A photonic nanojet is a local field enhancement generated in the vicinity of a properly chosen microsphere or microcylinder illuminated by a collimated light beam. These photonic nanojets have waists smaller than the diffraction limit and propagate over several optical wavelengths without significant diffraction. We investigate the properties of photonic nanojets using rigorous solutions of Maxwell’s equations. A remarkable property we have found is that they can significantly enhance the backscattering of light by nanometer-scale particles (as small as ~1 nm) located within the jets. The enhancement factor for the backscattering intensity can be as high as five to six orders of magnitude. As a result, the observed intensity of the backscattered light from the dielectric microsphere can be substantially altered due to the presence of a nanoparticle within the light jet. Furthermore, the intensity and angular distribution of the backscattered signal is extremely sensitive to the size of the nanoparticle, which may enable differentiating particles with accuracy up to 1 nm. These properties of photonic nanojets make them an ideal tool for detecting, differentiating and sorting nanoparticles, which is of immense necessity for the field of nano-biotechnology. For example, they could yield potential novel ultramicroscopy techniques using visible light for detecting proteins, viral particles, and even single molecules; and monitoring molecular synthesis and aggregation processes of importance in many areas of biology, chemistry, material sciences, and tissue engineering.
It is well recognized that the spectral characteristics of light scattered from living tissue can provide valuable diagnostic information. In order to address the gap in the understanding of light scattering by complex cellular and tissue structures, we developed analytical and computational methods to characterize light scattering signals from irregular shapes. Recently, we investigated the total-scattering-cross-section (TSCS) spectra of complicated geometries based on the finite-difference-time-domain (FDTD) simulations. We found that the TSCS spectra of many inhomogeneous and nonspherical particles can be approximated with those of their best-fitting homogeneous ellipsoidal counterparts, and calculated using a simple formula provided by the equiphase-sphere approximation. Furthermore, we have characterized backscattering spectra of inhomogeneous particles with stochastic distribution of interior refractive index. We have investigated the backscattering signals of a wide range of inhomogeneous micro-particles based on the FDTD method and the Gaussian Random Field model. Our numerical results indicate that, contrary to the TSCS, the backscattering spectrum is sensitive to small structures within a particle, with scales down to tens of nanometers. We also note that the spectroscopic properties of the backscattering signals are directly linked to the coherence length of the interior refractive index distribution, which characterizes the texture of the inhomogeneous particle. The implication of this study is the possibility of using spectroscopic techniques to detect cellular morphological and textural changes within scales several-times smaller than the wavelength.