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  • 1.
    Alidokht, Mehdi
    et al.
    Tabas Parvardeh Coal Company (TPCCO), Birjand, Iran.
    Yazdani, Samaneh
    Department of Electrical and Computer Engineering, Islamic Azad University, North Tehran Branch, Tehran, Iran.
    Hadavandi, Esmaeil
    Department of Industrial Engineering, Birjand University of Technology, Birjand, Iran.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Modeling metallurgical responses of coal tri-flo separators by a novel bnn: a “Conscious-lab” development2021Inngår i: International journal of coal science & technology, ISSN 2095-8293, Vol. 8, nr 6, s. 1436-1446Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Tri-flo cyclone, as a dense-medium separation device, is one of the most typical environmentally friendly industrial techniques in the coal washery plants. Surprisingly, no detailed investigation has been conducted to explore the effectiveness of tri-flo cyclone operating parameters on their representative metallurgical responses (yield and recovery). To fill this gap, this work for the first time in the coal processing sector is going to introduce a type of advanced intelligent method (boosted-neural network “BNN”) which is able to linearly and nonlinearly assess multivariable correlations among all variables, rank them based on their effectiveness and model their produced responses. These assessments and modeling were considered a new concept called “Conscious Laboratory (CL)”. CL can markedly decrease the number of laboratory experiments, reduce cost, save time, remove scaling up risks, expand maintaining processes, and significantly improve our knowledge about the modeled system. In this study, a robust monitoring database from the Tabas coal plant was prepared to cover various conditions for building a CL for coal tri-flo separators. Well-known machine learning methods, random forest, and support vector regression were developed to validate BNN outcomes. The comparisons indicated the accuracy and strength of BNN over the examined traditional modeling methods. In a sentence, generating a novel BNN within the CL concept can apply in various energy and coal processing areas, fill gaps in our knowledge about possible interactions, and open a new window for plants’ fully automotive process.

  • 2.
    Andrade, Elaine Cristina
    et al.
    Department of Mining and Petroleum Engineering, Polytechnic School, University of São Paulo, Av. Professor Mello Moraes, 2373, CEP 05508-900, São Paulo, SP, Brazil.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    de Salles Leal Filho, Laurindo
    Department of Mining and Petroleum Engineering, Polytechnic School, University of São Paulo, Av. Professor Mello Moraes, 2373, CEP 05508-900, São Paulo, SP, Brazil.
    A systematic study on gelatinization efficiency of starch by NaOH for enhanced hematite depression2024Inngår i: Minerals Engineering, ISSN 0892-6875, E-ISSN 1872-9444, Vol. 209, artikkel-id 108621Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Starch is a traditional depressant for hematite beneficiation by cationic reverse flotation separation from silicates. Alkali or thermal gelatinization must be used to prepare starch and promote its dissolution in water. In industry, gelatinization is typically carried out using sodium hydroxide at room temperature at different starch/NaOH mass ratios (SNMR). Surprisingly, no investigation has systematically studied the optimum SNMR for boosting hematite depression. This work examined the influence of starch gelatinization under various SNMR (3:1, 5:1, 7:1, and 9:1) on hematite depression (at pH = 10.5, 22 °C) by exploring flotation response (R), contact angle (θ), induction time (τ), hydrodynamic diameter (dH) of starch macromolecules, total energy of interaction starch/hematite (GTOT), based on its two components: the attractive Lifshitz-van der Waals energy (GLW) and attractive/repulsive electrostatic energy (GEL). Flotation test results indicated that SNMR = 5:1 promoted the lowest hematite recovery (14.8 %), coupled with the highest induction time (τ = 55 ms) and the lowest contact angle (θ = 11°). The hydrodynamic diameter (dH) of macromolecules in solutions prepared under different SNMR was determined by Dynamic Light Scattering, showing three peaks: amylopectin (350 < dH < 420 nm), amylose (50 < dH < 100 nm) and debris from gelatinization (dH ∼ 5000 nm). Since the latter only occurred in solutions prepared under SNMR of 7:1 and 9:1, deficient hematite depression might be caused by incomplete gelatinization. As amylopectin is the starch component that is responsible for its depressant ability, larger amylopectin macromolecules (dH = 411 nm) found in solutions prepared at SNMR = 5:1 contrast with smaller macromolecules (dH = 353 nm) produced at SNMR = 3:1. Considering starch macromolecules as a sphere, and hematite&apos;s surface as a plane; GLW, GEL, and GTOT were calculated in function of the sphere/plane separation distance (2 nm < H < 20 nm). GLW was determined based on the assessment of the Hamaker constant of the starch/water/hematite system (2.9 × 10−20J < A132 < 3.3 × 10−20J), whereas GEL was determined based on the zeta potential of starch (−2mV < ζ1 < −4mV) and hematite (ζ2 = −29 mV). GTOT for starch gelatinized at SNMR = 5:1 (−502.9 × 10−21 J) is greater than GTOT for starch prepared at SNMR = 3:1 (−468.8 × 10−21 J) and SNMR = 7:1 (−469.0 × 10−21 J), at a confidence level of 95 %. These results corroborate the more intensive hematite depression by starch prepared at SNMR = 5:1 compared to the other values explored by this study.

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  • 3.
    Asghari, M.
    et al.
    University of Tehran, Tehran, Iran.
    Noaparast, M.
    University of Tehran, Tehran, Iran.
    Shafaie, S. Z.
    University of Tehran, Tehran, Iran.
    Ghassa, S.
    University of Tehran, Tehran, Iran.
    Chelgani, Saeed Chehreh
    University of Michigan, Ann Arbor, USA.
    Recovery of coal particles from a tailing dam for environmental protection and economical beneficiations2018Inngår i: International Journal of Coal Science & Technology, ISSN 2095-8293Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Considerable amounts of coal particles are accumulated in the tailing dams of washing plants which can make serious environmental problems. Recovery of these particles from tailings has economically and environmentally several advantages. Maintaining natural resources and reducing discharges to the dams are the most important ones. This study was examined the possibility to recover coal particles from a tailing dam with 56.29% ash content by using series of processing techniques. For this purpose, gravity separation (jig, shaking table and spiral) and flotation tests were conducted to upgrade products. Based the optimum value of these processing methods, a flowsheet was designed to increase the rate of recovery for a wide range of coal particles. Results indicated that the designed circuit can recover over 90% of value coal particles and reduce ash content of product to less than 14%. These results can potentially be used for designing an industrial operation as a recycling plant and an appropriate instance for other areas to reduce the environmental issues of coal tailing dams.

  • 4.
    Asimi, Ali
    et al.
    Department of Mining and Metallurgical Engineering Yazd University, Yazd 89195-741, Iran. Bafgh Zinc Smelting Company (BZSC), Yazd 89195-741, Iran .
    Gharibi, Khodakaram
    Department of Mining and Metallurgical Engineering Yazd University, Yazd 89195-741, Iran.
    Abkhoshk, Emad
    Bafgh Zinc Smelting Company (BZSC), Yazd 89195-741, Iran.
    Moosakazemi, Farhad
    Chemical Engineering Department, Laval University, Québec, QC G1V 0A6, Canada. Beneficiation and Hydrometallurgy Research Group, Mineral Processing Research Center, Academic Center for Education, Culture and Research (ACECR) on TMU, Tehran 15119-43943, Iran.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Effects of Operational Parameters on the Low Contaminant Jarosite Precipitation Process-an Industrial Scale Study2020Inngår i: Materials, ISSN 1996-1944, E-ISSN 1996-1944, Vol. 13, nr 20, artikkel-id 4662Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Jarosite precipitation process (JPP) is the most frequently used procedure for iron removal in the hydrometallurgical zinc extraction process. However, there is a gap in the knowledge of the relationship between operational parameters and the low contaminant JPP on the industrial scale. This study will address these issues by investigating the behavior of zinc calcine (ZC) as a neutralizing agent, exploring the source of zinc and iron through leaching experiments, and simulating the Jarosite process of the Bafgh Zinc Smelting Company (BZSC). The results showed that the zinc dissolution efficiency was 90.3% at 90 °C, and 73% of the iron present in the calcine can be solubilized. The main outcome was the iron removal of about 85% by alkaline ions present in ZC without the addition of any precipitating agent. The second target was to evaluate the effect of operational parameters on jarosite precipitation. Results revealed that increasing the temperature to 90 °C and the stirring rate to 500 RPM as well as adjusting the ZC’s pH during the jarosite precipitation remarkably improved iron removal. Considering all these factors in the plant could improve Fe precipitation to around 80% on average.

  • 5.
    Asimi Neisiani, A.
    et al.
    Department of Mining and Metallurgical Engineering, Yazd University, Yazd 89195-741, Iran.
    Saneie, R.
    Department of Materials Engineering, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
    Mohammadzadeh, A.
    Laboratory for Strategic Materials, Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto M5S 3E5, Canada.
    Wonyen, D. G.
    Department of Material Science and Engineering (Mining and Mineral Processing Engineering), African University of Science and Technology, Abuja P.M.B 681, Nigeria.
    Chehreh Chelgani, Saeed
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Polysaccharides-based pyrite depressants for green flotation separation: An overview2023Inngår i: International Journal of Mining Science and Technology, ISSN 2095-2686, Vol. 33, nr 10, s. 1229-1241Artikkel, forskningsoversikt (Fagfellevurdert)
    Abstract [en]

    Froth flotation is an essential processing technique for upgrading low-grade ores. Flotation separation would not be efficient without chemical surfactants (collectors, depressants, frothers, etc.). Depressants play a critical role in the selective separation of minerals in that they deactivate unfavorable mineral surfaces and hinder them from floating into the flotation concentration zone. Pyrite is the most common and challenging sulfide gangue, and its conventional depressants could be highly harmful to nature and humans. Therefore, using available, affordable, eco-friendly polymers to assist or replace hazardous reagents is mandatory for a green transition. Polysaccharide-based (starch, dextrin, carboxymethyl cellulose, guar gum, etc.) polymers are one of the most used biodegradable depressant groups for pyrite depression. Despite the satisfactory flotation results obtained using these eco-friendly depressants, several gaps still need to be addressed, specifically in investigating surface interactions, adsorption mechanisms, and parameters affecting their depression performance. As a unique approach, this review comprehensively discussed previously conducted studies on pyrite depression with polysaccharide-based reagents. Additionally, practical suggestions have been provided for future assessments and developments of polysaccharide-based depressants, which pave the way to green flotation. This robust review also explored the depression efficiency and various adsorption aspects of naturally derived depressants on the pyrite surface to create a possible universal trend for each biodegradable depressant derivative.

