Sharif Digital Repository

We study the problem of stability of chiral states, also known as problem of chirality, within the framework of a two-dimensional approximation of a symmetric double-well potential. We show how the symmetry breaking of the potential due to the molecular parity violation can stop the tunneling in a coherent way, accordingly stabilize the chiral states. Then, we use the quantum Brownian motion within a linear Lindblad-type equation to model how the intermolecular interactions make the tunneling incoherent, thus inducing a racemization by dephasing. Finally, we investigate the normal physical conditions where the dephasing racemization does not suppress the effects of the molecular parity... 

We propose a simple, general, and accurate formula for analyzing the tunneling between classical configurations of a nonplanar molecule in a gas medium, as a function of the thermodynamic parameters of the gas. We apply it to two interesting cases: (i) the shift to zero frequency of the inversion line of ammonia, upon an increase in the pressure of the gas; and (ii) the destruction of the coherent tunneling of D 2S 2 molecules in a He gas. In both cases, we compare our analysis with previous theoretical and experimental results  

The proliferation of technologies such as combine heat and power systems has accelerated the integration of energy resources in energy hubs. Besides, the advances in smart grid technologies motivate the electricity utility companies toward developing demand response (DR) programs to influence the electricity usage behavior of the customers. In this paper, we modify the conventional DR programs in smart grid to develop an integrated DR (IDR) program for multiple energy carriers fed into an energy hub in smart grid, namely a smart energy (S. E.) hub. In our model, the IDR program is formulated for the electricity and natural gas networks. The interaction among the S. E. hubs is modeled as an... 

Within the elasticity formulation the most general displacement field for hygrothermal problems of long laminated composite plates is presented. The equivalent single-layer theories are then employed to determine the global deformation parameters appearing in the displacement fields of general cross-ply, symmetric, and antisymmetric angle-ply laminates under thermal and hygroscopic loadings. Reddy's layerwise theory is subsequently used to determine the local deformation parameters of various displacement fields. An elasticity solution is also developed in order to validate the efficiency and accuracy of the layerwise theory in predicting the interlaminar normal and shear stress... 

The superposition of chiral states of chiral molecules, as delocalized quantum states of a many-particle system, can be used for the experimental investigations of decoherence theory. In this regard, a great challenge is the precise quantification of the robustness of these superpositions against environmental effects. The methods so far proposed need the detailed specification of the internal states of the molecule, usually requiring heavy numerical calculations. Here, by using the linearized quantum Boltzmann equation and by borrowing ideas employed for analyzing other quantum systems, we present a general and simple approach, of wide applicability, which can be used to compute the... 

We carry out a coarse-grained molecular dynamics simulation of phospholipid vesicles with transmembrane proteins. We measure the mean and Gaussian curvatures of our protein-embedded vesicles and quantitatively show how protein clusters change the shapes of their host vesicles. The effects of depletion force and vesiculation on protein clustering are also investigated. By increasing the protein concentration, clusters are fragmented to smaller bundles, which are then redistributed to form more symmetric structures corresponding to lower bending energies. Big clusters and highly aspherical vesicles cannot be formed when the fraction of protein to lipid molecules is large  

Macroscale experiments show that a train of two immiscible liquid drops, a bislug, can spontaneously move in a capillary tube because of surface tension asymmetries. We use molecular dynamics simulation of Lennard-Jones fluids to demonstrate this phenomenon for NVT ensembles in submicron tubes. We deliberately tune the strength of intermolecular forces and control the velocity of bislug in different wetting and viscosity conditions. We compute the velocity profile of particles across the tube and explain the origin of deviations from the classical parabolae. We show that the self-generated molecular flow resembles the Poiseuille law when the ratio of the tube radius to its length is less... 

Implementation of various incentive-based demand response strategies has great potential to decrease peak load growth and customer electricity bill cost. Using advanced metering and automatic demand management makes it possible to optimize energy consumption, to reduce grid loss, and to release generation capacities for the sake of providing sustainable electricity supply. Executing an incentive-based program is a simple way for customers to monitor and manage their energy consumption, and therefore, to reduce their electricity bill. With these objectives, this paper examines the previously suggested load scheduling programs and proposes a new practical one for residential energy management.... 

Data aggregation is an effective technique which is introduced to conserve energy by reducing packet transmissions in wireless sensor networks (WSNs). In addition, it is possible to consume less energy by using the spatial correlation and redundancy of data in dense networks to form clusters of nodes sensing similar values and, in turn, transmit one data packet per cluster. In this paper, we propose a Data-Aware Clustering and Aggregation scheme (DACA) to manage the energy constraint in a query-driven WSN. The DACA selects cluster head nodes by forming a new factor as a function of three parameters including the residual energy, the data value, and the number of neighbors at each node.... 

The development of energy regeneration capability in electric vehicles can extend their driving range making them a competent alternative for conventional internal combustion engine vehicles. In this study, a novel energy regeneration technique, called a two-boost method, for electric vehicles driven by a brushless DC (BLDC) motor, a widely used motor in vehicular technology, is proposed. Based on this technique, the BLDC motor driver, which is selected to be a three-phase inverter, is converted into two simultaneous boost converters during energy regeneration periods in order to transfer energy from the BLDC motor into the battery and provide the braking force. Also, this method is compared... 

In this work, for the first time, we presented a novel design strategy to fabricate a new type of Octa-aminopropyl polyhedral oligomeric silsesquioxane hydrochloride salt (OA-POSS)-based Alg/PAAm DN gels, consisting of PAAm gel as the first chemical network and Alg/OA-POSS gel as the second chemical-physical network. Incorporation of OA-POSS nanoparticles with various feed ratio into the second network not only led to form strong coordination interactions but also in comparison to the other Alg/PAAm gels demonstrated superior mechanical properties. pH, temperature, contact time and salt effects parameters were studied on the swelling and dye removal properties of the synthesized DN hybrid... 

