The flotation separation of fluorite from calcite using hydroxypropyl starch as a depressant
Introduction
Fluorite is an important non-metallic mineral, which is the main source of industrial fluorine [1,2], and it is also used in the fields of metallurgy, chemistry, glass and ceramic industries. Fluorite usually coexists with other calcium bearing and silicate minerals in ores, such as calcite. Froth flotation is commonly used for recovering and purifying fluorite and other valuable minerals [[3], [4], [5], [6], [7]]. However, it is hard to separate fluorite from calcite using low-selective fatty acid as a collector without depressants because of their similar surface properties [4,5].
To achieve the efficient separation of fluorite from calcite, depressants were commonly introduced in the fluorite/calcite system. Currently, water glass and phosphates are the most widely-used depressants for calcite [[8], [9], [10]]. These depressants have proved to be effective in increasing the flotation selectivity, but these depressants usually cause serious issues, such as polluting the eco-system, depressing fluorite floatability, and reducing the filtration speed of the tailings. Hence, the efficient separation of fluorite and calcite was still challenging nowadays.
Hydroxypropyl starch (HPS) is a kind of modified starch, which uses propylene epoxide to replace the hydroxide groups of starch by nucleophilic substitution reaction in the solution of sodium hydroxide [11]. Currently, HPS has been applied in the fields of food, medicine, textile and household chemicals because of its advantages of non-toxicity, high transparency, and good stability [12,13]. Modified starches have also been used as depressants in different mineral flotation systems, such as hematite-quartz [14], barite-fluorite [2] and hydraulic diaspore-aluminum silicate [15]. However, very few investigations have been conducted concerning modified starch on the flotation of fluorite from calcite.
In this work, HPS was selected as a potential depressant for calcite in the flotation of fluorite when using NaOl as a collector. The selective separation performance between fluorite and calcite was examined by microflotation tests. The flotation separation mechanism was discussed by zeta potential measurements and FT-IR spectrum analyses.
Section snippets
Mineral samples and reagents
Fluorite and calcite were collected from Hunan Shizhuyuan Nonferrous Metals co., Ltd, China. These two samples were crushed to −1 mm and then dry ground through a porcelain ball mill. After that, the resultant pulverized materials were dry sieved to obtain the size fraction of 37−74 μm for micro-flotation tests. X-ray diffraction (XRD) (Fig. 1) and chemical composition analyses (Table 1) confirmed that the fluorite and calcite samples were of high purity and qualified to be used for the
Microflotation results
The floatability of fluorite and calcite as a function of NaOl dosage at pH 8.0 is shown in Fig. 4. As seen in Fig. 4, flotation recoveries of fluorite and calcite significantly increased with increasing dosage of NaOl and remained constant at high collector concentration. The flotation recovery of both fluorite and calcite was over 90 % using 1.5 × 10−4 mol/L NaOl, which is due to the interaction of Ca ions with oleate species on the minerals surface [5]. The result showed that NaOl has a good
Conclusion
HPS was selected as a potential inhibitor in the flotation separation of fluorite from calcite. Microflotation tests presented that calcite was selectively depressed during fluorite flotation using the reagent scheme of HPS/NaOl. The zeta potentials measurements indicated the interaction of HPS with fluorite was weaker than that of HPS with calcite. It also suggested that NaOl could interact with the HPS-treated fluorite surface but could not adsorb on the HPS-treated calcite surface. FT-IR
CRediT authorship contribution statement
Wenxing Zhu: Investigation, Writing - original draft, Project administration. Jianhua Pan: Methodology, Conceptualization. Xinyang Yu: Conceptualization, Formal analysis, Funding acquisition. Guichun He: Software, Resources. Cheng Liu: Software, Writing - review & editing. Siyuan Yang: Software, Writing - review & editing. Yuhui Zeng: Investigation, Data curation, Methodology. An Zeng: Validation, Visualization. Taotao Liu: Data curation.
Declaration of Competing Interest
The authors declare no conflicts of interest.
Acknowledgement
The authors acknowledge the support of the Natural Science Foundation of China (No. 51774152), The Project of Education Department of Jiangxi Province, China (No. GJJ170504), the Open Foundation of State Key Laboratory of Mineral Processing, BGRIMM Technology (No. BGRIMM-KJSKL-2021-22) and students Innovation and Entrepreneurship Training Program of Jiangxi University of Science and Technology (No. DC2018-006).
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