Article(id=1241081040958190178, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1241081025531540408, articleNumber=null, orderNo=null, doi=10.3969/j.issn.0253-6099.2024.04.035, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1710604800000, receivedDateStr=2024-03-17, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773826378334, onlineDateStr=2026-03-18, pubDate=1722441600000, pubDateStr=2024-08-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773826378334, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773826378334, creator=13701087609, updateTime=1773826378334, updator=13701087609, issue=Issue{id=1241081025531540408, tenantId=1146029695717560320, journalId=1235980550691926019, year='2024', volume='44', issue='4', pageStart='1', pageEnd='258', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773826374657, creator=13701087609, updateTime=1773827517159, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241085817590960730, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1241081025531540408, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241085817590960731, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1241081025531540408, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=185, endPage=188, ext={EN=ArticleExt(id=1241081042610746072, articleId=1241081040958190178, tenantId=1146029695717560320, journalId=1235980550691926019, language=EN, title=Investigation on Flotation of Low-Grade High-Sulfer Copper Ore, columnId=1236276106932842717, journalTitle=Mining and Metallurgical Engineering, columnName=MINERAL PROCESSING, runingTitle=null, highlight=null, articleAbstract=

A low-grade high-sulfur copper ore from Anhui Province has a sulfur grade of 41.30% and a copper grade of 0.53%. It is difficult to control the flotation index of this easy-to-oxidize ore. To improve the Cu/S separation effect, the influence of grinding fineness, reagent type and reagent dosage on copper flotation index was investigated. A closed-circuitflotation process including one stage of roughing, two stages of cleaning and two stages of scavenging was adopted to treat the ore with a grinding fineness of 83.88% -0.074 mm, with CaO and Na2S as a combined depressant, Z-200 as the collector and terpenic oil as the frother. It is found that a copper concentrate grading 15.27% Cu at 80.96% recovery can be obtained. This experimental study can provide a reference for flotation separation of copper from low-grade high-sulfur copper ore.

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安徽某高硫低品位铜矿硫品位41.30%、铜品位0.53%,易氧化,选矿指标不稳定。为了改善铜硫分离效果,研究了磨矿细度、药剂种类和药剂用量等对浮选指标的影响。结果表明,磨矿细度-0.074 mm粒级占83.88%,采用一粗二精二扫闭路浮选流程,以CaO+Na2S为组合抑制剂、Z-200为捕收剂、2#油为起泡剂,获得了铜品位15.27%、回收率80.96%的技术指标。试验结果可为高硫低品位铜矿浮选回收铜提供参考。

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余洪(1986—),男,四川达州人,博士,副教授,主要从事矿物加工、固废资源化利用等研究。E-mail:
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范宛惠(1998—),男,安徽阜阳人,硕士研究生,主要研究方向为矿物加工。E-mail:

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范宛惠(1998—),男,安徽阜阳人,硕士研究生,主要研究方向为矿物加工。E-mail:

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TFeCuSAl2O3SiO2CaOMgOAu1)Ag1)
40.880.5341.302.409.731.700.810.829.34
), ArticleFig(id=1241081054153470288, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1241081040958190178, language=CN, label=表1, caption=

原矿化学多元素分析结果(质量分数)

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TFeCuSAl2O3SiO2CaOMgOAu1)Ag1)
40.880.5341.302.409.731.700.810.829.34
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矿物名称质量分数/%面积占比/%面积/μm2统计相对误差
黄铁矿75.9076.1214 967 280.000.02
赤铁矿10.828.371 645 473.000.05
石英5.396.251 228 934.000.05
黄铜矿2.021.46286 780.800.11
钾长石1.601.77348 184.000.09
方解石1.161.61316 700.700.08
白云石0.700.98193 624.600.16
黑云母0.250.2549 870.050.12
辉石0.240.2448 126.500.15
生石膏0.210.2142 156.930.13
橄榄石+黄铁矿0.180.1834 427.250.15
橄榄石0.150.1120 949.960.27
绿泥石+黄铁矿0.140.1427 635.060.16
绿泥石0.110.1020 205.220.25
), ArticleFig(id=1241081054367379803, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1241081040958190178, language=CN, label=表2, caption=

原矿主要矿物组成

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矿物名称质量分数/%面积占比/%面积/μm2统计相对误差
黄铁矿75.9076.1214 967 280.000.02
赤铁矿10.828.371 645 473.000.05
石英5.396.251 228 934.000.05
黄铜矿2.021.46286 780.800.11
钾长石1.601.77348 184.000.09
方解石1.161.61316 700.700.08
白云石0.700.98193 624.600.16
黑云母0.250.2549 870.050.12
辉石0.240.2448 126.500.15
生石膏0.210.2142 156.930.13
橄榄石+黄铁矿0.180.1834 427.250.15
橄榄石0.150.1120 949.960.27
绿泥石+黄铁矿0.140.1427 635.060.16
绿泥石0.110.1020 205.220.25
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嵌布矿物二元共生/%三元包裹/%
方解石0.090.14
橄榄石1.690.35
生石膏0.000.14
石英1.530.77
绿泥石0.200.28
辉石0.340.46
钾长石0.350.73
黄铁矿15.422.28
黄铜矿0.080.47
黑云母0.000.16
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黄铜矿与其他矿物的嵌布特征

