Polymeric dispersions of particle mixes are common in a multitude of applications and products such as pharmaceutical, personal care, food, ceramics, pigments, inks, and cements. A proper dispersion of the particles is necessary to avoid sedimentation, instability, or product failure due to aggregation, oversize, and aging. Classizer™ ONE particle analyser based on patented Single Particle Extinction and Scattering (SPES) method introduces introduces a step forward in the way light scattering is exploited for single particle characterization. Classizer™ ONE provides the information on the different particulate populations in all the intermediate formulation steps and in the final product as required by bottom-up Quality-by-Design formulation, top-down Safe-by-Design approaches and product manufacturing.

Classify

Classify the particle polymeric populations in heterogeneous liquids on the base of single particle optical properties

Analyse

Analyse the numerical particle size distribution and the factors influencing stability and particle behaviour

Quantify

Count the numerical particle concentrations of single particle populations in heterogeneous liquids

Example of application: polystyrene spheres
A polymer that many particle size scientists should be familiar with is polystyrene, which is often used as materials for size standards employed in particle analysis, and instrument calibration and validation. Classizer™ ONE, based on patented SPES method, is the ideal solution for improving colloids formulations and for verifying product consistency with the target Quality-by-Design final expectations. Depending on the system configuration, sample material and sample preparation, Classizer™ ONE covers a dynamic range of 0.2 – 20 μm, concentration range of 1E5-1E7 ptc/mL @ 0.5-5ccm. External auto-dilution sampler and autosampler available.

(in figure) (TOP) SPES high-resolution characterization of PS 0.5µm spheres dispersed in filtered water at a nominal numerical concentration of 1E6 ptc/mL. About 4 mL of sample have been analysed at 5ccm using a lab syringe pump. About 8000 validated particles populate the EOS CLOUDS map and are employed for the quantitative analysis. The grey tones of the cloud are proportional to relative numerical particle concentration. Location of data in EOS CLOUDS is the optical fingerprint of the sample. Red line represents expected SPES position for PS spheres with different sizes. (BOTTOM) Numerical Particle Size Distribution of the PS sample. Average particle diameter retrieved by Classizer™ ONE software is 0.48 µm @ experimentally measured n=1.58.

AppCases_PolymericParticles_PS001new
AppCases_PolymericParticles_PS002new

Example of application: heterogeneous samples
In case of heterogeneous samples in terms of the sizes and/or of the refractive indexes, secondary populations could limit, or even preclude any reliable approaches with traditional analytical methods available on the market. Thanks to the SPES patented multiparametric single particle approach, Classizer™ ONE discriminates particles basing on their optical properties. Heterogeneous samples produce simultaneously more clouds on the EOS CLOUDS histogram for each particle population detected, which can be easily individually selected, analysed, counted, and compared. A SPES ahead in Particle Analysis.

(in figure) Example of EOS CLOUDS for a heterogeneous samples: (TOP) mix of PMMA 600nm and PS 600nm submicron particles. Two separate clouds are detected and can be selected and analyzed separately, as well as for the absolute and relative concentration of each particle population. Red line and blue line are expected trends for PMMA and PS, respectively. (BOTTOM) sample of silicon oil emulsion with PS 0.5µm spheres as traceable particles. Two principal and separated populations are detected. Red line represents expected size trend for droplets of silicon oil refractive index.

2dhist pmma PS
2dHist silicon oil ps