Announcements

11 August 2023
Minerals | Editor’s Choice Articles in 2022 in the Section “Mineral Exploration Methods and Applications”


Minerals
(ISSN: 2075-163X) has launched the “Mineral Exploration Methods and Applications” Section. The Section aims at publishing high-quality original research papers and critical reviews featuring the fundamental aspects and industrial applications in the field of mineral resources, including geological, geophysical, and geochemical methods, as well as satellite imagery. We invite contributions on historical, technical, and practical aspects of the exploration for mineral deposits. The papers should either focus on a novel methodology of mineral exploration or present case studies where established or innovative techniques were successfully used. In addition, we welcome contributions providing new insights into the foundations of geological, geophysical, and geochemical methods. The publications can be dedicated to field procedures and analytical techniques of geochemical exploration methods. Novel methods of gravity, magnetic, electromagnetic, radiometric, and seismic prospecting, in addition to their integration, including mathematical aspects of data processing and interpretation, as well as studies on remote sensing and geographic information systems in mineral exploration, are welcome. airborne, ground, and borehole methods could be presented. We also encourage the submission of papers that report rock sample studies required for mineral exploration and propose new physical, chemical, and mineralogical techniques for identifying mineral targets.

We are pleased to present the 2022 Editor’s Choice Articles, a carefully curated list of high-quality articles from “Mineral Exploration Methods and Applications” listed below:

Sedimentary Facies Controls for Reservoir Quality Prediction of Lower Shihezi Member-1 of the Hangjinqi Area, Ordos Basin
by Anees Aqsa, Hucai Zhang, Umar Ashraf, Ren Wang, Kai Liu, Ayesha Abbas, Zaheen Ullah, Xiaonan Zhang, Lizeng Duan,  Fengwen Liu et al.
Minerals 2022, 12(2), 126; https://doi.org/10.3390/min12020126
Available online: https://www.mdpi.com/2075-163X/12/2/126

Deep-Learning-Based Automatic Mineral Grain Segmentation and Recognition
by Ghazanfar Latif, Kévin Bouchard, Julien Maitre, Arnaud Back and Léo Paul Bédard
Minerals 2022, 12(4), 455; https://doi.org/10.3390/min12040455
Available online: https://www.mdpi.com/2075-163X/12/4/455

NHF as an Edge Detector of Potential Field Data and Its Application in the Yili Basin
by Tao Chen and Guibin Zhang
Minerals 2022, 12(2), 149; https://doi.org/10.3390/min12020149
Available online: https://www.mdpi.com/2075-163X/12/2/149

Deep Gold Exploration with SQUID TEM in the Qingchengzi Orefield, Eastern Liaoning, Northeast China
by Junjie Wu, Qingquan Zhi, Xiaohong Deng, Xingchun Wang, Xiaodong Chen, Yi Zhao and Yue Huang
Minerals 2022, 12(1), 102; https://doi.org/10.3390/min12010102
Available online: https://www.mdpi.com/2075-163X/12/1/102

Overview on the Development of Intelligent Methods for Mineral Resource Prediction under the Background of Geological Big Data
by Shi Li, Jianping Chen and Chang Liu
Minerals 2022, 12(5), 616; https://doi.org/10.3390/min12050616
Available online: https://www.mdpi.com/2075-163X/12/5/616

The Heavy Mineral Map of Australia: Vision and Pilot Project”
by Patrice de Caritat, Brent I. A. McInnes, Alexander T. Walker, Evgeniy Bastrakov, Stephen M. Rowins and Alexander M. Prent
Minerals 2022, 12(8), 961; https://doi.org/10.3390/min12080961
Available online: https://www.mdpi.com/2075-163X/12/8/961

Deep Learning Optimized Dictionary Learning and Its Application in Eliminating Strong Magnetotelluric Noise
by Guang Li, Xianjie Gu, Zhengyong Ren, Qihong Wu, Xiaoqiong Liu, Liang Zhang, Donghan Xiao and Cong Zhou
Minerals 2022, 12(8), 1012; https://doi.org/10.3390/min12081012
Available online: https://www.mdpi.com/2075-163X/12/8/1012

Coal Feed-Dependent Variation in Fly Ash Chemistry in a Single Pulverized-Combustion Unit
by James C. Hower, John G. Groppo, Shelley D. Hopps, Tonya D. Morgan, Heileen Hsu-Kim and Ross K. Taggart
Minerals 2022, 12(9), 1071; https://doi.org/10.3390/min12091071
Available online: https://www.mdpi.com/2075-163X/12/9/1071

Chemical and Mineralogical Characterization of Montevive Celestine Mineral
by Noemi Ariza-Rodríguez, Alejandro B. Rodríguez-Navarro, Mónica Calero de Hoces, Jose Manuel Martin and Mario J. Muñoz-Batista
Minerals 2022, 12(10), 1261; https://doi.org/10.3390/min12101261
Available online: https://www.mdpi.com/2075-163X/12/10/1261

Prospectivity Mapping of Heavy Mineral Ore Deposits Based upon Machine-Learning Algorithms: Columbite-Tantalite Deposits in West- Central Côte d’Ivoire”
by Kassi Olivier Shaw, Kalifa Goïta and Mickaël Germain
Minerals 2022, 12(11), 1453; https://doi.org/10.3390/min12111453
Available online: https://www.mdpi.com/2075-163X/12/11/1453

Fusion of Multispectral Remote-Sensing Data through GIS-Based Overlay Method for Revealing Potential Areas of Hydrothermal Mineral Resources
by Saad S.Alarifi, Mohamed Abdelkareem, Fathy Abdalla, Ismail S. Abdelsadek, Hisham Gahlan, Ahmad. M. Al-Saleh and Mislat Alotaibi
Minerals 2022, 12(12), 1577; https://doi.org/10.3390/min12121577
Available online: https://www.mdpi.com/2075-163X/12/12/1577

Multi-Dimensional Data Fusion for Mineral Prospectivity Mapping (MPM) Using Fuzzy-AHP Decision-Making Method, Kodegan-Basiran Region, East Iran
by Ali Shabani, Mansour Ziaii, Mehrdad Solimani Monfared, Adel Shirazy, and Aref Shirazi
Minerals 2022, 12(12), 1629; https://doi.org/10.3390/min12121629
Available online: https://www.mdpi.com/2075-163X/12/12/1629

Investigating the Capabilities of Various Multispectral Remote Sensors Data to Map Mineral Prospectivity Based on Random Forest Predictive Model: A Case Study for Gold Deposits in Hamissana Area, NE Sudan
by Abdallah M. Mohamed Taha, Yantao Xi, Qingping He, Anqi Hu, Shuangqiao Wang and Xianbin Liu
Minerals 2023, 13(1), 49; https://doi.org/10.3390/min13010049
Available online: https://www.mdpi.com/2075-163X/13/1/49

We would like to take this opportunity to thank all of the research groups that submitted to Minerals. We would appreciate it if you would circulate this document among your colleagues and network. Furthermore, the following opportunities for collaboration may be of interest:

Submitting a manuscript:
This Section is currently open for submissions. Papers may be submitted via the following link: https://susy.mdpi.com/user/manuscripts/upload?journal=minerals.

Launching a Special Issue:
You have the opportunity to propose hot topics and edit a Special Issue together with experts in the field: https://www.mdpi.com/journalproposal/sendproposalspecialissue/minerals.

Joining the Editorial Board:
If you are an active researcher in the field of mineral processing and extractive metallurgy and are interested in joining the Editorial Board, please do not hesitate to get in touch ([email protected]).

Minerals Editorial Office

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