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Minerals
Special Issues
Computer-Assisted Microscopy for Characterization of Ores and Rocks
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Computer-Assisted Microscopy for Characterization of Ores and Rocks

A special issue of Minerals (ISSN 2075-163X). This special issue belongs to the section "Mineral Processing and Extractive Metallurgy".

Deadline for manuscript submissions: closed (19 October 2022) | Viewed by 7054

Special Issue Editors

Dr. Otávio da Fonseca Martins Gomes

E-Mail Website
Guest Editor
CETEM - Centre for Mineral Technology, Rio de Janeiro 21941-908, Brazil
Interests: materials characterization; digital microscopy; correlative microscopy; image analysis; iron ore
Prof. Dr. Sidnei Paciornik

E-Mail Website
Guest Editor
Department of Chemical and Materials Engineering, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro 22451-900, Brazil
Interests: digital microscopy; image analysis; materials charaterization; X-ray microtomography
Prof. Dr. Mehdi Ostadhassan

E-Mail Website
Guest Editor
Key Laboratory of Continental Shale Hydrocarbon Accumulation and Efficient Development, Northeast Petroleum University, Daqing 163318, China
Interests: geochemistry; geomechanics; rock physics; analytical methods; materials characterization
Special Issues, Collections and Topics in MDPI journals
Dr. Eugene Donskoi

E-Mail Website
Guest Editor
Carbon Steel Futures group, CSIRO Mineral Resources, PO Box 883, Kenmore, QLD 4069, Australia
Interests: optical image analysis; downstream process performance modelling; ultrasonic treatment of iron ore; sinter properties modelling; coal and gas based direct reduction; coal pyrolysis and gasification modelling

Special Issue Information

Dear Colleagues,

Computer-assisted microscopy involves microscope control and automation, as well as digital image acquisition, processing, and analysis. Besides the automation of routine tasks in the microscopes, it extends the capabilities of traditional microscopy techniques. There are important characteristics of ores and rocks, such as, for instance, pore structure, texture, and mineral liberation, that can only be quantitatively evaluated using computer-assisted microscopy methods. Since the 1980s, with the development of so-called automated mineralogy systems, computer-assisted microscopy has created new possibilities for mineral analysis and it has been used as a framework for developing analytical tools that have become dominant in both academy and industry. Thus, this Special Issue will focus on novel developments and case studies of computer-assisted microscopy applied to the characterization of ores or rocks, which may include, but are not limited to, the following topics:

  • automated mineralogy
  • texture and liberation analysis
  • digital microscopy
  • correlative microscopy
  • multidimensional microscopy
  • x-ray micro-tomography
  • image analysis
  • machine learning/deep learning

Dr. Otávio da Fonseca Martins Gomes
Prof. Dr. Sidnei Paciornik
Prof. Dr. Mehdi Ostadhassan
Dr. Eugene Donskoi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Minerals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • applied mineralogy
  • mineral analysis
  • ore characterization
  • rock characterization
  • microstructural characterization
  • quantitative microscopy
  • x-ray microtomography
  • image analysis

Published Papers (3 papers)

