Printed red-green-blue liquid crystal lasers

We present printable laser devices formed by dispersing dye-doped chiral nematic liquid crystals in solution-processible polymers. Unlike current technology, this allows lasers to be formed on a wide variety of surfaces, e.g. paper, plastic, metal. © 2012 OSA.

Reinforcement learning using a continuous time actor-critic framework with spiking neurons.

Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD) learning of Doya (2000) to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity.

Enhanced infra-red emission from sub-millimeter microelectromechanical systems micro hotplates via inkjet deposited carbon nanoparticles and fullerenes

In this paper, we demonstrate a micro-inkjet printing technique as a reproducible post-process for the deposition of carbon nanoparticles and fullerene adlayers onto fully CMOS compatible micro-electro-mechanical silicon-on-insulator infrared (IR) light sources to enhance their infrared emission. We show experimentally a significant increase in the infrared emission efficiency of the coated emitters. We numerically validate these findings with models suggesting a dominant performance increase for wavelengths <5.5 μm. Here, the bimodal size distribution in the diameter of the carbon nanoparticles, relative to the fullerenes, is an effective mediator towards topologically enhanced emittance of our miniaturised emitters. A 90% improvement in IR emission power density has been shown which we have rationalised with an increase in the mean thickness of the deposited carbon nanoparticle adlayer. © 2013 AIP Publishing LLC.

Printed red-green-blue liquid crystal lasers

We present printable laser devices formed by dispersing dye-doped chiral nematic liquid crystals in solution-processible polymers. Unlike current technology, this allows lasers to be formed on a wide variety of surfaces, e.g. paper, plastic, metal. © OSA 2012.

In-Situ grown carbon nanotubes for enhanced CO2 detection in non-dispersive-infra-red system

Non-dispersive-infra-red (NDIR) sensors are believed to be one of the most selective and robust solutions for CO2 detection, though cost prohibits their broader integration. In this paper we propose a commercially viable silicon-on-insulator (SOI) complementary metal-oxide (CMOS) micro-electro-mechanical (MEMS) technology for an IR thermal emitter. For the first time, vertically aligned multi walled carbon nanotubes (VA-MWCNTs) are suggested as a possible coating for the enhancement of the emission intensity of the optical source of a NDIR system. VA-MWCNTs have been grown in situ by chemical vapour deposition (CVD) exclusively on the heater area. Optical microscopy, scanning electron microscopy and Raman spectroscopy have been used to verify the quality of the VA-MWCNTs growth. The CNT-coated emitter demonstrated an increased response to CO2 of approx. 60%. Furthermore, we show that the VA-MWCNTs are stable up to temperatures of 500°C for up to 100 hours. © 2013 IEEE.