Chemometric analysis of the influence of mechanical activation on the mica quality parameters

doi:10.1016/j.ceramint.2015.03.147

Ceramics International

Volume 41, Issue 7, August 2015, Pages 8894-8903

https://doi.org/10.1016/j.ceramint.2015.03.147 Get rights and content

Abstract

The differences in the set of the process parameters measured before and after mica mechanical activation and their influence on the grain size distribution related characteristics have been studied. The modification of the behavior for activated samples has been correlated to the particle size distribution effect produced by activation via an ultra centrifugal mill. The mechanical treatments are energetically and economically unsustainable procedures, therefore the mica activation was optimized on basis of assessment of the process variables effect on the final quality of product parameters. Response surface method, standard score analysis and principal component analysis were used as means of the optimization. Developed models showed r² values in the range of 0.816–0.988 and they were able to accurately predict quality parameters in a wide range of processing parameters. Standard score analysis highlighted that the optimal sample was obtained using sieve mesh of 80 μm set of processing parameters (SS=0.81). Multiple comparison tests revealed that the optimal variation in the processing parameters could reduce the negative effect of mica samples inherent properties on the final score and improve activation procedure energetic and economic sustainability.

Introduction

The mica comprises a group of 37 phyllosilicate minerals characterized by a layered texture. All mica minerals exhibit monoclinic symmetry with pseudohexagonal crystals, and the excellent cleavage due to the hexagonal sheet-like arrangement of atoms [1], [2]. From the commercial aspect, the most frequently applied mica is muscovite: KAl₂(AlSi₃O₁₀)(OH)₂ [3]. The applicability is based on the possibility of crystalline layers delamination into transparent to opaque thin sheets which are chemically inert, dielectric, elastic, flexible, hydrophilic, insulating, lightweight, reflective, refractive and resilient. This mica’s unique set of physical properties brings about its stability towards electricity, light, moisture, and extreme temperatures exposure. Muscovite, which is both insulator and dielectric, and has a high dielectric breakdown, is thermally stable to 500 °C [3]. Phlogopite (KMg₃(AlSi₃O₁₀)(OH)) mica remains stable at even higher temperatures (to 900 °C) [4]. Mica insulation ability is utilized in high temperature and fire-resistant materials like power cables in aluminum plants, blast furnaces, heaters and boilers, metal smelters, and tanks and furnace wiring [3], [4]. Construction and ceramic materials sector represents a wide target area for mica application. Mica is used as a compound for gypsum and for filling blemishes in gypsum wallboards because it acts as filler and extender (provides a smooth consistency, improves the workability and cracking resistance) [5]. Mica is also used as an insulator in concrete blocks, but it can also be applied as a pozzolanic material. Some lightweight aggregates, such as diatomite, perlite, and vermiculite, may be substituted with ground mica when used as filler [6], [7]. Mica can be a soil conditioner and an additive to drilling fluids [8]. Furthermore, it is applied in the paint industry as a pigment extender, in the production of rolled roofing and asphalt shingles, in glass–ceramics, and as filler in syntheses of variety of advanced materials [3], [9], [10], [11], [12], [13].

When mica is used in advanced ceramics the mechanical activation is regarded as a regular processing method, because traditional methods (comminuting, classification and flotation) can not produce fine enough mica concentrate [14]. Activation conducted via different mills results in changes in the crystal structure of treated mineral. Namely, the activation produces significant number of crystal lattice defects and meta-stable forms which cause changes in surface properties of solid phases and in the system structure [15], [16], [17]. Mechanical activation is a complex chemico-physical process that not only effects the simple change of the grain size, it also induces the increase in potential energy and chemical activity, surface reactivity and mineral phase alternations within the treated system. As a consequence, the activated system gains entirely different set of physical properties, which is followed by the alternations in the mechanical and thermal behavior of treated mineral [18], [19], [20], [21], [22], [23]. Ultra-fine grinding can be economically unsustainable due to low mill capacity and high energy consumption; therefore an optimization of the activation procedure is necessary. In this study, response surface methodology (RSM) was applied as a means of the mica mechanical activation procedure optimization. The RSM is an effective tool for optimizing a variety of processes [24], [25]. The main advantage of RSM is reduced number of experimental runs that provide sufficient information for statistically valid results. The RSM equations describe effects of the test variables on the observed responses, determine test variables interrelationships and represent the combined effect of all test variables in the observed responses, enabling the experimenter to make efficient exploration of the process.

The main objective of this study was to investigate the quality of the mechanically activated mica conducted by ultra centrifugal mechanical activator Retsch ZM-1 using different process parameters. To assess the quality of activated mica several parameters (d₁/d₂, R₁/R₂, d′, n, d₉₅, S_t and S_r) were determined, and the influence of NRR, CI, MAP, CRS, and Q, were observed. Experimental results were subjected to analysis of variance (ANOVA) to show relations between applied assays. In order to enable more comprehensive comparison between investigated samples, standard score (SS) was introduced. Principal component analysis (PCA) was applied to classify and discriminate analyzed samples. Multiple comparison tests revealed that the optimal variation in the processing parameters could reduce the negative effect of mica samples inherent properties on the final score and improve activation procedure energetic and economic sustainability.

