Nanoscale Mapping of the Conductivity and Interfacial Capacitance of an Electrolyte-Gated Organic Field-Effect Transistor under Operation

Probing nanoscale electrical properties of organic semiconducting materials at the interface with an electrolyte solution under externally applied voltages is key in the field of organic bioelectronics. It is demonstrated that the conductivity and interfacial capacitance of the active channel of an electrolyte-gated organic field-effect transistor (EGOFET) under operation can be probed at the nanoscale using scanning dielectric microscopy in force detection mode in liquid environment. Local electrostatic force versus gate voltage transfer characteristics are obtained on the device and correlated with the global current–voltage transfer characteristics of the EGOFET. Nanoscale maps of the conductivity of the semiconducting channel show the dependence of the channel conductivity on the gate voltage and its variation along the channel due to the space charge limited conduction. The maps reveal very small electrical heterogeneities, which correspond to local interfacial capacitance variations due to an ultrathin non-uniform insulating layer resulting from a phase separation in the organic semiconducting blend. Present results offer insights into the transduction mechanism at the organic semiconductor/electrolyte interfaces at scales down to ≈100 nm, which can bring substantial optimization of organic electronic devices for bioelectronic applications such as electrical recording on excitable cells or label-free biosensing.     

Neural network‐based routing protocol for opportunistic networks with intelligent water drop optimization

Opportunistic Networks (OppNets) is a system of wirelessly connected nodes in a varying network topology. Routing in OppNets is a challenge. To overcome the problem of routing, an intelligent dynamic strategy to select next best node for forwarding a message is required. This paper proposes an intelligent routing mechanism based on Intelligent Water Drop (IWD) Algorithm which is used in tandem with Neural Networks (NNs) as an optimization technique to solve the problem of routing in such networks. The nature–inspired IWD algorithm provides robustness, whereas the neural network base of the algorithm helps it to make intelligent routing decisions. The weights in the Neural Network model are calculated by IWD Algorithm using training data consisting of inputs that are characteristic parameters of nodes, such as buffer space, number of successful deliveries and energy levels along with transitive parameters such as delivery probabilities. The proposed protocol Intelligent Water Drop Neural Network (IWDNN) is compared with other protocols that use similar ideologies such as MLProph, K‐nearest neighbour classification based routing protocol (KNNR), Cognitive Routing Protocol for Opportunistic Network (CRPO), and Inheritance Inspired Context Aware Routing Protocol (IICAR), as well as the standard protocol Prophet. IWDNN is shown to outperform all other protocols with an average message delivery ratio of 60%, which is a significant improvement of over 10% in comparison to other similarly conceived algorithms. It has one of the lowest latency among the protocols studied, in a range of 3000 to 4000 s, and incurs comparably low overhead costs in the range of 15 to 30. The drop ratios are one of the lowest, staying near six and approaching zero as buffer size is increased. Average amount of time a message stayed in the buffer was the lowest, with a mean of 1600 s.     

A Proxy Signature Based Efficient and Robust Handover AKA Protocol for LTE/LTE-A Networks

Wireless Personal Communications - An efficient and robust handover is one of the essential requirements of several applications in LTE/LTE-A network. These applications are reliable only after a...     

Hybrid arithmetic optimization algorithm with hunger games search for global optimization

Multimedia Tools and Applications - Recently, many population-dependent methods have been proposed. Despite their acceptance in many applications, we are still exploring suggested methods to solve...     

Numerical modelling of ground surface topography: effect of traverse and helical superabrasive grinding with touch dressing

Grinding processes are often used for final finishing of components because of their ability to satisfy stringent requirements of surface roughness and dimensional tolerance. Surface topography generated during grinding depends upon many parameters like wheel parameters, wheel velocity, downfeed, grit density etc. and it also depends upon the type of grinding procedures (viz. plunge grinding, traverse grinding, helical grinding, touch dressing etc.) employed. Therefore, a correct examination of the parameters and type of process employed to carry out grinding are necessary. This paper is an attempt to develop the relation between the different grinding parameters and the grinding procedures like plunge, traverse and helical superabrasive grinding with touch dressing and the average surface roughness. For this purpose, a numerical simulation technique has been implemented to generate the grinding wheel topography. The ground workpiece surface has also been generated by simulating removal of work material depending upon the trajectory of the abrasive grits on the grinding wheel without taking rubbing and ploughing into consideration.     