    Fulltekst (pdf)
    fulltext
  • 6.
    Asimi Neisiani, A.
    et al.
    Department of Mining and Metallurgical Engineering Yazd University, Yazd 89195-741, Iran.
    Saneie, R.
    Department of Materials Engineering, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
    Mohammadzadeh, A.
    School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran.
    Wonyen, D. G.
    Department of Material Science and Engineering (Mining and Mineral Processing Engineering), African University of Science and Technology Abuja, Nigeria.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Biodegradable hematite depressants for green flotation separation – An overview2023Inngår i: Minerals Engineering, ISSN 0892-6875, E-ISSN 1872-9444, Vol. 199, artikkel-id 108114Artikkel, forskningsoversikt (Fagfellevurdert)
    Abstract [en]

    Due to environmental issues and the restrictions imposed on mineral flotation separation, the use of biodegradable and environmentally friendly reagents has gained widespread international attention. So far, several investigations have been conducted regarding the eco-friendly flotation separation of iron oxide ores for moving toward sustainable development and cleaner production. Yet, no critical review is specified on the green and eco-friendly depression reagents through their reverse flotation beneficiation. Therefore, this study will comprehensively discuss the previously conducted works in this area and provides suggestions for future assessments and developments. This robust study explored various adsorption aspects of natural-based depressants (polysaccharide-, polyphenolic-, and lignosulfonate-based) on iron oxide minerals (mainly hematite) to create a possible universal trend for each biodegradable depressant derivative. The laboratory and industrial experiments indicated that these depressants (except lignosulfonate-based) could selectively depress hematite at alkaline pHs and enhance its reverse flotation separation from their gangue phases (especially silicates as the main gangue phases). Although these eco-friendly depressants showed promising metallurgical results, several gaps still need to be addressed, notably in surface analyses and their adsorption mechanisms.

    Fulltekst (pdf)
    fulltext
  • 7.
    Asimi Neisiani, Ali
    et al.
    Department of Mining and Metallurgical Engineering, Yazd University, Yazd, Iran.
    Chehreh Chelgani, Saeed
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Biodegradable acids for pyrite depression and green flotation separation–an overview2023Inngår i: Critical reviews in biotechnology, ISSN 0738-8551, E-ISSN 1549-7801Artikkel, forskningsoversikt (Fagfellevurdert)
    Abstract [en]

    Exponential increasing demands for base metals have made meaningful processing of their quite low-grade (>1%) resources. Froth flotation is the most important physicochemical pretreatment technique for processing low-grade sulfide ores. In other words, flotation separation can effectively upgrade finely liberated base metal sulfides based on their surface properties. Various sulfide surface characters can be modified by flotation surfactants (collectors, activators, depressants, pH regulators, frothers, etc.). However, these reagents are mostly toxic. Therefore, using biodegradable flotation reagents would be essential for a green transition of ore treatment plants, while flotation circuits deal with massive volumes of water and materials. Pyrite, the most abundant sulfide mineral, is frequently associated with valuable minerals as a troublesome gangue. It causes severe technical and environmental difficulties. Thus, pyrite should be removed early in the beneficiation process to minimize its problematic issues. Recently, conventional inorganic pyrite depressants (such as cyanide, lime, and sulfur-oxy compounds) have been successfully assisted or even replaced with eco-friendly and green reagents (including polysaccharide-based substances and biodegradable acids). Yet, no comprehensive review is specified on the biodegradable acid depression reagents (such as tannic, lactic, humic acids, etc.) for pyrite removal through flotation separation. This study has comprehensively reviewed the previously conducted investigations in this area and provides suggestions for future assessments and developments. This robust review has systematically explored depression performance, various adsorption mechanisms, and aspects of these reagents on pyrite surfaces. Furthermore, factors affecting their efficiency were analyzed, and gaps within each area were highlighted.

    Fulltekst (pdf)
    fulltext
  • 8.
    Asimi Neisiani, Ali
    et al.
    Department of Mining and Metallurgical Engineering Yazd University, Yazd 8915818411, Iran; Bafgh Zinc Smelting Company (BZSC), Yazd 8915818411, Iran.
    Moosakazemi, Farhad
    Chemical Engineering Department, Laval University, Québec G1 V 0A6, Canada.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Technical and Economic Comparison between Sodium and Ammonium Agents in the Jarosite Precipitation Process─An Evaluation for Industrial Applications2023Inngår i: ACS Omega, E-ISSN 2470-1343, Vol. 8, nr 39, s. 35442-36613Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Iron content can cause severe challenges through zinc production from zinc sulfide concentrate. The zinc industry extensively uses the jarosite precipitation process (JPP) to precipitate dissolved iron and remove it before transferring the solution to downstream stages. Precipitating agents (PAs) play an essential role in the JPP. However, surprisingly, no study compares the efficiency of various PAs on an industrial scale. As an innovative approach, this investigation compares the technical and economic aspects of using various sodium and ammonium compounds (hydroxides, carbonates, bicarbonates, sulfates, and bisulfates) as typical PAs for the JPP at the Bafgh Zinc Smelting Company (BZSC) plant. Experimental results revealed that ammonium hydroxide, with 90.85% iron removal efficiency, had the highest performance, and sodium bisulfate and ammonium bisulfate had the lowest efficiency (74.54 and 77.13%, respectively). However, since ammonium hydroxide is a corrosive PA, it is not a promising alternative to sodium sulfate (with both economic and safety issues). Based on technical and economic assessments, sodium carbonate (84.31% iron removal efficiency) showed the highest potential for an efficient JPP.

    Fulltekst (pdf)
    fulltext
  • 9.
    Bastami, Sina
    et al.
    Department of Mining Engineering, Science and Research Branch, Islamic Azad University, Tehran 16846-13114, Iran.
    Ghassa, Sina
    School of Mining, College of Engineering, University of Tehran, Tehran 16846-13114, Iran.
    Seyedhakimi, Amin
    Department of Mining Engineering, Science and Research Branch, Islamic Azad University, Tehran 16846-13114, Iran.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Adsorption of Mercury from a Cyanide Leaching Solution Using Various Activation Rates of Granular Activated Carbon: A Laboratory- and Industrial-Scale Study2020Inngår i: Sustainability, E-ISSN 2071-1050, Vol. 12, nr 8, artikkel-id 3287Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The use of granular activated carbon (GAC) is a typical and sustainable technique for recovering precious metals from a cyanide leaching solution (CLS). The level of GAC activity is a fundamental factor in assessing the rate of precious metal adsorption; thus, it is essential to determine the efficiency of carbon elution for reproducing GACs. Since mercury (Hg) adsorption plays a critical role, economically and environmentally, in GAC efficiency, we conducted various laboratory and industrial experiments to explore the effect of different rates of GAC activation (10%, 35%, 70% and 100%) on Hg adsorption from CLS. Assessments of laboratory test results showed a direct relationship between the Hg adsorption and GAC activity; by increasing the GAC activity from 10% to 100%, the recovery of Hg was increased from 20% to 41%. Kinetic modeling results indicated that the Hg adsorption for all GAC activities followed chemisorption mechanisms. There was good agreement between the laboratory test results and the results of experiments on the industrial scale (that used a continuous circuit). These outcomes indicate that by increasing the frequency of carbon reactivation and using GAC with a high level of activity in the first tank, Hg desorption was meaningfully decreased and recovery was improved (for 10% GAC activity vs. 35% GAC activity, recovery was 40% vs. 90%, respectively).

    Fulltekst (pdf)
    Sus
  • 10.
    Bazar, July Ann
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Rahimi, M.
    Mining Engineering Department, Amirkabir University of Technology, Tehran, 1591634311, Iran.
    Fathinia, S.
    Mining Engineering Department, Amirkabir University of Technology, Tehran, 1591634311, Iran.
    Jafari, M.
    School of Mining, College of Engineering, University of Tehran, Tehran, 1439957131, Iran.
    Chipakwe, Vitalis
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Talc flotation—an overview2021Inngår i: Minerals, E-ISSN 2075-163X, Vol. 11, nr 7, artikkel-id 662Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Talc is a naturally hydrophobic gangue mineral in most sulfide ores. However, talc has vast applications in the cosmetics, paper, and paint industries due to its high chemical stability, and its demand continues to grow. Since flotation is the most effective beneficiation technique for up-grading sulfides, the high hydrophobicity of talc has made its selective separation challenging. This paper explored the different properties of talc and the different factors that affect its flotation separation performance as a proven versatile beneficiation technique. Surface properties, zeta potential measurements, contact angles, and other factors affecting the talc flotation efficiency were discussed in detail. It was observed that the surface face/edge ratio (particle size) has a direct relationship with the level of talc hydrophobicity. Talc surfaces are negatively charged in a wide pH range (pH 2–12). Different depressants have already been studied; however, most of them showed low selectivity. The addition of ions such as Ca2+ could enhance talc depression. Pretreatment methods such as ultrasonic and thermal treatments were reported to decrease the talc floatability. It was demonstrated that the development of new selective depressants or pretreatment options for talc flotation requires attention in future investigations to improve its selective separation. 

