A solid transportation problem for an item with fixed charge, vechicle cost and price discounted varying charge using genetic algorithm

In this paper, discount in transportation cost on the basis of transportated amount is extended to a solid transportation problem. In a transportation model, the available discount is normally offered on items/criteria, etc., in the form AUD (all unit discount) or IQD (incremental quantity discount) or combination of these two. Here transportation model is considered with fixed charges and vechicle costs where AUD, IQD or combination of AUD and IQD on the price depending upon the amount is offered and varies on the choice of origin, destination and conveyance. To solve the problem, genetic algorithm (GA) based on Roulette wheel selection, arithmetic crossover and uniform mutation has been suitably developed and applied. To illustrate the models, numerical examples have been presented. Here, different types of constraints are introduced and the corresponding results are obtained. To have better customer service, the entropy function is considered and it is displayed by a numerical example. To exhibit the efficiency of GA, another method—weighted average method for multi-objective is presented, executed on a multi-objective problem and the results of these two methods are compared.     

Realization of a temperature sensor using both two- and three-dimensional photonic structures through a machine learning technique

A temperature sensor based on photonic crystal structures with two- and three-dimensional geometries is proposed, and its measurement performance is estimated using a machine learning technique. The temperature characteristics of the photonic crystal structures are studied by mathematical modeling. The physics of the structure is investigated based on the effective electrical permittivity of the substrate (silicon) and column (air) materials for a signal at 1200 nm, whereas the mathematical principle of its operation is studied using the plane-wave expansion method. Moreover, the intrinsic characteristics are investigated based on the absorption and reflection losses as frequently considered for such photonic structures. The output signal (transmitted energy) passing through the structures determines the magnitude of the corresponding temperature variation. Furthermore, the numerical interpretation indicates that the output signal varies nonlinearly with temperature for both the two- and three-dimensional photonic structures. The relation between the transmitted energy and the temperature is found through polynomial-regression-based machine learning techniques. Moreover, rigorous mathematical computations indicate that a second-order polynomial regression could be an appropriate candidate to establish this relation. Polynomial regression is implemented using the Numpy and Scikit-learn library on the Google Colab platform.

     

A novel active auxiliary circuit for efficiency enhancement integrated with synchronous buck converter

In this paper, a novel auxiliary circuit is introduced for the synchronous buck converter. This auxiliary circuit provides zero‐current, zero‐voltage switching conditions for the main and synchronous switches while providing zero‐current condition for the auxiliary switch and diodes. The proposed active auxiliary circuit integrated with synchronous buck converter that emanates to zero‐voltage transition (ZVT)–zero‐current transition (ZCT) pulse width‐modulated (PWM) synchronous buck converter is analyzed, and its operating modes are presented. The additional voltage and current stresses on main, synchronous and auxiliary switches get decimated because of the resonance of the auxiliary circuit that acts for a small segment of time in the proposed converter. The important design feature of soft‐switching converters is the placement of resonant components that mollifies the switching and conduction losses. With the advent of ZVT–ZCT switching, there is an increase in the switching frequency that declines the resonant component values in the converters and also constricts the switching losses. The characteristics of the proposed converter are verified with the simulation in the Power Sim (PSIM) software co‐simulated with MATLAB/SIMULINK environment and implemented experimentally. Copyright © 2016 John Wiley & Sons, Ltd.     

A junctionless tunnel field effect transistor with low subthreshold slope

we demonstrate the design of a triple gate n-channel junctionless transistor that we call a junctionless tunnel field effect transistor (JLTFET). The JLTFET is a heavily doped junctionless transistor which uses the concept of tunneling, by narrowing the barrier between source and channel of the device, to turn the device ON and OFF. Simulation shows significant improvement compared to simple junctionless field effect transistor both in I _ON/I _OFF ratio and subthreshold slope. Here, junctionless tunnel field effect transistors with high-k dielectric and low-k spacers are demonstrated through simulation and shows an ON-current of 0.25 mA/μm for the gate voltage of 2 V and an OFF current of 3 pA/μm (neglecting gate leakage). In addition, our device shows optimized performance with high I _ON/I _OFF (～10⁹). Moreover, a subthreshold slope of 47 mV/decade is obtained for a 50 nm gate length of simulated JLTFET at room temperature which indicates that JLTFET is a promising candidate for switching performance.     

Dual material gate junctionless tunnel field effect transistor

This paper proposes a junctionless tunnel field effect transistor (JLTFET) with dual material gate (DMG) structure and the performance was studied on the basis of energy band profile modulation. The two-dimensional simulation was carried out to show the effect of conduction band minima on the abruptness of transition between the ON and OFF states, which results in low subthreshold slope (SS). Appropriate selection of work function for source and drain side gate metal of a double metal gate JLTFET can also significantly reduce the subthreshold slope (SS), OFF state leakage and hence gives improved I _ON/I _OFF.     

