Evidence map›Paper›PMID 40347258›Full record

ArticleAnalytical and bioanalytical chemistry2025

Enhanced electrochemical detection of acetaminophen using CoNi-LDH-based sensor with ultra-wide linear range and superior performance.

Jianxia Gu, Li Fan, Jian Bai, Zhanbin Jin, Tingting Wei

Abstract read
PubMed Publisher
In one paragraph

Article in Analytical and bioanalytical chemistry, 2025. 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

5 authors.

Jianxia GuDepartment of Chemistry, Xinzhou Normal University, Xinzhou, China. gujx349@xztu.edu.cn.
Li FanDepartment of Chemistry, Xinzhou Normal University, Xinzhou, China.
Jian BaiDepartment of Chemistry, Xinzhou Normal University, Xinzhou, China.
Zhanbin JinDepartment of Chemistry, Xinzhou Normal University, Xinzhou, China.
Tingting WeiDepartment of Chemistry, Xinzhou Normal University, Xinzhou, China.

Funding

the Foundation of Xinzhou Teachers University, China 2021KY07the Fundamental Research Program of Shanxi Province 202203021212177the Fundamental Research Program of Shanxi Province 202303021222235the Science and technology innovation project of higher education in Shanxi province 2021L450
6 · The paper itself

Abstract

Electrochemical sensors for acetaminophen (AP) determination often face limitations in linear range, rarely achieving millimolar levels. This work synthesized CoNi-LDH (cobalt-nickel layered double hydroxide) via a simple hydrothermal method. By optimizing the Co/Ni ratio, the sensor based on CoNi-LDH-1 demonstrates efficient AP detection with an ultra-wide linear range spanning from 5 μM to 5 mM, enabling versatile AP monitoring in diverse samples. Furthermore, the sensor also exhibits exceptional stability, reproducibility, and selectivity. Notably, it successfully quantified AP in real-world samples (tap water and urine) while maintaining a wide linear range. The superior performance of the sensor stems from CoNi-LDH-1's unique spiky sphere morphology, abundant active sites, enhanced electron transport capability, and the synergistic effect between Co and Ni components. This work provides valuable insights for expanding the linear range of electrochemical sensors, advancing their application in analytical chemistry.

Indexed as

AcetaminophenAnalgesics, Non-NarcoticCobaltElectrochemical TechniquesHydroxidesNickelHumansLimit of DetectionReproducibility of ResultsAcetaminophenAnalgesics, Non-NarcoticCobaltHydroxidesNickelCoNi-LDHElectrochemical sensorSynergistic effectWide linear range

Identifiers

PMID40347258

What OpenQuestion holds

Textmetadata
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.