Artificial Intelligence in Mining, Mineral and Material Processing
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Materials Science and Engineering".
Deadline for manuscript submissions: 30 October 2025 | Viewed by 43
Special Issue Editors
Interests: artificial intelligence; mineral processing; material processing; process automation; machine learning; deep learning; quantum computing; hydrogen storage; carbon capture
Interests: mineral processing; extractive metallurgy; physical metallurgy; corrosion; artificial intelligence; process automation; machine learning; complex systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue explores the transformative impact and potential of artificial intelligence (AI) in mining, mineral, and material processing industries. As the demand for sustainable and efficient resource utilization grows, AI is reshaping how we explore, extract, and process materials. This Special Issue encompasses innovative AI applications, including machine learning, deep learning, data analytics, the Internet of Things (IoT) and quantum computing, that enhance decision making, efficiency, safety, and sustainability in these critical sectors. Researchers and practitioners are invited to present cutting-edge innovative approaches, case studies, and reviews that demonstrate AI's role in revolutionizing mining and processing industries.
Recommended areas of focus include, but are not limited to, the following:
Automation and Optimization: AI-driven solutions and advancements for automating and optimizing mining operations, including predictive maintenance, resource estimation, and process control.
Data Integration and Analysis: Advanced data analytics techniques for integrating and interpreting complex data from mining and processing activities, improving decision making and operational insights.
Environmental Impact and Safety: AI applications aimed at minimizing environmental impact, enhancing safety protocols, and managing waste and resource utilization more effectively.
Innovative Processing Technologies: The development of new AI-based technologies and methods for mineral and material processing, including predictive modeling, ore sorting, quality control, and process optimization.
Dr. Xiu Liu
Prof. Dr. Chris Aldrich
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. Applied Sciences is an international peer-reviewed open access semimonthly 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
- artificial intelligence
- machine learning
- deep learning
- data analytics
- automation
- resource estimation
- process optimization
- environmental impact
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