Application of Non-Destructive Analysis and Imaging Technology in Mineral Exploration
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".
Deadline for manuscript submissions: 20 September 2026 | Viewed by 273
Editors
Interests: non-destructive analysis; machine learning; automated mineralogy; mineral exploration; XRF; LIBS; Raman; VIS-SWIR
Special Issue Information
Dear Colleagues,
As the demand for critical mineral resources grows, the mining industry faces increasing pressure to adopt efficient, cost-effective, and environmentally friendly exploration methods. Traditional bulk analytical techniques, while accurate, are often time-consuming, while in contrast, modern imaging technologies offer the ability to acquire high-resolution mineralogical, textural, and geochemical data rapidly.
This Special Issue aims to highlight recent advances in non-destructive and micro-destructive technologies applied to mineral exploration. We encourage submissions utilizing diverse imaging modalities, including, but not limited to, the following:
1. Optical and Structural Imaging: High-resolution optical photography (RGB), petrographic microscopy, Cathodoluminescence (CL), and X-ray Computed Tomography (µCT).
2. Spectral Mapping: Hyperspectral imaging (VIS-SWIR-LWIR), Raman spectroscopy, and Micro-XRF.
3. Micro-scale Chemical Imaging: Scanning Electron Microscopy (SEM-EDS), Laser-Induced Breakdown Spectroscopy (LIBS), and LA-ICP-MS elemental/isotopic mapping.
We invite authors to submit original research articles, reviews, and case studies. The scope of this Special Issue encompasses both methodological developments and the practical application of these technologies in specific geological contexts. Additionally, we welcome studies that employ artificial intelligence (AI) and machine learning to enhance data processing, image analysis, and interpretation workflows.
Dr. Jie Yang
Guest Editor
Dr. Molei Zhao
Guest Editor Assistant
Manuscript Submission Information
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Keywords
- non-destructive analysis
- micro-destructive analysis
- imaging techniques
- mineral exploration
- hyperspectral imaging
- chemical mapping
- automated mineralogy
- machine learning
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