Mineralogy-Guided Processing of Mining and Metallurgical Wastes into Geopolymeric and Alkali-Activated Materials

Mining and metallurgical wastes contain potentially valuable mineral resources but pose growing environmental risks. This review proposes a mineralogy-guided framework for converting these wastes into low-carbon binders and construction materials. Rather than classifying residues by origin or bulk oxide composition, it distinguishes them according to the reaction roles of their mineral phases. The framework first distinguishes self-sufficient systems, in which activation unlocks the intrinsic mineral inventory of the waste sufficiently for matrix or product formation, from mineralogically compensated systems, in which additional functional mineral solids are required to supply deficient reactive Si, Al, Ca, sulfate, alkalinity, or other phase-forming components. Binary and multicomponent formulations are then interpreted according to the specific mineralogical functions supplied by the complementary solids and the resulting changes in reaction pathways and products. Thermal, hydrothermal, mechanochemical, alkaline, and carbonation-based processing routes are compared in relation to phase composition, co-precursor function, and the mechanical, thermal, and service properties of concretes, foams, and backfill materials. Evidence indicates that performance depends more on chemical complementarity than on maximizing waste content. Environmental benefits must also account for contaminant immobilization, carbon dioxide binding, and the energy and reagent demand of pretreatment. Mineralogy-informed machine-learning models may support inverse mixture design, but their transferability remains constrained by feedstock heterogeneity and limited standardized data. The framework links mineralogy, processing, reaction products, performance, and scale-up.

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Publication Details

Journal
Minerals
Published
2026-09-13
DOI
https://doi.org/10.3390/min16090936
Primary Topic
Concrete and Cement Materials Research
Type
article
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article

Mineralogy-Guided Processing of Mining and Metallurgical Wastes into Geopolymeric and Alkali-Activated Materials

Aisulu Batkal, Aigerim Imash, V. L. Efremov, Aisulu Zhussupova et al.
Minerals
Concrete and Cement Materials Research
article

Mineralogy-Guided Processing of Mining and Metallurgical Wastes into Geopolymeric and Alkali-Activated Materials

Aisulu Batkal, Aigerim Imash, V. L. Efremov, Aisulu Zhussupova, Gaukhar Smagulova, Kaster Kamunur, Lyazzat Mussapyrova, Ryskul Azhigulova, Anton Kononov
article en

Abstract

Mining and metallurgical wastes contain potentially valuable mineral resources but pose growing environmental risks. This review proposes a mineralogy-guided framework for converting these wastes into low-carbon binders and construction materials. Rather than classifying residues by origin or bulk oxide composition, it distinguishes them according to the reaction roles of their mineral phases. The framework first distinguishes self-sufficient systems, in which activation unlocks the intrinsic mineral inventory of the waste sufficiently for matrix or product formation, from mineralogically compensated systems, in which additional functional mineral solids are required to supply deficient reactive Si, Al, Ca, sulfate, alkalinity, or other phase-forming components. Binary and multicomponent formulations are then interpreted according to the specific mineralogical functions supplied by the complementary solids and the resulting changes in reaction pathways and products. Thermal, hydrothermal, mechanochemical, alkaline, and carbonation-based processing routes are compared in relation to phase composition, co-precursor function, and the mechanical, thermal, and service properties of concretes, foams, and backfill materials. Evidence indicates that performance depends more on chemical complementarity than on maximizing waste content. Environmental benefits must also account for contaminant immobilization, carbon dioxide binding, and the energy and reagent demand of pretreatment. Mineralogy-informed machine-learning models may support inverse mixture design, but their transferability remains constrained by feedstock heterogeneity and limited standardized data. The framework links mineralogy, processing, reaction products, performance, and scale-up.

MineralsVol. 16(9)
Al-Farabi Kazakh National University (KZ)
Responsible consumption and production
Openalex Percentile: Top 17%
Concrete and Cement Materials Research
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