Advancing low-carbon and resource-efficient beneficiation through early coarse gangue rejection technologies: A comprehensive review

The declining grade and increasing complexity of mineral resources, together with growing demands for energy efficiency and environmental sustainability, have renewed interest in early coarse gangue rejection (ECGR) as a strategy for reducing unnecessary downstream processing. This review critically examines the major ECGR technologies, including screening, differential/selective blasting, dense media separation (DMS), Reflux™ classification, coarse particle flotation (CPF), and sensor-based ore sorting (SBOS), by evaluating their separation principles, ore suitability, operating particle-size ranges, industrial maturity, engineering advantages, and practical limitations. Reported industrial and pilot-scale applications across gold, base metals, lithium, rare earth elements, and coal are synthesized to compare technology performance and identify commodity-specific applications. Particular attention is given to the emerging role of artificial intelligence (AI), including machine learning, deep learning, multi-sensor fusion, predictive modelling, digital twins, and adaptive process control, in improving ore characterization, process monitoring, and intelligent decision-making. The comparative assessment demonstrates that successful ECGR implementation depends primarily on ore-specific separation characteristics, including preferential breakage, density contrast, surface chemistry, mineralogical associations, and sensor-detectable properties, rather than on any single separation technology. The review further identifies cross-cutting technical challenges associated with ore variability, process integration, AI deployment, and industrial scalability, and discusses future research directions for developing integrated, adaptive, and intelligent beneficiation systems. Beyond improving beneficiation efficiency, ECGR supports low-carbon and circular mineral processing by reducing energy and water demand, minimizing waste generation, and enabling more resource-efficient utilization of mineral resources.

Authors

Institutions

Publication Details

Journal
Next Chemical Engineering
Published
2026-09-05
DOI
https://doi.org/10.1016/j.nxcen.2026.100110
Primary Topic
Minerals Flotation and Separation Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Advancing low-carbon and resource-efficient beneficiation through early coarse gangue rejection technologies: A comprehensive review

Bogale Tadesse, Ghuzanfar Saeed, Shufeng Bo, Laurence Dyer et al.
Next Chemical Engineering
Minerals Flotation and Separation Techniques
article

Advancing low-carbon and resource-efficient beneficiation through early coarse gangue rejection technologies: A comprehensive review

Bogale Tadesse, Ghuzanfar Saeed, Shufeng Bo, Laurence Dyer, Iftikhar Hussain
article en

Abstract

The declining grade and increasing complexity of mineral resources, together with growing demands for energy efficiency and environmental sustainability, have renewed interest in early coarse gangue rejection (ECGR) as a strategy for reducing unnecessary downstream processing. This review critically examines the major ECGR technologies, including screening, differential/selective blasting, dense media separation (DMS), Reflux™ classification, coarse particle flotation (CPF), and sensor-based ore sorting (SBOS), by evaluating their separation principles, ore suitability, operating particle-size ranges, industrial maturity, engineering advantages, and practical limitations. Reported industrial and pilot-scale applications across gold, base metals, lithium, rare earth elements, and coal are synthesized to compare technology performance and identify commodity-specific applications. Particular attention is given to the emerging role of artificial intelligence (AI), including machine learning, deep learning, multi-sensor fusion, predictive modelling, digital twins, and adaptive process control, in improving ore characterization, process monitoring, and intelligent decision-making. The comparative assessment demonstrates that successful ECGR implementation depends primarily on ore-specific separation characteristics, including preferential breakage, density contrast, surface chemistry, mineralogical associations, and sensor-detectable properties, rather than on any single separation technology. The review further identifies cross-cutting technical challenges associated with ore variability, process integration, AI deployment, and industrial scalability, and discusses future research directions for developing integrated, adaptive, and intelligent beneficiation systems. Beyond improving beneficiation efficiency, ECGR supports low-carbon and circular mineral processing by reducing energy and water demand, minimizing waste generation, and enabling more resource-efficient utilization of mineral resources.

Next Chemical EngineeringVol. 3
City University of Hong Kong (HK), Curtin University (AU), Kalgoorlie Consolidated Gold Mines (Australia) (AU), Pusan National University (KR)
Curtin University of Technology
Responsible consumption and production
Openalex Percentile: Top 20%
Minerals Flotation and Separation Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.