Indication of the Measurement of Surface Area on Iron Ore Granulation

Lv, Xuewei; Huang, Xiaobo; Yin, Jaqing; Bai, Chenguang

doi:10.2355/isijinternational.51.1432

Cited by 10 publications

(5 citation statements)

References 9 publications

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“…The irregular morphology and rough texture can be the cause of the elevated specific surface area of the particles. Throughout the study on equipment, the hematite particles were supposed to be segregated to obtain the suspension of the particles [43].…”

Section: Kinetics Of As(iii) Adsorption On Iron Orementioning

confidence: 99%

Arsenic (III) Removal from Aqueous Water by Indigenous Iron Ore Adsorbent from Balochistan Province of Pakistan

Bhatti

2021

Mehran Univ. res. j. eng. technol.

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The work focuses on the removal of Arsenic-III (As(III)) from water sample by an indigenous iron ore from Balochistan by adsorption method. Three iron ore samples were analyzed by X-Ray Diffractometer (XRD) and a sample from Shikarap containing iron 36.2% was selected because it contained the highest amount of hematite. The batch study was conducted to examine the adsorption by iron ore and maximum adsorption was observed at pH 6, 1/2 g dose per 50 mL solution, contact time 2 hr and shaking speed 150 rpm. At the optimized conditions, the removal was 89% when monitored at 50μg L-1 initial concentration of arsenic. The arsenic removal was monitored by Atomic Absorption Spectrometer (AAS) using hydride generation. Dubinin - Radushkevich (D-R), Freundlich and Langmuir's isotherms were examined. The highest adsorption capacityof iron ore for As(III) removal was observed 13.67 μg g-1 by Langmuir model and Freundlich isotherm indicated good adsorption intensity with value n = 1.512. Thermodynamic parameters revealed that adsorption was exothermic and physisorption. The Scanning Electron Microscope (SEM) and Energy Dispersive X-Ray (EDX)techniques were applied to scan the surface morphology and the percentage elemental composition of samples respectively. SEM results demonstrated that Shikarap mineral grains are an oval shape and these were changed after the uptake of As(III). The EDX spectra of Shikarap mineral confirm the As(III) adsorption on particles as As 4.19%.

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Section: Kinetics Of As(iii) Adsorption On Iron Orementioning

confidence: 99%

Arsenic (III) Removal from Aqueous Water by Indigenous Iron Ore Adsorbent from Balochistan Province of Pakistan

Bhatti

2021

Mehran Univ. res. j. eng. technol.

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“…7,8) The effect of ore characteristics on the granulation effectiveness has so far been investigated by many researchers. [8][9][10][11][12][13] Reportedly, the granulation effectiveness was influenced by a series of ore properties such as particle size distribution, particle shape and surface characteristics, porosity and water-holding capacity, etc., all of which seemed to be independent with each other. Recently, the fractal parameter was introduced for interpretation of granulation process.…”

Section: Introductionmentioning

confidence: 99%

Granulation Effectiveness of Iron Ore Sinter Feeds: Effect of Ore Properties

et al. 2018

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This paper developed a quantitative understanding of the effect of ore properties on granulation effectiveness for different iron ore types based on the mechanistic model proposed by J.D. Litster et al. The granulation effectiveness was measured by the magnitude of x 0.5 , which was postulated to be a function of the layer binding strength. Water was adopted as the only binder for all granulation tests. A wide range of moisture contents, up to the optimum moisture content that yielded an optimum permeability, was tested for each ore type. The typical structure of granules made from different ores was investigated to reveal the effect of mineralogical properties of ore particles on the growth of granules. The results indicate that the granulation effectiveness x 0.5 varies markedly with ore type and moisture content. Feed particle size distribution and moisture for granulation are paramount factors determining the granulation effectiveness x 0.5 , which has a single relationship with the mass mean size of layering particles independent of ore type. The mass mean size of layering particles is dependent on the inherent size distribution of raw materials and the mass fraction of layering particles, while the latter is linear to available moisture content. The model works well for some ore types except for those with unreasonable size distributions: 1) excessive intermediate particles meanwhile lacking of fine particles; or 2) excessive ultrafine particles. An effective criteria closely related to layer binding strength, (1 − ε)S/ε d , is proposed to determine the applicability of the model.

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“…The influences of particle size grading 9,10) and physical properties [11][12][13] of iron ores on granulation results have been investigated by researchers. However, the particle…”

Section: Introductionmentioning

confidence: 99%