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Research

18 pages, 11319 KiB  
Article
Utilisation of Enhanced Thresholding for Non-Opaque Mineral Segmentation in Optical Image Analysis
by Andrei Poliakov and Eugene Donskoi
Minerals 2023, 13(3), 350; https://doi.org/10.3390/min13030350 - 01 Mar 2023
Cited by 2 | Viewed by 914
Abstract
To understand and optimise downstream processing of ores, reliable information about mineral abundance, association, liberation and textural characteristics is needed. Such information can be obtained by using Optical Image Analysis (OIA) in reflected light, which can achieve good discrimination for the majority of [...] Read more.
To understand and optimise downstream processing of ores, reliable information about mineral abundance, association, liberation and textural characteristics is needed. Such information can be obtained by using Optical Image Analysis (OIA) in reflected light, which can achieve good discrimination for the majority of minerals. However, reliable automated segmentation of non-opaque minerals, such as quartz, which have reflectivity close to that of the epoxy they are embedded in, has always been problematic. Application of standard thresholding techniques for that purpose typically results in significant misidentifications. This paper presents a sophisticated segmentation mechanism, based on enhanced thresholding of non-opaque minerals developed for Commonwealth Scientific and Industrial Research Organisation’s (CSIRO) Mineral5/Recognition5 OIA software, which significantly improves segmentation in many applications. The method utilises an enhanced image view using an adjusted reflectivity scale for more precise initial thresholding, and comprehensive clean-up procedures for further segmentation improvement. For more complex cases, the method also employs specific particle border thresholding with subsequent selective erosion-based “reduction to borders”, while “particle restoration” prevents the detachment of non-opaque grains from larger particles. This method can be combined with “relief-based discrimination of non-opaque minerals” to achieve improved overall segmentation of non-opaque minerals. Full article
(This article belongs to the Special Issue Computer-Assisted Microscopy for Characterization of Ores and Rocks)
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16 pages, 6645 KiB  
Article
Mineralogical Fingerprint of Iron Ore Tailings in Paraopeba River Bedload Sediments after the B1 Dam Failure in Brumadinho, MG (Brazil)
by Fernando Verassani Laureano, Rogerio Kwitko-Ribeiro, Lorena Guimarães and Lucas Pereira Leão
Minerals 2022, 12(6), 716; https://doi.org/10.3390/min12060716 - 03 Jun 2022
Cited by 6 | Viewed by 1965
Abstract
The study presents SEM-based automated mineralogy to distinguish between natural sediments and iron ore tailings deposits from the Paraopeba River, after the failure of B1 Dam in Brumadinho, Minas Gerais, Brazil. Samples were obtained from borehole cores drilled over channel bars and banks [...] Read more.
The study presents SEM-based automated mineralogy to distinguish between natural sediments and iron ore tailings deposits from the Paraopeba River, after the failure of B1 Dam in Brumadinho, Minas Gerais, Brazil. Samples were obtained from borehole cores drilled over channel bars and banks eight months after the failure. After preliminary facies description, sediments from 54 chosen intervals were subjected to density measurement, X-ray diffraction (XRD), SEM-based automated mineralogy (QEMSCAN) analysis and determination of geochemical major components. Hierarchical clustering analysis (HCA) and principal component analysis (PCA) revealed six main mineral associations governed by different contents and ratios of quartz, kaolinite and hematite. Natural sediments are predominantly composed of mineral associations containing kaolinite, quartz and quartz + hematite with density values ranging from 2.5 to 3.3 g/cm3. Tailings deposits have density values higher than 3.5 g/cm3 and are mainly composed of hematite with occasional occurrences of kaolinite + hematite. Because of geological complexity and historical terrain occupation and usage, geochemical anomalies are common in the Paraopeba River sediments. Our data suggests that mineralogical oriented studies should precede detailed geochemical investigations, to enhance the understanding of the source of such anomalies and the environmental jeopardy associated to the occurrence. In this sense, SEM-based mineralogy has an enormous potential in environment studies. Full article
(This article belongs to the Special Issue Computer-Assisted Microscopy for Characterization of Ores and Rocks)
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19 pages, 24094 KiB  
Article
Characterization of the Crystallographic Preferred Orientation Relationships of the Magnetite-Hematite-Goethite Phase Transformation during Martitization
by Victor Mota e Nogueira, Paola Ferreira Barbosa, Sathish Mayanna, Adalene Moreira Silva, Catarina Labouré Bemfica Toledo, Leonardo Evangelista Lagoeiro and Luciano Mozer de Assis
Minerals 2022, 12(3), 326; https://doi.org/10.3390/min12030326 - 05 Mar 2022
Viewed by 2887
Abstract
The most frequent crystallographic preferred orientations developed during the progressive phase transformation of magnetite-hematite-goethite are described and analyzed in two natural samples of banded iron formations from Carajás Mineral Province. Microtextures of martitized grains containing the three phases and the microplaty matrix were [...] Read more.
The most frequent crystallographic preferred orientations developed during the progressive phase transformation of magnetite-hematite-goethite are described and analyzed in two natural samples of banded iron formations from Carajás Mineral Province. Microtextures of martitized grains containing the three phases and the microplaty matrix were analyzed in a scanning electron microscope equipped with a detector for electron backscatter diffraction. For identifying the correlation between magnetite, hematite and goethite lattice and topotaxity during transformation, multiple orientation relationships between the three phases were tested and verified using three-dimensional misorientation analysis. The results show that basal planes of goethite coincide with basal planes of hematite, which coincide with octahedral planes of magnetite. This indicates that transformation between the three minerals happens topotactically, and the oxygen lattice framework is preserved in all members of the reaction as a form of crystallographic memory. As a result of progressive and cyclical changes in oxidation/reduction conditions, an assemblage of high-order orientation relationships is observed and assigned to a complex process of transformation twinning in-between phase transformation of magnetite, hematite and goethite. In the N4WS iron ore deposit, iron oxides/hydroxides from martitized grains work as susceptible markers of environmental changes still in solid state during the diagenetic process. Full article
(This article belongs to the Special Issue Computer-Assisted Microscopy for Characterization of Ores and Rocks)
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