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Article(id=1236276110082756756, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1236276104999268557, articleNumber=null, orderNo=null, doi=10.3969/j.issn.0253-6099.2025.04.011, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1739635200000, receivedDateStr=2025-02-16, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1772680793542, onlineDateStr=2026-03-05, pubDate=1753977600000, pubDateStr=2025-08-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1772680793542, onlineIssueDateStr=2026-03-05, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1772680793542, creator=13701087609, updateTime=1772680793542, updator=13701087609, issue=Issue{id=1236276104999268557, tenantId=1146029695717560320, journalId=1235980550691926019, year='2025', volume='45', issue='4', pageStart='1', pageEnd='200', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1772680792331, creator=13701087609, updateTime=1772681498687, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1236279067746562719, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1236276104999268557, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1236279067746562720, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1236276104999268557, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=63, endPage=67, ext={EN=ArticleExt(id=1236276110472827040, articleId=1236276110082756756, tenantId=1146029695717560320, journalId=1235980550691926019, language=EN, title=Beneficiation Experiment of Low Grade Niobium Ore for Super Enrichment, columnId=1236276106932842717, journalTitle=Mining and Metallurgical Engineering, columnName=MINERAL PROCESSING, runingTitle=null, highlight=null, articleAbstract=

A beneficiation experiment for super enrichment was carried out with the low-grade niobium ore from western zone of Bayan Obo mine. In the experiment, a process of magnetic separation followed by gravity concentration for tailings discarding was firstly adopted for pre-concentration, and the obtained rougher concentrate grading 2.61% Nb2O5 was subjected to a reverse flotation for desulfuration, followed by a direct flotation with CYN-7 as a collector and CYD-2 as a depressant for recovering Nb minerals, resulting in efficient separation between Nb and other gangue minerals. It is found that the raw ore grading 0.06% Nb2O5, with a grinding fineness of－0.074 mm 85% is treated by magnetic separation and gravity concentration for tailings discarding, followed by a reverse flotation for desulfuration, and a direct flotation consisting of one stage of roughing and three stage of cleaning. As a result, a Nb concentrate grading 22.37% Nb2O5 at 33.64% recovery can be finally obtained.

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对白云鄂博西矿区某低品位铌矿石进行了超常富集选矿试验研究，采用磁选-重选抛尾预富集，获得Nb2O5品位2.61%的铌粗精矿；铌粗精矿经浮选去除硫化矿后，采用捕收剂CYN-7和抑制剂CYD-2浮选回收铌矿物，达到铌矿物与脉石矿物的高效分离。结果表明，在给矿Nb2O5品位0.06%、磨矿细度－0.074 mm粒级占85%条件下，采用磁选-重选抛尾、反浮选脱硫、一粗三精正浮选选铌流程，最终可获得Nb2O5品位22.37%、Nb2O5回收率33.64%的铌精矿。

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周瑜林（1983—），女，湖南岳阳人，博士，高级工程师，主要研究方向为铁及铁基共伴生矿产资源开发利用。E-mail：

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周瑜林（1983—），女，湖南岳阳人，博士，高级工程师，主要研究方向为铁及铁基共伴生矿产资源开发利用。E-mail：

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周瑜林（1983—），女，湖南岳阳人，博士，高级工程师，主要研究方向为铁及铁基共伴生矿产资源开发利用。E-mail：

