catalunya for emerging technology clusters to carry out valorization and transfer of research results. Reference of the GraphCAT project: 001-P-001702.