Sharif Digital Repository

In the current century, burning fossil fuel for producing energy in human life such as in transportation applications leads to make problems, for example, global warming and climate change. Hence, researchers motivate to find out some clear renewable energy sources and design appropriate devices to store them. Rechargeable batteries and supercapacitors are two of the most important devices for energy storage. In the current century, they are playing a significant important role in communication, medical, and transportation devices. However, the electrochemical performances of rechargeable batteries and supercapacitors increasingly depend on the properties of their main components such as... 

Demand for high-capacity, long cycle life, and aqueous batteries based on abundant metals such as nickel, zinc, aluminum, and so on is rising in the energy storage field. In this study, we design a hierarchical morphology as a nanosheet-built microsphere of nickel vanadium layered double hydroxide (NiV LDH) with conductive agents graphene oxide (GO) and multiwalled carbon nanotubes (CNTs) through a low-cost hydrothermal synthesis method. The experimental results demonstrate that the graphitic structures and functional groups of the GO and CNT play an important role in controlling nucleation, growth speed, size, and finally morphology of hierarchical nanosheets. The electrochemical results... 

We have developed a fourth order compact finite volume method for the solution of low Mach number compressible flow equations on arbitrary nonuniform grids. The formulation presented here uses collocated grid that preserves fourth order accuracy on nonuniform meshes. This was achieved by introduction of a new fourth order method for calculation of cell and face averaged metrics. A special treatment of nonlinear terms is used to guarantee the stability of the fourth order compact method. Moreover an approach for applying this method to multi-block domains is presented for complicated geometries and parallel processing applications. Several test cases including the flow in a lid-driven cavity,... 

Here, an excellent superhydrophobic and highly oleophobic nanocomposite coating composed of fluoroethylene-vinyl ether (FEVE) resin as a matrix for modified SiO2 nanoparticles was synthesized on a stainless-steel wire mesh substrate via a facile sol-gel method. The surface morphology, microstructure, composition, and roughness of the coatings were investigated by field emission scanning electron microscopy (FESEM) equipped with energy-dispersive spectroscopy (EDS) and atomic force microscopy (AFM). The most efficient coating with superhydrophobicity and high oleophobicity feature indicates the water and oil repellency with contact angles (CAs) of 152° and 141°, respectively, with the high... 

Employing deep learning makes it possible to learn high-level features from raw data, resulting in more precise models. On the other hand, submodularity makes the solution scalable and provides the means to guarantee a lower bound for its performance. In this paper, a deep submodular network (DSN) is introduced, which is a deep network meeting submodularity characteristics. DSN lets modular and submodular features to participate in constructing a tailored model that fits the best with a problem. Various properties of DSN are examined and its learning method is presented. By proving that cost function used for learning process is a convex function, it is concluded that minimization can be... 

Abstractive multi-document summarization is a type of automatic text summarization. It obtains information from multiple documents and generates a human-like summary from them. In this paper, we propose an abstractive multi-document summarization method called HMSumm. The proposed method is a combination of extractive and abstractive summarization approaches. First, it constructs an extractive summary from multiple input documents, and then uses it to generate the abstractive summary. Redundant information, which is a global problem in multi-document summarization, is managed in the first step. Specifically, the determinantal point process (DPP) is used to deal with redundancy. This step... 

The increase in online text generation by humans and machines needs automatic text summarization systems. Recent research studies commonly use deep learning, besides sentence embedding and feature learning mechanisms, to find a solution for text summarization. But they ignore the fact that while finding the optimal solution for extractive text summarization is NP-hard, how do they ensure the quality of their solution? In our previous work, an extractive summarizer, called DSNSum, was proposed based on deep submodular network (DSN) that uses handcrafted features. It leverages submodularity to guarantee a minimum bound for performance. In this paper, submodular graph convolutional summarizer... 

The development of active and stable materials has great importance for the commercialization of nickel-zinc (Ni–Zn) batteries and hydrogen production. Transition metal sulfides have good theoretical properties for these applications. In this research, we present the synthesis and characterization of Ni3S2@MoS2 nanocatalyst and its hybrid with reduced graphene oxide (Ni3S2@MoS2-rGO). The capability of these materials is investigated as cathode material for Ni–Zn batteries and hydrogen evolution in alkaline media. In the case of Ni–Zn batteries, the assembled Ni3S2@MoS2-rGO//Zn battery shows a discharge capacity of 249.3 mAh g−1 with coulombic efficiency of 97.2%, showing a higher... 

Nickel-zinc batteries as safe and economic energy storage devices suffer from lack of high electrochemical performance of cathode materials. Herein, a new cathode material for rechargeable Ni/Zn batteries is introduced based on various compositions of mixed metal oxide (MMO) through a calcination process of nickel-vanadium layered double hydroxide at different temperatures. The results demonstrated that the prepared sample at 500 °C presents the best electrochemical properties such as a good electrochemical discharge capacity (278.4 mAh g-1 at 0.5 A g-1), good cycle life (capacity retention of 74% after 1000 cycles at 5 A g-1), and excellent rate capability (177 mAh g-1 at 5 A g-1). These... 

Using an array of coupled oscillators, a novel broadband radar signalling scheme is introduced. It is shown that the collective output of the oscillator array is a flexible signal that can be matched to a target at a specific aspect. Also, a new robust algorithm based on eigenvectors of the correlation matrix is introduced, by which the generated signal can be matched to the target over a limited range of aspects. This capability is important, because radars are unable to estimate the aspect of a real target precisely. In this new approach to radar target identification, after estimation of the approximate aspect of an unknown target, a variety of waveforms matched to different potential... 

Introducing suitable electrode materials and electrolytes for supercapacitors and next-generation batteries should be considered for the industrial application of these devices. Among the proposed materials for them, transition metal chalcogenides (TMCs), are attractive and efficient options due to their unique properties such as appropriate layered structure, good oxidation state of transition metals, high thermal and mechanical stabilities, etc. However, applying other layered materials with high electrical conductivity e.g. carbon-based materials can lead to producing remarkable results for the mentioned applications. However, an interesting point is how making TMCs composite with...