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China Mining Magazine, 2015, 24(4): 130-133., articleTitle=Resources status and mineral processing of pyrochlore, refAbstract=null), Reference(id=1236348228719923536, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, doi=null, pmid=null, pmcid=null, year=2022, volume=42, issue=6, pageStart=50, pageEnd=56, url=null, language=null, rfNumber=[11], rfOrder=18, authorNames=许海峰, 周瑜林, 卢翔, journalName=矿冶工程, refType=null, unstructuredReference=许海峰, 周瑜林, 卢翔, 等. 铌矿浮选药剂研究进展[J]. 矿冶工程, 2022, 42(6): 50-56., articleTitle=铌矿浮选药剂研究进展, refAbstract=null), Reference(id=1236348228837364062, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, doi=null, pmid=null, pmcid=null, year=2022, volume=42, issue=6, pageStart=50, pageEnd=56, url=null, language=null, rfNumber=[11], rfOrder=19, authorNames=XU Haifeng, ZHOU Yulin, LU Xiang, journalName=Mining and Metallurgical Engineering, refType=null, unstructuredReference=XU Haifeng, ZHOU Yulin, LU Xiang, et al. Research progress of niobium ore flotation reagents[J]. Mining and Metallurgical Engineering, 2022, 42(6): 50-56., articleTitle=Research progress of niobium ore flotation reagents, refAbstract=null), Reference(id=1236348228988359012, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, doi=null, pmid=null, pmcid=null, year=2021, volume=null, issue=2, pageStart=120, pageEnd=126, url=null, language=null, rfNumber=[12], rfOrder=20, authorNames=黎洁, 谢贤, 吕晋芳, journalName=金属矿山, refType=null, unstructuredReference=黎洁, 谢贤, 吕晋芳, 等. 铌矿资源概述及选矿技术研究进展[J]. 金属矿山, 2021(2): 120-126., articleTitle=铌矿资源概述及选矿技术研究进展, refAbstract=null), Reference(id=1236348229118382448, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, doi=null, pmid=null, pmcid=null, year=2021, volume=null, issue=2, pageStart=120, pageEnd=126, url=null, language=null, rfNumber=[12], rfOrder=21, authorNames=LI Jie, XIE Xian, LYU Jinfang, journalName=Metal Mine, refType=null, unstructuredReference=LI Jie, XIE Xian, LYU Jinfang, et al. Overview of niobium resources and research progress in mineral processing technology[J]. 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tableContent=null), ArticleFig(id=1236348222407496466, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=EN, label=Fig.2, caption=Effect of grinding fineness on magnetic separation, figureFileSmall=5f2ozbRaJ9SnWt+iJ1DWPQ==, figureFileBig=rl5e+pHtyNrPPu5kIDXRew==, tableContent=null), ArticleFig(id=1236348222675931945, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=CN, label=图2, caption=磨矿细度对磁选效果的影响, figureFileSmall=5f2ozbRaJ9SnWt+iJ1DWPQ==, figureFileBig=rl5e+pHtyNrPPu5kIDXRew==, tableContent=null), ArticleFig(id=1236348222810149688, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=EN, label=Fig.3, caption=Effect of collector types on niobium flotation, figureFileSmall=6PDu6BPbzDECYk0TDaCiEQ==, figureFileBig=Ehdu3yrKedxNRoaJh8wPBA==, tableContent=null), ArticleFig(id=1236348222931784514, tenantId=1146029695717560320, 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Multi-elemental analysis results of sample

, figureFileSmall=null, figureFileBig=null, tableContent=
Nb2O5REOFeCaF2Sc2O51）TiO2SiO2
0.060.718.091.4435.40.2331.88
Al2O3CaOMgOMnOBaOSrONa2O
8.112.299.360.660.630.272.61
K2OPSCF烧失 
3.910.380.963.781.2412.79 
), ArticleFig(id=1236348224043275186, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=CN, label=表1, caption=

试样化学多元素分析结果（质量分数）

, figureFileSmall=null, figureFileBig=null, tableContent=
Nb2O5REOFeCaF2Sc2O51）TiO2SiO2
0.060.718.091.4435.40.2331.88
Al2O3CaOMgOMnOBaOSrONa2O
8.112.299.360.660.630.272.61
K2OPSCF烧失 
3.910.380.963.781.2412.79 
), ArticleFig(id=1236348224143938493, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=EN, label=Table 2, caption=

Mineral composition of sample

, figureFileSmall=null, figureFileBig=null, tableContent=
铌矿物独居石氟碳铈矿类褐帘石磁铁矿赤褐铁矿菱铁矿
0.100.280.240.801.360.860.76
萤石黄铁矿方解石白云石长石云母绿泥石
1.291.919.2625.1221.0526.753.14
辉石-闪石磷灰石石英重晶石硅灰石钛铁矿其他
3.001.731.110.180.380.130.55
), ArticleFig(id=1236348224248796109, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=CN, label=表2, caption=