Section snippets

Characterization of the mica

The mica (KAl₂(Si₃Al)O₁₀(OH,F)₂) from ore deposit in Bujanovac, Serbia was used as the starting material in this investigation. The mica ore samples consisted of platelets of about 10 cm in length and 2 cm in thickness. Subsequently to the initial separation and crushing, samples were lightly ground using a knife-mill and sieved under 2 mm. Obtained mica sample had density of 3.00 g/cm³, humidity before/after drying 10.00/0.5%, and bulk density of 1.17 g/cm³ [26]. Comminuted mica was submitted to

Results and discussion

The first stage of the experiment was aimed towards assessing the benefits of different prerequisites of mechanical activation of mica samples via ultra centrifugal mill Retsch ZM-1. Subsequently, the obtained values of operation parameters (MAP, CRS, Q, SEC) and the product parameters (mean grain diameter, theoretical and real specific surface area) were compared and evaluated. The 80, 120, 200 and 500 μm mesh sizes of initial sieves were used in experimental sequences No. I (MS80), II (MS120),

Conclusion

The main intention of the investigation was to statistically optimize the mechanical activation of mica as a natural mineral raw material used in advanced and high temperature ceramics. The RSM was applied in optimization, since it reduces the number of experimental runs that provide sufficient information for statistically valid results. The PCA revealed the position regarding quality data and directions for characteristics improvement. ANOVA calculation of the response parameters showed

Acknowledgments

This investigation was supported by Serbian Ministry of Education, Science and Technological Development and it was conducted under following projects: OI 172057, III 45008, TR 31055 and TR 33007.

References (40)

M.F. Brigatti et al.
Chapter 2 – structure and mineralogy of clay minerals
Dev. Clay Sci.
(2013)
C. Martias et al.
A new composite based on gypsum matrix and mineral additives: hydration process of the matrix and thermal properties at room temperature
Thermochim. Acta
(2013)
C. He et al.
Thermal stability and pozzolanic activity of raw and calcined mixed-layer mica/smectite
Appl. Clay Sci.
(2000)
B. Lagerblad et al.
Evaluation of the quality of fine materials and filler from crushed rocks in concrete production
Constr. Build. Mater.
(2014)
S. Wu et al.
Effect of fluorine content on the crystallization and flexural strength of fluoro-mica glass ceramics
Ceram. Int.
(2013)
S.H. Chang et al.
The adsorption of water-soluble polymers on mica, talc limestone, and various clay minerals
Colloids Surf.
(1991)
S.X. Zhang et al.
Effects of swift heavy ion irradiation parameters on optical properties of muscovite mica
Nucl. Instrum. Methods B
(2015)
A. Metya et al.
Development of hydrophobicity of mica surfaces by ion beamsputtering
Appl. Surf. Sci.
(2014)
Y.D. Noh et al.
Highly charged swelling micas of different charge densities: synthesis, characterization, and selectivity for Sr and Ba
Sep. Purif. Technol.
(2013)
P. Balaz
Mechanical activation in hydrometallurgy
Int. J. Min. Process.
(2003)

E. Kristof-Mako et al.

Effect of mechanical treatment on the crystal structure and thermal decomposition of dolomite

Thermochim. Acta

(1999)

G. Suraj et al.

The effect of micronization on kaolinites and their sorption behaviour

Appl. Clay Sci.

(1997)

L. Perez-Maqueda et al.

The influence of sonication on the thermal behavior of muscovite and biotite

J. Eur. Ceram. Soc.

(2004)

M. Arsenović et al.

Prediction and fuzzy synthetic optimization of process parameters in heavy clay brick production

Ceram. Int.

(2013)

U. Ulusoy

Application of ANOVA to image analysis results of talc particles produced by different milling

Powder Technol.

(2008)

L.j. Andrić et al.

Comparative kinetic study of mechanical activation process of mica and talc for industrial application

Compos. Part B-Eng.

(2014)

F. Gridi-Bennadji et al.

Mechanical properties of textured ceramics frommuscovite–kaolinite alternate layers

J. Eur. Ceram. Soc.

(2009)

S. Komarneni et al.

Synthesis and characterization of low-charge sodium fluorophlogopite mica-type clay minerals

Appl. Clay Sci.

(2009)

L. Xu et al.

Flotation and adsorption of mixed cationic/anionic collectors on muscovite mica

Miner. Eng.

(2013)

V. Boldyrev et al.

Interrelation between fine grinding and mechanical activation

Comminution

(1996)

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Chemometric analysis of the influence of mechanical activation on the mica quality parameters

Abstract

Introduction

Section snippets

Characterization of the mica

Results and discussion

Conclusion

Acknowledgments

Dev. Clay Sci.

Thermochim. Acta

Appl. Clay Sci.

Constr. Build. Mater.

Ceram. Int.

Colloids Surf.

Nucl. Instrum. Methods B

Appl. Surf. Sci.

Sep. Purif. Technol.

Int. J. Min. Process.

Thermochim. Acta

Appl. Clay Sci.

J. Eur. Ceram. Soc.

Ceram. Int.

Powder Technol.

Compos. Part B-Eng.

J. Eur. Ceram. Soc.

Appl. Clay Sci.

Miner. Eng.

Comminution