Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 283

The DOI matches its Crossref record; 139 of the 139 references it cites were found in a registry or an index.

Progress of Nanocomposite Membranes for Water Treatment

Open access
Ursino, Claudia, Castro-Muñoz, Roberto, Drioli, Enrico, Gzara, Lassaad, Albeirutty, Mohammad, Figoli, Alberto·2018·Membranes

Abstract

The use of membrane-based technologies has been applied for water treatment applications; however, the limitations of conventional polymeric membranes have led to the addition of inorganic fillers to enhance their performance. In recent years, nanocomposite membranes have greatly attracted the attention of scientists for water treatment applications such as wastewater treatment, water purification, removal of microorganisms, chemical compounds, heavy metals, etc. The incorporation of different nanofillers, such as carbon nanotubes, zinc oxide, graphene oxide, silver and copper nanoparticles, titanium dioxide, 2D materials, and some other novel nano-scale materials into polymeric membranes have provided great advances, e.g., enhancing on hydrophilicity, suppressing the accumulation of pollutants and foulants, enhancing rejection efficiencies and improving mechanical properties and thermal stabilities. Thereby, the aim of this work is to provide up-to-date information related to those novel nanocomposite membranes and their contribution for water treatment applications.

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 · 10.3390/membranes8020018

Cites

139 of 139 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 139 references

Metadata

Authors
Ursino, C., Castro-Muñoz, R., Drioli, E., Gzara, L., Albeirutty, M., & Figoli, A.
Venue
Membranes
Publisher
MDPI AG
Published
2018-04-03
Volume
8
Issue
2
Pages
18
ISSN
2077-0375 (ISSN-L)
OpenAlex
W2795755959
Cited by
283
References
139
FWCI
12.84
Type
journal article
Language
en
Open access
gold

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: Progress of Nanocomposite Membranes for Water Treatment. https://app.cochat.ai/papers/10.3390/membranes8020018
The paper
Ursino, C., Castro-Muñoz, R., Drioli, E., Gzara, L., Albeirutty, M., & Figoli, A. (2018). Progress of Nanocomposite Membranes for Water Treatment. Membranes. https://doi.org/10.3390/membranes8020018

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.