试样矿物组成（质量分数）

, figureFileSmall=null, figureFileBig=null, tableContent=
铌矿物独居石氟碳铈矿类褐帘石磁铁矿赤褐铁矿菱铁矿
0.100.280.240.801.360.860.76
萤石黄铁矿方解石白云石长石云母绿泥石
1.291.919.2625.1221.0526.753.14
辉石-闪石磷灰石石英重晶石硅灰石钛铁矿其他
3.001.731.110.180.380.130.55
), ArticleFig(id=1236348224345265117, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=EN, label=Table 3, caption=

Contents of niobium minerals and distribution of Nb element in sample

, figureFileSmall=null, figureFileBig=null, tableContent=
矿物名称矿物含量（质量分数）/%Nb分布率/%
铌铁矿0.068 987.80
易解石0.010 37.03
烧绿石0.026 03.21
（含铌）金红石0.018 20.68
包头矿0.001 20.23
其他0.002 41.05
合计0.103 6100.00
), ArticleFig(id=1236348224479482860, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=CN, label=表3, caption=

试样中铌矿物含量及Nb元素分布

, figureFileSmall=null, figureFileBig=null, tableContent=
矿物名称矿物含量（质量分数）/%Nb分布率/%
铌铁矿0.068 987.80
易解石0.010 37.03
烧绿石0.026 03.21
（含铌）金红石0.018 20.68
包头矿0.001 20.23
其他0.002 41.05
合计0.103 6100.00
), ArticleFig(id=1236348224580146175, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=EN, label=Table 4, caption=

Mineral composition of HIMS concentrate

, figureFileSmall=null, figureFileBig=null, tableContent=
铌矿物稀土矿物方解石绿泥石菱铁矿辉石-闪石云母长石
0.691.882.946.445.634.8025.641.16
白云石磁/赤铁矿磷灰石钛铁矿赤褐铁矿（磁）黄铁矿萤石其他
38.712.150.352.130.866.170.470.39
), ArticleFig(id=1236348224726945806, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=CN, label=表4, caption=

强磁选精矿矿物组成（质量分数）

, figureFileSmall=null, figureFileBig=null, tableContent=
铌矿物稀土矿物方解石绿泥石菱铁矿辉石-闪石云母长石
0.691.882.946.445.634.8025.641.16
白云石磁/赤铁矿磷灰石钛铁矿赤褐铁矿（磁）黄铁矿萤石其他
38.712.150.352.130.866.170.470.39
), ArticleFig(id=1236348224840192025, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=EN, label=Table 5, caption=

Mineral composition of gravity-separation concentrate

, figureFileSmall=null, figureFileBig=null, tableContent=
铌矿物稀土矿物萤石辉石-闪石石英菱铁矿（磁）黄铁矿
3.297.890.0521.370.316.9021.77
磷灰石磁/赤铁矿长石白云石-方解石云母钛铁矿其他
1.110.180.3716.0516.083.303.12
), ArticleFig(id=1236348224974409770, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=CN, label=表5, caption=

重选精矿矿物组成（质量分数）

, figureFileSmall=null, figureFileBig=null, tableContent=
铌矿物稀土矿物萤石辉石-闪石石英菱铁矿（磁）黄铁矿
3.297.890.0521.370.316.9021.77
磷灰石磁/赤铁矿长石白云石-方解石云母钛铁矿其他
1.110.180.3716.0516.083.303.12
), ArticleFig(id=1236348225100238900, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=EN, label=Table 6, caption=

Desulfurization of gravity-separation concentrate by reverse flotation

, figureFileSmall=null, figureFileBig=null, tableContent=
产品名称作业产率/%品位/%作业回收率/%
Nb2O5SNb2O5S
硫精矿22.830.2845.234.2097.98
浮硫尾矿77.173.240.2895.802.02
给矿（重选精矿）100.002.6110.54100.00100.00
), ArticleFig(id=1236348225192513602, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=CN, label=表6, caption=

重选精矿反浮选脱硫试验结果

, figureFileSmall=null, figureFileBig=null, tableContent=
产品名称作业产率/%品位/%作业回收率/%
Nb2O5SNb2O5S
硫精矿22.830.2845.234.2097.98
浮硫尾矿77.173.240.2895.802.02
给矿（重选精矿）100.002.6110.54100.00100.00
), ArticleFig(id=1236348225284788301, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=EN, label=Table 7, caption=

