Distinguishing the sources of silica nanoparticles by dual isotopic fingerprinting and machine learning

Determining the source of nanoparticles is critical for nanotechnology risk assessment. Here, the authors develop an approach that, by taking into account the isotopic signatures of both Si and O, may be able to distinguish between natural and engineered SiO2 nanoparticles, and even those synthesize...

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Autores principales:	Xuezhi Yang, Xian Liu, Aiqian Zhang, Dawei Lu, Gang Li, Qinghua Zhang, Qian Liu, Guibin Jiang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/ab1fa37fd61b4fb1bc2805de4387921d
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spelling	oai:doaj.org-article:ab1fa37fd61b4fb1bc2805de4387921d2021-12-02T17:01:34ZDistinguishing the sources of silica nanoparticles by dual isotopic fingerprinting and machine learning10.1038/s41467-019-09629-52041-1723https://doaj.org/article/ab1fa37fd61b4fb1bc2805de4387921d2019-04-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-09629-5https://doaj.org/toc/2041-1723Determining the source of nanoparticles is critical for nanotechnology risk assessment. Here, the authors develop an approach that, by taking into account the isotopic signatures of both Si and O, may be able to distinguish between natural and engineered SiO2 nanoparticles, and even those synthesized by different manufacturers.Xuezhi YangXian LiuAiqian ZhangDawei LuGang LiQinghua ZhangQian LiuGuibin JiangNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-9 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Xuezhi Yang Xian Liu Aiqian Zhang Dawei Lu Gang Li Qinghua Zhang Qian Liu Guibin Jiang Distinguishing the sources of silica nanoparticles by dual isotopic fingerprinting and machine learning
description	Determining the source of nanoparticles is critical for nanotechnology risk assessment. Here, the authors develop an approach that, by taking into account the isotopic signatures of both Si and O, may be able to distinguish between natural and engineered SiO2 nanoparticles, and even those synthesized by different manufacturers.
format	article
author	Xuezhi Yang Xian Liu Aiqian Zhang Dawei Lu Gang Li Qinghua Zhang Qian Liu Guibin Jiang
author_facet	Xuezhi Yang Xian Liu Aiqian Zhang Dawei Lu Gang Li Qinghua Zhang Qian Liu Guibin Jiang
author_sort	Xuezhi Yang
title	Distinguishing the sources of silica nanoparticles by dual isotopic fingerprinting and machine learning
title_short	Distinguishing the sources of silica nanoparticles by dual isotopic fingerprinting and machine learning
title_full	Distinguishing the sources of silica nanoparticles by dual isotopic fingerprinting and machine learning
title_fullStr	Distinguishing the sources of silica nanoparticles by dual isotopic fingerprinting and machine learning
title_full_unstemmed	Distinguishing the sources of silica nanoparticles by dual isotopic fingerprinting and machine learning
title_sort	distinguishing the sources of silica nanoparticles by dual isotopic fingerprinting and machine learning
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/ab1fa37fd61b4fb1bc2805de4387921d
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Distinguishing the sources of silica nanoparticles by dual isotopic fingerprinting and machine learning

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