Evidence map›Paper›PMID 41202096›Full record

ArticlePloS one2025

Enhanced surface plasmon resonance biosensor with graphene-black phosphorus heterostructure for ultra-high sensitivity refractive index detection with machine learning for behaviour prediction.

Jacob Wekalao, Hussein A Elsayed, Ahmed Mehaney, Amuthakkannan Rajakannu, Haifa A Alqhtani, May Bin-Jumah, Jonas Muheki, Stefano Bellucci

Expression of concernAbstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It carries an expression of concern. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Jacob WekalaoDepartment of Optics and Optical Engineering, University of Science and Technology of China, 96 Jinzhai Road, Hefei, China.
Hussein A ElsayedDepartment of Physics, College of Science, University of Ha'il, Ha'il, Saudi Arabia.
Ahmed MehaneyPhotonic and Phononic Crystals Lab., Physics Department, Faculty of Science, Beni-Suef University, Beni-Suef, Egypt.
Amuthakkannan RajakannuDepartment Of Mechanical And Industrial Engineering, College Of Engineering, National University Of Science And Technology, Sultanate Of Oman, Oman, Muscat.ORCID https://orcid.org/0000-0002-9657-4556
Haifa A AlqhtaniDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
May Bin-JumahDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Jonas MuhekiDepartment of Physics, University of Houston, Houston, Texas, United States of America.ORCID https://orcid.org/0000-0001-6666-2785
Stefano BellucciINFN-Laboratori Nazionali di Frascati, Via E. Fermi 54, Frascati, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study reports a five-layer surface plasmon resonance biosensor architecture comprising a BK7 glass substrate, silver plasmonic film, monolayer graphene, black phosphorus dielectric, and analyte region, engineered for high-precision detection of low refractive index media. The graphene-black phosphorus heterostructure synergistically exploits the exceptionally high surface-to-volume ratio of graphene and the anisotropic optical response of black phosphorus, enabling pronounced electromagnetic field confinement at the sensor interface. In particular, the detection procedure is mainly dependent on the emergence of the angular surface plasmon resonance based on the optimum values of the different geometrical and structural parameters. Therefore, the electromagnetic optimization using COMSOL Multiphysics was performed by varying the silver thickness, graphene thickness and black phosphorus thickness over an analyte index range of 1.29-1.38 RIU. The optimized configuration achieved a maximum sensitivity of 300°/RIU at n = 1.35 RIU, with a figure of merit of 45.455 RIU-1 and a detection limit of 0.018 RIU, surpassing previously reported architectures. Furthermore, predictive validation employing K-nearest neighbours regression demonstrated excellent reliability, yielding R² values between 92-100% and mean absolute errors of 0.005-0.012 RIU.

Indexed as

Biosensing TechniquesMachine LearningRefractometrySurface Plasmon ResonanceElectromagnetic FieldsGraphitePhosphorusSilverGraphitePhosphorusSilver

Identifiers

PMID41202096
PMCPMC12594348

What Socratic holds

Textmetadata
LicenceCC0
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 Socratic graph.