  • 11.
    Bu, Xiangning
    et al.
    Key Laboratory of Coal Processing and Efficient Utilization (Ministry of Education), School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou, China.
    Danstan, January Kadenge
    Key Laboratory of Coal Processing and Efficient Utilization (Ministry of Education), School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou, China.
    Hassanzadeh, Ahmad
    Department of Geoscience and Petroleum, Faculty of Engineering Science, Norwegian University of Science and Technology, Trondheim, Norway; Maelgwyn Mineral Services Ltd, Cardiff, UK.
    Behrad Vakylabad, Ali
    Department of Materials, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Metal extraction from ores and waste materials by ultrasound-assisted leaching -an overview2024Inngår i: Mineral Processing and Extractive Metallurgy Review, ISSN 0882-7508, E-ISSN 1547-7401, Vol. 45, nr 1, s. 28-45Artikkel, forskningsoversikt (Fagfellevurdert)
  • 12.
    Bu, Xiangning
    et al.
    School of Chemical Engineering and Technology, China University of Mining and Technology, Jiangsu, Xuzhou, 221116, China.
    Taghizadeh Vahed, Amir
    EPosture AB Luleå, Kvartsstigen 6, SE-977 53, Sweden.
    Ghassa, Sina
    School of Mining, College of Engineering, University of Tehran, Tehran, 16846-13114, Iran.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Modelling of coal flotation responses based on operational conditions by random forest2021Inngår i: International Journal of Oil, Gas and Coal Technology, ISSN 1753-3309, E-ISSN 1753-3317, Vol. 27, nr 4, s. 457-468Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Coal consumption is one of the critical factors in the economy of China. Flotation separation of coal from its inorganic part (ash) can reduce environmental problems of coal consumption and improve its combustion. This investigation used random forest (RF) as an advanced machine learning method to rank flotation operations by variable importance measurement and predict flotation responses based on operational parameters. Fifty flotation experiments were designed, and performed based on various flotation conditions and by different variables (collector dosage, frother dosage, air flowrate, pulp density, and impeller speed). Statistical assessments indicated that there is a significant negative correlation between yield and ash content. Experiments indicated that in the optimum conditions, yield and ash content would be 80 and 9%, respectively. Variable importance measurement by RF showed that frother has the highest effectiveness on yield. Outcomes of modelling released that RF can accurately be used for ranking flotation parameters, and generating models within complex systems in mineral processing.

  • 13.
    Bu, Xiangning
    et al.
    Key Laboratory of Coal Processing and Efficient Utilization of Ministry of Education, School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China.
    Zhou, Shaoqi
    Key Laboratory of Coal Processing and Efficient Utilization of Ministry of Education, School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China.
    Sun, Meng
    Fengxian Power Supply Co., Ltd., State Grid Jiangsu Electric Power Co., Ltd., Fengxian, Jiangsu 221700, China.
    Alheshibri, Muidh
    Department of Basic Science, Deanship of Preparatory Year and Supporting Studies, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia; Basic & Applied Scientific Research Center, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.
    Shakhaoath Khan, Md.
    ARC Research Hub for Computational Particle Technology, Department of Chemical Engineering, Monash University, Clayton, VIC 3800, Australia.
    Xie, Guangyuan
    Key Laboratory of Coal Processing and Efficient Utilization of Ministry of Education, School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Exploring the Relationships between Gas Dispersion Parameters and Differential Pressure Fluctuations in a Column Flotation2021Inngår i: ACS Omega, E-ISSN 2470-1343, Vol. 6, nr 34, s. 21900-21908Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Flotation separation, which is the most important mineral beneficiation technique, is dependent on gas dispersion (hydrodynamic conditions). Thus, many investigations have focused on the precise determination of hydrodynamic conditions such as Reynolds number of the bubbles, bubble velocity, and bubble diameter. However, few studies have examined their relationships with pressure fluctuations in a column flotation. This study introduced the differential pressure fluctuations as an actual variable that could be considered to determine the collection zone’s hydrodynamic conditions in a cyclonic microbubble flotation column. In general, the outcomes indicated that superficial gas velocity had the most substantial relationship with the differential pressure fluctuations among other flotation factors (such as pump speed, superficial gas velocity, superficial water velocity, and frother dosage). Furthermore, a high coefficient of determination (R2 > 0.77) for the equation generated to assess the relationships demonstrated that differential pressure fluctuations could be used as a promising tool to determine the hydrodynamic parameters’ characteristics in the flotation columns. 

  • 14.
    Chehreh Chelgani, S.
    et al.
    Surface Science Western, Research Park, University of Western Ontario, Ontario, Canada.
    Hart, B.
    Surface Science Western, Research Park, University of Western Ontario, Ontario, Canada.
    Xia, L.
    Surface Science Western, Research Park, University of Western Ontario, Ontario, Canada.
    A TOF-SIMS surface chemical analytical study of rare earth element minerals from micro-flotation tests products2013Inngår i: Minerals Engineering, ISSN 0892-6875, E-ISSN 1872-9444, Vol. 45, nr May, s. 32-40Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The Thor lake deposit is a world class resource of rare earth (REE) metals and minerals in Canada. Development work to optimize a REE mineral recovery process flow sheet is underway, however, given the ore mineralogy; the developed reagent scheme is relatively complex. As part of a research project, micro-flotation tests were conducted on a feed sample in order to examine factors affecting stream partitioning. SEM–EDX was performed to evaluate variability in grain composition between streams (concentrate and tails) and TOF-SIMS surface analysis was used to determine statistically significant differences in surface species particularly related to potential activation (or depression) of the examined mineral phases. SEM–EDX analysis reveal that the concentrate has a significantly higher proportion of REE bearing grains (carbonates and phosphates) relative to the tail (almost none were identified). Spectral fingerprinting by TOF-SIMS has allowed for the identification of all reagent species investigated. Reagent signal intensity discrimination on test stream mineral surfaces was observed by the TOF-SIMS analysis using reagents at plant concentration levels. TOF-SIMS analysis confirmed that REE bearing grains reporting to the concentrate are doing so in response to collector attachment whereas grains reporting to the tail are doing so in response to a lack of collector and/or in combination with the presence of the depressant. The surface analysis of gangue phases reveal a similar reagent discrimination; the signal intensity of collector species was significantly higher on the concentrate samples relative to the tails while depressant species were significantly enriched on the surface of the gangue phases in the tail samples. A detailed evaluation of the surface species representing the various reagents used in flotation scheme revealed a distinct competitive relationship between two of the reagents. The surface analysis identified that when used in concurrently, there appears to be a negative feedback resulting in a significant reduction in loading for several of the collectors on grains reporting to the concentrate. An evaluation of the effect of reagents on REE mineral in pilot plant is currently under way.

  • 15.
    Chehreh Chelgani, Saeed
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi. Wallenberg Initiative Materials Science for Sustainability, Department of Civil, Environmental and Natural Resources Engineering, Swedish School of Mines, Luleå University of Technology, Luleå, Sweden.
    Homafar, Arman
    Electrical and Computer Engineering Department, Semnan University, Semnan, Iran.
    Nasiri, Hamid
    Department of Computer Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.
    Rezaei laksar, Mojtaba
    Delijan Copper Flotation Company, Delijan, Iran.
    CatBoost-SHAP for modeling industrial operational flotation variables – A “conscious lab” approach2024Inngår i: Minerals Engineering, ISSN 0892-6875, E-ISSN 1872-9444, Vol. 213, artikkel-id 108754Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Flotation separation is the most important upgrading critical raw material technique. Measuring interactions within flotation variables and modeling their metallurgical responses (grade and recovery) is quite challenging on the industrial scale. These challenges are because flotation separation includes several sub-micron processes, and their monitoring won&apos;t be possible for the processing plants. Since many flotation plants are still manually operating and maintaining, understanding interactions within operational variables and their effect on the metallurgical responses would be crucial. As a unique approach, this study used the “Conscious Lab” concept for modeling flotation responses of an industrial copper upgrading plant when Potassium Amyl Xanthate substituted the secondary collector (Sodium Ethyl Xanthate) in the process. The main aim is to understand and compare interactions before and after the collector substitution. For the first time, the conscious lab was constructed based on the most advanced explainable artificial intelligence model, Shapley Additive Explanations, and Catboost. Catboost- Shapley Additive Explanations could accurately model flotation responses (less than 2% error between actual and predicted values) and illustrate variations of complex interactions through the substitution. Through a comparative study, Catboost could generate more precise outcomes than other known artificial intelligence models (Random Forest, Support Vector Regression, Extreme Gradient Boosting, and Convolutional Neural Network). In general, substituting Sodium Ethyl Xanthate by Potassium Amyl Xanthate reduced process predictability, although Potassium Amyl Xanthate could slightly increase the copper recovery.

