Evidence map›Paper›PMID 42328001›Full record

ArticleECS sensors plus2026

Photoelectrochemical Immuno-Sensing via Plasmon-Induced Resonance Energy Transfer Mechanism.

Joeseph Bright, Yingjie Hang, Weirui Tan, Anyang Wang, Hui Yang, Nianqiang Wu

Abstract read
In one paragraph

Article in ECS sensors plus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Joeseph BrightDepartment of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, West Virginia 26506, United States of America.ORCID https://orcid.org/0000-0002-9017-0809
Yingjie HangDepartment of Chemical and Biomolecular Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States of America.ORCID https://orcid.org/0000-0002-0783-0651
Weirui TanDepartment of Chemical and Biomolecular Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States of America.ORCID https://orcid.org/0000-0001-8773-5656
Anyang WangDepartment of Chemical and Biomolecular Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States of America.ORCID https://orcid.org/0000-0003-1897-8915
Hui YangChemical Engineering Molinaroli College of Engineering and Computing, University of South Carolina, Columbia, South Carolina 29208, United States of America.ORCID https://orcid.org/0000-0001-9614-5164
Nianqiang WuDepartment of Chemical and Biomolecular Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States of America.ORCID https://orcid.org/0000-0002-8888-2444

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Photoelectrochemical (PEC) sensors integrate light excitation with electrochemical detection, providing low background noise and robust anti-interference capabilities. Surface plasmon resonance (SPR) acts as an effective light antenna for signal transduction in these sensors. Traditionally, plasmon-mediated PEC sensors operate via hot carrier injection, which necessitates direct contact between the plasmonic antenna and the semiconductor, thereby limiting sensor design flexibility. In this work, we introduce plasmon-induced resonance energy transfer (PIRET) as a novel signal transduction mechanism in a PEC immunosensor. A Bi

Indexed as

ImmunoassayPhotoelectrochemical sensorsPlasmonics - Light ModulationPlasmon-induced resonance energy transfer

Identifiers

PMID42328001
PMCPMC13276971

What OpenQuestion holds

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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.