Influence of surface roughness on flotation kinetics of quartz

Surface roughness of quartz particles was determined by measuring the specific surface area of particles. The wettability characteristics of particles were determined by measuring the flotation rate using a laboratory flotation cell. Experimental results show that the rod mill product has higher roughness than the ball mill product. For the particles with larger surface roughness, the flotation kinetics constant is also higher. Finally, empirical relationships between surface roughness (r) and the flotation kinetics constant (k) of quartz particles as k=A+Br+Cr ^0.5lnr+D/lnr+E/r and k=A+Br are presented, in which A, B, C, D and E are constants related to experimental conditions and mineralogical properties of mineral.     

贫磁铁矿反浮选降硅试验

湖北省某地具有较为丰富铁矿资源,矿石中铁含量较低,原矿中全铁（TFe）含量约15%,属于贫磁铁矿,铁矿物的嵌布粒度较细,通过单一弱磁选很难得到全铁品位超过60%的铁精矿,针对该矿弱磁选精矿进行反浮选提铁脱硅研究,一粗一精开路反浮选流程精矿品位可达60%以上,铁回收率60%,产率50%左右.通过小型闭路试验,反浮选最终获得较好指标：精矿产率为68.57%,品位为58.62%,回收率为82.83%.     

磷矿反浮选捕收剂的评价方法

磷矿反浮选捕收剂大多数是由天然脂肪酸制成的,种类繁多,性能各异.从市场快速、准确地选择磷矿反浮选捕收剂,对浮选实践和浮选研究十分重要.浮选捕收剂的评价有助于掌握捕收剂的浮选性能,了解其在浮选过程中的作用.浮选法是浮选捕收剂的传统评价方法,程序复杂,耗时耗力.提出了一种新的浮选研究方法:燃烧-吸附量评价法,通过燃烧无机的矿石样品来测定其表面吸附的有机捕收剂量,评价磷矿反浮选捕收剂的性能.通过对油酸、硬脂酸和软脂酸这些结构明确且浮选工作者熟悉的脂肪酸的浮选性能和在白云石上的吸附量,建立了一个评价模型,验证燃烧-吸附量评价法的可行性.     

硝酸钠-碘化钾-氯化十四烷基二甲基苄基铵体系浮选铜

研究了硝酸钠-碘化钾-氯化十四烷基二甲基苄基铵体系浮选分离铜的行为及其与常见离子分离的条件,实验表明,控制pH=1～6,能使Cu(Ⅱ)与常见离子Zn(Ⅱ)、Fe(Ⅲ)、Al(Ⅲ)、Co(Ⅱ)、Ni(Ⅱ)、Mn(Ⅱ)分离.     

电化学调控法抑硫浮选的研究

进行了电化学法抑硫浮选的研究，探索了化学试剂法和外控电位法对细粒煤浮选脱硫的影响，通过试验证实，在低的矿浆电位下，黄铁矿能被有效抑制，提高了脱硫效率，它是一种经济有效、简单而无污染的抑制黄铁矿的新方法．     

Hydrogen and Oxygen Bubble Attachment to a Bitumen Drop

Air bubble – bitumen attachment is a critical step in the flotation of bitumen from mined oil sand. In this study, single bubble – bitumen drop attachment was observed directly using a novel experimental technique. Induction time is determined and used as an indication of bubble‐bitumen attachment potency for both hydrogen and oxygen bubbles. The attachment tests were conducted in deaerated municipal water (City of Edmonton tap water) at temperatures ranging from 22–50°C. Induction times measured for hydrogen bubble attachment were shorter than those for oxygen bubbles. Coalescence tests were also conducted in the absence of bitumen, and showed that hydrogen bubbles coalesced more rapidly than oxygen bubbles in both deaerated municipal water and clear (solids‐free) process water.     

Upgrading a rutile concentrate produced from Athabasca oil sands tailings

A rutile concentrate recently produced by Lakefield Research Ltd and Syncrude Canada Ltd from athabasca oil sands tailings was characterized and attempts were made to upgrade it to market-grade. The rutile concentrate contained 75.5% TiO₂, 18.7% Fe₂O₃, 1.03% Al₂O₃, 1.94% SiO₂, and 563 ppm Th+U. The amount of rutile (anatase) in the concentrate was estimated to be about 10-17%, and the remaining TiO₂ came from ilmenite in various altered forms. Magnetic separation could remove the Fe from the concentrate but it increased the SiO₂ content from 1.94 to 6.01%. A reverse flotation process was developed to remove the SiO₂. Although the fine dissemination of SiO₂ in the rutile matrix limited the removal of SiO₂, the upgraded rutile concentrate, containing 87-89% TiO₂, could be used as a feedstock to the chloride titanium pigment processes.     

十二胺浮选脱硫副产物亚硫酸镁实验及其机理研究

以镁法烟气脱硫技术产生的脱硫副产物亚硫酸镁为研究对象,采用一粗一精浮选的方法,分析副产物粒度、十二胺捕收剂和水玻璃调整剂用量等因素对脱硫副产物中亚硫酸镁浮选的影响,通过红外光谱及Zeta电位探究十二胺与脱硫副产物中亚硫酸镁的作用机理。结果表明,最佳的浮选条件为副产物粒径<0.074 mm的粒子质量分数为82.8%、粗选捕收剂十二胺用量为120 g/t、水玻璃用量为150 g/t、精选药剂的量为粗选的20%,脱硫副产物精矿中亚硫酸镁（以氧化镁质量分数计）品位达35.78%,回收率达56.8%。红外光谱及Zeta电位分析表明,十二胺与亚硫酸镁的作用原理主要以静电力吸附为主,并伴随着微弱的化学吸附作用。     

Dynamic global feature extraction and importance-correlation selection for the prediction of concentrate copper grade and recovery rate

Large-scale industrial data have brought great challenges to data calculation and analysis. Feature extraction and selection have become one of the research emphases in data mining. To mine the dynamic characteristics of large-scale industrial data, a dynamic global feature extraction (DGFE) method integrating principal component analysis (PCA) and kernel principal component analysis (KPCA) is proposed such that the achieved feature set is not only dynamic but also contains linear and non-linear features. To ensure that the obtained feature set is optimal with the minimum redundancy, a new importance-correlation-based feature selection (ICFS) method is proposed. To verify the validity and feasibility of the proposed methods, the partial least square (PLS) and least square support vector machine (LSSVM) prediction models for the concentrate copper grade and the recovery rate are established. The effectiveness of the proposed methods is verified through data experiments on a copper flotation industrial process.