    Fulltekst (pdf)
    fulltext
  • 16.
    Chelgani, S. Chehreh
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Nasiri, H.
    Department of Computer Engineering, Amirkabir University of Technology, Tehran, Iran.
    Alidokht, M.
    Tabas Parvardeh Coal Company (TPCCO), Birjand, Iran.
    Interpretable modeling of metallurgical responses for an industrial coal column flotation circuit by XGBoost and SHAP-A “conscious-lab” development2021Inngår i: International Journal of Mining Science and Technology, ISSN 2095-2686, Vol. 31, nr 6, s. 1135-1144Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Surprisingly, no investigation has been explored relationships between operating variables and metallurgical responses of coal column flotation (CF) circuits based on industrial databases for under operation plants. As a novel approach, this study implemented a conscious-lab “CL” for filling this gap. In this approach, for developing the CL dedicated to an industrial CF circuit, SHapley Additive exPlanations (SHAP) and extreme gradient boosting (XGBoost) were powerful unique machine learning systems for the first time considered. These explainable artificial intelligence models could effectively convert the dataset to a basis that improves human capabilities for better understanding, reasoning, and planning the unit. SHAP could provide precise multivariable correlation assessments between the CF dataset by using the Tabas Parvadeh coal plant (Kerman, Iran), and showed the importance of solid percentage and washing water on the metallurgical responses of the coal CF circuit. XGBoost could predict metallurgical responses (R-square > 0.88) based on operating variables that showed quite higher accuracy than typical modeling methods (Random Forest and support vector regression).

  • 17.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Estimation of gross calorific value based on coal analysis using an explainable artificial intelligence2021Inngår i: Machine Learning with Applications, ISSN 2666-8270, Vol. 6, artikkel-id 100116Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Developing fuel resources is strategically crucial for Armenia. Far more than any other fossil fuel resource, coal roughly generates half the nation’s electricity. Although coal could play a critical role, no vast data is available about Armenia coal properties. Using robust modeling of energy indexes such as coal gross calorific value (GCV) by considering trivial existing datasets could be an essential clue for ensuring sustainable development. For the first time, this investigation is going to model GCV for Armenia coal samples. For this purpose, SHAP (SHapley Additive exPlanations) as a novel explainable artificial intelligence will be introduced. SHAP enables understanding the magnitude of relationships between each individual input record and its representative output and ranks input variables based on their effectiveness. SHAP was coupled by extreme gradient boosting (xgboost) as the most recently generated powerful predictive machine learning tool (SHAP-Xgboost). SHAP-Xgboost could accurately (R2=0.99) model GCV based on proximate and ultimate variables of Armenia coal samples. These significant outcomes open a new window for developing high interpretability models to assess coal properties and pinpoint the influential parameters.

  • 18.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Exploring relationships of gross calorific value and valuable elements with conventional coal properties for North Korean coals2019Inngår i: International Journal of Mining Science and Technology, ISSN 2095-2686, Vol. 29, nr 6, s. 867-871Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Coal in North Korean (NKC) is one of the most important products; however, based on various strategic policies its detail properties remain opaque even for general researchers. Since there are some signs for opening of the North Korea economy, this investigation as a modest effort is going to explore principle relationships among some essential parameters of NKCs such as gross calorific value (GCV), valuable elements and conventional properties by different statistical methods. Correlations indicated that ultimate parameters (carbon, nitrogen, and hydrogen) are the best GCV predictors for NKCs in comparison with proximate parameters (ash, moisture and volatile matter). Multivariable regression demonstrated that predicted GCV based on ultimate properties has a quite accuracy when correlation of determination was 0.99. Descriptive statistics processes showed that on average, the contents of valuable elements such as Ga and V for NKCs are higher than the world coal ranges and they can be considered as byproducts of combustion of NKCs. Pearson correlations indicated that Y may have a mixed organic-inorganic affinity while Ga and V mainly occur in the inorganic part (mineral matter) of NKCs. High inter-correlations between Ga-V and Al showed that aluminosilicates can be considered as their main bring minerals.

  • 19.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Investigating the occurrences of valuable trace elements in African coals as potential byproducts of coal and coal combustion products2019Inngår i: Journal of African Earth Sciences, ISSN 1464-343X, Vol. 150, s. 131-135Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    There is a growing attention in valuable trace elements (TEs) in coal and coal combustionproducts as they can potentially be future resources of valuable TEs. Therefore, understanding the mode of occurrences of valuable TEs in coal has several advantages for their economical and industrial extractions. Since there is limited information on the affinity of valuable TEs in the structure of African coals, this study explores correlations between conventional coal properties and concentration of vanadium, yttrium, gallium and lithium as valuable TEs for a wide range of African coal samples (139 samples) from South Africa, Botswana, Egypt, Tanzania, Nigeria and Zambia by statistical methods. Statistical assessments indicated that the concentrations of Y, V, Li and Ga for these countries are higher than their value in the world coal (on average). The outcomes of assessments showed that the Li, Ga and V are associated with the mineral matter fraction (inorganic affinity) of the coal where they have significant positive correlations with ash and Al (as a major element) and potentially clay minerals are their main bearing minerals. However, statistical explorations suggested that Y may have both the organic and inorganic occurrences in the African coal samples

  • 20.
    Chelgani, Saeed Chehreh
    University of Michigan, Ann Arbor, USA.
    Occurrences of valuable trace elements in Iranian coals as potential coal combustion byproducts2021Inngår i: International Journal of Coal Preparation and Utilization, ISSN 1939-2699, Vol. 41, nr 7, s. 508-520Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In Iran, coal as one of the primary energy resources mainly has just one customer (Iranian Steel Corporation); therefore, coal and production of its combustion have recently attracted much attention as promising alternative sources for valuable trace metals (VTM). Since there has been few principle exploration on occurrence modes of VTM for Iranian coal, this investigation assessed possible interactions between various coal conventional properties (proximate and ultimate analysis) and Y, Li, Ga, and V as VTM for Iranian coals. Statistical analyses indicated that on average, the contents of all these elements are higher than the general world coal ranges. Inter-correlation assessments showed that Ga and V in the samples are mainly associated with mineral matter (inorganic fracture of coal), e.g., mostly adsorbed by aluminosilicate (clay minerals) while Y and Li have a mixed organic and inorganic affinity. Strong interactions of Ga and V with inorganic fraction for samples with over 70% ash content released that host rocks of Iranian coal seams may also have the potential for the extraction of these two VTM. On the other hand, the mixed organic and inorganic affinity of Y and Li showed high possibility of their extraction from the coal combustion products. These results could be a critical key not only for geological and environmental information but also for developing possible procedures for their extraction.

  • 21.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Prediction of specific gravity of Afghan coal based on conventional coal properties by stepwise regression and random forest2023Inngår i: Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, ISSN 1556-7036, E-ISSN 1556-7230, Vol. 45, nr 2, s. 4323-4334Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Coal can be considered as the main fuel for electricity generation in Afghanistan. However, there is a quite limited data available about the overall quality, distribution, and character of coals in Afghanistan. Specific gravity (S.G) of coal as a key factor can be used for the estimation of potential tonnage production and be a fundamental parameter for the selection of coal washery process method. However, there is no investigation which comprehensively explores relationships between S.G and coal properties. In this investigation, the potential of S.G prediction based on conventional properties for Afghan coal samples was explored by stepwise regression and random forest. Pearson correlation (r) and variable importance measurement (VIM) of random forest (RF) were applied to select the most effective variables among conventional parameters for the S.G prediction. Results of VIM indicated that ash and carbon content of coal samples had the highest importance for the S.G prediction. Stepwise regression and RF models were developed based on these two coal variables. Testing the generated models indicated that S.G of Afghan coals can quite accurately predict by these models (R2 > 0.90). Modeling outcomes showed that the highest S.G (S.G > 2) for Afghan coal occurred when ash was higher than 40% and carbon was lower than 30%.

    Fulltekst (pdf)
    fulltext
  • 22.
    Chelgani, Saeed Chehreh
    et al.
    Department of Mining Engineering, Science and Research Branch,Islamic Azad University.
    Dehghan, F.
    Department of Computer engineering, Jajarm Branch, Islamic Azad University, Iran.
    Hower, J. C.
    Center for Applied Energy Research, University of Kentucky, USA.
    Estimation of some coal parameters depending on petrographic and inorganic analyses by using Genetic algorithm and adaptive neuro-fuzzy inference systems2011Inngår i: Energy Exploration and Exploitation, ISSN 01445987, Vol. 29, nr 4, s. 479-494Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Adaptive neuro-fuzzy inference systems (ANFIS) in combination with genetic algorithm (GA); provide valuable modeling approaches of complex systems for a wide range of coal samples. Evaluation of this combination (GA-ANFIS) showed that the GA-ANFIS approach can be utilized as an efficient tool for describing and estimating some of coal variables such as Hardgrove grindability index, gross calorific value, free swelling index, and maximum vitrinite reflectance with various coal analyses (proximate, ultimate, elemental, and petrographic analysis). Statistical factors (correlation coefficient, mean square error, and variance accounted for) and differences between actual and predicted values demonstrated that the GA-ANFIS can be applied successfully, and provide high accuracy for prediction of those coal variables.

  • 23.
    Chelgani, Saeed Chehreh
    et al.
    University of Michigan, Ann Arbor, USA .
    Hadavandi, E
    Birjand University of Technology, Birjand, Iran.
    Hower, James C
    University of Kentucky, Lexington, USA .
    Study Relationship Between the Coal Thermoplastic Factor With Its Organic and Inorganic Properties by the Support Vector Regression Method2020Inngår i: International Journal of Coal Preparation and Utilization, ISSN 1939-2699, Vol. 40, nr 11, s. 743-754Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Metallurgical cokes, as fuel for blast furnaces, have certain properties which are directly related to their blended parental coal characters. The maximum fluidity (MF) of coal as an energy index is typically used to estimate the coke properties. In this investigation, Support Vector Regression (SVR), as an intelligent method, has been applied to link characteristics and pyrolysis properties of coal samples with their representative MFs. SVR variable importance measurement (VIM) through a wide range of coal properties indicated that volatile matter (VM) and maximum vitrinite reflectance (Rmax) are the most effective parameters for the MF prediction. The results indicated that low rank coal samples (VM>45% and Rmax>0.7) have log(MF) higher than 14 and high rank ones (VM<35% and Rmax<0.6) have log(MF) less than 4. The evaluation of the SVR model trained with these two selected input variables showed that SVR can predict MF quite accurately where the coefficient of determination (R2) between actual MF and SVR predicted was 0.86. According to these results, generation of SVR models which can predict and measure variable importance dependently, potentially may be applied for the scaling up of laboratory coal thermoplastic behavior to industrial levels, helping to sustainable development, and satisfactorily estimating coal consumption in the steel-making plants.

