Evidence map›Paper›PMID 40710076›Full record

ArticleBiosensors2025

A SERS Sensor Prepared via Electrostatic Self-Assembly of Ta

Kai Hua, Liang Li, Pei Liang

Abstract read
In one paragraph

Article in Biosensors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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

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

3 authors.

Kai HuaCollege of Science, China Jiliang University, Hangzhou 310018, China.ORCID 0009-0006-1154-4603
Liang LiCollege of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018, China.ORCID 0009-0009-2956-6706
Pei LiangCollege of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018, China.ORCID 0000-0002-2493-2238

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MXenes are a class of two-dimensional materials exhibiting excellent surface-enhanced Raman scattering (SERS) performance. Currently, the SERS studies of MXenes have been primarily focused on those with M

Indexed as

Biosensing TechniquesNanocompositesSpectrum Analysis, RamanLimit of DetectionMetal NanoparticlesSilverStatic ElectricitySilverAgNPsMXene nanosheetphotoinduced charge transferSERSZiram

Identifiers

PMID40710076
PMCPMC12293568

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.