Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 671

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Safety Assessment of Graphene-Based Materials: Focus on Human Health and the Environment

Open access
Fadeel, Bengt, Bussy, Cyrill, Merino, Sonia, Vázquez, Ester, Flahaut, Emmanuel, Mouchet, Florence, Evariste, Lauris, Gauthier, Laury, Koivisto, Antti J., Vogel, Ulla, Martín, Cristina, Delogu, Lucia G., Buerki-Thurnherr, Tina, Wick, Peter, Beloin-Saint-Pierre, Didier, Hischier, Roland, Pelin, Marco, Candotto Carniel, Fabio, Tretiach, Mauro, Cesca, Fabrizia, Benfenati, Fabio, Scaini, Denis, Ballerini, Laura, Kostarelos, Kostas, Prato, Maurizio, Bianco, Alberto·2018·ACS Nano

Abstract

Graphene and its derivatives are heralded as "miracle" materials with manifold applications in different sectors of society from electronics to energy storage to medicine. The increasing exploitation of graphene-based materials (GBMs) necessitates a comprehensive evaluation of the potential impact of these materials on human health and the environment. Here, we discuss synthesis and characterization of GBMs as well as human and environmental hazard assessment of GBMs using in vitro and in vivo model systems with the aim to understand the properties that underlie the biological effects of these materials; not all GBMs are alike, and it is essential that we disentangle the structure-activity relationships for this class of materials.

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/acsnano.8b04758

Cites

12 of 12 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 671

Metadata

Authors
Fadeel, B., Bussy, C., Merino, S., Vázquez, E., Flahaut, E., Mouchet, F., Evariste, L., Gauthier, L., Koivisto, A. J., Vogel, U., Martín, C., Delogu, L. G., Buerki-Thurnherr, T., Wick, P., Beloin-Saint-Pierre, D., Hischier, R., Pelin, M., Candotto Carniel, F., Tretiach, M., Cesca, F., Benfenati, F., Scaini, D., Ballerini, L., Kostarelos, K., Prato, M., & Bianco, A.
Venue
ACS Nano
Published
2018-11-02
Volume
12
Issue
11
Pages
10582-10620
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W2899421489
Cited by
671
References
12
FWCI
24.26
Type
journal article
Language
en
Open access
hybrid

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.