  • 24.
    Chelgani, Saeed Chehreh
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Hadavandi, Esmaeil
    Department of Industrial Engineering, Birjand University of Technology, Birjand, Iran.
    Hower, James C.
    Center for Applied Energy Research, University of Kentucky, Lexington, KY, USA.
    Estimation of heavy and light rare earth elements of coal by intelligent methods2021Inngår i: Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, ISSN 1556-7036, E-ISSN 1556-7230, Vol. 43, nr 1, s. 70-79Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Since last two decades, several investigations in various countries have been started to discover new rare earth element (REE) resources. It was reported that coal can be considered as a possible source of them. REE of coal occur in low concentrations, and their detection is a complicated process; therefore, their predictions based on conventional coal properties (proximate, ultimate and major elements (ME)) may have several advantages. However, few studies have been conducted in this area. This study examined relationships between coal properties and REE (HREE and LREE) for a wide range of coal samples (708 samples). Variable importance measure (VIM) by Mutual information (MI) as a new feature selection method was applied to consider the heterogeneous structure of coal and assess the individual relation between coal parameters and REE to select the compact subsets as input variables for modeling and improve the performance of prediction. VIM by MI showed that Si-Carbon, and Al-Hydrogen are the best subsets for the prediction of HREE and LREE concentrations, respectively. A boosted neural network (BNN) model as a new predictive tool was used for REE prediction. BNN can significantly reduce generalization of error. Results of BNN models showed that the HREE and LREE concentrations can satisfactory estimate (R 2 : 0.83 and 0.89, respectively). Results of this investigation were approved that MI-BNN can be used as a potential tool for prediction of other complex problems in energy and fuel areas.

  • 25.
    Chelgani, Saeed Chehreh
    et al.
    University of Michigan, Ann Arbor, USA.
    Hart, B.
    University of Western Ontario, Ontario N6G0J3, Canada.
    Explaining surface interactions for common associated gangues of rare earth minerals in response to the oxalic acid2018Inngår i: International Journal of Mining Science and Technology, ISSN 2095-2686, Vol. 28, nr 2, s. 343-346Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In the flotation of rare earth minerals (REMs), oxalic acid is reportedly acting both as a depressant and pH modifier. Although results of testing have established the significance of oxalic acid in the flotation process, its specific role in either the recovery or selectivity of REMs over their common gangue minerals is not well understood. Pulp pH reduction trials with alternative acids have not shown the same effect on the REMs recovery or the depression of gangue phases. This work studies the effect of oxalic acid on the surface of common REMs gangue minerals (quartz and carbonates (dolomite and calcite)) in a series of conditioning tests. Gangue surface analyses by time of flight secondary ion mass spectroscopy (TOF-SIMS) indicate that oxalic acid inhibits the transfer of secondary ions generated during the conditioning process from one mineral to another. In this regard, the oxalate anion acts to fix ions in solution through chelation, limiting their participation in surface adsorption.

  • 26.
    Chelgani, Saeed Chehreh
    et al.
    Surface Science Western, Research Park, University of Western Ontario, Canada.
    Hart, B.
    Surface Science Western, Research Park, University of Western Ontario, Candada.
    Marois, J.
    Niobec Inc., Canada.
    Ourriban, M.
    Niobec Inc., Canada.
    Study of pyrochlore matrix composition effects on froth flotation by SEM-EDX2012Inngår i: Minerals Engineering, ISSN 0892-6875, Vol. 30, s. 62-66Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM–EDX) was used to analyse pyrochlore grains from Niobec froth flotation plant. Approximately 200 pyrochlore gains from the mill feed, pyrochlore rougher feed, pyrochlore rougher concentrate, and tail were analysed in order to identify a potential relationship between pyrochlore matrix composition and selective separation. Analyses indicate that pyrochlore grains with high Fe content appear to be less recoverable than those with a lower Fe content. Furthermore, analysis indicates that the flotation response is related to matrix Fe rather than Fe occurring as inclusions within the pyrochlore. These mineralogical investigation results are from a much larger program where pyrochlore matrix composition will be examined in relation to surface chemistry and flotation selectivity.

  • 27.
    Chelgani, Saeed Chehreh
    et al.
    Surface Science Western, Research Park, University of Western Ontario, Canada.
    Hart, B.
    Surface Science Western, Research Park, University of Western Ontario, Candada.
    Marois, J.
    Niobec Inc., Canada.
    Ourriban, M.
    Niobec Inc., Canada.
    Study of pyrochlore surface chemistry effects on collector adsorption by TOF-SIMS2012Inngår i: Minerals Engineering, ISSN 0892-6875, Vol. 39, s. 71-76Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Time of flight secondary ion mass spectrometry (TOF-SIMS) was used to analyse the surface of two different types of pyrochlore, high Fe pyrochlore and low Fe pyrochlore, from Niobec Saint-Honore mine deposit. Pyrochlore grains were analysed in order to identify a potential relationship between pyrochlore matrix composition, the corresponding surface expression and the related effect on cationic collector adsorption. TOF-SIMS analyses of pyrochlore surfaces from a conditioning test show that the species indicative of the cationic collector, favour the surface of Fe poor pyrochlore relative to the Fe rich variety. Lower collector signals on the surface of the Fe-pyrochlore are matched by higher relative intensities of Fe, OH, O and FeOH. The TOF-SIMS results illustrate a negative relationship between a cationic collector adsorption and the presence of Fe and Fe oxidation species on the surface of pyrochlore grains, and supports previous work which identified a negative correlation between matrix Fe content and pyrochlore floatability. The surface analysis illustrates the link between pyrochlore matrix chemistry, the expression of surface species and their effect on collector adsorption.

  • 28.
    Chelgani, Saeed Chehreh
    et al.
    Surface Science Western, Research Park, University of Western Ontario, Canada.
    Hart, B.
    Surface Science Western, Research Park, University of Western Ontario, Candada.
    Marois, J.
    Niobec Inc., Canada.
    Ourriban, M.
    Niobec Inc., Canada.
    Study the relationship between the compositional zoning of high iron content pyrochlore and adsorption of cationic collector2013Inngår i: Minerals Engineering, ISSN 0892-6875, Vol. 46-47, s. 34-37Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The matrix composition and surface chemistry of high iron pyrochlore (Fe pyrochlore) grains from Niobec (St-Horone carbonatite deposit) were analyzed, in order to identify a potential relationship between Fe pyrochlore matrix composition and the related effect on cationic collector adsorption (tallow diamine). SEM–EDX analyses indicate compositional zoning in the structure Fe pyrochlores. TOF-SIMS was used to analyse the surface of different compositional zones of Fe pyrochlore, in order to identify their related effects on tallow diamine adsorption. Surface analyses of high and low iron zones of treated Fe pyrochlore show that species indicative of the collector favour the regions of low iron content The low iron areas also show a lower relative proportion of species indicative of oxidation. This study identifies the link between Fe pyrochlore compositional zoning, surface oxidation and, area selective collector loading.

  • 29.
    Chelgani, Saeed Chehreh
    et al.
    Surface Science Western, Research Park, University of Western Ontario, Canada.
    Hart, Brian
    Surface Science Western, Research Park, University of Western Ontario, Candada.
    Grady, William C.
    West Virginia Geological and Economic Survey, USA.
    Hower, James C.
    Center for Applied Energy Research, University of Kentucky, USA.
    Study Relationship between Inorganic and Organic Coal Analysis with Gross Calorific Value by Multiple Regression and ANFIS2011Inngår i: International Journal of Coal Preparation and Utilization, ISSN 1939-2699, Vol. 31, nr 1, s. 9-19Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The relationship between maceral content plus mineral matter and gross calorific value (GCV) for a wide range of West Virginia coal samples (from 6518 to 15330 BTU/lb; 15.16 to 35.66 MJ/kg) has been investigated by multivariable regression and adaptive neuro-fuzzy inference system (ANFIS). The stepwise least square mathematical method comparison between liptinite, vitrinite, plus mineral matter as input data sets with measured GCV reported a nonlinear correlation coefficient (R 2) of 0.83. Using the same data set the correlation between the predicted GCV from the ANFIS model and the actual GCV reported a R 2 value of 0.96. It was determined that the GCV-based prediction methods, as used in this article, can provide a reasonable estimation of GCV.

  • 30.
    Chelgani, Saeed Chehreh
    et al.
    University of Michigan, Ann Arbor, USA.
    Hower, J. C.
    University of Kentucky, Lexington, USA.
    Relationships between noble metals as potential coal combustion products and conventional coal properties2018Inngår i: Fuel, ISSN 0016-2361, E-ISSN 1873-7153, Vol. 226, s. 345-349Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Increasing coal consumption has generated million tons of ash and caused various environmental issues. Exploring statistical relationships between concentrations of valuable metals in coal and other coal properties may have several benefits for their commercial extraction as byproducts. This investigation studied relationships between conventional coal concentrations and concentration of noble metals for a wide range (708 samples) of eastern Kentucky coal samples (EKCS) by statistical methods. The results indicate that there are significant positive Pearson correlations (r) > 0.90 among all noble metals (Au, Pt, Pd, Ru and Rh) except for Ag (r < 0.2). The results also showed that the noble metals (except Ag) are associated with the minerals of the coal and have high positive correlations with ash (and high negative correlations with the organic fraction). Modeling through the database demonstrated that the highest Au concentrations in the EKCS occur when Si is between 6000 and 8000 ppm and Fe is below 10000 ppm, and the highest Ag was observed when both Cu and Ni were over 40 ppm. Outcomes suggested that aluminosilicate minerals and pyrite are possibly the main host of noble metals (except Ag) in the EKCS whereas Ag might occur in various forms including organic association, mineral species, and as a native metal.

