Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 282

The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.

Hydrophilic Silver Nanoparticles Induce Selective Nanochannels in Thin Film Nanocomposite Polyamide Membranes

Yang, Zhe, Guo, Hao, Yao, Zhi-kan, Mei, Ying, Tang, Chuyang Y.·2019·Environmental Science & Technology

Abstract

Thin-film nanocomposite (TFN) membranes have been widely studied over the past decade for their desalination applications. For some cases, the incorporation of nonporous hydrophilic nanofillers has been reported to greatly enhance membrane separation performance, yet the underlying mechanism is poorly understood. The current study systematically investigates TFN membranes incorporated with silver nanoparticles (AgNPs). For the first time, we reveal the formation of nanochannels of approximately 2.5 nm in size around the AgNPs, which can be attributed to the hydrolysis of trimesoyl chloride monomers and thus the termination of interfacial polymerization by the water layer around each hydrophilic nanoparticle. These nanochannels nearly tripled the membrane water permeability for the optimal membrane. In addition, this membrane showed increased rejection against NaCl, boron, and a set of small-molecular organic compounds (e.g., propylparaben, norfloxacin, and ofloxacin), thanks to its combined effects of improved size exclusion, enhanced Donnan exclusion, and suppressed hydrophobic interaction. Our work provides fundamental insights into the formation and transport mechanisms involved in solid-filler incorporated TFN membranes. Future studies should take advantage of this spontaneous nanochannel formation in the design of TFN to overcome the classical membrane permeability-selectivity trade-off.

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 · 10.1021/acs.est.9b00473

Cites

39 of 39 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

Cited by

See all 282

Metadata

Authors
Yang, Z., Guo, H., Yao, Z.-K., Mei, Y., & Tang, C. Y.
Venue
Environmental Science & Technology
Published
2019-04-11
Volume
53
Issue
9
Pages
5301-5308
ISSN
  • 0013-936X (ISSN-L)
  • 1520-5851
OpenAlex
W2938257832
Cited by
282
References
39
FWCI
12.68
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

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.