Chemical Leaching on Sulfur and Mineral Matter Removal from Asphaltite (Harbul, SE Anatolia, Turkey)

2011 ◽  
Vol 33 (5) ◽  
pp. 383-391 ◽  
Author(s):  
A. Saydut ◽  
M. Z. Duz ◽  
S. Erdogan ◽  
Y. Tonbul ◽  
C. Hamamci
Keyword(s):  
Mineral Matter ◽  
Chemical Leaching

Parameter Estimation of Kinetic Model Equations for Chemical Leaching of Coal

2014 ◽  
Vol 9 (2) ◽  
pp. 133-141 ◽  
Author(s):  
Santosh Kumar Sriramoju ◽  
A. Suresh ◽  
Pratik Swarup Dash ◽  
P. K. Banerjee
Keyword(s):  
Rate Equation ◽  
Kinetic Equations ◽  
Parametric Estimation ◽  
Core Model ◽  
Mineral Matter ◽  
Shrinking Core Model ◽  
Chemical Leaching ◽  
Leaching Process ◽  
Heterogeneous Rock ◽  
Shrinking Core

Abstract Coals are invariably associated with mineral matter, which makes it unsuitable for efficient utilisation. For difficult-to-wash coals, advanced coal beneficiation technologies like chemical leaching methods are under development. In this paper, kinetic equations using different methods have been evolved, and related parameters have been estimated, using the experimental results obtained during coal leaching process. As coal is a heterogeneous rock, three different methods namely (i) parametric estimation through rate equation, (ii) non-linear regression and (iii) parametric estimation through shrinking core model have been developed and validated to check the minimum level of permitted error tolerance. Experiments were designed, using full factorial design with three variables, which are sensitive to the process. Values of activation energy and k0 obtained, using the parametric estimation of rate equation and shrinking core model, are almost in the same range. The order of the reaction for silica and alumina is two, using rate equation method. The parametric data obtained from the polynomial regression method were compared with the actual data. The exponential polynomial provides a better fit for the chemical leaching process of coal.

Maximizing Demineralization during Chemical Leaching of Coal through Optimal Reagent Addition Policy

2015 ◽  
Vol 10 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Pratik S. Dash ◽  
D. N. Prasad ◽  
Santosh K. Sriramoju ◽  
R. K. Lingam ◽  
A. Suresh ◽  
...  
Keyword(s):  
Coal Ash ◽  
Hierarchical Optimization ◽  
Mineral Matter ◽  
Batch Reactors ◽  
Simulation Studies ◽  
Time Intervals ◽  
Chemical Leaching ◽  
Minimal Quantity ◽  
Leaching Experiments ◽  
Optimum Sequence

Abstract The main objective of the optimal reagent addition was to maximize the quantity of product with minimal quantity of feed. In the present study, the optimal addition of reagents during the chemical leaching of coal was computed. Chemical leaching of coal was carried out using aqueous solution of caustic to dissolve and remove the mineral matter. Simulation studies were carried out using the optimal reagent addition for chemical leaching of coal in batch reactors. This was experimentally validated, using the bench-scale reactor setup with hierarchical optimization architecture. Chemical leaching experiments were conducted using West Bokaro coal. Samples collected at various time intervals during the experiment were analyzed. Variations in silica (SiO2) and alumina (Al2O3) concentrations, which were main constituents present in coal ash, were evaluated with respect to time for different concentrations of caustic. The simulation studies for optimal addition were carried out at 6, 8 and 10 intervals. An objective function, required for maximum ash removal, was solved, using sequential quadratic programming (SQP) algorithm to find out the optimum sequence for reagent dosing. An improvement of about 1% (wt) ash reduction on an average was observed with implementation of optimal reagent addition.

Silicon Tetrachloride Synthesis from Rice Hulls: Transmission and Scanning Electron Microscope Study

1972 ◽  
Vol 30 ◽  
pp. 236-237 ◽  
Author(s):  
Richard S. Thomas ◽  
Prabir K. Basu ◽  
Francis T. Jones
Keyword(s):  
Silicon Tetrachloride ◽  
Silica Sand ◽  
Mineral Matter ◽  
Chemical Heterogeneity ◽  
Scanning Electron Microscope Study ◽  
Rice Hulls ◽  
Hull Structure ◽  
Lower Temperature ◽  
Image Position ◽  
Disposal Problem

Silicon tetrachloride, used in industry for the production of highest purity silicon and silica, is customarily manufactured from silica-sand and charcoal.SiCl4 can also be made from rice hulls, which contain up to 20 percent silica and only traces of other mineral matter. Hulls, after carbonization, actually prove superior as a starting material since they react at lower temperature. This use of rice hulls may offer a new, profitable solution for a rice mill byproduct disposal problem.In studies of the reaction kinetics with carbonized hulls, conversion of SiO2 to SiCl4 was found to proceed within a few minutes to a constant, limited yield which depended reproducibly on the ambient temperature of the reactor. See Fig. 1. This suggested that physical or chemical heterogeneity of the silica in the hull structure might be involved.