  • 31.
    Chelgani, Saeed Chehreh
    et al.
    Surface Science Western, University of Western Ontario, Canada.
    Hower, J. C.
    Center for Applied Energy Research, University of Kentucky, USA.
    Hart, B.
    Surface Science Western, University of Western Ontario, Canada.
    Estimation of free-swelling index based on coal analysis using multivariable regression and artificial neural network2011Inngår i: Fuel Processing Technology, ISSN 0378-3820, Vol. 92, nr 3, s. 349-355Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The effects of proximate, ultimate and elemental analysis for a wide range of American coal samples on Free-swelling Index (FSI) have been investigated by multivariable regression and artificial neural network methods (ANN). The stepwise least square mathematical method shows that variables of ultimate analysis are better predictors than those from proximate analysis. The non linear multivariable regression, correlation coefficients (R2) from ultimate analysis inputs was 0.71, and for proximate analysis input variables was 0.49. With the same input sets, feed-forward artificial neural network (FANN) procedures improved accuracy of predicted FSI with R2 = 0.89, and 0.94 for proximate and ultimate analyses, respectively. The ANN based prediction method, as a first report, shows FSI is a predictable variable, and ANN can be further employed as a reliable and accurate method in the free-swelling index prediction.

  • 32.
    Chelgani, Saeed Chehreh
    et al.
    Department of Mining Engineering, Science and Research Branch,Islamic Azad University.
    Hower, J. C.
    Center for Applied Energy Research, University of Kentucky, USA.
    Jorjani, E.
    Department of Mining Engineering, Science and Research Branch,Islamic Azad University.
    Mesroghli, Sh.
    Department of Mining Engineering, Research and Science Campus, Islamic Azad University, Iran.
    Bagherieh, A. H.
    Department of Mining Engineering, Research and Science Campus, Islamic Azad University, Iran.
    Prediction of coal grindability based on petrography, proximate and ultimate analysis using multiple regression and artificial neural network models2008Inngår i: Fuel Processing Technology, ISSN 0378-3820, Vol. 89, nr 1, s. 13-20Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The effects of proximate and ultimate analysis, maceral content, and coal rank (Rmax) for a wide range of Kentucky coal samples from calorific value of 4320 to 14960 (BTU/lb) (10.05 to 34.80 MJ/kg) on Hardgrove Grindability Index (HGI) have been investigated by multivariable regression and artificial neural network methods (ANN). The stepwise least square mathematical method shows that the relationship between (a) Moisture, ash, volatile matter, and total sulfur; (b) ln (total sulfur), hydrogen, ash, ln ((oxygen + nitrogen)/carbon) and moisture; (c) ln (exinite), semifusinite, micrinite, macrinite, resinite, and Rmax input sets with HGI in linear condition can achieve the correlation coefficients (R2) of 0.77, 0.75, and 0.81, respectively. The ANN, which adequately recognized the characteristics of the coal samples, can predict HGI with correlation coefficients of 0.89, 0.89 and 0.95 respectively in testing process. It was determined that ln (exinite), semifusinite, micrinite, macrinite, resinite, and Rmax can be used as the best predictor for the estimation of HGI on multivariable regression (R2 = 0.81) and also artificial neural network methods (R2 = 0.95). The ANN based prediction method, as used in this paper, can be further employed as a reliable and accurate method, in the hardgrove grindability index prediction.

  • 33.
    Chelgani, Saeed Chehreh
    et al.
    University of Michigan, Ann Arbor, Michigan, USA.
    Hower, James C.
    University of Kentucky, Lexington, USA.
    Estimating REY content of eastern Kentucky coal samples based on their associated ash elements2018Inngår i: Journal of Rare Earths, ISSN 1002-0721, E-ISSN 2509-4963, Vol. 36, nr 11, s. 1234-1238Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Coal and coal combustion byproducts can be considered as an alternative source of rare earth elements and yttrium (REY). The study of relationships between REY and other main coal properties could have several advantages such as estimating REY content of coal particles and designing beneficial extraction method. In this investigation, inter-correlations between REY content with coal parameters (proximate and ash elements) for a wide range of eastern Kentucky coal samples (708 records) were explored. Results demonstrate that zircon and monazite are the main source of heavy and light rare earth elements (HREE and LREE), respectively. Zr has the highest correlation with Y and Th has the strength relationship with Ce and La. In general, LREE have higher interaction with coal ash content in comparison with HREE. Results indicated that REY can be estimated quite satisfactorily by using their associated elements in coal ash.

  • 34.
    Chelgani, Saeed Chehreh
    et al.
    Department of Mining Engineering, Science and Research Branch, Islamic Azad University, Iran.
    Jorjani, E.
    Department of Mining Engineering, Science and Research Branch,Islamic Azad University.
    Microwave irradiation pretreatment and peroxyacetic acid desulfurization of coal and application of GRNN simultaneous predictor2011Inngår i: Fuel, ISSN 0016-2361, Vol. 90, nr 11, s. 3156-3163Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Artificial neural network was used to predict the effects of operational parameters on coal desulfurization using peroxyacetic acid from microwave pretreated coal. Coal particle size (150–1125 μm), leaching temperature (25–85 °C), leaching time (0–120 min), microwave irradiation power (0–1000 W) and time (0–110 s) were used as inputs to the network. The outputs of the model were organic and inorganic sulfur reductions for 40 of the data sets. The GRNN artificial neural network with spread of 0.3 was used to estimate both organic and inorganic sulfur reduction from a combined database, which was established from microwave pretreatment and leaching experiments. Thirty-two data sets were used for training and eight data sets for testing. Simulated values obtained from the neural network, correspond closely to the experimental results. Satisfactory correlations of R2 = 0.99 and 0.97 were achieved during the testing stages of the prediction of inorganic and organic sulfur reductions respectively.

  • 35.
    Chelgani, Saeed Chehreh
    et al.
    Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany.
    Leißner, T.
    TU Bergakademie Freiberg, Freiberg, Germany.
    Rudolph, M.
    Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany; TU Bergakademie Freiberg, Freiberg, Germany.
    Peuker, U. A.
    TU Bergakademie Freiberg, Freiberg, Germany.
    Study of the relationship between zinnwaldite chemical composition and magnetic susceptibility2015Inngår i: Minerals Engineering, ISSN 0892-6875, E-ISSN 1872-9444, Vol. 72, s. 27-30Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This study investigates the relationship between chemical analyses and magnetic susceptibility of zinnwaldite through magnetic separation of various size fractions. Statistical analyses were used to increase information about magnetic properties of this mineral as a future source of lithium. Statistical modeling indicated that magnetic susceptibility (as a main factor of magnetic separation) accurately can be predicted based on cations content of zinnwaldite. However the size of particles had a significant effect on magnetic susceptibility. The small difference between the estimated and measured values for the non-linear relationship of this prediction (less than 1 (10−8 m3/kg)) shows that these accurate theoretical techniques can be also applied to estimate magnetic properties of zinnwaldite in other resources, and in-situ analysis.

  • 36.
    Chelgani, Saeed Chehreh
    et al.
    Surface Science Western, Research Park, University of Western Ontario, Canada.
    Makaremi, S.
    Biomedical Engineering Graduate Program, University of Western Ontario, Canada.
    Explaining the relationship between common coal analyses and Afghan coal parameters using statistical modeling methods2013Inngår i: Fuel Processing Technology, ISSN 0378-3820, Vol. 110, s. 79-85Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This study investigates the effects of proximate, ultimate and elemental analysis for Afghan coal samples on Hardgrove grindability index (HGI), Gross calorific value (GCV), and Ash fusion temperatures (AFTs) by using multivariable regression (MR) and Adaptive neuro-fuzzy inference system (ANFIS) to increase information about the properties of the Afghan coal. Statistical modeling (MR, and ANFIS) indicated that coal parameters (HGI, GCV, AFTs) can be predicted with high accuracy, where GCV, AFTs, and HGI were estimated by R2 = 0.99, 0.95, and 0.94, respectively. The small difference between the estimated parameters and their actual values shows that these accurate results can be also applied to estimate coal properties in other coal resources of Afghanistan.

  • 37.
    Chelgani, Saeed Chehreh
    et al.
    University of Michigan, Ann Arbor, USA; Islamic Azad University, Islamshahr, Iran.
    Matin, S. S.
    University of Michigan, Ann Arbor, USA; Islamic Azad University, Islamshahr, Iran.
    Study the relationship between coal properties with Gieseler plasticity parameters by random forest2018Inngår i: International Journal of Oil, Gas and Coal Technology, ISSN 1753-3309, E-ISSN 1753-3317, Vol. 17, nr 1, s. 113-127Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Gieseler fluidity provides thermoplastic information and the compatibility of blended coals for the cokemaking. A novel soft computing method, random forest (RF), for prediction of the softening temperature (Ts), the temperature of maximum fluidity (Tf), resolidification temperature (Tr) and maximum fluidity (MF) [Gieseler parameters (Gp)] was conducted based on the coal proximate analysis. Variable importance measurements were performed by RF to select the most effective variables for the prediction of Gp. Selected variables have been used as an input set of RF model for the modelling and prediction. Results of models indicated that RF can provide a satisfactory prediction of Gp with the correlation of determination R2: 0.64, 0.82, 0.90, and 0.86 for Ts, Tf, Tr and MF, respectively. Based on these results, it can be proposed that RF as a reliable non-parametric reliable predictive tool can be used for modelling of complex relationships in the fuel and energy investigations. 

