Visualising and Analysing Particles Using Nanoparticle Analysis

Tag : Optical Distribution Frame
Introduction Nanoparticle

The analysis of nanoparticles is an increasingly importantrequirement in a broad range of industry sectors. Productperformance and stability frequently depends on the ability tomanufacture particle suspensions to fine tolerances without thepresence of contaminants or aggregates. Similarly, the constructionof complex, multi-layer nanoparticles (e.g. for drug delivery,speciality coatings, etc.) requires knowledge of particle size andcomposition at all stages of manufacture. Finally, informationregarding the environmental release and toxicity of engineerednanoparticles is an area of widespread and growing concern.

Foremost in such analyses is particle size and size distributionmeasurement for which a number of techniques are well establishedand commonly employed in routine quality control as well as in aresearch and development environment. Depending on the nature ofthe product and the particle characteristics sought, one or moreanalytical methodologies are routinely employed and which includeelectron microscopy, dynamic light scattering, Fraunhoferscattering, single particle detection techniques, opticalmicroscopy, etc. For particles at the nanoscale, however, only thefirst two of these examples are used frequently. Electronmicroscopy has significant and recognised drawbacks includingcapital and running costs, lengthy analysis turnaround time anduncertainty as to whether the images of the lyophilised and coatedsurface bound structures reflect those in the native state. Dynamic Light Scattering

While Dynamic Light Scattering methods (exemplified by thetechnique known as Photon Correlation Spectroscopy - PCS) areindustry standard methodologies and are used routinely and verysuccessfully for the analysis of monodisperse and homogenous sampletypes, it is also well recognized that such dynamic lightscattering methods can become unreliable when presented withheterogeneous samples which contain a wide range of particle sizes,i.e. are polydisperse, and that the basic information obtained, theintensity weighted, mean size (the z-average) and apolydispersity quotient indicating the width of the particle sizedistribution, does not always reflect the sample compositionaccurately. Furthermore, successful analysis of the correlationfunction by classical deconvolution algorithms to extract, forinstance, multimodal distributions are realistically limited tosample types containing only two (or exceptionally three)monodisperse particle sizes, each needing to differ from each otherby a size factor of, in practice, >3:1. Finally, DLS is limitedin its ability to allow the user to recognize when the sample isunsuitable for analysis by that method and that the data (i.e. theparticle size distribution profile) obtained should accordingly betreated with some suspicion. Nanoparticle Tracking Analysis

An alternative light scattering method for nanoparticle analysishas recently become available, Nanoparticle Tracking Analysis (NTA), and it is being increasingly used for determining nanoparticlesize through simultaneously but individually tracking and analysingthe trajectories described nanoparticles undergoing Brownian motionin a fluid. This technique has recently been made commerciallyavailable and is described here. Method

The technique is centred on a sample analysis module (Fig. 1a)which comprises a small metal housing containing a solid-state,single-mode laser diode (<35mW, 638 nm) configured to launch afinely focused beam through the sample of liquid containing adilute suspension of nanoparticles placed directly above aspecially designed optical flat. The sample chamber isapproximately 250