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: | , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2019
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/ab1fa37fd61b4fb1bc2805de4387921d |
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| Sumario: | 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. |
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