The unique features of nanocomposite materials depend on the type and size of nanoparticles, as well as their placement in the composite matrices. Therefore the nanocomposites manufacturing process requires inline control over certain parameters of nanoparticles such as dispersion and concentration. Keeping track of nanoparticles parameters inside a matrix is currently a difficult task due to lack of a fast, reliable and cost effective way of measurement that can be used for large volume samples. For this purpose the Optical Coherence Tomography (OCT) has been used. OCT is an optical measurement method, which is a non-destructive and non-invasive technique. It is capable of creating tomographic images of inner structure by gathering depth related backscattered signal from scattering particles. In addition, it can analyse, in a single shot, area of the centimetre range with resolution up to single micrometres. Still to increase OCT measurement capabilities we are using additional system extensions such as Spectroscopic OCT (SOCT). With such addition, we are able to measure depth related parameters such as scattering spectra and intensity of backscattered signal. Those parameters allow us to quantitatively estimate nanoparticles concentration. Gaining those, information allows to calculate volume concentration of nanoparticles. In addition, we analyse metallic oxides nanoparticles. To fully characterize nanoparticles it is necessary to find and differentiate those that are single particles from agglomerated ones. In this contribution we present our research results on using the LCI based measurement techniques for evaluation of materials with nanoparticles. The laboratory system and signal processing algorithms are going to be shown in order to express the usefulness of this method for inline constant monitoring of the nanocomposite material fabrication.
Authors
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1117/12.2188063
- Category
- Aktywność konferencyjna
- Type
- materiały konferencyjne indeksowane w Web of Science
- Language
- angielski
- Publication year
- 2015
