Optical tweezers manipulate microscopic objects with light by exchanging momentum and angular momentum between particle and light, generating optical forces and torques. Understanding and predicting them is essential for designing and interpreting experiments. Here, we focus on geometrical optics and optical forces and torques in this regime, and we employ neural networks to calculate them. Using an optically trapped spherical particle as a benchmark, we show that neural networks are faster and more accurate than the calculation with geometrical optics. We demonstrate the effectiveness of our approach in studying the dynamics of systems that are computationally “hard” for traditional computation.
Microengines have shown promise for a variety of applications in nanotechnology, from microfluidics to nanomedicine and targeted drug delivery. However, their precise control over their dynamics is still challenging. We introduce a micro engine that exploits both optical and thermal effects to achieve a high degree of controllability. We find that a gold-silica Janus particle illuminated by a high focused laser beam can be confined at the stationary point where the optical and thermal forces balance. By using circularly polarized light the symmetry between these forces can be broken by transferring angular momentum to the particle, resulting in a tangential force that induces an orbital motion of the particle. We can simultaneously control the velocity and direction of rotation of the particle, changing the ellipticity of the incoming light beam while tuning the radius of the orbit with laser power. We validate our results using a geometrical optics model that incorporates optical force, the absorption of optical power, and the resulting heating of the particle.
Optical nano-printing provides a versatile platform to print various nanoparticles into arbitrary configurations. Optical printing, the use of light to direct the formation of a desired structure, has been of significant interest in the last two decades. For particles much smaller than the laser wavelength, optical forces can be well described in the dipole approximation. For a focused laser beam, two main optical force components are identified: the gradient force, which attracts particles toward the high-intensity focal spot, and the scattering force, which tends to push particles along the beam propagation direction. When the wavelength light is close to the particle localized surface plasmons resonance, a scattering force is dominant and can be used to efficiently push nanoparticles along the beam optical axis onto a substrate. In this context, optical forces can be applied to optically print nanoparticles into patterns aggregated on surfaces such as glass. Here, we report on use optical nanoprinting of plasmonic nanoparticles to create an active aggregate in a solution containing dyes or nanoplastics. The active aggregate, produced by optical forces, serves as a sensitive sensor which is used to detect dyes in concentrations below the limit of detection for Raman spectroscopy and/or to detection of plastic nanoparticles.
Intracavity optical tweezers have been proven successful for trapping microscopic particles at very low average power intensity – much lower than the one in standard optical tweezers. This feature makes them particularly promising for the study of biological samples. The modeling of such systems, though, requires time-consuming numerical simulations that affect its usability and predictive power. With the help of machine learning, we can overcome the numerical bottleneck – the calculation of optical forces, torques, and losses – reproduce the results in the literature and generalize to the case of counterpropagating-beams intracavity optical trapping.
We study theoretically the opto-mechanics of a metallic nano-shell with a gain-enriched dielectric core in stationary Optical Tweezers. In order to avoid the counterproductive effects of scattering forces we choose a two counter-propagating beams configuration. The application of an external pump enhances the plasmonic resonance of the nano-shell thus affecting the optical forces acting on the particle even at pump powers below the emission threshold. We show that the trapping strength can be largely improved without the necessity to increase the trapping beam power. We support the theoretical analysis with Brownian dynamics simulations that show how particle position locking is achieved at high gains in exended optical trapping potentials. Finally, for wavelengths blue-detuned with respect to the plasmon-enhanced resonance, we observe particle channeling by the standing wave antinodes due to gradient force reversal.
We present an application of machine learning to deal with the optimization of testing strategies in the event of large-scale epidemic outbreaks. We describe the disease using the archetypal SIR model. Cost-effective containment relies on making the best possible use of the available resources to identify infectious cases. We present a neural-network-powered strategy that adapts to an epidemic without knowing the underlying parameters of the model. The neural network results are more effective than standard approaches, also in the presence of asymptomatic cases. We envision that similar methods can be employed in public health to control epidemic outbreaks.
