Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 398

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Nanomaterials based electrochemical sensor and biosensor platforms for environmental applications

Open access
Maduraiveeran, Govindhan, Jin, Wei·2017·Trends in Environmental Analytical Chemistry

Abstract

Abstract A wide range of toxic chemicals is currently released into the environmental in terms of airborne, aquatic and solid wastes due to the rapid international globalization and industrialization. Thus, a sensitive, reliable and cost-effective sensor platform for emerging environmental pollutants is of great importance. The considerable advancements have been made on the successful electrochemical sensor and biosensor platforms based on nanomaterials for environmental applications. In the present review, the recent trends in the development of the electrochemical sensor platforms based on state-of-the-art nanomaterials such as metal nanoparticles, metal oxide nanomaterials, carbon nanomaterials, polymer and biomaterials are assessed. The unique synthetic approaches, properties, integration strategies, selected sensing applications and future prospects of these nanostructured materials for the design of advanced sensor platforms are also highlighted. The significant development of the nanomaterials based electrochemical sensor platforms is giving rise to new impetus of generating novel technologies for securing the human and environmental safety.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.teac.2017.02.001

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Cited by

See all 398

Metadata

Authors
Maduraiveeran, G., & Jin, W.
Venue
Trends in Environmental Analytical Chemistry
Publisher
Elsevier BV
Published
2017-01
Volume
13
Pages
10-23
ISSN
2214-1588 (ISSN-L)
OpenAlex
W2591039955
Cited by
398
References
2
FWCI
12.31
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Nanomaterials based electrochemical sensor and biosensor platforms for environmental applications. https://app.cochat.ai/papers/10.1016/j.teac.2017.02.001
The paper
Maduraiveeran, G., & Jin, W. (2017). Nanomaterials based electrochemical sensor and biosensor platforms for environmental applications. Trends in Environmental Analytical Chemistry. https://doi.org/10.1016/j.teac.2017.02.001

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.