Microfluidic-based linear-optics label-free imager.

Linear optics based nanoscopy previously reached resolution beyond the diffraction limit, illuminating samples in the visible light regime while allowing light to interact with freely moving metallic nanoparticles. However, the hydrodynamics governing the nanoparticle motion used to scan the sample is very complex and has low probability of achieving appropriate and fast mapping in practice. Hence, an implementation of the technique on real biological samples has not been demonstrated so far.

Drag controlled formation of polymeric colloids with optical traps.

Optical trapping is a powerful optical manipulation technique for controlling various mesoscopic systems that allows formation of tailor-made polymeric micro-sized colloids by directed coalescence of nucleation sites. However, control over the size of a single colloid requires constant monitoring of the growth process and deactivation of the optical trap once it reaches the required dimensions. Moreover, producing more than one colloid requires moving the sample to a pristine location where the process must be repeated.

Imaging of nanoparticle dynamics in live and apoptotic cells using temporally-modulated polarization.

Gold nanoparticles are widely exploited in phototherapy. Owing to their biocompatibility and their strong visible-light surface plasmonic resonance, these particles also serve as contrast agents for cell image enhancement and super-resolved imaging. Yet, their optical signal is still insufficiently strong for many important real-life applications.

Plasma dispersion effect based super-resolved imaging in silicon.

We present here a new method for shaping a pulsed IR (λ = 1550nm) laser beam in silicon. The shaping is based on the plasma dispersion effect (PDE). The shaping is done by a second pulsed pump laser beam at 532nm (in either a Gaussian mode or a donut mode) which simultaneously and collinearly illuminates the silicon's surface with the IR beam.

Color image identification and reconstruction using artificial neural networks on multimode fiber images: towards an all-optical design.

The rapid growth of applications that rely on artificial neural network (ANN) concepts gives rise to a staggering increase in the demand for hardware implementations of neural networks. New types of hardware that can support the requirements of high-speed associative computing while maintaining low power consumption are sought, and optical artificial neural networks fit the task well. Inherently, optical artificial neural networks can be faster, support larger bandwidth, and produce less heat than their electronic counterparts.

Non-labeled lensless micro-endoscopic approach for cellular imaging through highly scattering media.

We describe an imaging approach based on an optical setup made up of a miniature, lensless, minimally invasive endoscope scanning a sample and matching post processing techniques that enable enhanced imaging capabilities. The two main scopes of this article are that this approach enables imaging beyond highly scattering medium and increases the resolution and signal to noise levels reaching single cell imaging. Our approach has more advantages over ordinary endoscope setups and other imaging techniques.

Optical-tweezing-based linear-optics nanoscopy.

Previous works reported that linear optics could be used to observe sub-wavelength features with a conventional optical microscope. Yet, the ability to reach a sub-200 nm resolution with a visible light remains limited. We present a novel widely-applicable method, where particle trapping is employed to overcome this limit.