ArticleMicromachines2026
Graphene-Based Chemical Field-Effect Transistors: Impact of Electric Double Layer Model and Quantum Capacitance on Na
Article in Micromachines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Computational Simulation of a Surface Plasmonic Resonance Biosensor for β2-Microglobulin Based on Electrolyte-Gated Graphene.Sensors (Basel, Switzerland) · 2026Article
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Authors and funding
13 authors.
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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
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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.