  • 38.
    Chelgani, Saeed Chehreh
    et al.
    University of Michigan, Ann Arbor, Michigan, USA.
    Matin, S. S.
    Islamic Azad University, Tehran, Iran.
    Hower, James C.
    University of Kentucky, Lexington, Kentucky, USA.
    Explaining relationships between coke quality index and coal properties by Random Forest method2016Inngår i: Fuel, ISSN 0016-2361, E-ISSN 1873-7153, Vol. 182, s. 754-760Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this study was shown that random forest (RF) can be used as a sensible new data mining tool for variable importance measurements (VIMs) through various coal properties for prediction of coke quality (Free Swelling Index (FSI)). The VIMs of RF within coal analyses (proximate, ultimate, and petrographic analyses) were applied for the selection of the best predictors of FSI over a wide range of Kentucky coal samples. VIMs assisted by Pearson correlation through proximate, ultimate, and petrographic analyses indicated that volatile matter, carbon, vitrinite, and Rmax (coal rank parameters) are the most effective variables for the prediction of FSI. These important predictors have been used as inputs of RF model for the FSI prediction. Outputs in the testing stage of the model indicated that RF can predict FSI quite satisfactorily; the R2 was 0.93 and mean square error from actual FSIs was 0.15 (had less than interval unit of FSI; 0.5). According to the result, by providing nonlinear inter-dependence approximation among parameters for variable selection and also non-parametric predictive model RF can potentially be further employed as a reliable and accurate technique for the determination of complex relationship through fuel and energy investigations.

  • 39.
    Chelgani, Saeed Chehreh
    et al.
    University of Michigan, Ann Arbor, Michigan, USA.
    Matin, S. S.
    Islamic Azad University, Tehran, Iran.
    Makaremi, S.
    McMaster University, ON, Canada.
    Modeling of Free Swelling Index Based on Variable Importance Measurements of Parent Coal Properties by Random Forest Method2016Inngår i: Measurement, ISSN 0263-2241, E-ISSN 1873-412X, Vol. 94, s. 416-422Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Coke quality has a critical role in the steelmaking industry. The aim of this study is to examine the complex relationships between various conventional coal analyses using coke making index “free swelling index (FSI)”. Random forest (RF) associated with variable importance measurements (VIMs), which is a new powerful statistical data mining approach, is utilized in this study to analyze a high-dimensional database (3961 samples) to rank variables, and to develop an accurate FSI predictive model based on the most important variables. VIMs was performed on various types of analyses which indicated that volatile matter, carbon, moisture (coal rank parameters) and organic sulfur are the most effective coal properties for the prediction of FSI. These variables have been used as an input set of RF model for the FSI modeling and prediction. Results of FSI model indicated that RF can provide a satisfactory prediction of FSI with the correlation of determination R2 = 0.96 and mean square error of 0.16 from laboratory FSIs (which is smaller than the interval unit of FSI; 0.5). Based on this result, RF can be used to rank and select effective variables by evaluating nonlinear relationships among parameters. Moreover, it can be further employed as a non-parametric reliable predictive method for modeling, controlling, and optimizing complex variables; which to our knowledge has never been utilized in the fuel and energy sectors.

  • 40.
    Chelgani, Saeed Chehreh
    et al.
    Surface Science Western, University of Western Ontario, Canada.
    Mesroghli, S.
    Department of Mining Engineering, Science and Research Branch,Islamic Azad University, Iran.
    Hower, J. C.
    Center for Applied Energy Research, University of Kentucky, USA.
    Simultaneous prediction of coal rank parameters based on ultimate analysis using regression and artificial neural network2010Inngår i: International Journal of Coal Geology, ISSN 0166-5162, Vol. 83, nr 1, s. 31-34Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Results from ultimate analysis, proximate and petrographic analyses of a wide range of Kentucky coal samples were used to predict coal rank parameters (vitrinite maximum reflectance (Rmax) and gross calorific value (GCV)) using multivariable regression and artificial neural network (ANN) methods. Volatile matter, carbon, total sulfur, hydrogen and oxygen were used to predict both Rmax and GCV by regression and ANN. Multivariable regression equations to predict Rmax and GCV showed R2 = 0.77 and 0.69, respectively. Results from the ANN method with a 2–5–4–2 arrangement that simultaneously predicts GCV and Rmax showed R2 values of 0.84 and 0.90, respectively, for an independent test data set. The artificial neural network method can be appropriately used to predict Rmax and GCV when regression results do not have high accuracy.

  • 41.
    Chelgani, Saeed Chehreh
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Nasiri, H.
    Department of Computer Engineering, Amirkabir University of Technology, Tehran, Iran.
    Tohry, A.
    Mining and Metallurgical Engineering Department, Yazd University, Yazd, Iran; Research and Development Unit, Rahbar Farayand Arya Company (RFACo), Tehran, Iran.
    Modeling of particle sizes for industrial HPGR products by a unique explainable AI tool- A “Conscious Lab” development2021Inngår i: Advanced Powder Technology, ISSN 0921-8831, E-ISSN 1568-5527, Vol. 32, nr 11, s. 4141-4148Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    High-Pressure Grinding Rolls (HPGR), as a modified type of roll crushers, could intensively reduce the energy consumptions in the mineral processing comminution units. However, several problems counted for their operational modeling, especially in the industrial scales. Expanding a conscious laboratory (CL) as a recently developed concept based on the recorded datasets from the HPGR operational variables could be tackled those complications and fill the gap. Moreover, constructing such a CL base on explainable artificial intelligence (EAI) systems would be an innovative point for the digitalizing powder technology industries. Using a robust EAI model as a strategic approach could significantly improve system transparency and trustworthiness to convert any complicated black-box machine learning to a logical human basis system. This study introduced the SHapley Additive exPlanations (SHAP) and extreme gradient boosting (XGBoost) as the latest powerful EAI tool for the CL modeling of the particle sizes produced by an industrial HPGR (P80) in the Fakoor Sanat iron ore processing plant (Kerman, Iran). SHAP precisely assessed multivariable relationships between the monitored operational variables and correlated them with the HPGR P80. SHAP values showed relationship magnitudes among variables and ranked them based on their effectiveness on the P80 prediction. The working gap demonstrated the highest importance for the P80 prediction. XGBoost could precisely predict the P80 and showed higher accuracy than typical machine learning methods (random forest and support vector regression) for constructing the CL of HPGR. These significant outcomes would open a new window for robust consideration of the EAI models within powder technology.

  • 42.
    Chelgani, Saeed Chehreh
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Nasiri, H.
    Department of Computer Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.
    Tohry, A.
    Research and development unit, Rahbar Farayand Arya Company (RFACo), Tehran, Iran.
    Heidari, H. R.
    Deputy of the operation and production, Rahbar Farayand Arya Company (RFACo), Tehran, Iran.
    Modeling industrial hydrocyclone operational variables by SHAP-CatBoost - A "conscious lab" approach2023Inngår i: Powder Technology, ISSN 0032-5910, E-ISSN 1873-328X, Vol. 420, artikkel-id 118416Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Undoubtedly hydrocyclones play a critical role in powder technology, which can considerably affect the plants&apos; process efficiency. However, hydrocyclones were rarely modeled on an industrial scale, where a model can be used to train operators and minimize potential scale-up errors and lab costs. The novel approach for filling such a gap would be using conscious lab "CL" as a new concept that builds based on an industrial dataset and explainable artificial intelligence (XAI). As a novel approach, this study developed a CL and explored the interactions between hydrocyclone variables by the most recent XAI method called "SHapley Additive exPlanations (SHAP)", and a novel machine-learning model, "CatBoost". The hydrocyclone output and the particle size of the plant magnetic separator were modeled by SHAP-CatBoost. SHAP could successfully model all the relationships, and CatBoost could predict the O80 and K80, where outcomes had a higher accuracy (R2 similar to 0.90) than other conventional AIs.

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    fulltext
  • 43.
    Chelgani, Saeed Chehreh
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Neisiani, Ali Asimi
    Department of Mining and Metallurgical Engineering, Yazd University, Yazd, Iran.
    Dry Mineral Processing2022 (oppl. 1)Bok (Annet vitenskapelig)
    Abstract [en]

    This book introduces and explains all existing dry processing methods, drawing from larges studies about these techniques in both the academia and industrial sectors. Potentially, water insufficiency is one of the critical issues that could be the major cause of international conflicts. Thus, reducing water consumption and pollution in all industrial sectors is an essential issue for all countries. As a main part of the mining industry, ore processing plants are highly dependent on water, and water scarcity poses significant risk to the industry. Thus, water consumption is a strategic issue for mineral processing plants, particularly in dry climate countries. To select dry or wet processing, the differences between these conditions should be taken into consideration, which needs an in-depth understanding of the various possible methods. This book will be of interest to professionals and researchers.

