Cargando…

Quantitative characterization of agglomerates and aggregates of pyrogenic and precipitated amorphous silica nanomaterials by transmission electron microscopy

BACKGROUND: The interaction of a nanomaterial (NM) with a biological system depends not only on the size of its primary particles but also on the size, shape and surface topology of its aggregates and agglomerates. A method based on transmission electron microscopy (TEM), to visualize the NM and on...

Descripción completa

Detalles Bibliográficos
Autores principales: De Temmerman, Pieter-Jan, Van Doren, Elke, Verleysen, Eveline, Van der Stede, Yves, Francisco, Michel Abi Daoud, Mast, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3462150/
https://www.ncbi.nlm.nih.gov/pubmed/22709926
http://dx.doi.org/10.1186/1477-3155-10-24
Descripción
Sumario:BACKGROUND: The interaction of a nanomaterial (NM) with a biological system depends not only on the size of its primary particles but also on the size, shape and surface topology of its aggregates and agglomerates. A method based on transmission electron microscopy (TEM), to visualize the NM and on image analysis, to measure detected features quantitatively, was assessed for its capacity to characterize the aggregates and agglomerates of precipitated and pyrogenic synthetic amorphous silicon dioxide (SAS), or silica, NM. RESULTS: Bright field (BF) TEM combined with systematic random imaging and semi-automatic image analysis allows measuring the properties of SAS NM quantitatively. Automation allows measuring multiple and arithmetically complex parameters simultaneously on high numbers of detected particles. This reduces operator-induced bias and assures a statistically relevant number of measurements, avoiding the tedious repetitive task of manual measurements. Access to multiple parameters further allows selecting the optimal parameter in function of a specific purpose. Using principle component analysis (PCA), twenty-three measured parameters were classified into three classes containing measures for size, shape and surface topology of the NM. CONCLUSION: The presented method allows a detailed quantitative characterization of NM, like dispersions of precipitated and pyrogenic SAS based on the number-based distributions of their mean diameter, sphericity and shape factor.