SWCNT networks on nanoporous silica catalyst support : morphological and connectivity control for nanoelectronic, gas-sensing, and biosensing devices

Effective control of morphology and electrical connectivity of networks of single-walled carbon nanotubes (SWCNTs) by using rough, nanoporous silica supports of Fe catalyst nanoparticles in catalytic chemical vapor deposition is demonstrated experimentally. The very high quality of the nanotubes is evidenced by the G-to-D Raman peak ratios (>50) within the range of the highest known ratios. Transitions from separated nanotubes on smooth SiO2 surface to densely interconnected networks on the nanoporous SiO2 are accompanied by an almost two-order of magnitude increase of the nanotube density. These transitions herald the hardly detectable onset of the nanoscale connectivity and are confirmed by the microanalysis and electrical measurements. The achieved effective nanotube interconnection leads to the dramatic, almost three-orders of magnitude decrease of the SWCNT network resistivity compared to networks of similar density produced by wet chemistry-based assembly of preformed nanotubes. The growth model, supported by multiscale, multiphase modeling of SWCNT nucleation reveals multiple constructive roles of the porous catalyst support in facilitating the catalyst saturation and SWCNT nucleation, consistent with the observed higher density of longer nanotubes. The associated mechanisms are related to the unique surface conditions (roughness, wettability, and reduced catalyst coalescence) on the porous SiO2 and the increased carbon supply through the supporting porous structure. This approach is promising for the direct integration of SWCNT networks into Si-based nanodevice platforms and multiple applications ranging from nanoelectronics and energy conversion to bio- and environmental sensing.

Nanoscale-electrical and optical properties of iii-nitrides

III-nitrides are wide-band gap materials that have applications in both electronics and optoelectronic devices. Because to their inherent strong polarization properties, thermal stability and higher breakdown voltage in Al(Ga,In)N/GaN heterostructures, they have emerged as strong candidates for high power high frequency transistors. Nonetheless, the use of (Al,In)GaN/GaN in solid state lighting has already proved its success by the commercialization of light-emitting diodes and lasers in blue to UV-range. However, devices based on these heterostructures suffer problems associated to structural defects. This thesis primarily focuses on the nanoscale electrical characterization and the identification of these defects, their physical origin and their effect on the electrical and optical properties of the material. Since, these defects are nano-sized, the thesis deals with the understanding of the results obtained by nano and micro-characterization techniques such as atomic force microscopy(AFM), current-AFM, scanning kelvin probe microscopy (SKPM), electron beam induced current (EBIC) and scanning tunneling microscopy (STM). This allowed us to probe individual defects (dislocations and cracks) and unveil their electrical properties. Taking further advantage of these techniques,conduction mechanism in two-dimensional electron gas heterostructures was well understood and modeled. Secondarily, origin of photoluminescence was deeply investigated. Radiative transition related to confined electrons and photoexcited holes in 2DEG heterostructures was identified and many body effects in nitrides under strong optical excitations were comprehended.

Electrostatic layer-by-layer deposition and electrochemical characterization of thin films composed of MnO(2) nanoparticles in a room-temperature ionic liquid

Thin films of MnO(2) nanoparticles were grown using the layer-by-layer method with poly (diallyldimetylammonium) as the intercalated layer. The film growth was followed by UV-vis, electrochemical quartz crystal microbalance (EQCM), and atomic force microscopy. Linear growth due to electrostatic immobilization of layers was observed up to 30 bilayers, but electrical connectivity was maintained only for 12 MnO(2)/PPDA bilayers. The electrochemical characterization of this film in 1-butyl-2,3-dimethyl-imidazolium (BMMI) bis(trifluoromethanesulfonyl)imide (TFSI) (BMMITFSI) with and without addition of a lithium salt indicated a higher electrochemical response of the nanostructured electrode in the lithium-containing electrolyte. On the basis of EQCM experiments, it was possible to confirm that the charge compensation process is achieved mainly by the TFSI anion at short times (<2 s) and by BMMI and lithium cations at longer times. The fact that large ions like TFSI and BMMI participate in the electroneutrality is attributed to the redox reaction that occurs at the superficial sites and to the high concentration of these species compared to that of lithium cations.

