ReviewMicromachines2021
2D Electronics Based on Graphene Field Effect Transistors: Tutorial for Modelling and Simulation.
Review in Micromachines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Graphene-Based Chemical Field-Effect Transistors: Impact of Electric Double Layer Model and Quantum Capacitance on NaMicromachines · 2026Article
- A THz graphene-on-hBN stack patch antenna for future 6G communications.Scientific reports · 2025Article
- Basic Characteristics of Ionic Liquid-Gated Graphene FET Sensors for Nitrogen Cycle Monitoring in Agricultural Soil.Biosensors · 2025Article
- Modeling Carbon-Based Nanomaterials (CNMs) and Derived Composites and Devices.Sensors (Basel, Switzerland) · 2024Review
- Modular Fabrication of Microfluidic Graphene FET for Nucleic Acids Biosensing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- The design of a point of care FET biosensor to detect and screen COVID-19.Scientific reports · 2023Article
- Extraction of Graphene's RF Impedance through Thru-Reflect-Line Calibration.Micromachines · 2023Article
- Numerical Evaluation of the Effect of Geometric Tolerances on the High-Frequency Performance of Graphene Field-Effect Transistors.Nanomaterials (Basel, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
This paper provides modeling and simulation insights into field-effect transistors based on graphene (GFET), focusing on the devices' architecture with regards to the position of the gate (top-gated graphene transistors, back-gated graphene transistors, and top-/back-gated graphene transistors), substrate (silicon, silicon carbide, and quartz/glass), and the graphene growth (CVD, CVD on SiC, and mechanical exfoliation). These aspects are explored and discussed in order to facilitate the selection of the appropriate topology for system-level design, based on the most common topologies. Since most of the GFET models reported in the literature are complex and hard to understand, a model of a GFET was implemented and made available in MATLAB, Verilog in Cadence, and VHDL-AMS in Simplorer-useful tools for circuit designers with different backgrounds. A tutorial is presented, enabling the researchers to easily implement the model to predict the performance of their devices. In short, this paper aims to provide the initial knowledge and tools for researchers willing to use GFETs in their designs at the system level, who are looking to implement an initial setup that allows the inclusion of the performance of GFETs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.