Improved efficiency in fluorescent blue organic light emitting diode with a carrier confining structure

A blue organic light emitting device (OLED) with improved efficiency and good color purity is reported. The highest occupied molecular orbital (HOMO) level of the hole transport layer (HTL) and that of the emissive layer (EML) differs by 0.3 eV. This energy level mismatch confines the carriers at the HTL/EML interface. Conventional devices have only one HTL/EML interface, with a current efficiency of 2.9 cd/A. Without adding a separate hole blocking layer, incorporating multi-layers of the same HTL and EML increases this efficiency to 5.8 cd/A, with only a small increase in operating voltage yielding increased power efficiency also. But, there are an optimum number of layers, beyond which efficiency loss results. Also, including the multilayer structure simultaneously improves the blue color co-ordinates. To gain insight into the role of multilayer structures in modifying charge transport and recombination zone a simulator was developed. The simulated results could qualitatively explain the experimental observations.     

Analysis of read speed latency in 6T-SRAM cell using multi-layered graphene nanoribbon and cu based nano-interconnects for high performance memory circuit design

In this study, we designed a 6T-SRAM cell using 16-nm CMOS process and analyzed the performance in terms of read-speed latency. The temperature-dependent Cu and multilayered graphene nanoribbon (MLGNR)-based nano-interconnect materials is used throughout the circuit (primarily bit/bit-bars [red lines] and word lines [write lines]). Here, the read speed analysis is performed with four different chip operating temperatures (150K, 250K, 350K, and 450K) using both Cu and graphene nanoribbon (GNR) nano-interconnects with different interconnect lengths (from 10 μm to 100 μm), for reading-0 and reading-1 operations. To execute the reading operation, the CMOS technology, that is, the16-nm PTM-HPC model, and the16-nm interconnect technology, that is, ITRS-13, are used in this application. The complete design is simulated using TSPICE simulation tools (by Mentor Graphics). The read speed latency increases rapidly as interconnect length increases for both Cu and GNR interconnects. However, the Cu interconnect has three to six times more latency than the GNR. In addition, we observe that the reading speed latency for the GNR interconnect is ~10.29 ns for wide temperature variations (150K to 450K), whereas the reading speed latency for the Cu interconnect varies between ~32 ns and 65 ns for the same temperature ranges. The above analysis is useful for the design of next generation, high-speed memories using different nano-interconnect materials.     

Spectroscopic investigations on Dy3+ ions doped zinc lead alumino borate glasses for photonic device applications

This paper presents the structural, optical absorption, photoluminescence (PL) and decay spectral properties of Dy~(3+)ions doped zinc lead alumino borate (ZPAB) glasses to elucidate their possible usage in photonic devices such as w-LEDs and lasers. A broad hump shown by the XRD spectrum recorded for an un-doped ZPAB glass confirms its non-crystalline nature. The Judd-Ofelt (J-O) intensity parameter evaluated from the measured oscillator strengths of the absorption spectral features were used to estimate various radiative parameters and also to understand the nature of bonding between Dy~(3+)ions and oxygen ligands. Under 350 nm excitation, the as-prepared glasses are exhibiting two emission bands~4F_(9/2)→~6H_(15/2)(blue),and~4F_(9/2)→~6H_(13/2)(yellow) at 483 and 575 nm,respectively. From the PL spectra,the Y/B ratio values, CIE chromaticity color coordinates and color correlated temperature (CCT) were evaluated. The experimental lifetimes measured from the decay profiles are decreasing with increase in Dy~(3+)ions concentration in these glasses which may be attributed to the cross-relaxation and nonradiative multiphonon relaxation process. Decay profiles observed for higher concentration were well fitted to Inokuti-Hirayama (I-H) model to understand the energy transfer process and subsequent decrease in experimental lifetimes. The higher values of radiative parameters, emission cross-sections,quantum efficiency, optical gain and gain band width suggest the suitability of 0.5 mol%of Dy~(3+) ions in these ZPAB glasses for the photonic device application.