Even though in most cases optical forces can be calculated semi-analytically, the computation becomes prohibitively slow in problems where the calculation needs to be repeated several times. Starting from a spherical particle in an optical trap, we show how machine learning can be used to improve not only the speed but also the accuracy of the optical force calculations in the geometrical optics approach. This is demonstrated to work efficiently at least up to 9 degrees of freedom, constituting a tool for exploring problems that were out of the scope of the traditional geometrical optics calculation.
Cosmic dust particles are usually collected in space or in the Earth’s stratosphere and deposited on a substrate to be analysed at large terrestrial facilities.
We use Raman tweezers technique for the contacless manypulation of cosmic dust particles, to identify their compositions and to characterize their response to optical forces without any substrate effects, documenting the high potential of this novel technique for space exploration.
In standard optical tweezers optical forces arise from the interaction of a tightly focused laser beam with a microscopic particle. The particle is always outside the laser cavity and the incoming beam is not affected by the particle position. Here we describe an optical trapping scheme inside the cavity of a fiber laser where the laser operation is nonlinearly influenced by the displacement of trapped particle and there is a coupling between laser operation to the motion of the trapped particle and this can dramatically enhances optical tweezers action and gives rise to nonlinear feedback forces. This scheme operates using an aspheric lens at low numerical aperture (NA=0.125), NIR wavelength (λ = 1030 nm), and very low average power which results in about two orders of magnitude reduction in exposure to laser intensity compared to standard optical tweezers. Ultra-low intensity at our wavelength can grant a safe, temperature-controlled environment, away from surfaces for microfuidics manipulation of biosamples that are sensitive to light intensity. As the main advantage of our approach and highly relevant application, we observed that we can trap single yeast cells at a very low power, corresponding to an intensity of 0.036 mW μm-2, that is more than a tenfold less intensity than standard techniques reported in the literature.
Random optical media (ROM) are a novel class of photonic materials characterized by a disordered assembly of the elementary constituents (such as particles, wires and fibers), that determines unique scattering, absorption and emission properties. The propagation of light in ROM is affected by the size and optical properties (refractive index, absorption and emission wavelengths) of their components, as well as by the overall 3-dimensional architecture. So far, most of the investigated ROM have been realized using liquid dispersions or bulk samples embedding colloidal nanoparticles or porous systems. While nanowire-based ROM are poorly investigated, such materials can feature new optical effects related to the elongated shape of their building blocks and to their light-transport properties. Here we report on the fabrication and on the morphological and spectroscopic characterization of hybrid organic-inorganic nanowires, realized by doping polymers with dielectric nanoparticles. We investigate light diffusion and multi-scattering properties of 3- dimensional ROM formed by organic and hybrid nanowires, as well as field localization in 2-dimensional networks. The influence of nanowire geometry and composition on the scattering properties is also discussed.
Electrospinning technologies for the realization of active polymeric nanomaterials can be easily up-scaled, opening perspectives to industrial exploitation, and due to their versatility they can be employed to finely tailor the size, morphology and macroscopic assembly of fibers as well as their functional properties. Light-emitting or other active polymer nanofibers, made of conjugated polymers or of blends embedding chromophores or other functional dopants, are suitable for various applications in advanced photonics and sensing technologies. In particular, their almost onedimensional geometry and finely tunable composition make them interesting materials for developing novel lasing devices. However, electrospinning techniques rely on a large variety of parameters and possible experimental geometries, and they need to be carefully optimized in order to obtain suitable topographical and photonic properties in the resulting nanostructures. Targeted features include smooth and uniform fiber surface, dimensional control, as well as filament alignment, enhanced light emission, and stimulated emission. We here present various optimization strategies for electrospinning methods which have been implemented and developed by us for the realization of lasing architectures based on polymer nanofibers. The geometry of the resulting nanowires leads to peculiar light-scattering from spun filaments, and to controllable lasing characteristics.
