The Flotation of Kyanite and Sillimanite with Sodium Oleate as the Collector

Kyanite and sillimanite are two polymorphic minerals with the same formula of Al2SiO5, but different crystal structures. Despite their high economic values, selectively recovering them by flotation is a challenge. In this study, the flotation behaviors of the two minerals with sodium oleate as the collector were examined at different pH conditions. Zeta potential measurement, infrared spectroscopic measurement, chemical speciation and X-ray photoelectron spectroscopy measurement were conducted to identify the underpinning mechanisms. It is found that the flotation behavior of both minerals is different under the same flotation condition. The flotation recovery of sillimanite is much higher than that of kyanite in the presence of the collector sodium oleate. Sodium oleate adsorbs onto the surfaces of kyanite and sillimanite mainly through the chemical interaction of the ionic–molecular dimers with aluminum atoms at pH 8.0. The higher sillimanite flotation recovery between the two minerals is related to the higher electrostatic charge densities of the aluminum atoms in six-fold coordination, which leads to the higher collector adsorption

The separation of kyanite from quartz by flotation at acidic pH

An effective separation of kyanite from quartz by flotation is a challenge due to their similar surface properties and surface activation by metal ions. This study investigated the effect of pH, Fe and sodium silicate on the separation of kyanite from quartz using anionic collector, sodium petroleum sulfonate (SPS). Zeta potential measurement, infrared spectroscopic analysis and chemical speciation were conducted to identify the underpinning mechanisms. It was found that a good separation of kyanite from quartz was achieved at pH = 4.0 due to the selective adsorption of SPS on kyanite. However, the presence of Fe altered the electrical property on quartz which became attractive to SPS, enhanced quartz flotation and hence exacerbated the separation of kyanite from quartz. It is interesting that sodium silicate selectively depressed the flotation of iron-activated quartz by covering the activation sites and prohibiting collector adsorption. Although sodium silicate also interacted with kyanite, SPS still adsorbed on kyanite through reacting with Al atoms and therefore the depression of kyanite flotation by sodium silicate in the presence of Fe was limited

The flotation of aluminosilicate polymorphic minerals with anionic and cationic collectors

Andalusite, sillimanite, and kyanite are three polymorphic minerals with the same formula of Al2SiO5 but different crystal structures. Despite their high economic values, selectively recovering them by flotation is a challenge. In this study, the flotation behavior of the three minerals with two types of widely used collectors, anionic sodium hexadecanesulfonate (SHS) and cationic octadecylamine (OA) were examined at acidic pH. It was found that the flotation behavior of the three polymorphic minerals was different under the same flotation condition. In the presence of collector OA, the order of the flotation recovery of the three minerals was kyanite > sillimanite > andalusite, and the recovery increased with slurry pH. However, in the presence of collector SHS, the trend of the flotation recovery of the three minerals was completely opposite. X-ray photoelectron spectroscopy (XPS) was applied to quantitatively measure the collector adsorption and the surface active sites. The interaction between collectors and minerals was also studied by zeta potential measurements and calculating the adsorption energy using molecular dynamics (MD) simulation. It was found that the adsorption of collector OA was through the interaction of amine cations with O atoms by electrostatic attraction and hydrogen bonding. The highest flotation recovery of kyanite among the three minerals was related to the closest packing arrangement of oxygen atoms which leads to the highest electronegativity and therefore the lowest adsorption energy of OA. In comparison, the adsorption of collector SHS was mainly through the chemical interaction of sulfonate anions with Al atoms. The adsorption energy of SHS on andalusite surface was the lowest, which resulted from the lowest electronegativity of andalusite surface

Kinetics of Rare Earth and Aluminum Leaching from Kaolin

In this paper, magnesium sulfate was used as a lixiviant to recover rare earth from kaolin. The effects of column leaching conditions, such as the concentration of magnesium sulfate, liquid/solid ratio, flow rate, and pH of the magnesium sulfate solution on the leaching efficiency of rare earth and aluminum, were investigated. In addition, the leaching kinetics of rare earth and aluminum were analyzed based on the magnesium concentration. The results showed that the optimal leaching conditions 0.2 mol/L magnesium sulfate solution with no pH adjustment, 1.2:1 for the liquid/solid ratio, and at a flow rate of 0.5 mL/min led to an 89% rare earth leaching efficiency and an 81% aluminum leaching efficiency. The aluminum leaching efficiency by magnesium sulfate was 7% less than that by ammonium sulfate. Moreover, the equilibrium time for rare earth was 33 min shorter than aluminum, which is of benefit to reduce the leaching time of aluminum. The leaching kinetic data fitted an unreacted shrinking-core model. Semi-empirical equations based on the apparent rate constant and magnesium concentration of rare earth and aluminum were established, and the reaction orders for rare earth and aluminum were determined to be 1.69 and 1.61, respectively. The results of this study could help to better understand and optimize the leaching process by magnesium sulfate

The enhanced connectivity between the frontoparietal, somatomotor network and thalamus as the most significant network changes of chronic low back pain

The prolonged duration of chronic low back pain (cLBP) inevitably leads to changes in the cognitive, attentional, sensory and emotional processing brain regions. Currently, it remains unclear how these alterations are manifested in the interplay between brain functional and structural networks. This study aimed to predict the Oswestry Disability Index (ODI) in cLBP patients using multimodal brain magnetic resonance imaging (MRI) data and identified the most significant features within the multimodal networks to aid in distinguishing patients from healthy controls (HCs). We constructed dynamic functional connectivity (dFC) and structural connectivity (SC) networks for all participants (n = 112) and employed the Connectome-based Predictive Modeling (CPM) approach to predict ODI scores, utilizing various feature selection thresholds to identify the most significant network change features in dFC and SC outcomes. Subsequently, we utilized these significant features for optimal classifier selection and the integration of multimodal features. The results revealed enhanced connectivity among the frontoparietal network (FPN), somatomotor network (SMN) and thalamus in cLBP patients compared to HCs. The thalamus transmits pain-related sensations and emotions to the cortical areas through the dorsolateral prefrontal cortex (dlPFC) and primary somatosensory cortex (SI), leading to alterations in whole-brain network functionality and structure. Regarding the model selection for the classifier, we found that Support Vector Machine (SVM) best fit these significant network features. The combined model based on dFC and SC features significantly improved classification performance between cLBP patients and HCs (AUC=0.9772). Finally, the results from an external validation set support our hypotheses and provide insights into the potential applicability of the model in real-world scenarios. Our discovery of enhanced connectivity between the thalamus and both the dlPFC (FPN) and SI (SMN) provides a valuable supplement to prior research on cLBP