AIMC Topic: Minerals

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Flocculation-dewatering prediction of fine mineral tailings using a hybrid machine learning approach.

Chemosphere Nov 25, 2019
Polymer-assisted flocculation-dewatering of mineral processing tailings (MPT) is crucial for its environmental disposal. To reduce the number of laboratory experiments, this study proposes a novel and hybrid machine learning (ML) method for the predi...
Minerals Flocculation Machine Learning Waste Disposal, Fluid Principal Component Analysis Polymers
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On-line prediction of ferrous ion concentration in goethite process based on self-adjusting structure RBF neural network.

Neural networks : the official journal of the International Neural Network Society Mar 29, 2019
Outlet ferrous ion concentration is an essential indicator to manipulate the goethite process in the zinc hydrometallurgy plant. However, it cannot be measured on-line, which leads to the delay of this feedback information. In this study, a self-adju...
Forecasting Feedback Minerals Neural Networks, Computer Algorithms Iron Compounds Neurons Metallurgy Ferrous Compounds
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Computational model for vitamin D deficiency using hair mineral analysis.

Computational biology and chemistry Aug 30, 2017
Vitamin D deficiency is prevalent in the Arabian Gulf region, especially among women. Recent studies show that the vitamin D deficiency is associated with a mineral status of a patient. Therefore, it is important to assess the mineral status of the p...
Minerals Hair Vitamin D Deficiency Mutation Machine Learning Algorithms Female Vitamin D Humans
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Ontogeny and the process of biomineralization in the trichomes of Loasaceae.

American journal of botany Mar 8, 2017
PREMISE OF THE STUDY: South American Loasaceae have a morphologically complex trichome cover, which is characterized by multiple biomineralization. The current study investigates the ontogeny of these complex trichomes and the process of their biomin...
Trichomes Magnoliopsida Species Specificity Models, Biological Minerals Biological Ontologies Microscopy, Electron, Scanning Plant Leaves Calcium Phosphates
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Synergistic effects of proanthocyanidin, tri-calcium phosphate and fluoride on artificial root caries and dentine collagen.

Materials science & engineering. C, Materials for biological applications Nov 22, 2016
BACKGROUND: Proanthocyanidin has been shown to enhance dentine collagen stability and remineralization of artificial root caries.
Minerals Humans Collagenases Hydrogen-Ion Concentration Microscopy, Confocal Calcium Phosphates Proanthocyanidins Fluorides Microradiography X-Ray Diffraction Crystallization Drug Synergism Dentin Root Caries Hydroxyproline Collagen
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Degradation and mineralization of phenol compounds with goethite catalyst and mineralization prediction using artificial intelligence.

PloS one Apr 7, 2015
The efficiency of phenol degradation via Fenton reaction using mixture of heterogeneous goethite catalyst with homogeneous ferrous ion was analyzed as a function of three independent variables, initial concentration of phenol (60 to 100 mg /L), weigh...
Catalysis Minerals Oxidants Ferrous Compounds Neural Networks, Computer Hydrogen Peroxide Artificial Intelligence Phenols Software Ferric Compounds Iron Compounds Water Pollutants
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Analyzing the impact of clay minerals on the reservoir quality of the Lower Goru Formation using Unsupervised Machine Learning.

PloS one Jan 1, 2025
The reservoir quality of the Lower Goru Formation is highly variable due to its heterogeneous nature influenced by sea level fluctuations during the Early Cretaceous period. This study applies an unsupervised machine learning workflow, integrating Pr...
Unsupervised Machine Learning Principal Component Analysis Aluminum Silicates Clay Minerals Geologic Sediments Pakistan
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