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Title: Toward computational and experimental characterisation for risk assessment of metal oxide nanoparticles

Abstract

Metal oxide (MeO) nanoparticles (NPs) have become common in our everyday life over the past years. However, there is still an important knowledge gap regarding their toxicological effect and, in particular, how the different physical and chemical properties of MeO NPs influence their cytotoxicity and the subsequent implications for risk assessment. This work analyses the physicochemical properties of MeO NPs that have been reported as relevant for risk assessment and the experimental and theoretical methods used to obtain them. The surface, physical and chemical properties of NPs have been critically revisited to shed light on the features that can cause toxicity. Due to the large number of existing MeO NPs, in silico studies are necessary to get a good understanding of the NPs' physicochemical properties; therefore this review focuses on the state of the art computational methods used to model MeO NP toxicity: QSAR and QSTR models and their alternative approaches provide a better understanding of MeO NP biological toxicity in organisms.

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]
  1. Departament d'Enginyeria Química; Universitat Rovira i Virgili; 43007 Tarragona; Spain
  2. Advanced Computing, Mathematics, and Data Division; Pacific Northwest National Laboratory; Richland; USA
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1508245
Report Number(s):
PNNL-SA-136568
Journal ID: ISSN 2051-8153; ESNNA4
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Environmental Science: Nano
Additional Journal Information:
Journal Volume: 5; Journal Issue: 10; Journal ID: ISSN 2051-8153
Publisher:
Royal Society of Chemistry
Country of Publication:
United States
Language:
English
Subject:
77 NANOSCIENCE AND NANOTECHNOLOGY

Citation Formats

Escorihuela, Laura, Martorell, Benjamí, Rallo, Robert, and Fernández, Alberto. Toward computational and experimental characterisation for risk assessment of metal oxide nanoparticles. United States: N. p., 2018. Web. doi:10.1039/c8en00389k.
Escorihuela, Laura, Martorell, Benjamí, Rallo, Robert, & Fernández, Alberto. Toward computational and experimental characterisation for risk assessment of metal oxide nanoparticles. United States. doi:10.1039/c8en00389k.
Escorihuela, Laura, Martorell, Benjamí, Rallo, Robert, and Fernández, Alberto. Mon . "Toward computational and experimental characterisation for risk assessment of metal oxide nanoparticles". United States. doi:10.1039/c8en00389k. https://www.osti.gov/servlets/purl/1508245.
@article{osti_1508245,
title = {Toward computational and experimental characterisation for risk assessment of metal oxide nanoparticles},
author = {Escorihuela, Laura and Martorell, Benjamí and Rallo, Robert and Fernández, Alberto},
abstractNote = {Metal oxide (MeO) nanoparticles (NPs) have become common in our everyday life over the past years. However, there is still an important knowledge gap regarding their toxicological effect and, in particular, how the different physical and chemical properties of MeO NPs influence their cytotoxicity and the subsequent implications for risk assessment. This work analyses the physicochemical properties of MeO NPs that have been reported as relevant for risk assessment and the experimental and theoretical methods used to obtain them. The surface, physical and chemical properties of NPs have been critically revisited to shed light on the features that can cause toxicity. Due to the large number of existing MeO NPs, in silico studies are necessary to get a good understanding of the NPs' physicochemical properties; therefore this review focuses on the state of the art computational methods used to model MeO NP toxicity: QSAR and QSTR models and their alternative approaches provide a better understanding of MeO NP biological toxicity in organisms.},
doi = {10.1039/c8en00389k},
journal = {Environmental Science: Nano},
issn = {2051-8153},
number = 10,
volume = 5,
place = {United States},
year = {2018},
month = {1}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Figures / Tables:

Fig. 1 Fig. 1: Comparison of the percentage of atoms exposed on the surface at macro and nano scales. Adapted from the book Science at the Nanoscale.

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    Figures / Tables found in this record:

      Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.