Effect of polymer concentration on stabilized large-tilt-angle flexoelectro-optic switching

In this letter, the uniform lying helix (ULH) liquid crystal texture, required for the flexoelectro-optic effect, is polymer stabilized by the addition of a small percentage of reactive mesogen to a high-tilt-angle (φ>60°) bimesogenic chiral nematic host. The electro-optic response is measured for a range of reactive mesogen concentration mixtures, and compared to the large-tilt-angle switch of the pure chiral nematic mixture. The optimum concentration of reactive mesogen, which is found to provide ample stabilization of the texture with minimal impact on the electro-optic response, is found to be approximately 3%. Our results indicate that polymer stabilization of the ULH texture using a very low concentration of reactive mesogen is a reliable way of ruggedizing flexoelectro-optic devices without interfering significantly with the electro-optics of the effect, negating the need for complicated surface alignment patterns or surface-only polymerization. The polymer stabilization is shown to reduce the temperature dependence of the flexoelectro-optic response due to "pinning" of the chiral nematic helical pitch. This is a restriction of the characteristic thermochromic behavior of the chiral nematic. Furthermore, selection of the temperature at which the sample is ultraviolet cured allows the tilt angle to be optimized for the entire chiral nematic temperature range. The response time, however, remains more sensitive to operating temperature than curing temperature. This allows the sample to be cured at low temperature and operated at high temperature, providing simultaneous optimization of these two previously antagonistic performance aspects. © 2006 American Institute of Physics.

Beam propagation modelling of tapered waveguide lasers

A dynamic beam propagation model allows design optimization of high power low divergence tapered waveguide lasers. The model is extended to include spatially-resolved temperature profiles and a temperature dependent gain. Using this model, design parameters such as the optimum facet reflectivity, taper angle, and waveguide dimension can be calculated for low far-field divergence and high continuous wave power.

Acoustic radiation force of a Bessel beam on a porous sphere.

The possibility of using acoustic Bessel beams to produce an axial pulling force on porous particles is examined in an exact manner. The mathematical model utilizes the appropriate partial-wave expansion method in spherical coordinates, while Biot's model is used to describe the wave motion within the poroelastic medium. Of particular interest here is to examine the feasibility of using Bessel beams for (a) acoustic manipulation of fine porous particles and (b) suppression of particle resonances. To verify the viability of the technique, the radiation force and scattering form-function are calculated for aluminum and silica foams at various porosities. Inspection of the results has shown that acoustic manipulation of low porosity (<0.3) spheres is similar to that of solid elastic spheres, but this behavior significantly changes at higher porosities. Results have also shown a strong correlation between the backscattered form-function and the regions of negative radiation force. It has also been observed that the high-order resonances of the particle can be effectively suppressed by choosing the beam conical angle such that the acoustic contribution from that particular mode vanishes. This investigation may be helpful in the development of acoustic tweezers for manipulation of micro-porous drug delivery carrier and contrast agents.

Occurrence of particle debris field during focused Ga ion beam milling of glassy carbon

To explore the machining characteristics of glassy carbon by focused ion beam (FIB), particles induced by FIB milling on glassy carbon have been studied in the current work. Nano-sized particles in the range of tens of nanometers up to 400 nm can often be found around the area subject to FIB milling. Two ion beam scanning modes - slow single scan and fast repetitive scan - have been tested. Fewer particles are found in single patterns milled in fast repetitive scan mode. For a group of test patterns milled in a sequence, it was found that a greater number of particles were deposited around sites machined early in the sequence. In situ EDX analysis of the particles showed that they were composed of C and Ga. The formation of particles is related to the debris generated at the surrounding areas, the low melting point of gallium used as FIB ion source and the high contact angle of gallium on glassy carbon induces de-wetting of Ga and the subsequent formation of Ga particles. Ultrasonic cleaning can remove over 98% of visible particles. The surface roughness (Ra) of FIB milled areas after cleaning is less than 2 nm. © 2010.

Guided self-organization in a dynamic embodied system based on attractor selection mechanism

Guided self-organization can be regarded as a paradigm proposed to understand how to guide a self-organizing system towards desirable behaviors, while maintaining its non-deterministic dynamics with emergent features. It is, however, not a trivial problem to guide the self-organizing behavior of physically embodied systems like robots, as the behavioral dynamics are results of interactions among their controller, mechanical dynamics of the body, and the environment. This paper presents a guided self-organization approach for dynamic robots based on a coupling between the system mechanical dynamics with an internal control structure known as the attractor selection mechanism. The mechanism enables the robot to gracefully shift between random and deterministic behaviors, represented by a number of attractors, depending on internally generated stochastic perturbation and sensory input. The robot used in this paper is a simulated curved beam hopping robot: a system with a variety of mechanical dynamics which depends on its actuation frequencies. Despite the simplicity of the approach, it will be shown how the approach regulates the probability of the robot to reach a goal through the interplay among the sensory input, the level of inherent stochastic perturbation, i.e., noise, and the mechanical dynamics. © 2014 by the authors; licensee MDPI, Basel, Switzerland.