A review of chemical leaching of coal by acid and alkali solution

Low rank or low-grade (LRC or LGC) coals are most abundant distribute around the several regions in the world. The contribution of low-rank coal is a significant role in the energy sectors and chemical feedstock to the industries. The hard coal reserves are gradually depleting, and the mining operation at deeper coal seam with greater difficulties as well as the cost of exploration is so high, which has a significant issue for plant economics. Therefore, the low-grade coal can be used as an alternative energy source to minimize these problems. Low-rank coals are usually associated with high mineral matter and moisture content, which exerts substantial impacts on their consumption including pyrolysis, liquefaction, gasification and combustion process. In order to understand the essential treatment of coal for efficient removal of mineral matters and improve coal properties by beneficiation techniques are crucial to developing advanced technologies. The present article provides a comprehensive overview of the various processes concerning demineralization of coal by chemical beneficiation technique. It has been found from the study; the degree of demineralization was greater in chemical beneficiation compared to physical beneficiation. It is because the chemical reagents are attacked to the interior of coal which removes the inorganic materials and finely dispersed minerals from the coal matrix. The chemical methods have separated all types of minerals from the coal matrix. However, the separation of minerals by the physical method depends on the mineral properties. Chemical beneficiation is an appropriate method to reduce both organic and inorganic mineral constituents from the LGC by leaching method. The chemical reagents are diffusing to the interior of coal matrix through the pores and subsequently dissolute the minerals. Throughout the study challenges, the chemical cleaning of low-grade coal has been efficient techniques for reducing the minerals to a minimum level that can be upgraded to high rank coal

Generalized PVO‐based dynamic block reversible data hiding for secure transmission using firefly algorithm

In this paper, we proposed a novel generalized pixel value ordering–based reversible data hiding using firefly algorithm (GPVOFA). The sequence of minimum and maximum number pixels value has been used to embed the secret data while prediction and modification are held on minimum, and the maximum number of pixel blocks is used to embed the secret data into multiple bits. The host image is divided into the size of noncoinciding dynamic blocks on the basis of firefly quadtree partition, whereas rough blocks are divided into a larger size; moreover, providing more embedding capacity used small flat blocks size and optimal location in the block to write the information. Our proposed method becomes able to embed large data into a host image with low distortion. The rich experimental results are better, as compared with related preceding arts

Artificial neural network approach for rheological characteristics of coal-water slurry using microwave pre-treatment

Detailed experimental investigations were carried out for microwave pre-treatment of high ash Indian coal at high power level (900 W) in microwave oven. The microwave exposure times were fixed at 60 s and 120 s. A rheology characteristic for microwave pre-treatment of coal-water slurry (CWS) was performed in an online Bohlin viscometer. The non-Newtonian character of the slurry follows the rheological model of Ostwald de Waele. The values of n and k vary from 0.31 to 0.64 and 0.19 to 0.81 Pa⋅sn, respectively. This paper presents an artificial neural network (ANN) model to predict the effects of operational parameters on apparent viscosity of CWS. A 4-2-1 topology with Levenberg-Marquardt training algorithm (trainlm) was selected as the controlled ANN. Mean squared error (MSE) of 0.002 and coefficient of multiple determinations (R2) of 0.99 were obtained for the outperforming model. The promising values of correlation coefficient further confirm the robustness and satisfactory performance of the proposed ANN model. Keywords: Microwave pre-treatment, Coal-water slurry, Apparent viscosity, Artificial neural network, Back propagation algorith

Optimization of ammonia production from urea in continuous process using ASPEN Plus and computational fluid dynamics study of the reactor used for hydrolysis process

