Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 321

The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.

A pH-responsive drug delivery system based on chitosan coated mesoporous silica nanoparticles

Popat, Amirali, Liu, Jian, Lu, Gao Qing (Max), Qiao, Shi Zhang·2012·Journal of Materials Chemistry

Abstract

Herein, we report a core–shell pH-responsive drug-carrier based on chitosan-coated mesoporous silica nanospheres. The efficient positively charged polymer (chitosan) coating is realized by the phosphoramidate covalent bonding between phosphonate groups on the surface of the mesoporous silica nanoparticles (MSNs) and amino groups on chitosan. A pH-responsive release of ibuprofen has been achieved by varying the shell structure of positively charged chitosan in the designed pH 4.0–7.4 solution. Under basic conditions, chitosan forms a gel like structure which is insoluble and hence prevents ibuprofen release at pH 7.4. When the pH is below its PI (6.3), the drug has been released due to protonation of the amino group on chitosan. These results imply that the chitosan coated-MSNs are promising platforms to construct pH-responsive controlled drug delivery systems.

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 · 10.1039/c2jm30501a

Cites

29 of 29 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 29 references

Cited by

See all 321

Metadata

Authors
Popat, A., Liu, J., Lu, G. Q. (., & Qiao, S. Z.
Venue
Journal of Materials Chemistry
Published
2012
Volume
22
Issue
22
Pages
11173
ISSN
  • 0959-9428 (ISSN-L)
  • 1364-5501
OpenAlex
W1971859416
Cited by
321
References
29
FWCI
12.16
Type
journal article
Language
en
Open access
closed

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: A pH-responsive drug delivery system based on chitosan coated mesoporous silica nanoparticles. https://app.cochat.ai/papers/10.1039/c2jm30501a
The paper
Popat, A., Liu, J., Lu, G. Q. (., & Qiao, S. Z. (2012). A pH-responsive drug delivery system based on chitosan coated mesoporous silica nanoparticles. Journal of Materials Chemistry. https://doi.org/10.1039/c2jm30501a

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.