Search results for: Yufan Sun

Authors: Yufan Mu

Abstract:

The selective depression of pyrite in the flotation of copper minerals is difficult due to the activation of pyrite surface by copper ions. Novel depressants for pyrite are needed to responsibly extract copper resources for a greener and cleaner future. In this paper, the non-toxic sodium alginate was employed as a depressant to selectively separate chalcopyrite from pyrite in flotation using potassium amyl xanthate as the collector. The results from flotation tests showed that sodium alginate significantly depressed pyrite flotation while had slight influence on chalcopyrite flotation. The adsorption tests showed that the adsorption amount of sodium alginate on pyrite surface was much higher than that on chalcopyrite surface. The pre-adsorbed sodium alginate could effectively hinder the subsequent adsorption of collector on pyrite surface, thereby inhibiting pyrite flotation. The selective adsorption of sodium alginate on pyrite surface was caused by the interactions between the activating cuprous ions on pyrite surface and the carboxyl groups in sodium alginate. The paper shows that sodium alginate is a promising depressant for pyrite in the flotation of chalcopyrite.

Keywords: chalcopyrite flotation, pyrite depression, sodium alginate, copper-activated pyrite, adsorption

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Authors: Yufan Mu

Abstract:

High salinity process water (HSPW) is often applied in copper ore flotation to alleviate freshwater shortage; however, it is detrimental to copper flotation as it strongly enhances copper activation of pyrite. In this study, the depression effect of a strong oxidiser, potassium ferrate (𝐾₂𝐹₄), on the flotation of copper-activated pyrite was tested to realise the selective separation of pyrite from copper minerals (e.g., chalcopyrite) in flotation using HSPW. The flotation results show that when (𝐾₂𝐹₄) was added in the flotation cell during conditioning, (𝐾₂𝐹₄) could selectively depress copper-activated pyrite while improving chalcopyrite flotation. The depression mechanism of (𝐾₂𝐹₄) on pyrite was ascribed to the significant increase in the pulp potential (Eₕ), dissolved oxygen (DO) concentration and the amount of ferric oxyhydroxides as a result of ferrate decomposition. In the flotation cell, the high Eh and DO concentration promoted the oxidation of low valency metal species (𝐶⁺𝐹e²⁺) released from mineral surfaces and forged steel grinding media, and the resultant high valency metal oxyhydroxides 𝐶u(𝑂H)₂⁄Fe(OH)₃ together with the ferric oxyhydroxides from ferrate decomposition preferentially precipitated on pyrite surface due to its more cathodic nature compared with chalcopyrite, which increased pyrite surface hydrophilicity and reduced its floatability. This study reveals that (𝐾₂𝐹₄) is a highly efficient depressant for pyrite when separating copper minerals from pyrite in flotation using HSPW if dosed properly.

Keywords: copper flotation, pyrite depression, copper-activated pyrite, potassium ferrate, high salinity process water

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Authors: John-Nelson Ekumah, Selorm Yao-Say Solomon Adade, Mingming Zhong, Yufan Sun, Qiufang Liang, Muhammad Safiullah Virk, Xorlali Nunekpeku, Nana Adwoa Nkuma Johnson, Bridget Ama Kwadzokpui, Xiaofeng Ren

Abstract:

Enhancing starch gel strength and stability is crucial. However, traditional gel property assessment methods are destructive, time-consuming and resource intensive. Thus, understanding ethanol treatment effects on kudzu starch gel strength and developing a rapid, nondestructive gel strength assessment method is essential for optimizing the treatment process and ensuring product quality consistency. This study investigated the effects of different ethanol concentrations on the microstructure of kudzu starch gels using a comprehensive microstructural analysis. We also developed a nondestructive method for predicting gel strength and classifying treatment levels using near-infrared (NIR) spectroscopy, and advanced data analytics. Scanning electron microscopy revealed progressive network densification and pore collapse with increasing ethanol concentration, correlating with enhanced mechanical properties. NIR spectroscopy, combined with various variable selection methods (CARS, GA, and UVE) and modeling algorithms (PLS, SVM, and ELM), was employed to develop predictive models for gel strength. The UVE-SVM model demonstrated exceptional performance, with the highest R² values (Rc = 0.9786, Rp = 0.9688) and lowest error rates (RMSEC = 6.1340, RMSEP = 6.0283). Pattern recognition algorithms (PCA, LDA, and KNN) successfully classified gels based on ethanol treatment levels, achieving near-perfect accuracy. This integrated approach provided a multiscale perspective on ethanol-induced starch gel modification, from molecular interactions to macroscopic properties. Our findings demonstrate the potential of NIR spectroscopy, coupled with advanced data analysis, as a powerful tool for rapid, nondestructive quality assessment in starch gel production. This study contributes significantly to the understanding of starch modification processes and opens new avenues for research and industrial applications in food science, pharmaceuticals, and biomaterials

Keywords: kudzu starch gel, near-infrared spectroscopy, gel strength prediction, support vector machine (SVM), pattern recognition algorithms, ethanol treatment

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