Closed-circuit test results

, figureFileSmall=null, figureFileBig=null, tableContent=
产品名称产率/%Nb2O5品位/%Nb2O5回收率/%
铌精矿0.09622.37033.64
浮选尾矿3.4260.28915.51
硫精矿0.2710.5302.25
重选中矿3.8030.32019.07
重选尾矿8.6940.0354.77
强磁选尾矿82.6100.01722.00
弱磁选精矿1.1000.1602.76
合计100.0000.064100.00
), ArticleFig(id=1236348225398034521, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1236276110082756756, language=CN, label=表7, caption=

闭路试验结果

, figureFileSmall=null, figureFileBig=null, tableContent=
产品名称产率/%Nb2O5品位/%Nb2O5回收率/%
铌精矿0.09622.37033.64
浮选尾矿3.4260.28915.51
硫精矿0.2710.5302.25
重选中矿3.8030.32019.07
重选尾矿8.6940.0354.77
强磁选尾矿82.6100.01722.00
弱磁选精矿1.1000.1602.76
合计100.0000.064100.00
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低品位铌矿石超常富集选矿试验研究
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周瑜林
矿冶工程杂志 | 选矿 2025,45(4): 63-67
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矿冶工程杂志 | 选矿 2025, 45(4): 63-67
低品位铌矿石超常富集选矿试验研究
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周瑜林
作者信息
  • 长沙矿冶研究院有限责任公司，湖南　长沙　410012

    • 周瑜林（1983—），女，湖南岳阳人，博士，高级工程师，主要研究方向为铁及铁基共伴生矿产资源开发利用。E-mail：

Beneficiation Experiment of Low Grade Niobium Ore for Super Enrichment
Yulin ZHOU
Affiliations
  • Changsha Research Institute of Mining and Metallurgy Co Ltd, Changsha 410012, Hunan, China
出版时间: 2025-08-01 doi: 10.3969/j.issn.0253-6099.2025.04.011
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摘要
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对白云鄂博西矿区某低品位铌矿石进行了超常富集选矿试验研究，采用磁选-重选抛尾预富集，获得Nb2O5品位2.61%的铌粗精矿；铌粗精矿经浮选去除硫化矿后，采用捕收剂CYN-7和抑制剂CYD-2浮选回收铌矿物，达到铌矿物与脉石矿物的高效分离。结果表明，在给矿Nb2O5品位0.06%、磨矿细度－0.074 mm粒级占85%条件下，采用磁选-重选抛尾、反浮选脱硫、一粗三精正浮选选铌流程，最终可获得Nb2O5品位22.37%、Nb2O5回收率33.64%的铌精矿。

白云鄂博铌矿  /  铌铁矿  /  超常富集  /  浮选  /  铌  /  捕收剂  /  抑制剂

A beneficiation experiment for super enrichment was carried out with the low-grade niobium ore from western zone of Bayan Obo mine. In the experiment, a process of magnetic separation followed by gravity concentration for tailings discarding was firstly adopted for pre-concentration, and the obtained rougher concentrate grading 2.61% Nb2O5 was subjected to a reverse flotation for desulfuration, followed by a direct flotation with CYN-7 as a collector and CYD-2 as a depressant for recovering Nb minerals, resulting in efficient separation between Nb and other gangue minerals. It is found that the raw ore grading 0.06% Nb2O5, with a grinding fineness of－0.074 mm 85% is treated by magnetic separation and gravity concentration for tailings discarding, followed by a reverse flotation for desulfuration, and a direct flotation consisting of one stage of roughing and three stage of cleaning. As a result, a Nb concentrate grading 22.37% Nb2O5 at 33.64% recovery can be finally obtained.