We propose a novel approach for trapping micron-sized particles and living cells based on optical feedback. This approach can be implemented at low numerical aperture (NA=0.5, 20X) and long working distance. In this configuration, an optical tweezers is constructed inside a ring cavity fiber laser and the optical feedback in the ring cavity is controlled by the light scattered from a trapped particle. In particular, once the particle is trapped, the laser operation, optical feedback and intracavity power are affected by the particle motion. We demonstrate that using this configuration is possible to stably hold micron-sized particles and single living cells in the focal spot of the laser beam. The calibration of the optical forces is achieved by tracking the Brownian motion of a trapped particle or cell and analysing its position distribution.
We present a computational model for the simulation of optically interacting nano-structures immersed in a viscous fluid. In this scheme, nanostructures are represented by aggregates of small spheres. All optical and hydrodynamic interactions, including thermal fluctuations, are included. As an example, we consider optical binding of dielectric nanowires in counterpropagating plane waves. In particular, the formation of stable, ladder like structures, is demonstrated. In these arrangements, each nanowire lies parallel to the polarization direction of the beams, with their centres of mass colinear.
We present a study of the manipulation of microparticles and the formation of optically bound structures of
particles in evanescent wave traps. Two trapping geometries are considered: the first is a surface trap where
the evanescent field above a glass prism is formed by the interference of a number of laser beams incident on
the prism-water interface; the second uses the evanescent field surrounding a biconical tapered optical fiber that
has been stretched to produce a waist of submicron diameter. In the surface trap we observe optical binding
of microparticles in to one-dimensional chain structures. In the tapered optical fiber trap we demonstrate
both particle transport for long distances along the fiber, and the formation of stable arrays of particles. In
both experiments we use video microscopy to track the particle locations and make quantitative measures of
the particle dynamics. The experimental studies of particle structures are complemented by light scattering
calculations based on Mie theory to infer how the geometries of the observed particle structures are controlled
by the underlying incident and scattered optical fields.
We present the result of an investigation into the optical trapping of micropaticles using laser beams with a spatially inhomogeneous polarization (cylindrical vector beams). We perform three-dimensional tracking of the Brownian fluctuations in position of a trapped particle and extract the trap spring constants. We characterize the trap geometry by the aspect ratio of spring constants in the directions transverse and parallel to the beam propagation direction and evaluate this figure of merit as a function of polarization angle. We show that the additional degree of freedom present in cylindrical vector beams (CVBs) allows us to control the optical trap strength and geometry by adjusting the polarization of the trapping beam only. Experimental results are compared with a theoretical model of optical trapping using CVBs derived from electromagnetic scattering theory in the T-matrix framework.
We consider the trapping of low refractive index objects, such as ultrasound contrast agent microbubbles, in a dual-beam fibre-optic trap. We confirm numerically that such a configuration results in stable trapping and we present the calculated trapping forces and spring constants. Furthermore we calculate the photonic stress profile over the surface of the trapped microbubble using both ray optics and Mie scattering approaches, and compare the results. We then find the optical stress-induced deformation of the microbubble for both the ray optics and Mie scattering stress profiles using linear elastic membrane theory. We suggest that this method could be a useful tool for quantifying the mechanical properties of the shell material of an ultrasound contrast agent microbubble.
We investigate experimentally and theoretically plasmon-enhanced optical trapping of metal nanoparticles. We calculate
the optical forces on gold and silver nanospheres through a procedure based on the Maxwell stress tensor in the transition
T-matrix formalism. We compare our calculations with experimental results finding excellent agreement. We also
demonstrate how light-driven rotations can be generated and detected in non-symmetric nanorods aggregates. Analyzing
the motion correlations of the trapped nanostructures, we measure with high accuracy both the optical trapping
parameters, and the rotation frequency induced by the radiation pressure.
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