1.013
IF5
0.901
IF
20
MNiSW
539
Cites 2016
 
 

Central composite design application in oil agglomeration of talc

Izabela Polowczyk 1  ,  
 
1
Wroclaw University of Science and Technology
Physicochem. Probl. Miner. Process. 2017;53(2):1061–1078
Publish date: 2017-05-09
KEYWORDS:
TOPICS:
ABSTRACT:
Talc has many applications in various branches of industry. This material is an inert one with a naturally hydrophobic surface. Talc agglomeration is within the wide interest of pharmaceutical industry. Oil agglomeration experiments of talc were carried out to find out and assess the significance of experimental factors. Central composite design (CCD) was used to estimate the importance and interrelation of the agglomeration process parameters. Four experimental factors have been evaluated, i.e. concentration of cationic surfactant and oil, agitation intensity as well as time of the process. The median size of agglomerates (D50) and the polydispersity span (PDI) were used as the process responses. Logarithmic transformations of the responses provide better description of the model, than untransformed responses, with the reduced cubic model for D50 and quadratic model for PDI. This was supported by the Box-Cox plots. It was shown that there were many statistically important factors, including the concentration of cationic surfactant and stirring rate for D50, concentration of oil and stirring rate for PDI, as well as various interactions, up to third order for D50. Optimal conditions for minimum values of reagent amounts as well as mixing time and intensity for the maximum size of agglomerates but of rather narrow size distribution were found.
CORRESPONDING AUTHOR:
Izabela Polowczyk   
Wroclaw University of Science and Technology, Wybrzeze Wyspianskiego 27, 50-370 Wroclaw, Poland
 
