Particle characterization

Median, mean and cumulative / density distribution

• Particle size distribution using STEP technology^® in suspensions, according to ISO 13317 / 13318-2 with LUMiSizer^® analytical photo centrifuge and LUMiReader^® PSA, typical particle sizes of 10 nm to 30 µm or 500 nm to 300 µm
• Particle size distribution by laser diffractionin suspensions, application of Mie and Fraunhofer theorytypical particle sizes from 0.1 μm to 1200 μm
• Particle size distribution by means of laser light scatteringin suspensions, by single particle light scattering analyzer, with the LUMiSpoc, typical particle sizes from 0.2 μm to 2 μm

Effective density, skeletal density, density distribution

 

Determining the effective density of suspended nano- and microparticles is a key procedure in materials science. Using special sedimentation analysis methods, we can precisely analyze the density distribution of these particles. An important aspect here is the determination of the particle migration velocity in continuous phases with different densities.

These precise methods for determining the effective density contribute significantly to the understanding of material properties and the optimization of processes. By precisely characterizing the density distribution, valuable insights can be gained into the structure and functionality of the materials, which in turn contributes to the development of more efficient and higher-performance products.

 

We offer two methodological approaches:

• Method of Isopycnic Interpolation

In the suspended state, the particle density corresponds exactly to the density of the liquid suspension medium (Archimedes principle). The particles are dispersed in different solutions with densities close to, above and below the expected particle density, and the direction and magnitude of the velocity of the moving particles are determined. The effective particle density is determined by interpolation of the liquid density to the particle velocity zero.

• Multiple - Velocity Method

The multiple velocity method is used ito determine the effective density of particles. The average effective particle density is calculated from the experimentally determined separation velocities of the particles. The particles are dispersed in two or more liquids with different densities, such as H₂O, D₂O and their mixtures. The effective density of the particles is determined from the measured velocities using the Stokes equation.

 

Basic principle: The method is based on measuring the velocity of an object in a medium and combining these measurements with different values of the density-determining variables (e.g. mass or volume) in order to calculate the density.

 

Procedure:

1. The speed of the object is measured as it moves through the medium.
2. This measurement is repeated for different values of the density-determining variable (either different masses at constant volume or different volumes at constant mass).
3. From the recorded velocities at different masses or volumes, relationships can be derived to calculate the density.

 

Density calculation: By recording a series of velocities at different density-determining quantities, a relationship between velocity and density can be established. This relationship is analyzed, often by regression, to determine the density of the object

The Hansen Solubility Parameters (HSP) are a proven method for analyzing particle surface properties. Based on the "like dissolves like" principle, HSP theory is used to investigate dispersibility, wettability, and adsorption characteristics of particle surfaces.

Determining Hansen Parameters for Accurate Particle Characterization

HSP/HDP analysis is based on three key parameters:

✔ δD (Dispersion Forces) – Van der Waals interactions
✔ δP (Polarity) – Dipole-dipole interactions between molecules
✔ δH (Hydrogen Bonding) – Strong intermolecular forces

To disperse particles, test solvents from the 3D Hansen space are used as continuous phases. The separation kinetics of particles in each liquid are then analyzed using STEP technology. Based on their behavior, the test solvents are classified as "good" or "poor" dispersants.

Optimized Data Analysis with HSPiP Software

The collected data is processed using HSPiP software, ensuring precise calculation of Hansen dispersibility parameters. This method provides a reliable classification of particles, allowing targeted optimization of their surface properties.

Benefits of HSP/HDP Analysis for Research & Industry

✅ Targeted optimization of particle dispersion
✅ Enhanced wettability & adsorption properties
✅ Efficient material and process development

Leverage state-of-the-art HSP/HDP analysis to improve your material properties. Contact us today for a personalized consultation!