This article has been devoted to investigation of the tribological properties of ultra-high molecular polyethylene/graphene oxide nanocomposite. The nanocomposite of ultra-high molecular polyethylene/graphene oxide was prepared with 0.5, 1.5, and 2.5 wt% of graphene oxide and with a molecular weight of 3.7 × 106 by in-situ polymerization using Ziegler–Natta catalyst. In this method, graphene oxide was used along with magnesium ethoxide as a novel bi-support of the Ziegler–Natta catalyst. Analyzing the pin-on-disk test, the tribological properties of the nanocomposite, such as wear rate and mean friction coefficient, were investigated under the mentioned contents of graphene oxide. The... 

In this paper, an artificial neural network (ANN) model has been developed to predict the yield and tensile strengths of hot pressed NiAl intermetallic compound based on the experimental data from Albiter et al. [A. Albiter, M. Salazar, E. Bedolla, R.A.L. Drew, R. Perez, Mater. Sci. Eng. A 347 (2003) 154]. The predicted results, with a correlation relation between 0.9791 and 0.9921, show a very good agreement with the experimental values. Furthermore, the sensitivity analysis was performed to investigate the importance of the effects of chemical composition and temperature on the mechanical behavior of hot pressed NiAl intermetallic compound. © 2008 Elsevier B.V. All rights reserved  

Purpose: This study aims to systematically review the economic complexity literature to advance the knowledge on its contribution to building regional competitiveness. Design/methodology/approach: In this study, we did a systematic review of 111 relevant papers. In this regard, we did a thematic analysis on all the collected papers, which led to a two-level processed approach. In the first level, the contributions of the reviewed articles have been classified into three main streams. In the second level, the findings under each contribution category are analyzed and explained. This approach led to a thematic network demonstrating economic complexity and the dynamics of regional... 

How a proposed quantum nonlocal phenomenon could be incompatible with the requirements of special relativity is studied. To show this, the least set of assumptions about the formalism and the interpretation of non-relativistic quantum theory is considered. Then, without any reference to the collapse assumption or any other stochastic processes, an experiment is proposed, involving two quantum systems, that interacted at an arbitrary time, with results which seem to be in conflict with requirements of special relativity  

A zirconia/alumina nanocomposite stabilized with cerium oxide (Ce-TZP/Al2O3 nanocomposite) can be a good substitute as reinforcement in metal matrix composites. In the present study, the effect of the amount of 10Ce-TZP/Al2O3 particles on the microstructure and properties of Al/(10Ce-TZP/Al2O3) nanocomposites was investigated. For this purpose, aluminum powders with average size of 30μm were ball-milled with 10Ce-TZP/Al2O3 nanocomposite powders (synthesized by aqueous combustion) in varying amounts of 1, 3, 5, 7, and 10wt.%. Cylindrical-shape samples were prepared by pressing the powders at 600MPa for 60min while heating at 400-450°C. The specimens were then characterized by scanning and... 

We report the effect of gold nanoparticles on the sensitivity and selectivity of SnO2-based sensors for detection of CO in the presence of methane and C3H8, a model compound representing liquid petroleum gas (LPG). 1.0 wt% Au/SnO2 powder was prepared by a co-precipitation method. The powder formed was washed, dried at 150 °C, and calcined at 300 °C for 3 h. The BET surface area of SnO2 and Au/SnO2 was measured to be 210 and 110 m2/g, corresponding to 4 and 7.5 nm loose spherical particles, respectively. Responses of the Au/SnO2 and SnO2 sensors to 40-1000 ppm CO, 0.2-1.0% C3H8 and 1.0-3.0% CH4 were studied at 170-300 °C in an automated gas sensing system. In this temperature range, the... 

In this investigation a theoretical model based on artificial neural network (ANN) has been developed to predict porosity percent and correlate the chemical composition and cooling rate to the amount of porosity in Al-Si casting alloys. In addition, the sensivity analysis was performed to investigate the importance of the effects of different alloying elements, composition, grain refiner, modifier and cooling rate on porosity formation behavior of Al-Si casting alloys. By comparing the predicted values with the experimental data, it is demonstrated that the well-trained feed forward back propagation ANN model with eight nodes in hidden layer is a powerful tool for prediction of porosity... 

In this investigation, a neural network model was used to predict mechanical properties of dual phase (DP) steels and sensivity analysis was performed to investigate the importance of the effects of pre-strain, deformation temperature, volume fraction and morphology of martensite on room temperature mechanical behavior of these steels. In order to train the neural network, dual-phase (DP) steels with different morphology and volume fractions of martensite were deformed between 2 and 8%, at high temperature range of 150-450 °C. The results of this investigation show that there is a good agreement between experimental and predicted values and the well-trained neural network has a great... 

Embedded Systems (ESs) have migrated from special-purpose hardware to commodity hardware. These systems have also tended to Mixed-Criticality (MC) implementations, executing applications of different criticalities upon a shared platform. Multi-cores, which are commonly used to design MC Systems (MCSs), bring out new challenges due to the Process Variation (PV). Power and frequency asymmetry affects the predictability of ESs. In this work, variation-aware techniques are explored to not only improve the reliability of MCSs, but also aid the scheduling and energy saving of them. We leverage the Core-to-Core (C2C) variations to protect high-criticality tasks and provide full service for a high...