Bayan Obo niobium ore  /  niobite  /  super enrichment  /  flotation  /  niobium  /  collector  /  depressant
周瑜林. 低品位铌矿石超常富集选矿试验研究. 矿冶工程杂志, 2025 , 45 (4) : 63 -67 . DOI: 10.3969/j.issn.0253-6099.2025.04.011
Yulin ZHOU. Beneficiation Experiment of Low Grade Niobium Ore for Super Enrichment[J]. Mining and Metallurgical Engineering, 2025 , 45 (4) : 63 -67 . DOI: 10.3969/j.issn.0253-6099.2025.04.011
正文
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铌具有熔点高、抗腐蚀性能强、低温下超导性能好等特点，广泛应用于高强度钢筋材料、高温合金材料、超导材料等，是现代工业和尖端技术中不可缺少的重要关键金属。美国地质调查局资料显示，1994—2022年世界铌产品总量总体保持增长趋势[1]。全球铌资源分布相对集中，巴西和加拿大的铌资源占世界铌资源总量的90%以上，也是世界主要铌生产国，2022年巴西铌产量占全球铌产量的91%（71 000 t），加拿大铌产量占8%[2]。
目前，全球主要经济体的铌供应都高度依赖进口，欧盟[3]、美国[4]和中国[5]都将铌列为重点保障的关键原材料、关键矿产。我国铌资源储量较为丰富，储量（以Nb2O5计）达到了927万t[6]，其中白云鄂博Fe-REE-Nb矿床是我国最大的铌储量基地，铌储量（以Nb2O5计）达到了660万t，约占全国铌储量的71%，但因铌品位低、铌矿物与其他矿物之间共生关系复杂，未能开发利用形成实际生产能力[7]。
推动白云鄂博铌矿资源的有效开发和利用，对解决我国铌资源开发“卡脖子”问题具有重要而深远的意义。本文对白云鄂博西矿区某低品位铌矿资源进行铌选矿研究，取得了突破性进展，试验指标先进。
1　矿石性质
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试验所用矿样来自白云鄂博西矿区低品位铌矿石，其化学多元素、矿物组成和铌矿物含量及Nb元素分布分析结果分别见表1～3。由表1～2可知，该矿中Nb2O5品位仅0.06%，长石、云母、绿泥石、辉石-闪石、石英等硅酸盐类脉石矿物含量达到55.05%，白云石、方解石等碳酸盐类脉石矿物含量34.38%，其次还有多种铁矿物和稀土矿物等，矿物组成十分复杂。由表3可知，该矿的铌元素主要分布于铌铁矿中，其次在易解石中，再次在烧绿石中，铌在三者中总分布率为98.04%。
2　试验原则流程及试验药剂
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试验矿样中脉石矿物种类多、含量大，主要包含硅酸盐矿物长石、云母、绿泥石、辉石-闪石以及碳酸盐矿物白云石、方解石等，高效预选脱除硅酸盐、碳酸盐脉石对提高铌矿分选效率具有重要作用。磁选是白云鄂博铌矿预选去除脉石较为常用且有效的方法[8]，试验矿样中主要铌矿物为弱磁性铌铁矿，采用强磁选可实现大量非磁性脉石矿物如长石、方解石、白云石等矿物的预抛尾；云母、绿泥石、辉石-闪石及白云石等具有一定弱磁性，易与铌铁矿一起进入强磁选精矿，但这些矿物密度相对较小，重选法是去除这部分脉石较好的方法；弱磁性黄铁矿密度较大，难以通过磁选-重选预选分离，可采用硫化矿浮选法有效去除黄铁矿。羟肟酸类捕收剂是铌矿物浮选的优良捕收剂[9]，在白云鄂博铌矿浮选研究中常表现出较好的选择性，可显著提高铌矿正浮选分选效率。综合考虑，确定低品位复杂铌矿选矿原则流程为：磁选-重选抛尾、反浮选脱硫、正浮选选铌。试验原则流程如图1所示。