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嵌布矿物二元共生/%三元包裹/%
方解石0.090.14
橄榄石1.690.35
生石膏0.000.14
石英1.530.77
绿泥石0.200.28
辉石0.340.46
钾长石0.350.73
黄铁矿15.422.28
黄铜矿0.080.47
黑云母0.000.16
), ArticleFig(id=1241081054761644402, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1241081040958190178, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
嵌布矿物二元共生/%三元包裹/%
方解石0.180.21
生石膏0.060.22
绿泥石0.150.10
赤铁矿3.340.51
辉石0.210.30
钾长石0.570.38
黄铜矿1.050.09
黑云母0.080.22
石英0.720.69
橄榄石0.170.11
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黄铁矿与其他矿物的嵌布特征

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嵌布矿物二元共生/%三元包裹/%
方解石0.180.21
生石膏0.060.22
绿泥石0.150.10
赤铁矿3.340.51
辉石0.210.30
钾长石0.570.38
黄铜矿1.050.09
黑云母0.080.22
石英0.720.69
橄榄石0.170.11
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某高硫低品位铜矿浮选试验研究
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范宛惠 , 谢蕾 , 郭泽 , 张汉泉 , 余洪
矿冶工程杂志 | 选矿 2024,44(4): 185-188
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矿冶工程杂志 | 选矿 2024, 44(4): 185-188
某高硫低品位铜矿浮选试验研究
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范宛惠 , 谢蕾, 郭泽, 张汉泉, 余洪
作者信息
  • 武汉工程大学 资源与安全工程学院,湖北 武汉 430205
  • 范宛惠(1998—),男,安徽阜阳人,硕士研究生,主要研究方向为矿物加工。E-mail:

通讯作者:

余洪(1986—),男,四川达州人,博士,副教授,主要从事矿物加工、固废资源化利用等研究。E-mail:
Investigation on Flotation of Low-Grade High-Sulfer Copper Ore
Wanhui FAN , Lei XIE, Ze GUO, Hanquan ZHANG, Hong YU
Affiliations
  • School of Resources and Safety Engineering, Wuhan Institute of Technology, Wuhan 430205, Hubei, China
出版时间: 2024-08-01 doi: 10.3969/j.issn.0253-6099.2024.04.035
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安徽某高硫低品位铜矿硫品位41.30%、铜品位0.53%,易氧化,选矿指标不稳定。为了改善铜硫分离效果,研究了磨矿细度、药剂种类和药剂用量等对浮选指标的影响。结果表明,磨矿细度-0.074 mm粒级占83.88%,采用一粗二精二扫闭路浮选流程,以CaO+Na2S为组合抑制剂、Z-200为捕收剂、2#油为起泡剂,获得了铜品位15.27%、回收率80.96%的技术指标。试验结果可为高硫低品位铜矿浮选回收铜提供参考。

低品位  /  高硫铜矿  /  铜硫分离  /  组合抑制剂

A low-grade high-sulfur copper ore from Anhui Province has a sulfur grade of 41.30% and a copper grade of 0.53%. It is difficult to control the flotation index of this easy-to-oxidize ore. To improve the Cu/S separation effect, the influence of grinding fineness, reagent type and reagent dosage on copper flotation index was investigated. A closed-circuitflotation process including one stage of roughing, two stages of cleaning and two stages of scavenging was adopted to treat the ore with a grinding fineness of 83.88% -0.074 mm, with CaO and Na2S as a combined depressant, Z-200 as the collector and terpenic oil as the frother. It is found that a copper concentrate grading 15.27% Cu at 80.96% recovery can be obtained. This experimental study can provide a reference for flotation separation of copper from low-grade high-sulfur copper ore.

