Forces from highly focused laser beams: Modeling, measurement and application to refractive index measurements

The optical forces in optical tweezers can be robustly modeled over a broad range of parameters using generalsed Lorenz–Mie theory. We describe the procedure, and show how the combination of experimental measurement of properties of the trap coupled with computational modeling, can allow unknown parameters of the particle—in this case, the refractive index—to be determined.

Computational modeling of optical trapping of vaterite microspheres

The ability to grow microscopic spherical birefringent crystals of vaterite, a calcium carbonate mineral, has allowed the development of an optical microrheometer based on optical tweezers. However, since these crystals are birefringent, and worse, are expected to have non-uniform birefringence, computational modeling of the microrheometer is a highly challenging task. Modeling the microrheometer - and optical tweezers in general - typically requires large numbers of repeated calculations for the same trapped particle. This places strong demands on the efficiency of computational methods used. While our usual method of choice for computational modelling of optical tweezers - the T-matrix method - meets this requirement of efficiency, it is restricted to homogeneous isotropic particles. General methods that can model complex structures such as the vaterite particles, such as finite-difference time-domain (FDTD) or finite-difference frequency-domain (FDFD) methods, are inefficient. Therefore, we have developed a hybrid FDFD/T-matrix method that combines the generality of volume-discretisation methods such as FDFD with the efficiency of the T-matrix method. We have used this hybrid method to calculate optical forces and torques on model vaterite spheres in optical traps. We present and compare the results of computational modelling and experimental measurements.

Nanotrapping and the thermodynamics of optical tweezers

Particles that can be trapped in optical tweezers range from tens of microns down to tens of nanometres in size. Interestingly, this size range includes large macromolecules. We show experimentally, in agreement with theoretical expectations, that optical tweezers can be used to manipulate single molecules of polyethylene oxide suspended in water. The trapped molecules accumulate without aggregating, so this provides optical control of the concentration of macromolecules in solution. Apart from possible applications such as the micromanipulation of nanoparticles, nanoassembly, microchemistry, and the study of biological macromolecules, our results also provide insight into the thermodynamics of optical tweezers.

Optical trapping of a cube

The successful development and optimisation of optically-driven micromachines will be greatly enhanced by the ability to computationally model the optical forces and torques applied to such devices. In principle, this can be done by calculating the light-scattering properties of such devices. However, while fast methods exist for scattering calculations for spheres and axisymmetric particles, optically-driven micromachines will almost always be more geometrically complex. Fortunately, such micromachines will typically possess a high degree of symmetry, typically discrete rotational symmetry. Many current designs for optically-driven micromachines are also mirror-symmetric about a plane. We show how such symmetries can be used to reduce the computational time required by orders of magnitude. Similar improvements are also possible for other highly-symmetric objects such as crystals. We demonstrate the efficacy of such methods by modelling the optical trapping of a cube, and show that even simple shapes can function as optically-driven micromachines.

Distance measurement using the change in junction voltage across a laser diode due to the self-mixing effect

Conventional detection scheme for self-mixing sensors uses an integrated photodiode within the laser package to monitor the self mixing signal. This arrangement can be simplified by directly obtaining the self-mixing signals across the laser diode itself and omitting the photodiode. This work reports on a Vertical-Cavity Surface-Emitting Laser (VCSEL) based selfmixing sensor using the laser junction voltage to obtain the selfmixing signal. We show that the same information can be obtained with only minor changes to the extraction circuitry leading to potential cost saving with reductions in component costs and complexity and significant increase in bandwidth favoring high speed modulation. Experiments using both photo current and voltage detection were carried out and the results obtained show good agreement with the theory.

PhotoVoltaic DC-DC module integrated converter for novel cascaded and bypass grid connection topologies - design and optimisation

Grid connected PhotoVoltaic (PV) inverters fall into three broad categories — Central, String and Module Integrated Converers (MICs). MICs offer any avantaes in performance and flexibility, but are at a cost disadvantage. Two alternative novel approaches proposed by the author — cascaded dc-dc MICs and bypass dc-dc MICs — integrate a simple non-isolated intelligent dc-dc converter with each PV module to provide the advantages of dc-ac MICs at a lower cost. A suitable universal 150W 5A dc-dc converter design is presented based on two interleaved MOSFET half bridges. Testing shows Zero Voltage Switching (ZVS) keeps losses under 1W for bi-directional power flows up to 15W between two adjacent 12V PV modules for the bypass application, and efficiencies over 94% for most of the operational power range for the cascaded converter application. Based on the experimental results, potential optimizations to further reduce losses are discussed.

Left-right information flow in the brain during EEG arousals

In disorders such as sleep apnea, sleep is fragmented with frequent EEG-arousal (EEGA) as determined via changes in the sleep-electroencephalogram. EEGA is a poorly understood, complicated phenomenon which is critically important in studying the mysteries of sleep. In this paper we study the information flow between the left and right hemispheres of the brain during the EEGA as manifested through inter-hemispheric asynchrony (IHA) of the surface EEG. EEG data (using electrodes A1/C4 and A2/C3 of international 10-20 system) was collected from 5 subjects undergoing routine polysomnography (PSG). Spectral correlation coefficient (R) was computed between EEG data from two hemispheres for delta-delta(0.5-4 Hz), theta-thetas(4.1-8 Hz), alpha-alpha(8.1-12 Hz) & beta-beta(12.1-25 Hz) frequency bands, during EEGA events. EEGA were graded in 3 levels as (i) micro arousals (3-6 s), (ii) short arousals (6.1-10 s), & (iii) long arousals (10.1-15 s). Our results revealed that in beta band, IHA increases above the baseline after the onset of EEGA and returns to the baseline after the conclusion of event. Results indicated that the duration of EEGA events has a direct influence on the onset of IHA. The latency (L) between the onset of arousals and IHA were found to be L=2plusmn0.5 s (for micro arousals), 4plusmn2.2 s (short arousals) and 6.5plusmn3.6 s (long arousals)