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An enormous amount of waste materials (tailings, fly ash and slag) are generated during mineral processing, power generation and metallurgical processes. A vast literature on utilising mill tailings for paste backfilling, fly ash and slag as partial replacement to cement is available. However, a detailed review on the application of mill tailings, fly ash and slag as mine paste backfill material has been lacking. This article provides a critical review of these industrial wastes’ utilisation as paste backfill material for backfilling of the underground mine voids. The properties of backfill materials affecting the paste backfill performance, advancements made in geomechanical, microstructural properties, strength prediction, leaching and economic aspects are scientifically reviewed. In addition to the above, the effect of alternative binders, specifically fly ash and slag, modification of paste backfill using alkali activator, superplasticizer, admixture and fibre reinforcement are comprehensively reviewed. The review ended with some future research directions in mine paste backfilling, especially applying natural and artificial additives for early strength development, strength and flowability prediction using statistical and artificial intelligence tools, leachates stabilization and geochemical modeling of leaching. Hence, this review would help in further application of such industrial waste materials for mine paste backfilling.

The increasing popularity of paste backfilling demands alternative binder optimisation and bulk waste disposal. This study investigates the efficacy of fly ash (FA) as partial replacement of ordinary portland cement (OPC) for paste backfill application in underground mines. The effect of FA addition on uniaxial compressive strength (UCS) and cohesion of paste backfill are demonstrated. The strength development was correlated with microstructural evolution using scanning electron microscopy (SEM)-energy dispersive X-ray spectroscopy (EDS). The study revealed that the rate of strength development in paste backfill slowed down when OPC was substituted by FA. However, the targeted 28 days' UCS of 1.1 MPa for the backfilling stope of lead-zinc mine was achieved with binder dosages of 8 wt% OPC, 7 wt% OPC, 6 wt% OPC, 7 wt% OPC +1 wt% FA and 6 wt% OPC +2 wt% FA. Thus, FA is a suitable binder substitute and up to 25% of OPC (8 wt%) can be replaced with FA. Analysis of microstructural evolution in paste backfill revealed that calcium silicate hydrate (C–S–H) did not develop in OPC-FA binder based paste backfill at its early days’ of curing and gypsum was found only in samples with OPC as sole binder. The multiple linear regression analysis on interaction effects of OPC, curing time, FA replacement percentage for 8 wt% and 5 wt% binder groups indicated that the UCS development is more sensitive towards FA replacement. The obtained results would help in better understanding and design of paste backfill for lead-zinc underground mines.

The methane retention mechanism in coal seams is markedly different from those of conventional gas reservoirs. Methane remains mainly as physically adsorbed molecules on micropore surface. Chemical and petrographic compositions of coal are the measures of maturity and type of organic matter that control the methane sorption characteristics of the coal. 99% of Indian coal occurrences are contributed by lower Gondwana sequences housed in two major geologic formations, younger Raniganj and older Barakar. The Raniganj Formation is best exposed in Raniganj Sub-basin and Barakar Formation is best exposed in Jharia Sub-basin of Damodar Valley. Present work attempts a systematic investigation on comparative account of methane sorption characteristics of coals from Raniganj Formation of Raniganj Sub-basin and Barakar Formations of Jharia Sub-basin in relation to their chemical composition and petrographic makeup. Chemical analyses shows that moisture, ash, volatile matter and fixed carbon varies between 2.5 and 4.6%, 10.0–27.2%, 38.8–40.2% (dmmf) and 59.8–61.2% (dmmf), respectively for Raniganj coals and, 0.5–1.1%, 16.7–32.9%, 20.7–22.0% (dmmf) and 78.0–79.3% (dmmf), respectively for Barakar coals. Carbon content is distinct for the suites of coal, 79.2–85.4% and 85.6–92.0% for Raniganj and Barakar coals, respectively. The vitrinite reflectance for the Raniganj coals ranges 0.53–0.72% and the Barakar coals ranges 1.09–1.23%. Based on the chemical composition and vitrinite reflectance value Raniganj coals belongs to high volatile bituminous type, whereas Barakar coals belongs to high to medium volatile bituminous type. Such variation in composition and maturity is mainly attributed to the variation in precursor organic matter as well as the basinal and thermal history of the sub-basins under consideration. H/C atomic ratio of the Raniganj and Barakar coals varies between 0.65 and 0.80 and 0.51–0.72 and O/C atomic ratio varies between 0.05 and 0.13 and 0.01–0.07, respectively. Coals of both the Raniganj and Barakar formations are mostly of kerogen Type-III with Raniganj coals falling in wet gas maturity stage approaching early-thermogenic methane generation whereas Barakar coals falling in condensate gas stage approaching peak-thermogenic methane generation. The Langmuir volume ranges from 9.3–21.8 cc/g (daf) for Raniganj coals and 21.1–29.1 cc/g (daf) for Barakar coals. Sorption capacity for the set of coals shows a strong rank dependency and increase with corresponding increase in rank down the stratigraphic column. Methane sorption capacity shows positive relationship with carbon content and vitrinite reflectance, and negative relationship with moisture content, ash and volatile matter. Moisture effect is more prominent in low rank Raniganj coals. The adsorption capacity shows a strong positive relation with vitrinite content and a moderate negative relation with inertinite content for both the Raniganj and Barakar coals, which may be attributed to dominancy of micropores in vitrinites with rank enhancement. The multiple regression analysis shows that the moisture is the main predictor of the VL, and the interaction of moisture with ash and reflectance mainly control the sorption capacity. A predictive model equation is developed for determination of sorption for Damodar basin coals from carbon, ash and moisture data.