SPES Technology: How It Works and Advantages

SPES, or Single Particle Extinction and Scattering, is a family of advanced and patented optical technologies designed for particle size analysis and characterization of complex samples. Unlike techniques that mainly provide an average response from the whole sample, SPES is built to analyse particles individually, making it particularly useful when working with heterogeneous systems. This approach gives laboratories a richer and more realistic view of what is actually present in the sample. SPES is implemented in instruments designed and produced by EOS Instruments (EOS S.r.l.), including the Classizer™ ONE.

For companies and research teams dealing with emulsions, liposomes, biofluids, pigments, or particle mixtures, this level of detail can make a significant difference. SPES is especially relevant when the sample is too complex to be described accurately through a single bulk value. By focusing on single-particle behaviour, EOS Instruments’s technologies address analytical needs that are increasingly important in research, product development, and high-value quality control workflows.

How SPES Works

SPES works by measuring the light scattered in the forward direction and in the side by particles in liquid flowing through a focused laser beam inside a flow cell. As each particle crosses the beam waist, it generates a self‑referenced interference signal between the strong transmitted field and the particle’s forward (zero‑angle) scattered field, enabling the instrument to retrieve two independent parameters linked to the real and imaginary parts of the forward scattering amplitude for that individual particle.

At the same time, the scattered intensity at 90 degrees is analysed during the transit of the same particle through the measurement region, providing additional third independent optical information for particle characterization. These parameters generate the SPES data, so called EOS Clouds, two or three dimensional histograms where different particles populate different areas. Here particles can be easily separated by size and/or refractive index, and with a few clicks the different PSDs can be obtained.

At variance with traditional methods, the measurement of the effective refractive index enables an accurate estimation of the real PSD, without relying on heavy hypothesis about particle’s RI and structure.

Figure 1: The SPES sensor measures the complex fields scattered by single particles, illuminated by the laser focused on the cuvette. From this signal the software obtains the two optical parameters α and Cext . The intensity scattred at 90˚ is also measured for each particle providing further independent optical information on single particles.

Figure 2: A EOS Clouds plot, in logarithmic scales, pixels whose intensity is proportional to the number of particles measured with given (α, Cext). Here, as an example, an emulsion of silicon oil (red, faint pixels, RI 1.40) and 500 nm polystyrene particles (black, highlighted dot, RI 1.59). The emulsion is polydisperse, extending widely along the “size” axis, in blue, while the PS particles have a compact distribution. Both populations have well defined refractive index and shape, thus ending up in different positions along the Refractive Index axis, in red.

This measurement principle is particularly powerful when dealing with complex particle populations. In many real-world samples, particles differ not only in size but also in structure, composition, or refractive index behaviour. SPES allows the analyst to observe these differences with greater clarity, supporting a deeper understanding of the sample. In practical terms, this means better discrimination between populations, improved characterization, and more meaningful interpretation of measurement data.

Advantages of SPES Technology

One of the main advantages of SPES technology is its ability to deliver high-resolution information on heterogeneous samples that may be difficult to analyse with more conventional techniques. Because SPES measures particles one‑by‑one and extracts three independent optical observables simultaneously under identical illumination conditions, it can separate and classify overlapping particle populations in heterogeneous samples where ensemble techniques often struggle. The method is commonly described as calibration‑free / particle‑model‑free in the sense that it leverages the particle’s own forward scattering / extinction signature rather than relying on ensemble inversion assumptions, supporting robust outputs such as absolute particle size distribution and numerical concentration for each population. Finally, SPES is well suited to real‑time monitoring in continuous flow, making it attractive for R&D, formulation screening, stability or aggregation tracking, and process monitoring in complex fluids. This is especially important in applications where the analyst needs to distinguish between multiple particle populations, identify structural differences, or understand how a sample behaves in a realistic fluid environment. In these cases, single-particle analysis provides a clear analytical advantage.

Another major strength of SPES is its versatility. It can support advanced characterization in fields where formulation complexity is high and analytical confidence is essential, such as pharmaceuticals, biotechnology, materials science, and environmental analysis. Rather than being only another measurement technique, SPES provides a way to obtain more relevant and actionable insight from complex particle systems.

SPES vs traditional (ensemble) methods

Traditional particle sizing methods like DLS and laser diffraction (SLS) infer size distributions from ensemble-averaged scattering signals, so the reported PSD depends on model assumptions (e.g., Brownian-motion/Stokes–Einstein in DLS; Mie/Fraunhofer optical inversion in laser diffraction) and can be biased when samples are heterogeneous or contain a small fraction of larger outliers. In contrast, SPES measures particles one-by-one in continuous flow, using a self-referenced interference between the transmitted field and the particle’s forward (zero-angle) and side (e.g. 90 degree) scattered fields, extracting three independent parameters linked to the real and imaginary parts of the forward scattering amplitude and the side scattered intensity for each particle. This single-particle, dual-observable approach makes SPES inherently suited to mixtures and polydisperse systems, because it can build PSDs from discrete particle events rather than from an averaged signal that must be mathematically “unmixed.” Practically, that means SPES can deliver size distribution plus optical classification (effective refractive index and optical “fingerprint”) and numerical concentration in situations where ensemble methods may struggle to separate overlapping populations or to track subtle population changes over time. This is also why SPES is often positioned as complementary to DLS/SLS: .e.g., DLS excels at fast nanoscale screening and hydrodynamic size, while SPES adds population-level discrimination and per-particle optical information without relying on ensemble inversion to the same extent.

SPES vs traditional single particle methods 

Classic single-particle counters such as light obscuration (LO) / SPOS size particles from the magnitude of light blocking and/or scattering pulses compared to calibration curves, delivering robust count-and-size outputs but limited insight into particle identity beyond “equivalent spherical diameter,” and they can be constrained by sample suitability (e.g., coincidence/dilution needs; sensitivity to bubbles/complex formulations in compendial contexts). NTA also works particle-by-particle, but it relies on video tracking of Brownian motion and light scattering visibility, which makes performance dependent on optical detectability and Brownian-motion measurability across the size range. Coulter Counter are powerful orthogonal single-particle approaches, but they primarily report size/mass/volume and often require specific media/handling constraints. By comparison, SPES stays purely optical yet goes beyond “single signal amplitude = size” by retrieving two independent forward-scattering/extinction-related and one independent side intensity-scattering-related observables simultaneously for the same particle transit, enabling more robust optical classification of mixed populations alongside sizing and concentration. Finally, imaging-based single-particle methods (e.g., flow imaging microscopy) add morphology and visual classification, but they are fundamentally image/contrast-limited and typically operate best when particles are large enough and sufficiently contrasted to be imaged reliably; SPES complements imaging by providing high-throughput optical signatures in flow even when morphological imaging is less informative.