Co-catalytic absorption layers for controlled laser-induced chemical vapor deposition of carbon nanotubes.

The concept of co-catalytic layer structures for controlled laser-induced chemical vapor deposition of carbon nanotubes is established, in which a thin Ta support layer chemically aids the initial Fe catalyst reduction. This enables a significant reduction in laser power, preventing detrimental positive optical feedback and allowing improved growth control. Systematic study of experimental parameters combined with simple thermostatic modeling establishes general guidelines for the effective design of such catalyst/absorption layer combinations. Local growth of vertically aligned carbon nanotube forests directly on flexible polyimide substrates is demonstrated, opening up new routes for nanodevice design and fabrication.

Optimal recall from bounded metaplastic synapses: predicting functional adaptations in hippocampal area CA3.

A venerable history of classical work on autoassociative memory has significantly shaped our understanding of several features of the hippocampus, and most prominently of its CA3 area, in relation to memory storage and retrieval. However, existing theories of hippocampal memory processing ignore a key biological constraint affecting memory storage in neural circuits: the bounded dynamical range of synapses. Recent treatments based on the notion of metaplasticity provide a powerful model for individual bounded synapses; however, their implications for the ability of the hippocampus to retrieve memories well and the dynamics of neurons associated with that retrieval are both unknown. Here, we develop a theoretical framework for memory storage and recall with bounded synapses. We formulate the recall of a previously stored pattern from a noisy recall cue and limited-capacity (and therefore lossy) synapses as a probabilistic inference problem, and derive neural dynamics that implement approximate inference algorithms to solve this problem efficiently. In particular, for binary synapses with metaplastic states, we demonstrate for the first time that memories can be efficiently read out with biologically plausible network dynamics that are completely constrained by the synaptic plasticity rule, and the statistics of the stored patterns and of the recall cue. Our theory organises into a coherent framework a wide range of existing data about the regulation of excitability, feedback inhibition, and network oscillations in area CA3, and makes novel and directly testable predictions that can guide future experiments.

Digital data transmission using electro-optically modulated vertical-cavity surface-emitting laser with saturable absorber

An electro-optically (EO) modulated oxide-confined vertical-cavity surface-emitting laser (VCSEL) containing a saturable absorber in the VCSEL cavity is studied. The device contains an EO modulator section that is resonant with the VCSEL cavity. A type-II EO superlattice medium is employed in the modulator section and shown to result in a strong negative EO effect in weak electric fields. Applying the reverse bias voltages to the EO section allows triggering of short pulses in the device. Digital data transmission (return-to-zero pseudo-random bit sequence, 27-1) at 10Gb/s at bit-error-rates well below 10-9 is demonstrated. © 2014 AIP Publishing LLC.