A neural-network-based space-vector PWM controller for athree-level voltage-fed inverter induction motor drive

A neural-network-based implementation of space-vector modulation (SVM) of a three-level voltage-fed inverter is proposed in this paper that fully covers the linear undermodulation region. A neural network has the advantage of very fast implementation of an SVM algorithm, particularly when a dedicated application-specific IC chip is used instead of a digital signal processor (DSP). A three-level inverter has a large number of switching states compared to a two-level inverter and, therefore, the SVM algorithm to be implemented in a neural network is considerably more complex. In the proposed scheme, a three-layer feedforward neural network receives the command voltage and angle information at the input and generates symmetrical pulsewidth modulation waves for the three phases with the help of a single timer and simple logic circuits. The artificial-neural-network (ANN)-based modulator distributes switching states such that neutral-point voltage is balanced in an open-loop manner. The frequency and voltage can be varied from zero to full value in the whole undermodulation range. A simulated DSP-based modulator generates the data which are used to train the network by a backpropagation algorithm in the MATLAB Neural Network Toolbox. The performance of an open-loop volts/Hz speed-controlled induction motor drive has been evaluated with the ANN-based modulator and compared with that of a conventional DSP-based modulator, and shows excellent performance. The modulator can be easily applied to a vector-controlled drive, and its performance can be extended to the overmodulation region     

Design and performance study of phase‐locked loop using fractional‐order loop filter

The present work reports the realization of an analog fractional‐order phase‐locked loop (FPLL) using a fractional capacitor. The expressions for bandwidth, capture range, and lock range of the FPLL have been derived analytically and then compared with the experimental observations using LM565 IC. It has been observed that bandwidth and capture range can be extended by using FPLL. It has also been found that FPLL can provide faster response and lower phase error at the time of switching compared to its integer‐order counterpart. Copyright © 2014 John Wiley & Sons, Ltd.     

High-Valent Iron-Oxo and -Nitrido Complexes: Bonding and Reactivity

Multiple-bonded iron-oxo and -nitrido species have been identified or proposed as key intermediates in a range of important chemical transformations. The reported model complexes feature various coordination geometries and distinct electronic structures, and therefore exhibit diverse reactivity. The present contribution highlights the synergy from both experimental and theoretical standpoints to elucidate their different bonding situations and delineate their common mechanistic features in hydrogen-atom abstraction processes. Our analysis reveals that a radical centered on the abstracting atom E (E=O, N), which is generated via homolysis of covalent Fe−E bonds upon approaching the transition state, is an intrinsic C−H cleaving agent. The iron-oxo species is predicted to be more reactive than its nitride congener, in general, because the O−H bond formed in the H-atom transfer process is often stronger than the corresponding N−H bond.     

Microstructural evolution and fracture toughness of plasma sprayed CNT reinforced Yttria-stabilized Hafnia coating

Yttria (8 wt%)-stabilized hafnia (YSH) and carbon nanotubes (CNTs) (1 wt%) reinforced yttria-stabilized hafnia (YSHC) coatings were fabricated on alumina substrate using atmospheric plasma spray technique. Raman spectra confirmed the survival of CNTs in plasma sprayed YSHC coating and indicated about graphitization of CNTs. Whereas, the FE-SEM micrograph infers the presence of few 2-D graphene platelet-like structure in plasma sprayed YSHC coating. Addition of 1 wt% CNTs has significantly increased the densification of YSH coating from 86% to 92%, whereas average hardness and elastic modulus increased by ~57% and ~16%, respectively. A phenomenal increase of ~125% in relative fracture toughness was observed in YSHC coating, which is attributed to three major factors viz. (a) Enhanced densification (b) High fraction of fully melted regions and (c) Various toughening mechanisms, like CNTs pull out, CNTs braiding, graphene splat wrapping, CNTs anchoring.     

Efficient Host-Guest Complexation of a Bisporphyrin Host with Electron Deficient Guests: Synthesis,Structure, and Photoinduced Electron Transfer

The encapsulation of 1,8-naphthalic anhydride (NAN), 9-dicyanomethylenefluorene (9-DCF), acenaphthenequinone (ANQ), and 4-chloro-7-nitrobenzofurazan (NBD-Cl) by diethylpyrrole-bridged bisporphyrin (H₄DEP) and its dizinc(II) analogue (Zn₂DEP) are employed to investigate the structural and spectroscopic changes within the bisporphyrin cavity upon substrate binding. Synthesis and X-ray structures of all four encapsulated host-guest complexes (H₄DEP⋅NAN, H₄DEP⋅9-DCF, Zn₂DEP⋅ANQ, and Zn₂DEP⋅NBD-Cl) are reported here. The binding constant calculations show strong 1 : 1 binding between the hosts (H₄DEP and Zn₂DEP) and the guests (NAN/9-DCF/ANQ/NBD-Cl). ¹H-NMR spectra also support the retention of the host-guest assemblies in solution. Negative and positive shifts of the reduction and oxidation potentials, respectively, indicate that it is difficult to reduce/oxidize the encapsulated complexes. The emission intensities of the bisporphyrins (H₄DEP and Zn₂DEP) are substantially quenched in all the complexes, owing to photoinduced electron transfer from the excited state of the bisporphyrins to guest molecules. All the experimental evidence is further substantiated by DFT calculations. Such an efficient electron transfer is only possible when the donor and the acceptor moieties are in close propinquity to each other, which eventually lowers the reorganization energy.