low grade  /  high-sulfur copper ore  /  Cu/S separation  /  combined depressant
范宛惠, 谢蕾, 郭泽, 张汉泉, 余洪. 某高硫低品位铜矿浮选试验研究. 矿冶工程杂志, 2024 , 44 (4) : 185 -188 . DOI: 10.3969/j.issn.0253-6099.2024.04.035
Wanhui FAN, Lei XIE, Ze GUO, Hanquan ZHANG, Hong YU. Investigation on Flotation of Low-Grade High-Sulfer Copper Ore[J]. Mining and Metallurgical Engineering, 2024 , 44 (4) : 185 -188 . DOI: 10.3969/j.issn.0253-6099.2024.04.035
铜是国民经济建设中重要的有色金属资源,广泛应用于电气、化工、钢铁、国防等领域[1-2]。自然界中已发现的主要含铜矿物有黄铜矿、辉铜矿和斑铜矿,其中黄铜矿占70%左右[3]。黄铜矿天然可浮性较好,在工业上常采用浮选富集分离。随着世界铜产量和需求量不断增长,铜矿在不断开采中逐渐呈现贫、细、杂的特点,入选铜矿石品位从20世纪初的1.5%~4.0%降到现在的0.4%,预期会持续降低[4]。如何从低品位复杂难选铜矿石中选出铜,已成为铜资源开发利用的重要内容。
安徽某高硫铜矿以硫为主,伴生铜、金、银、铁等多种金属元素[5],其中铜主要以黄铜矿形式存在,伴生黄铁矿,硫含量高,矿石易氧化,且浮选过程中难免离子Cu2+与黄铁矿表面会发生反应,改变其可浮性,使铜硫分离更加困难[6],目前对这种硫品位极高的矿石浮选研究较少。为了提高精矿铜品位与回收率,本文采用优先浮选工艺对该地区矿石进行试验设计与研究,在工艺矿物学研究基础上,结合已有铜矿浮选流程,确定合理的药剂制度,较好实现了该矿石资源的综合利用,可为现场工业化试验提供可靠的数据支持。
安徽某高硫铜矿原矿化学多元素分析结果见表1。由表1可知,原矿中除铁之外可利用的有价元素为硫、铜,含有少量金、银,主要脉石矿物为石英。
对原矿进行AMICS面扫描法分析,结果见表2。由表2可知,原矿主要由黄铁矿、赤铁矿、黄铜矿等金属矿物组成,脉石矿石主要由石英、长石类矿物(包括钾长石和钠长石)和方解石组成,此外还含有少量的白云石、黑云母、辉石、生石膏、橄榄石、绿泥石。
黄铜矿为矿石中主要有价铜矿物。黄铜矿呈它形粒状,粒径0.01~0.80 mm,多与三期白云石一起呈细脉状分布,部分交代黄铁矿。以单体解离态形式存在的黄铜矿占比为70.10%,其余黄铜矿则与其他矿物形成共生关系或包裹关系。黄铜矿嵌布特征分析结果如表3所示。
黄铁矿为矿石中主要有价硫矿物,且与黄铜矿表面性质相似,如何将其与黄铜矿浮选分离是回收铜的重点。黄铁矿主要呈半自形-近半自形粒状,较少量显它形粒状、微粒状、棱角状,少量呈尘点状,粒径0.01~3.00 mm,多呈集合体状聚集分布。一期黄铁矿颗粒细小,呈微粒状、尘点状,与白云石、赤铁矿分布在一起,或残留于二期白云石粒内;二期黄铁矿晶型好,颗粒大,多呈条带状聚集分布或与二期白云石混杂分布,局部显破碎状。黄铁矿单体解离度为88.07%,其余黄铁矿则与其他矿物呈共生关系或包裹关系。黄铁矿的嵌布特征分析结果如表4所示。
采用QM(BM)系列Ф150×50智能球磨机磨矿,磨矿浓度50%;使用XFGⅡ5-35型浮选机浮选。试验所用药剂包括Z-200(工业级)、CaO(分析纯)、硫酸(分析纯)、硫化钠(分析纯)等。浮选原则流程见图1
合适的磨矿细度是获得良好浮选指标的关键。在抑制剂CaO用量6 000 g/t、捕收剂Z-200用量75 g/t、起泡剂2#油用量90 g/t条件下,探究了磨矿细度对浮选指标的影响,结果见图2。由图2可知,随着给矿粒度减小,精矿产率增大,精矿Cu品位先增大后减小,回收率先减小后增大再减小,磨矿细度-0.074 mm粒级占83.88%时,精矿Cu品位和Cu回收率均较高,分别为8.55%和65.63%。综合考虑,确定磨矿细度-0.074 mm粒级占83.88%。
常用的黄铜矿捕收剂多为硫氮类、黄药、黑药及其衍生物等[7]。与黄药、黑药相比,硫氮类捕收剂捕收性能相近,但选择性更好、浮选效率更快。Z-200作为一种常用的硫氮类捕收剂,具有选择性好、捕收性强的优点。在磨矿细度-0.074 mm粒级占83.88%、CaO用量6 000 g/t、2#油用量90 g/t条件下,进行了捕收剂Z-200用量试验,结果见图3。由图3可知,随着粗选Z-200用量增加,精矿Cu品位和回收率先增大后减小。Z-200用量50 g/t时,精矿Cu品位为13.27%、Cu回收率为48.02%。综合考虑品位、回收率及成本,确定适宜的捕收剂用量为50 g/t。
