Characterization and remote sensing of biological particles using circular polarization

- We use MSTM code to model biological particles as optically active aggregates.
- Modeling reproduces the circular polarization trends found in lab measurements.
- A sharp change of circular polarization within absorption bands is replicated.
- The circular polarization depends on the porosity and size of aggregates.
- Our findings facilitate identification and characterization of biological particles.

Biological molecules are characterized by an intrinsic asymmetry known as homochirality. The result is optical activity of biological materials and circular polarization in the light scattered by microorganisms, cells of living organisms, as well as molecules (e.g. amino acids) of biological origin. Lab measurements (Sparks et al. (2009) [6,7]) have found that light scattered by certain biological systems, in particular photosynthetic organisms, is not only circular polarized but contains a characteristic spectral trend, showing a fast change and reversal of sign for circular polarization within absorption bands. Similar behavior can be expected for other biological and prebiological organics, especially amino acids. We begin our study by reproducing the laboratory measurements for photosynthetic organisms through modeling the biological material as aggregated structures and using the Multiple Sphere T-matrix (MSTM) code for light scattering calculations. We further study how the spectral effect described above depends on the porosity of the aggregates and the size and number of the constituent particles (monomers). We show that larger aggregates are characterized by larger values of circular polarization and discuss how light-scattering characteristics of individual monomers and electromagnetic interaction between them affect this result. We find that circular polarization typically peaks at medium (40-140°) scattering angles, and discuss recommendations for efficient remote observation of circular polarization from (pre)biological systems.