Evidence map›Paper›PMID 36850440›Full record

ArticleSensors (Basel, Switzerland)2023

Compact Modeling of Two-Dimensional Field-Effect Biosensors.

Francisco Pasadas, Tarek El Grour, Enrique G Marin, Alberto Medina-Rull, Alejandro Toral-Lopez, Juan Cuesta-Lopez, Francisco G Ruiz, Lassaad El Mir, Andrés Godoy

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 14 citations in OpenAlex.

  1. Enhancing pH prediction accuracy in AlScientific reports · 2025
    Article
  2. Article
  3. Advanced Field-Effect Sensors.Sensors (Basel, Switzerland) · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 2 countries.

Francisco PasadasPervasive Electronics Advanced Research Laboratory (PEARL), Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, 18071 Granada, Spain.ORCID 0000-0003-3992-9864
Tarek El GrourLaboratory of Physics of Materials and Nanomaterials Applied at Environment (LaPhyMNE) LR05ES14, Faculty of Sciences of Gabes, Gabes University, Erriadh City, Zrig, 6072 Gabes, Tunisia.
Enrique G MarinPervasive Electronics Advanced Research Laboratory (PEARL), Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, 18071 Granada, Spain.ORCID 0000-0002-0302-3764
Alberto Medina-RullPervasive Electronics Advanced Research Laboratory (PEARL), Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, 18071 Granada, Spain.
Alejandro Toral-LopezPervasive Electronics Advanced Research Laboratory (PEARL), Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, 18071 Granada, Spain.ORCID 0000-0001-5612-0536
Juan Cuesta-LopezPervasive Electronics Advanced Research Laboratory (PEARL), Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, 18071 Granada, Spain.ORCID 0000-0001-7905-9969
Francisco G RuizPervasive Electronics Advanced Research Laboratory (PEARL), Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, 18071 Granada, Spain.ORCID 0000-0003-4659-2454
Lassaad El MirLaboratory of Physics of Materials and Nanomaterials Applied at Environment (LaPhyMNE) LR05ES14, Faculty of Sciences of Gabes, Gabes University, Erriadh City, Zrig, 6072 Gabes, Tunisia.ORCID 0000-0003-4459-3779
Andrés GodoyPervasive Electronics Advanced Research Laboratory (PEARL), Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, 18071 Granada, Spain.ORCID 0000-0002-3014-8765
Universidad de Granada · ESUniversity of Gabès · TN

Funding

Government of Spain FPU019/05132Government of Spain PID2020-116518GB-I00Government of Spain PTA2020-018250-IGovernment of Spain TED2021-129769B-I00PAIDI 2020 and European Social Fund Operational Programme 2014-2020 20804Regional Government of Andalusia A-TIC-646-UGR20Regional Government of Andalusia P20_00633University of Granada Plan Propio
6 · The paper itself

Abstract

A compact model able to predict the electrical read-out of field-effect biosensors based on two-dimensional (2D) semiconductors is introduced. It comprises the analytical description of the electrostatics including the charge density in the 2D semiconductor, the site-binding modeling of the barrier oxide surface charge, and the Stern layer plus an ion-permeable membrane, all coupled with the carrier transport inside the biosensor and solved by making use of the Donnan potential inside the ion-permeable membrane formed by charged macromolecules. This electrostatics and transport description account for the main surface-related physical and chemical processes that impact the biosensor electrical performance, including the transport along the low-dimensional channel in the diffusive regime, electrolyte screening, and the impact of biological charges. The model is implemented in Verilog-A and can be employed on standard circuit design tools. The theoretical predictions obtained with the model are validated against measurements of a MoS

Indexed as

2Dbiosensorfield-effect transistorimmunosensormodelingMoS2sensorTMDtwo-dimensionalVerilog-A

Identifiers

PMID36850440
PMCPMC9958801
OpenAlexW4319601701

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.