原矿中硫含量达41.30%,浮选过程中黄铜矿与黄铁矿无法有效分离。为了提高铜精矿品位和回收率,需使用抑制剂对原矿进行选择性抑制。铜硫分离常用的无机抑制剂包含氧化钙、硫化钠等,有机抑制剂包含羧甲基纤维素等[8-10]
在磨矿细度-0.074 mm粒级占83.88%、Z-200用量50 g/t、2#油用量90 g/t条件下,以CaO为抑制剂,CaO用量对浮选指标的影响见图4。由图4可知,随着CaO用量增加,精矿Cu品位和回收率均增大,CaO用量6 000 g/t时,一次粗选精矿Cu品位和回收率分别为3.81%和64.12%。
原矿硫品位较高,磨矿后易被氧化,抑制剂用量较小时,容易发生跑槽现象。使用氧化类抑制剂时需对原矿进行深度氧化,用量大,不利于生产。为了进一步抑制硫、提高精矿铜品位与回收率,选择CaO+Na2S作为组合抑制剂。组合抑制剂可去除矿浆中的难免离子Cu2+,避免其活化黄铁矿,也可在还原气氛下解吸黄铁矿表面吸附的黄药[11]
在CaO用量6 000 g/t、Z-200用量50 g/t、2#油用量90 g/t条件下,研究了Na2S用量对浮选指标的影响,结果见图5。由图5可知,随着Na2S用量增加,精矿Cu品位和回收率均先增大后减小,Na2S用量40 g/t时,精矿Cu品位和回收率均达到最大值,分别为9.4%和68.39%。CaO+Na2S为组合抑制剂时,较少用量的Na2S可取得良好的抑制效果。同时试验过程中对抑制剂的添加方式进行了探索,采取分段加药和在磨矿阶段添加的方式,均未发现有明显效果,因此抑制剂用量是决定选矿指标的关键因素。
起泡剂可以改善泡沫稳定性、泡沫层厚度、气泡结构和大小等,在矿物浮选中有着重要作用[12]。在磨矿细度-0.074 mm粒级占83.88%、Z-200用量50 g/t、CaO+Na2S用量6 000 g/t+40 g/t条件下,研究了起泡剂2#油用量对浮选效果的影响,结果见图6。由图6可知,随着2#油用量增加,精矿Cu品位先减小后增大,Cu回收率一直增大。2#油用量30 g/t时,Cu品位达到最大值,为4.29%;2#油用量大于90 g/t后,Cu回收率趋于稳定。综合考虑精矿品位和回收率,适宜的2#油用量为60 g/t。
在条件试验基础上,进行了一粗两精两扫全流程闭路浮选试验,工艺流程见图7。磨矿细度-0.074 mm粒级占83.88%,使用CaO+Na2S(用量6000 g/t+40 g/t)为组合抑制剂、Z-200为捕收剂(粗选用量50 g/t、扫选1用量25 g/t)、2#油为起泡剂(用量60 g/t),闭路试验获得了铜品位15.36%、铜回收率81.73%的铜精矿。经分析发现,浮选尾矿中主要矿物为黄铁矿和磁性铁矿物,后续可通过活化浮选回收硫后,再进行弱磁选回收磁性铁矿物,实现资源综合利用。
1)安徽某铜矿中铜主要以黄铜矿形式存在,单体解离态存在的黄铜矿占70.10%,硫品位41.30%,属于易氧化的高硫低品位铜矿石。矿石成分复杂且共生关系密切,主要含有价矿物黄铁矿、赤铁矿和黄铜矿等,脉石矿石主要为石英、长石类矿物和方解石,此外还有少量白云石、黑云母、辉石等,其余黄铜矿与其他矿物形成共生关系或者包裹关系。
2)磨矿细度-0.074 mm粒级占83.88%,以CaO和Na2S为组合抑制剂、Z-200为捕收剂、2#油为起泡剂,采用一粗两精两扫闭路浮选流程,在原矿铜品位0.53%条件下,获得了铜品位15.36%、回收率81.73%的铜精矿产品,有效抑制了大量硫进入精矿,改善了生产指标。
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2024年第44卷第4期
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doi: 10.3969/j.issn.0253-6099.2024.04.035
  • 接收时间:2024-03-17
  • 首发时间:2026-03-18
  • 出版时间:2024-08-01
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  • 收稿日期:2024-03-17
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    武汉工程大学 资源与安全工程学院,湖北 武汉 430205

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余洪(1986—),男,四川达州人,博士,副教授,主要从事矿物加工、固废资源化利用等研究。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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