HYDROMETALLURGY METHOD OF REY-RICH MUD - CHEMICAL LEACHING AND SEPARATION -

2017 ◽  
Author(s):  
Yutaro Takaya ◽  
◽  
Koichiro Fujinaga ◽  
Yasuhiro Kato
Keyword(s):  
Chemical Leaching

The Planet in a Pebble

2010 ◽  
Author(s):  
Jan Zalasiewicz
Keyword(s):  
Solar System ◽  
Volcanic Eruptions ◽  
Big Bang ◽  
Forensic Analysis ◽  
Mineral Matter ◽  
Supernova Explosions ◽  
Deep Underground ◽  
The Big Bang ◽  
The Universe

This is the story of a single pebble. It is just a normal pebble, as you might pick up on holiday - on a beach in Wales, say. Its history, though, carries us into abyssal depths of time, and across the farthest reaches of space. This is a narrative of the Earth's long and dramatic history, as gleaned from a single pebble. It begins as the pebble-particles form amid unimaginable violence in distal realms of the Universe, in the Big Bang and in supernova explosions and continues amid the construction of the Solar System. Jan Zalasiewicz shows the almost incredible complexity present in such a small and apparently mundane object. Many events in the Earth's ancient past can be deciphered from a pebble: volcanic eruptions; the lives and deaths of extinct animals and plants; the alien nature of long-vanished oceans; and transformations deep underground, including the creations of fool's gold and of oil. Zalasiewicz demonstrates how geologists reach deep into the Earth's past by forensic analysis of even the tiniest amounts of mineral matter. Many stories are crammed into each and every pebble around us. It may be small, and ordinary, this pebble - but it is also an eloquent part of our Earth's extraordinary, never-ending story.

scholarly journals Prediction of metabolizable energy values in poultry offal meal for broiler chickens

2010 ◽  
Vol 39 (10) ◽  
pp. 2237-2245 ◽  
Author(s):  
Edney Pereira da Silva ◽  
Carlos Bôa-Viagem Rabello ◽  
Luiz Fernando Teixeira Albino ◽  
Jorge Victor Ludke ◽  
Michele Bernardino de Lima ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Broiler Chickens ◽  
Crude Protein ◽  
Matter Content ◽  
Metabolizable Energy ◽  
Mineral Matter ◽  
Ether Extract ◽  
High Fat ◽  
Collection Method ◽  
Gross Energy

This research aimed at generating and evaluating prediction equations to estimate metabolizable energy values in poultry offal meal. The used information refers to values of apparent and true metabolizable energy corrected for nitrogen balance (AMEn and TMEn) and for chemical composition of poultry offal meal. The literature review only included published papers on poultry offal meal developed in Brazil, and that had AMEn and TMEn values obtained by the total excreta collection method from growing broiler chickens and the chemical composition in crude protein (CP), ether extract (EE), mineral matter (MM), gross energy (GE), calcium (Ca) and phosphorus (P). The general equation obtained to estimate AMEn values of poultry offal meal was: AMEn = -2315.69 + 31.4439(CP) + 29.7697(MM) + 0.7689(GE) - 49.3611(Ca), R² = 72%. For meals with high fat contents (higher than 15%) and low mineral matter contents (lower than 10%), it is suggest the use of the equation AMEn = + 3245.07 + 46.8428(EE), R² = 76%, and for meals with high mineral matter content (higher than 10%), it is suggest the equations AMEn = 4059.15 - 440.397(P), R² = 82%. To estimate values of TMEn, it is suggested for meals with high mineral matter content the equation: TMEn = 5092.57 - 115.647(MM), R² = 78%, and for those with low contents of this component, the option is the equation: TMEn = 3617.83 - 15.7988(CP) - 18.2323(EE) - 96.3884(MM) + 0.4874(GE), R² = 76%.

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