EOS CLASSIZER SPES particle analysis

POLYMERICS

Particle size distribution, aggregation, oversize, and aging analysis of submicron and micrometric polymeric particle dispersions.

BIOFLUIDS

Improve formulation monitoring composition and stability of particles in unfiltered target biological fluids as plasma and cell lysate.

PIGMENTS AND INKS

Obtain a thorough characterization of pigments for cosmetics, paintsm and inks! Speed up the R&D and Quality Control processes!

ABS PARTICLES

Classify and monitor the behaviour, structure, and stability of absorbing submicron / micron sized particles even in flowing fluids.

ENVIRONMENT

Analyse mineral particles, carbon black, and micro/nanopastics to improve your research on the environmental changes.

AEROSOL

Multiparametric realtime classification and analysis of heterogeneous airborne particles thanks to patented SPES method.

EOS @ Making Cosmetics 2021 on 25 Nov 2021 at 10:30 CET! Save the date!

New Scientific Paper Published on SPES method: On the quasi-universality of the forward light scattering lobe for micrometric objects.

New AppNote AN006 : Multiparametric Classification of Particles as a Pathway to Oversize Analysis in Complex Fluids via SPES Technology

New AppNote AN012 : Monitor the Fate of a Lipid/ZnO Emulsion in Environments

New AppNote AN002 : Continuous SPES Flow Analysis (CFA-SPES)

SPES Technology

SPES (Single Particle Extinction & Scattering) is a novel patented technology for the multiparametric analysis of subvisible / submicron particles in industrial, environmental, and biological complex fluids.

Classizer™ ONE

EOS develops multiparametric platforms based on SPES patented technology for the development, formulation and quality control of novel classes of products based on the use of submicron/subvisible particles.

Contract Analysis Lab

EOS team is available for providing taylored services and support in the research, development and quality control of your innovative products based on submicron / subvisible particles in complex fluids.

This project has received funding from the European Union’s H2020 SME Instruments
Phase 1 research and innovation programme under grant agreement No 781906