Detection of crystal structure of chemically-deposited copper selenide thin films

A low cost Chemical Bath Deposition (CBD) system has been developed in our laboratory for the preparation of copper selenide thin film. Good quality thin films of smooth surface of copper selenide thin films of compositions Cu2-xSe (x = 0.1–0.5) and Cu3Se2 were deposited using sodium selenosulfate as a source of selenide ions. Crystal structure of copper selenide (Cu1.8Se and Cu3Se2) thin films has been identified by X-ray diffraction (XRD) method. When the film is annealed at 250ºC in air, the phases of Cu1.8Se and Cu3Se2 become crystalline, with structures of cubic (berzelianite) and tetragonal, respectively, whereas the as-deposited film was found to be disorder. The crystallinity is very low in as-deposited samples, which improves on annealing in air at 250ºC. The grain size of the as-deposited samples was very small, which was increased about 30% owing to annealing in air at 250ºC.Author Affiliation: Al-Mamun, S H Firoz and A B M O Islam 1.Department of Physics, University of Dhaka, Dhaka-1000, Bangladesh 2.Institute of Glass and Ceramic Research and Testing Bangladesh Council for Scientific and Industrial Research (BCSIR), Dhaka-1205, Bangladesh E-mail : [email protected] of Physics, University of Dhaka, Dhaka-1000, Bangladesh 2.Institute of Glass and Ceramic Research and Testing Bangladesh Council for Scientific and Industrial Research (BCSIR), Dhaka-1205, Banglades

Data-driven sparse estimation of nonlinear fluid flows

Estimation of full state fluid flow from limited observations is central for many practical applications in physics and engineering science. Fluid flows are manifestations of nonlinear multiscale partial differential equations (PDE) dynamical systems with inherent scale separation. Although the Navier-stokes equations can successfully model fluid flows, there are only limited cases of flows for which it is feasible to acquire exact analytical or numerical solutions. For many real-life fluid flow problems, extremely complex boundary conditions limit accurate modeling and simulations. In such situations, data from experiments or field measurements represents the absolute truth and very few in numbers thus limiting the potential of in-depth analysis. Consequently different data-driven techniques have been critical in active research in recent days. The ability to reconstruct important fluid flows from limited data is critical in applications extending from active flow control to as diverse as cardiac blood flow modeling and climate science. In this work, we investigated both (1) linear estimation method by leveraging data specific proper orthogonal decomposition (POD) technique, and (2) nonlinear estimation method on the ground of machine learning using deep neural network (DNN) algorithm. Given that sparse reconstruction is an inherently ill-posed problem, to generate well-posedness our linear sparse estimation (LSE) approach encodes the physics into the underlying sparse basis obtained from POD. On the other hand, for nonlinear sparse estimation (NLSE) we tried to find an optimal neural network model working over different ranges of hyperparameters through a systematic implementation. Our NLSE approach learns an end-to-end mapping between the sensor measurements and the high dimensional fluid flow field. We demonstrate the performance of both approaches for low and high dimensional examples in fluid mechanics. We also assess the interplay between sensor quantity and their placements introducing some greedy-smart sensor placement methods such as Discrete Empirical Interpolation Method (DEIM), QR-pivoting, etc. The LSE method needs the knowledge of low dimensional sparse basis to be known a priori, whereas the NLSE requires no prior knowledge to be available. The estimation algorithm of NLSE is purely data-driven with a comparable level of performance. To make our neural network optimization more robust we implemented Latin Hypercube Sampling (LHS) algorithm to ensure that each hyperparameter sample has all portions of its distribution in the considered range of analysis instead of sampling them randomly. Throughout the thesis, we demonstrate a comparison of each approach taken into consideration to conclude on their performances. A special focus has been placed to learn high dimensional multiscale system such as the near-wall turbulent channel flow using the NLSE method to evaluate the advantages and limitations of the nonlinear approach in comparison to the traditional linear estimation

Hybrid technology for the use of solar energy : the challenge towards green energy / S. I. Hossain ... [et al.]

Large areas in many countries are populated but have no connection to a national electricity grid. Centralized electricity generating facilities burning fossil fuels have been the normal. Renewable energy resources, especially solar energy is now penetrating this sector. Long-term energy storage is the universal challenge in providing renewables-based electricity with high availability across the seasons. Solar domestic hot water system is widely used and developing fast in recent years. However many problems occur at the same time, for example more energy consumption by circulation pump, water reheating, long investment payback period, and etc. The motivation for the development of a combined hot water and sorption store is to complement the advantages and to reduce the disadvantages of the two particular storage technologies. Hot water stores offer high heat supply rates but are particularly suitable for short term storage due to heat losses whereas for a sorption store the power drain is low but it shows the advantage of a high storage density and long-term heat storage almost without losses. We investigated the demonstration project and discuss the need for authoritative system modelling in order to size the system components for minimum cost at a designated availability of supply