Electrical control of nanoscale functionalization in graphene by the scanning probe technique

Functionalized graphene is a versatile material that has well-known physical and chemical properties depending on functional groups and their coverage. However, selective control of functional groups on the nanoscale is hardly achievable by conventional methods utilizing chemical modifications. We demonstrate electrical control of nanoscale functionalization of graphene with the desired chemical coverage of a selective functional group by atomic force microscopy (AFM) lithography and their full recovery through moderate thermal treatments. Surprisingly, our controlled coverage of functional groups can reach 94.9% for oxygen and 49.0% for hydrogen, respectively, well beyond those achieved by conventional methods. This coverage is almost at the theoretical maximum, which is verified through scanning photoelectron microscope measurements as well as first-principles calculations. We believe that the present method is now ready to realize 'chemical pencil drawing' of atomically defined circuit devices on top of a monolayer of graphene. © 2014 Nature Publishing Group All rights reserved.

The influence of connectivity on the firing rate in a neuronal network with electrical and chemical synapses

We study the firing rate properties of a cellular automaton model for a neuronal network with chemical synapses. We propose a simple mechanism in which the nonlocal connections are included, through electrical and chemical synapses. In the latter case, we introduce a time delay which produces self-sustained activity. Nonlocal connections, or shortcuts, are randomly introduced according to a specified connection probability. There is a range of connection probabilities for which neuron firing occurs, as well as a critical probability for which the firing ceases in the absence of time delay. The critical probability for nonlocal shortcuts depends on the network size according to a power-law. We also compute the firing rate amplification factor by varying both the connection probability and the time delay for different network sizes. (C) 2011 Elsevier B.V. All rights reserved.

Thermal and electrical currents in nanoscale electronic interferometers

We theoretically study thermal transport in an electronic interferometer comprising a parallel circuit of two quantum dots, each of which has a tunable single electronic state which are connected to two leads at different temperature. As a result of quantum interference, the heat current through one of the dots is in the opposite direction to the temperature gradient. An excess heat current flows through the other dot. Although locally, heat flows from cold to hot, globally the second law of thermodynamics is not violated because the entropy current associated with heat transfer through the whole device is still positive. The temperature gradient also induces a circulating electrical current, which makes the interferometer magnetically polarized.

Large magnetoelectric coupling in nanoscale BiFeO3 from direct electrical measurements

We report the results of direct measurement of remanent hysteresis loops on nanochains of BiFeO3 at room temperature under zero and ∼20 kOe magnetic field. We noticed a suppression of remanent polarization by nearly ∼40% under the magnetic field. The powder neutron diffraction data reveal significant ion displacements under a magnetic field which seems to be the origin of the suppression of polarization. The isolated nanoparticles, comprising the chains, exhibit evolution of ferroelectric domains under dc electric field and complete 180 switching in switching-spectroscopy piezoresponse force microscopy. They also exhibit stronger ferromagnetism with nearly an order of magnitude higher saturation magnetization than that of the bulk sample. These results show that the nanoscale BiFeO3 exhibits coexistence of ferroelectric and ferromagnetic order and a strong magnetoelectric multiferroic coupling at room temperature comparable to what some of the type-II multiferroics show at a very low temperature.

Microscale study of electrical characteristics of epoxy-multiwall carbon nanotube nanocomposites

Epoxy-multiwall carbon nanotube nanocomposite thin films were prepared by spin casting. High power air plasma was used to preferentially etch a coating of epoxy and expose the underlying carbon nanotube network. Scanning electron microscopy (SEM) examination revealed well distributed and spatially connected carbon nanotube network in both the longitudinal direction (plasma etched surface) and traverse direction (through-thickness fractured surface). Topographical examination and conductive mode imaging of the plasma etched surface using atomic force microscope (AFM) in the contact mode enabled direct imaging of topography and current maps of the embedded carbon nanotube network. Bundles consisting of at least three single carbon nanotubes form part of the percolating network observed under high resolution current maps. Predominantly non-ohmic response is obtained in this study; behaviour attributed to less than effective polymer material removal when using air plasma etching.

Temperature dependent electrical resistivity in expoxy : multiwall carbon nanotube nanocomposites

Thin films of expoxy nanocomposites modified by multiwall carbon nanotubes (MWCNTs) were prepared by shear mixing and spin casting. The electrical behaviour and its dependence with temperature between 243 and 353 degrees Kelvin were characterized by measuring the direct current (DC) conductivity. Depending on the fabrication process, both linear and non-linear relationships between conductivity and temperature were observed. In addition, the thermal history also played a role in dictating the conductivity. The implications of these observations for potential application of these files as strain sensors are discussed.