The present study addresses the methods and means to safely produce relatively small amounts (i.e., up to 50 kg/h) of ammonia. The optimization and simulation study conducted for continuous process and effect of operation conditions like reaction temperature, initial feed concentration and pressure on ammonia production carried out using ASPEN Plus. Also, a computational fluid dynamics (CFD) model was proposed to simulate the hydrolysis of urea for synthesis of ammonia. A series of parametric studies to investigate flow rates, thermal boundary conditions and reactor geometry was performed for hydrolysis of urea and the optimized operating conditions and reactor geometry were obtained. Detailed three-dimensional flow, heat and chemistry simulations of ammonia, carbon dioxide and ammonium carbamate. The study demonstrates that simulation is a useful tool for diagnosing hydrolysis reactor mixing pathologies and for identifying practical countermeasures that could improve process performance. (C) 2010 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved

Microstructure characterization of titanium-base aluminium alloys by X-ray diffraction using Warren-Averbach and Rietveld method

Present study considers microstructural characterization of titanium-base aluminium (Ti-Al) alloys, which are widely used in the aviation industry due to its excellent combination of strength and ductility. The microstructural parameters like domain size, microstrain within the domain, dislocation density and stacking fault probabilities have been evaluated in hexagonal Ti-Al alloys having four different nominal compositions in at.% by X-ray diffraction Fourier line profile analysis using Warren-Averbach and Rietveld method taking silicon as standard. This analysis shows that the deformation growth faults beta are totally absent in this hexagonal system, because it has been observed to be either negligibly small (within experimental error) or negative. This analysis also reveals that the tendency for deformation faulting alpha increases by the addition of aluminium as solute and hence lowers its stacking fault energy. (C) 2006 Elsevier B.V. All rights reserved

Microstructural studies on variation of defect parameters in Zr-Sn alloys and their transition with interchange of solvent and solute in Zr-Ti and Ti-Zr alloy systems by modified Rietveld method and Warren-Averbach method

The effects of deformation and the transition of microstructural defect states with the interchange of solvent and solute in Ti-Zr and Zr-Ti alloys of six different compositions and Zr-Sn alloys in three different compositions have been investigated by X-ray diffraction line profile analysis. The detailed analysis of the Xray powder diffraction line profiles was interpreted by Fourier line shape analysis using modified Rietveld method and Warren-Averbach method taking silicon as standard. Finally the nucrostructural parameters such as coherent domain size, microstrains within domains, faulting probability and dislocation density were evaluated from the analysis of X-ray powder diffraction data of Zr base Sri, Ti and Ti base Zr alloys by modified Rietveld powder structure refinement. This analysis confirms that the growth fault, beta, is totally absent or negligibly present in Zr-Ti, Ti-Zr and Zr-Sn alloy systems, because the growth fault, beta, has been observed to be either negative or very small for these alloy systems. This analysis also revealed that the deformation fault, alpha, has significant presence in titanium-base zirconium alloy systems but when zirconium content in the matrix goes on increasing beyond 50%, this faulting behaviour suffers a drastic transition and faulting tendency abruptly drops to a level of negligible presence or zero. This tendency has also been observed in Zr-Sn alloys signifying high stacking fault energy. Therefore, Zr and Zr-base alloys having high stacking fault energy can be used as hard alloys in nuclear technology at high temperature

Enhanced magnetoconductivity and electrical property of MWCNT-CdS nanocomposite embedded in polyaniline

PANI/MWCNT-CdS nanocomposites with different content of CdS wt.% has been synthesized by the chemical oxidative in-situ polymerization reaction of aniline in the presence of multi-walled carbon nanotubes (MWCNT). TEM, XRD, FTIR, and TGA studies were done for the structural and thermal characterization of the samples respectively. The particle size of CdS nanoparticles distributes in between 2.7 and 4.8 nm. XRD spectrum reveals that the co-existence of MWCNT, CdS in PANI matrix, where CdS forms a hexagonal structure. TGA result shows that nanocomposite becomes more thermally stable with the increase in CdS content. The dc electrical transport property of PANI/MWCNT-CdS nanocomposites has been investigated within a temperature range 77 ≤ T ≤ 300 K. The dc conductivity follows a 3D variable range hopping (VRH) model. A large magnetoconductivity change (19%) is observed for 2 wt% CdS content in PANI/MWCNT-CdS, which is explained by the wave function shrinkage model