PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 3, 2026Micromachines2 citationsOpen Access

Graphene-Based Chemical Field-Effect Transistors: Impact of Electric Double Layer Model and Quantum Capacitance on Na+ Detection Capabilities

View Full Paper
GBGhassem BaridiALArslan LiaquatLMLeonardo Martini

Key Points

  • This research aims to analyze the detection performance of graphene-based biosensors for sodium ions using different electric double layer models.
  • Examined the electric double layer formation at the electrolyte-graphene interface.
  • Performed comparative analysis of the Gouy–Chapman and Stern models.
  • Calculated the sensitivity of devices incorporating graphene quantum capacitance.
  • Determined sensitivities of 3200 V/M and 5500 V/M for the Gouy–Chapman and Stern models, respectively.
  • Achieved increased sensitivity of up to 5620 V/M with the inclusion of quantum capacitance.

Abstract

Graphene-based ion-sensitive field-effect transistors can operate as biosensors by utilizing the formation of an electric double layer at the interface between the electrolyte and the graphene channel, enabling high sensitivity, scalability, and cost-effective fabrication. In this work, we focus on the working principles and current methodologies associated with these devices, making a comparative analysis of different models that describe the electric double layer in the electrolyte, referring to sodium ions (Na+) as a case study for the detection performance of the graphene biosensor, and taking into account the impact of graphene quantum capacitance. Our study addresses the sensitivity of graphene field-effect transistors within the framework of the Gouy–Chapman model, as well as the Stern model, computing device sensitivities of 3200 V/M and 5500 V/M, respectively. By incorporating the impact of graphene’s quantum capacitance in the calculations, increased sensitivity up to 5620 V/M was found. The present work shines light on the rationalization of graphene-based biosensors' operation and performance.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Baridi et al. (2026) studied this question.

synapsesocial.com/papers/69cf5f225a333a821460e0b4https://doi.org/10.3390/mi17040433
Ask AI
Helpful
Bookmark
Share
View Full Paper