REFERENCES:
1. AKTAS, Z., 2002. Some factors affecting spherical oil agglomeration performance of coal fines. Int. J. Miner. Process. 65, 177-190.
2. ANTONY, J., 2003. 7 - Fractional factorial designs, in Antony, J. (Ed.), Design of Experiments for Engineers and Scientists. Butterworth-Heinemann, Oxford, pp. 73-92.
3. ASLAN, N., 2013. Use of the grey analysis to determine optimal oil agglomeration with multiple performance characteristics. Fuel 109, 373-378.
4. ASLAN, N., UNAL, I., 2011. Multi-response optimization of oil agglomeration with multiple performance characteristics. Fuel Process. Technol. 92, 1157-1163.
5. ASLAN, N., UNAL, I., 2009. Optimization of some parameters on agglomeration performance of Zonguldak bituminous coal by oil agglomeration. Fuel 88, 490-496.
6. AZAMI, M., BAHRAM, M., NOURI, S., 2013. Central composite design for the optimization of removal of the azo dye, Methyl Red, from waste water using Fenton reaction. Curr. Chem. Lett. 2, 57-68.
7. AZAMI, M., BAHRAM, M., NOURI, S., NASERI, A., 2012. Central composite design for the optimization of removal of the azo dye, methyl orange, from waste water using Fenton reaction. J. Serb. Chem. Soc. 77, 235-246.
8. BALAKIN, B.V., KUTSENKO, K.V., LAVRUKHIN, A.A., KOSINSKI, P., 2015. The collision efficiency of liquid bridge agglomeration. Chem. Eng. Sci. 137, 590-600.
9. BASTRZYK, A., POLOWCZYK, I., SADOWSKI, Z., 2012. Influence of hydrophobicity on agglomeration of dolomite in cationic-anionic surfactant system. Sep. Sci. Technol. 47, 1420-1424.
10. BASTRZYK, A., POLOWCZYK, I., SADOWSKI, Z., SIKORA, A., 2011. Relationship between properties of oil/water emulsion and agglomeration of carbonate minerals. Sep. Purif. Technol. 77, 325-330.
11. BOX, G.E.P., 1953. Non-normality and tests on variances. Biometrika 40, 318-335.
12. BOX, G.E.P., BEHNKEN, D.W., 1960. Some new three level designs for the study of quantitative variables. Technometrics 2, 455-475.
13. BOX, G.E.P., COX, D.R., 1964. An analysis of transformations. J. Roy. Statist. Soc. Ser. B 26, 211-252.
14. BOX, G.E.P., DRAPER, N.R., 1987. Empirical Model-Building and Response Surfaces, 1st ed. Wiley, New York.
15. BOX, G.E.P., WILSON, K.B., 1951. On the experimental attainment of optimum conditions. J. Roy. Statist. Soc. Ser. B 13, 1-45.
16. BREMMELL, K.E., ADDAI-MENSAH, J., 2005. Interfacial-chemistry mediated behavior of colloidal talc dispersions. J. Colloid Interface Sci. 283, 385-391.
17. CEBECI, Y., SONMEZ, I., 2006. Application of the Box-Wilson experimental design method for the spherical oil agglomeration of coal. Fuel 85, 289-297.
18. CEBECI, Y., SONMEZ, I, 2004. A study on the relationship between critical surface tension of wetting and oil agglomeration recovery of calcite. J. Colloid Interface Sci. 273, 300-305.
19. CHARY, G.H.V.C., DASTIDAR, M.G., 2013. Comprehensive study of process parameters affecting oil agglomeration using vegetable oils. Fuel 106, 285-292.
20. CHARY, G.H.V.C., DASTIDAR, M.G., 2010. Optimization of experimental conditions for recovery of coking coal fines by oil agglomeration technique. Fuel 89, 2317-2322.
21. DEMIREL, M., KAYAN, B., 2012. Application of response surface methodology and central composite design for the optimization of textile dye degradation by wet air oxidation. Int. J. Ind. Chem. 3, 1-10.
22. DRAPER, N.R., 2008. Rotatable designs and rotatability, in Ruggeri, F., Kenett, R.S., Faltin, F.W. (Eds.), Encyclopedia of Statistics in Quality and Reliability. John Wiley & Sons. Ltd., Chichester, UK, pp. 1-7.
23. DRZYMALA, J., 2007. Mineral Processing: Foundations of Theory and Practice of Minerallurgy, 1st English ed. Oficyna Wydawnicza Politechniki Wrocławskiej, Wrocław, Poland.
24. DUZYOL, S., OZKAN, A., 2014. Effect of contact angle, surface tension and zeta potential on oil agglomeration of celestite. Miner. Eng. 65, 74-78.
25. DUZYOL, S., OZKAN, A., 2010. Role of hydrophobicity and surface tension on shear flocculation and oil agglomeration of magnesite. Sep. Purif. Technol. 72, 7-12.
26. DUZYOL, S., 2015. Investigation of oil agglomeration behaviour of Tuncbilek clean coal and separation of artificial mixture of coal–clay by oil agglomeration. Powder Technol. 274, 1-4.