From the microscopic to the macroscopic world: from nucleons to neutron stars

Recent observations of neutron-star properties, in particular the recent detection of gravitational waves emitted from binary neutron stars, GW 170817, open the way to put strong constraints on nuclear interactions. In this paper, we review the state of the art in calculating the equation of state of strongly interacting matter from first principle calculations starting from microscopic interactions among nucleons. We then review selected properties of neutron stars that can be directly compared with present and future observations.Comment: 28 pages, 9 figures, Special Issue Article for Journal of Physics

Water Purification and Disinfection by Using Solar Energy: Towards Green Energy Challenge

The aim of this work was to design a solar water treatment plant for household purpose. Water purification is the process of eradicating detrimental chemicals, biological poisons, suspended solids and gases from contaminated water. In this work we have reported an investigation of compact filter which is cost effective for developing countries and ease of maintenance. We have arranged a solar water disinfection system that improves the microbiological quality of drinking water at household level. We get 14 L pure water and 16 ml water vapour within 240 min by using filtration method. From our work we get hot water up to 49°C. The efficiency of the system at sunny days and cloudy days are 18.23% and 18.13% respectively. This simple solar hybrid system helps to remove turbidity as well as chemical and pathogenic contaminants from water sources in the most affordable, and expedient manner possibly

Влияние эффектов перетекания волатильности на политическую неопределенность, цены на нефть, биржу и рынки драгоценных металлов в российской экономике

The Russian economy is emerging, meaning that natural resources play a dominant role in economic development. Given the considerable volatility in resource prices, we investigate the volatility spillovers among policy uncertainty, international oil prices, exchange rate, stock index and metal prices covering the period of 2 July 2008 to 15 May 2020 for the Russian economy applying Dynamic Connectedness based on Time-Varying Parameter Vector Autoregression (TVP-VAR). Our empirical investigation demonstrates that gold price, Russian policy uncertainty, oil price and stock index are net volatility contributors, whereas palladium, platinum, silver and exchange rate are net volatilities receivers. Market capitalisation and silver market are found to be the highest net contributor and net receiver, respectively. The palladium appears as a net volatility receiver initially, just after the global financial crisis. The Russian economic policy uncertainty appears to be the dominant volatility contributor from 2008 to 2014, but onward it turned to be a net volatility receiver. Over the year 2014, gold price was the prominent volatility contributor to another market when the oil price dropped significantly. The total connectivity of the markets are highly anchored with several exogenous shocks, including economic sanction, adoption of floating exchange rate, oil price plunge. Our empirical findings provide several policy implications to portfolio managers and Russian regional stakeholders. © Sohag K., Husain S., Chukavina K., Al Mamun Md Text. 2022.Russian Foundation for Basic Research, РФФИ; Iran National Science Foundation, INSFThe article has been prepared with the support of the grant of RFBR and INSF, code: 20-510-56021 “Modeling the future of Oil Demand and Fiscal Sustainability: Evidence from Iran and Russia”

Numerical simulation of periodic MHD casson nanofluid flow through porous stretching sheet

The perspective of this paper is to characterize a Casson type of Non-Newtonian fluid flow through heat as well as mass conduction towards a stretching surface with thermophoresis and radiation absorption impacts in association with periodic hydromagnetic effect. Here heat absorption is also integrated with the heat absorbing parameter. A time dependent fundamental set of equations, i.e. momentum, energy and concentration have been established to discuss the fluid flow system. Explicit finite difference technique is occupied here by executing a procedure in Compaq Visual Fortran 6.6a to elucidate the mathematical model of liquid flow. The stability and convergence inspection has been accomplished. It has observed that the present work converged at, Pr ≥ 0.447 indicates the value of Prandtl number and Le ≥ 0.163 indicates the value of Lewis number. Impact of useful physical parameters has been illustrated graphically on various flow fields. It has inspected that the periodic magnetic field has helped to increase the interaction of the nanoparticles in the velocity field significantly. The field has been depicted in a vibrating form which is also done newly in this work. Subsequently, the Lorentz force has also represented a great impact in the updated visualization (streamlines and isotherms) of the flow field. The respective fields appeared with more wave for the larger values of magnetic parameter. These results help to visualize a theoretical idea of the effect of modern electromagnetic induction use in industry instead of traditional energy sources. Moreover, it has a great application in lung and prostate cancer therapy

Use of Wireless Sensor and Microcontroller to Develop Water-level Monitoring System

This paper presents the design and development process of Wireless Data Acquisition System (WiDAS) which is a multi-sensor system for water level monitoring. It also consists of a microcontroller (ATMega8L), a data display device and an ultrasonic distance sensor (Parallax Ping). This wireless based acquisition system can communicate through RF module (Tx-Rx) from the measurement sources, such as sensors and devices as digital or analog values over a period of time. The developed system has the option to store the data in the computer memory. It was tested in real time and showed continuous and correct data. The developed system is consisting of a number of features, such as low energy consumption, easy to operate and well-built invulnerability, which cangive successful results to measure the water level. Finally, its flexibility facilitates an extensive application span for self-directed data collection with trustworthy transmission in few sparse points over huge areas