  • 44.
    Chelgani, Saeed Chehreh
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Parian, Mehdi
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Semsari, Parisa
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Ghorbani, Yousef
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Rosenkranz, Jan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    A comparative study on the effects of dry and wet grinding on mineral flotation separation: a review2019Inngår i: Journal of Materials Research and Technology, ISSN 2238-7854, Vol. 8, nr 5, s. 5004-5011Artikkel, forskningsoversikt (Fagfellevurdert)
    Abstract [en]

    Water scarcity dictates to limit the use of water in ore processing plants particularly in arid regions. Since wet grinding is the most common method for particle size reduction and mineral liberation, there is a lack of understanding about the effects of dry grinding on downstream separation processes such as flotation. This manuscript compiles various effects of dry grinding on flotation and compares them with wet grinding. Dry grinding consumes higher energy and produces wider particle size distributions compared with wet grinding. It significantly decreases the rate of media consumption and liner wear; thus, the contamination of pulp for flotation separation is lower after dry grinding. Surface roughness, particle agglomeration, and surface oxidation are higher in dry grinding than wet grinding, which all these effects on the flotation process. Moreover, dry ground samples in the pulp phase correlate with higher Eh and dissolved oxygen concentration. Therefore, dry grinding can alter the floatability of minerals. This review thoroughly assesses various approaches for flotation separation of different minerals, which have been drily ground, and provides perspectives for further future investigations.

  • 45.
    Chelgani, Saeed Chehreh
    et al.
    Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany; University of Michigan, Ann Arbor, Michigan, USA.
    Rudolph, M.
    Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany.
    Kratzsch, R.
    Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany; TU Bergakademie Freiberg, Freiberg, Germany.
    Sandmann, D.
    TU Bergakademie Freiberg, Freiberg, Germany.
    Gutzmer, J.
    Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany.
    A Review of Graphite Beneficiation Techniques2016Inngår i: Mineral Processing and Extractive Metallurgy Review, ISSN 0882-7508, E-ISSN 1547-7401, Vol. 37, nr 1, s. 58-68Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Graphite as the most common polymorph of naturally occurring crystalline carbon is required for many different applications such as batteries, refractories, electrical products, and pencils. Graphite resources are currently being subjected to intensive exploration to help meet rapidly growing global demand – and graphite has made it onto the list of critical raw materials as issued by the European Union. Graphite ore is mostly beneficiated using flotation separation techniques. The increasing demand for high-grade graphite products with up to 99.99% carbon has resulted in the development of various approaches to remove impurities even to parts per million range. This paper considers separation and purification techniques that are currently employed for graphite mineral beneficiation, and identifies areas in need of further research.

  • 46.
    Chelgani, Saeed Chehreh
    et al.
    Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz-Institute Freiberg for Resource Technology, Germany.
    Rudolph, M.
    Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz-Institute Freiberg for Resource Technology, Germany.
    Leistner, T.
    Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz-Institute Freiberg for Resource Technology, Germany.
    Gutzmer, J.
    Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz-Institute Freiberg for Resource Technology, Germany.
    Peuker, U. A.
    Institute of Mechanical Process Engineering and Minerals Processing, TU Bergakademie Freiberg, Germany.
    A review of rare earth minerals flotation: Monazite and xenotime2015Inngår i: International Journal of Mining Science and Technology, ISSN 2095-2686, Vol. 25, nr 6, s. 877-883Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper reviews rare earth minerals (monazite and xenotime) separation by flotation. A wide range of monazite and xenotime flotation test results are summarized including: reasons of variation in the point of zero charges on these minerals, the effects of various flotation conditions on zeta potential of monazite and xenotime, interactions of collectors and depressants on the surface of these minerals during flotation separation, relationship between surface chemistry of the minerals and different types of collector adsorptions and effects of the conditioning temperature on flotation of rare earth minerals. This review collects various approaches for the selective separation of monazite and xenotime by flotation and gives perspectives for further research in the future.

  • 47.
    Chelgani, Saeed Chehreh
    et al.
    University of Michigan, USA.
    Shahbazi, B.
    Tarbiat Modares University, Tehran, Iran.
    Hadavandi, E.
    Birjand University of Technology, Birjand, Iran.
    Support vector regression modeling of coal flotation based on variable importance measurements by mutual information method2018Inngår i: Measurement, ISSN 0263-2241, E-ISSN 1873-412X, Vol. 114, s. 102-108Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Support vector regression (SVR) modeling was used to predict the coal flotation responses (recovery (R∗) and flotation rate constant (k)) as a function of measured particle properties and hydrodynamic flotation variables. Coal flotation is a complicated multifaceted separation process and many measurable and unmeasurable variables can be considered for its modeling. Therefore, feature selection can be used to save time and cost of measuring irrelevant parameters. Mutual information (MI) as a powerful variable selection tool was used through laboratory measured variables to assess interactions and choose the most effective ones for predictions of R∗ and k. Feature selection by MI through variables indicated that the best arrangements for the R∗ and k predictions are the sets of particle Reynolds number-energy dissipation and particle size-bubble Reynolds number, respectively. Correlation of determination (R2) and difference between laboratory measured and SVR predicted values based on MI selected variables indicated that the SVR can model R∗ and k quite accurately with R2 = 0.93 and R2 = 0.72, respectively. These results demonstrated that the MI-SVR combination can quite satisfactorily measure the importance of variables, increase interpretability, reduce the risk of overfitting, decrease complexity and generate predictive models for high dimension of variables based on selected features for complicated processing systems.

  • 48.
    Chen, Yuran
    et al.
    School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China; School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Bu, Xiangning
    School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China.
    Xie, Guangyuan
    School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China.
    Effect of the ultrasonic standing wave frequency on the attractive mineralization for fine coal particle flotation2021Inngår i: Ultrasonics sonochemistry, ISSN 1350-4177, E-ISSN 1873-2828, Vol. 77, artikkel-id 105682Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Froth flotation for mineral beneficiation is one of the most important separation techniques; however, it has several challenges for processing fine and ultrafine particles. Attractive mineralization between particles and bubbles by ultrasonic standing wave (USW) is a novel and high-efficiency method that could assist fine particle flotation. Frequency is an important ultrasound parameter, whose effectiveness mechanisms on the attractive mineralization did not compressively address. This study explored the effect of the USW field with various frequencies on the fine coal flotation for filling this gap. Herein, a high-speed camera and a focused beam reflectance measurement (FBRM) were used to analyze three sub-processes of the attractive mineralization, including the microbubbles’ formation, the conventional flotation bubbles (CFBs)’ dispersion, and the particles’ movement. It was found that the maximum flotation metallurgical responses were obtained under the highest examined USW frequency (600 kHz). However, the flotation outcomes by a low USW frequency (50 kHz) were even lower than the conventional flotation tests. Observation and theoretical calculation results revealed these results were originated from the influence of frequency on the carrier bubbles’ formation and the action of the secondary acoustic force during USW-assisted flotation. These outcomes demonstrated that frequency is a key factor determining the success of attractive mineralization for fine particles’ flotation.

  • 49.
    Chen, Yuran
    et al.
    School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China.
    Li, Pan
    School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China.
    Bu, Xiangning
    School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    Kong, Yapeng
    School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China.
    Liang, Xuemin
    School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China; Zhengzhou Hongyue Environmental Protection Technology Co., Ltd., Zhengzhou 450001, Henan, China.
    Resource utilization strategies for spent pot lining: A review of the current state2022Inngår i: Separation and Purification Technology, ISSN 1383-5866, E-ISSN 1873-3794, Vol. 300, artikkel-id 121816Artikkel, forskningsoversikt (Fagfellevurdert)
    Abstract [en]

    During a long-term operation of the aluminum electrolysis cell, the molten salts continuously infiltrate and corrode the pot lining, resulting in a huge amount of hazardous waste after the overhaul. The first cut of spent pot linings (SPL) contains several carbon-rich materials with potential economic value and hazardous matters such as soluble fluorite and cyanide. The continuous accumulation and disposal of SPL in depots or landfills have created a severe challenge to the aluminum industry. Nowadays, the technologies of harmless disposal and resource utilization of SPL have been paid more attention. This work has explored and presented the properties of SPL (including chemical, physical, and thermodynamic properties, etc.) and methods for its detoxification and purification. In this regard, the resource utilization strategies of SPL are systematically sorted out from three aspects: traditional, co-processing, and high-value technologies. In the end, the current challenges and future perspectives for the environmental recycling of SPL have been analyzed and summarized.

  • 50.
    Chen, Yuran
    et al.
    School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China.
    Li, Pan
    School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China.
    Bu, Xiangning
    School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China.
    Wang, Liqiang
    School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China.
    Liang, Xuemin
    School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China.
    Chelgani, Saeed Chehreh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
    In-depth purification of spent pot-lining by oxidation-expansion acid leaching: A comparative study2022Inngår i: Separation and Purification Technology, ISSN 1383-5866, E-ISSN 1873-3794, Vol. 303, artikkel-id 122313Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Spent pot lining (SPL) is a hazardous solid waste generated after overhauling the aluminum electrolytic cell. SPL contains carbon resources with high graphitization and toxic impurities, such as NaF, Na3AlF6, and CaF2. These toxic substances are difficult to remove from graphite completely. This study introduces an innovative method of oxidation-expansion acid leaching (OEAL) to eliminate impurities inside the graphitized carbon. For such a purpose, typical purification methods (conventional leaching, flotation-acid leaching) were investigated and compared to OEAL. The experimental outcomes indicated that the process efficiency for removing SPL impurities by various methods had the following sequence from high to low: OEAL > flotation-acid leaching > conventional leaching. The maximum SPL impurities removal rate by conventional leaching and flotation-acid leaching was 89.65 %, while it was 99.36 % with the OEAL method. For understanding fundamental aspects of the SPL impurity removal, their rejection mechanisms in the examined methods were systematically studied by different instrumentals and chemical analysis techniques. As a result of the reaction between H+ and residuals during OEAL process, the distance between graphitized carbon layers expands. This expansion resulted in a qualitative improvement in the SPL impurity removal by OEAL, making SPL one of the graphite or graphene oxide resources.

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