Optimally increasing secure connectivity in multihop wireless ad hoc networks

We consider the problem of how to maximize secure connectivity of multi-hop wireless ad hoc networks after deployment. Two approaches, based on graph augmentation problems with nonlinear edge costs, are formulated. The first one is based on establishing a secret key using only the links that are already secured by secret keys. This problem is in NP-hard and does not accept polynomial time approximation scheme PTAS since minimum cutsets to be augmented do not admit constant costs. The second one is based of increasing the power level between a pair of nodes that has a secret key to enable them physically connect. This problem can be formulated as the optimal key establishment problem with interference constraints with bi-objectives: (i) maximizing the concurrent key establishment flow, (ii) minimizing the cost. We show that both problems are NP-hard and MAX-SNP (i.e., it is NP-hard to approximate them within a factor of 1 + e for e > 0 ) with a reduction to MAX3SAT problem. Thus, we design and implement a fully distributed algorithm for authenticated key establishment in wireless sensor networks where each sensor knows only its one- hop neighborhood. Our witness based approaches find witnesses in multi-hop neighborhood to authenticate the key establishment between two sensor nodes which do not share a key and which are not connected through a secure path.

Complexity of increasing the secure connectivity in wireless ad hoc networks

We consider the problem of maximizing the secure connectivity in wireless ad hoc networks, and analyze complexity of the post-deployment key establishment process constrained by physical layer properties such as connectivity, energy consumption and interference. Two approaches, based on graph augmentation problems with nonlinear edge costs, are formulated. The first one is based on establishing a secret key using only the links that are already secured by shared keys. This problem is in NP-hard and does not accept polynomial time approximation scheme PTAS since minimum cutsets to be augmented do not admit constant costs. The second one extends the first problem by increasing the power level between a pair of nodes that has a secret key to enable them physically connect. This problem can be formulated as the optimal key establishment problem with interference constraints with bi-objectives: (i) maximizing the concurrent key establishment flow, (ii) minimizing the cost. We prove that both problems are NP-hard and MAX-SNP with a reduction to MAX3SAT problem.

Development of the 'rich club' in brain connectivity networks from 438 adolescents & adults aged 12 to 30

The 'rich club' coefficient describes a phenomenon where a network's hubs (high-degree nodes) are on average more intensely interconnected than lower-degree nodes. Networks with rich clubs often have an efficient, higher-order organization, but we do not yet know how the rich club emerges in the living brain, or how it changes as our brain networks develop. Here we chart the developmental trajectory of the rich club in anatomical brain networks from 438 subjects aged 12-30. Cortical networks were constructed from 68×68 connectivity matrices of fiber density, using whole-brain tractography in 4-Tesla 105-gradient high angular resolution diffusion images (HARDI). The adult and younger cohorts had rich clubs that included different nodes; the rich club effect intensified with age. Rich-club organization is a sign of a network's efficiency and robustness. These concepts and findings may be advantageous for studying brain maturation and abnormal brain development.

Effect of antimony addition on the thermal and electrical-switching behavior of bulk Se-Te glasses

The thermal properties and electrical-switching behavior of semiconducting chalcogenide SbxSe55-xTe45 (2 <= x <= 9) glasses have been investigated by alternating differential scanning calorimetry and electrical-switching experiments, respectively. The addition of Sb is found to enhance the glass forming tendency and stability as revealed by the decrease in non-reversing enthalpy Delta H-nr. and an increase in the glass-transition width Delta T-g. Further, the glass-transition temperature of SbxSe55-xTe45 glasses, which is a measure of network connectivity, exhibits a subtle increase, suggesting a meager network growth with the addition of Sb. The crystallization temperature is also observed to increase with Sb content. The SbxSe55-xTe45 glasses (2 <= x <= 9) are found to exhibit memory type of electrical switching, which can be attributed to the polymeric nature of network and high devitrifying ability. The metallicity factor has been found to dominate over the network connectivity and rigidity in the compositional dependence of switching voltage. which shows a profound decrease with the addition of Sb.

Inferring neuronal network connectivity from spike data: A temporal data mining approach

Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent d evelopments in electrophysiology and imaging allow one to simultaneously record activities of hundreds of neurons. Inferring the underlying neuronal connectivity patterns from such multi-neuronal spike train data streams is a challenging statistical and computational problem. This task involves finding significant temporal patterns from vast amounts of symbolic time series data. In this paper we show that the frequent episode mining methods from the field of temporal data mining can be very useful in this context. In the frequent episode discovery framework, the data is viewed as a sequence of events, each of which is characterized by an event type and its time of occurrence and episodes are certain types of temporal patterns in such data. Here we show that, using the set of discovered frequent episodes from multi-neuronal data, one can infer different types of connectivity patterns in the neural system that generated it. For this purpose, we introduce the notion of mining for frequent episodes under certain temporal constraints; the structure of these temporal constraints is motivated by the application. We present algorithms for discovering serial and parallel episodes under these temporal constraints. Through extensive simulation studies we demonstrate that these methods are useful for unearthing patterns of neuronal network connectivity.