Results 81 to 90 of about 478,532 (305)
Sources of ore fluid components in IOCG deposits
Many diverse hydrothermal copper deposits containing iron oxides are classified as IOCG deposits. Genetic models need to consider a number of different ore fluid components that may not all have the same source in an individual ore system, and also that ...
Kendrick, Mark +2 more
core
Sulphur isotope geochemistry of black shale-hosted antimony mineralization, Arnsberg, northern Rhenish Massif, Germany [PDF]
Vein-type and bedding-concordant mesothermal (180–410 °C) stibnite–sulphosalt mineralization at Arnsberg, NE Rhenish Massif, Germany, is hosted by Carboniferous pyrite-rich black shales and siliceous limestones.
Wagner, T., Boyce, A.J.
core +1 more source
B1 is bord width 1, B2 is bord width 2, L is the pillar length, W is the pillar width, red color and letter A represent the pillars, and white color and number 1 represent excavated areas. Pstress is the average pillar stress; σv is the vertical component of the virgin stress, MPa; and e is the areal extraction ratio. e = B o B o + B P ${\rm{e}}=\frac{{
Tawanda Zvarivadza +4 more
wiley +1 more source
Based on the 90 datasets, ERT and four optimization algorithms were used to build four hybrid models to predict the UCS of the backfill body. The SMA‐ERT model was the most effective model, and it can reliably guide the design of the backfill ratio parameters. Abstract This study analyzed the feasibility of using titanium (Ti) tailings as a backfilling
Weijun Liu, Zida Liu, Zhixiang Liu
wiley +1 more source
For the first time, the results of modern studies of the earth's crust based on gravity data from the GOCE satellite Project are used for a comparative regional metallogenic analysis of the geodynamic settings of the formation of polymetallic deposits in
Galyamov A. L. +2 more
doaj +1 more source
This research proposes an interpretable hybrid stacking ensemble framework, optimized by the Sparrow Search Algorithm, to enhance hard rock pillar stability prediction. By integrating six machine learning models—k‐nearest neighbors, support vector machines, random forests, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, and Light Gradient ...
Ning Wang +3 more
wiley +1 more source
Methodological Aspects of Predictive Mineragenic Studies Using Earth Remote Sensing Data
The article considers methodological aspects of allocation and substantiation of exploration areas for scarce types of ore minerals taking into account the concept of of mineral systems and using Earth remote sensing data with the application of ...
Petrov Vladislav +2 more
doaj +1 more source
Ore mineralogy of the In-bearing Ayawilca Zn-Ag-Sn-Cu project, Pasco, Peru
The Ayawilca Zn-In-Ag-Sn-Cu project is located in the Central Andean polymetallic belt of Peru. It is a carbonate replacement deposit with strong similarities to porphyry-related epithermal polymetallic ("Cordilleran") deposits in the Central Andes ...
Torro, Lisard +8 more
core
Recovery and Repurposing of End‐of‐Life Graphitic Anodes for Green Lithium‐Ion Batteries
This review summarizes the degradation mechanisms of spent graphite anodes in lithium‐ion batteries and highlights key recycling, regeneration, and modification strategies, including hydrometallurgical and pyrometallurgical approaches. It also discusses recent advances in surface engineering, structural regulation, and material hybridization, offering ...
Wei Wei, Weiguo Liu, Jiangqi Zhou
wiley +1 more source