27. ENNIS, B.J., 1996. Agglomeration and size enlargement. Powder Technol. 88, 203-225.
28. FENDRI, I., KHANNOUS, L., GHARSALLAH, N., GDOURA, R., 2013. Optimization of coagulation-flocculation process for printing ink industrial wastewater treatment using response surface methodology. Afr. J. Biotechnol. 12, 4819-4826.
29. HOUSE, P.A., VEAL, C.J., 1992. Spherical agglomeration in minerals processing, in Williams, R.A. (Ed.), Colloid and Surface Engineering: Applications in Process Industries, 1st ed. Butterworth-Heinemann, Oxford, pp. 188-212.
30. HUANG, A.Y., BERG, J.C., 2003. Gelation of liquid bridges in spherical agglomeration. Colloids Surf. A 215, 241-252.
31. JADHAV, N.R., PAWAR, A.P., PARADKAR, A.R., 2011. Preparation and evaluation of talc agglomerates obtained by wet spherical agglomeration as a substrate for coating. Pharm. Dev. Technol. 16, 152-161.
32. KAWASHIMA, Y., CAPES, C.E., 1974. An experimental study of the kinetics of spherical agglomeration in a stirred vessel. Powder Technol. 10, 85-92.
33. KELEBEK, S., DEMIR, U., SAHBAZ, O., UCAR, A., CINAR, M., KARAGUZEL, C., OTEYAKA, B., 2008. The effects of dodecylamine, kerosene and pH on batch flotation of Turkey's Tuncbilek coal. Int. J. Miner. Process. 88, 65-71.
34. KHURI, A.I., MUKHOPADHYAY, S., 2010. Response surface methodology. WIREs Comp. Stat. 2, 128-149.
35. KUMAR, S., CHARY, G.H.V.C., DASTIDAR, M.G., 2015. Optimization studies on coal–oil agglomeration using Taguchi (L16) experimental design. Fuel 141, 9-16.
36. LASKOWSKI, J.S., YU, Z., 2000. Oil agglomeration and its effect on beneficiation and filtration of low-rank/oxidized coals. Int. J. Miner. Process. 58, 237-252.
37. LIU, J., WEN, D., LIU, M., LV, M., 2011. Response surface methodology for optimization of copper leaching from a low-grade flotation middling. Miner. Metall. Process. 28, 139-145.
38. MERKUS, H.G., 2009. Particle Size Measurements. Fundamentals, Practice, Quality., 1st ed. Springer Netherlands.
39. MONTGOMERY, D.C., 2001. Design and Analysis of Experiments, 1st ed. John Wiley, New York.
40. NEGREIROS, A.A., ALTHAUS, T.O., NIEDERREITER, G., PALZER, S., HOUNSLOW, M.J., SALMAN, A.D., 2015. Microscale study of particle agglomeration in oil-based food suspensions: The effect of binding liquid. Powder Technol. 270, Part B, 528-536.
41. ONEY, O., TANRIVERDI, M., 2012. Optimization and modeling of fine coal beneficiation by Knelson concentrator using Central Composite Design (CCD). J. Ore Dressing 14, 11-18.
42. OZKAN, A., AYDOGAN, S., YEKELER, M., 2005. Critical solution surface tension for oil agglomeration. Int. J. Miner. Process. 76, 83-91.
43. PIETSCH, W., 1991. Size Enlargement by Agglomeration, 1st ed. Wiley, Chichester, West Sussex, England.
44. PIETSCH, W., 2005. Agglomeration in Industry. Occurrence and Applications. WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
45. PLACKETT, R.L., BURMAN, J.P., 1946. The design of optimum multifactorial experiments. Biometrika 33, 305-325.
46. POLOWCZYK, I., BASTRZYK, A., KOŹLECKI, T., SADOWSKI, Z., 2014. Characterization of glass beads surface modified with ionic surfactants. Sep. Sci. Technol. 49, 1768-1774.
47. RAMYADEVI, D., SUBATHIRA, A., SARAVANAN, S., 2012. Central composite design application for optimization of aqueous two-phase extraction of protein from shrimp waste. J. Chem. Pharm. Res. 4, 2087-2095.
48. ROSSETTI, D., SIMONS, S.J.R., 2003. A microscale investigation of liquid bridges in the spherical agglomeration process. Powder Technol. 130, 49-55.
49. SADOWSKI, Z., 1995. Selective spherical agglomeration of fine salt-type mineral particles in aqueous solution. Colloids Surf. A 96, 277-285.
50. SHESKIN, D.J., 2004. Handbook of Parametric and Nonparametric Statistical Procedures, 3rd ed. Chapman & Hall/CRC.
51. SONMEZ, I., CEBECI, Y., 2003. A study on spherical oil agglomeration of barite suspensions. Int. J. Miner. Process. 71, 219-232.
52. WONG, A., PARK, C.B., 2012. The effects of extensional stresses on the foamability of polystyrene–talc composites blown with carbon dioxide. Chem. Eng. Sci. 75, 49-62.
eISSN:2084-4735
ISSN:1643-1049