Poster Short Abstract

Monitoring air and water using optical and magneto‑gravitational traps, with holographic particle reconstruction and public access to the results

Poster Abstract

The analysis of air and water is essential for continuous environmental monitoring. Digital holography provides an innovative method for three-dimensional visualization and analysis of airborne particles. The project aims to study the composition of air and water both in situ and within mobile laboratories.

Air samples are collected within a controlled “air cube,” a closed, sterile, non-conductive container mechanically isolated from vibrations. An optical trap with a high numerical aperture lens immobilizes suspended particles using radiation pressure. The particles are illuminated (by a laser beam) to perform elastic light scattering, which is recorded by a sensor connected to a computer. Raw data are processed in Python, and through numerical propagation techniques, a three-dimensional model of each particle is reconstructed, including shape, size, and surface roughness.

The sensor records an angular intensity pattern containing the interferometric component, which constitutes the digital hologram. To obtain a physical reconstruction, the amplitude and phase maps are sent to a Spatial Light Modulator (SLM), which recreates the optical field inside an observation chamber.

Water samples are collected in cuvettes containing a substrate that retains particulate matter during evaporation. The remaining particles are recovered and combined with diamagnetic nanoparticles (silica, graphite, GaN). The magneto-gravitational trap operates effectively when the diamagnetic component dominates; particulates and pollutants are treated as ions adsorbed on the matrix.

Prepared particles are then introduced into magneto-gravitational traps and illuminated with a laser. The analysis follows the same methodology used for airborne particulate matter, including elastic scattering and digital hologram formation, followed by numerical reconstruction and SLM visualization.

The system is designed for use in mobile laboratories and for sharing results with the public through an open-source platform, allowing citizens to access the data and report potential environmental pollution risks.