试验所用抑制剂包括市购的工业品氟硅酸氨、腐殖酸钠、草酸以及自主研发的抑制剂CYD-2，捕收剂包括市购的LN-2（N-十二烷基-N，N-二甲基磷酸）、辛硫基羟肟酸以及自主研发的CYT-38A（C5～9烷基羟肟酸）和CYN-7（C6～12烷基羟肟酸）。
3　试验结果与讨论
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3.1　预选试验
试验矿样中含有少量磁铁矿，对弱磁选去除磁铁矿后的弱磁选尾矿再进行强磁选，可提高强磁选效率。在弱磁选磁场强度0.15 T、强磁选粗选磁场强度1.5 T条件下，考察了磨矿细度对磁选效果的影响，结果如图2所示。由图2可知，磨矿细度－0.074 mm粒级占65.0%～96.0%条件下，随着磨矿细度增加，强磁选精矿Nb2O5品位从0.23%提高到0.33%；但随着磨矿细度增加，强磁选精矿Nb2O5回收率先升后降，其主要原因是过磨产生大量极微细粒铌铁矿，难以使用磁选捕获回收，铌矿物损失较大。磨矿细度－0.074 mm粒级占86.80%条件下，经弱磁选-强磁选，可获得Nb2O5品位0.30%、回收率78.59%的强磁选精矿。
采用MLA对强磁选精矿进行矿物组成及含量分析，结果见表4。结果表明，强磁选精矿中主要脉石矿物为白云石和云母，其次为绿泥石、辉石-闪石、方解石，这些矿物密度均小于铌铁矿、易解石、烧绿石等铌矿物，可采用重选去除这些脉石矿物。
采用摇床重选法，对强磁选精矿进行分选，效果显著，可得到Nb2O5品位2.61%的铌粗精矿，重选尾矿Nb2O5品位为0.095%。
采用MLA对重选精矿进行矿物组成及含量分析，结果见表5。由表5可知，重选精矿中铌矿物含量达到3.29%，主要脉石矿物为辉石-闪石、云母，其次为白云石-方解石，尤为显著的是，重选精矿中（磁）黄铁矿含量较高，达到了21.77%，需要进行浮选去除。
经过调整硫化矿浮选药剂种类及用量，最终在丁基黄药200 g/t、Z-200用量50 g/t条件下进行硫化矿浮选，可获得Nb2O5品位3.24%、作业回收率95.80%的铌精矿，同时可产出S品位45.23%、Nb2O5品位0.28%的硫精矿。重选精矿反浮选脱硫试验结果见表6。
3.2　铌矿浮选试验
白云鄂博低品位铌矿石磁选-重选预选以及浮选脱硫后进入铌矿浮选，铌矿浮选给矿中主要脉石为硅酸盐和碳酸盐矿物，其次还有少量稀土矿和钛铁矿，为实现铌矿物的高效分选，进行了铌矿捕收剂和抑制剂种类和用量以及流程结构试验。
3.2.1　铌浮选捕收剂种类和用量试验
Araxa矿、Ctalao矿以及Niobec矿等铌矿山的浮选实践中均采用胺类捕收剂[10]，但据文献报道[11]，胺类捕收剂对烧绿石、铌铁矿等铌矿物与石英、钾长石、霓石-辉石、黑云母等硅酸盐矿物的浮选分离效果不理想。羟肟酸类、膦酸类和胂酸类捕收剂对铌有较强的选择性作用，在铌矿物与硅酸盐矿物浮选分离中表现优良，且相对膦酸类和胂酸类捕收剂，羟肟酸类捕收剂具有显著的环境友好性[12]。本研究选用羟肟酸类药剂作为铌矿浮选捕收剂。
抑制剂氟硅酸氨用量1500 g/t、捕收剂用量500 g/t，采用一次粗选的浮选流程，进行了捕收剂LN-2、辛硫基羟肟酸、CYT-38A、CYN-7的铌浮选对比试验，捕收剂种类对铌浮选效果的影响见图3。结果表明，CYT-38A一次粗选铌精矿Nb2O5品位超过了7.00%，但铌回收率相对较低；辛硫基羟肟酸、CYN-7对铌的浮选回收率高，均达到90%以上，但CYN-7相对辛硫基羟肟酸浮选铌精矿品位更高。确定以CYN-7为捕收剂进行铌矿浮选。
相同条件下，进行了捕收剂CYN-7用量试验，结果见图4。由图4可以看出，随着CYN-7用量增加，铌浮选粗精矿Nb2O5作业回收率显著增加，但CYN-7用量超过500 g/t后，再增加CYN-7用量，Nb2O5作业回收率变化较小，且铌精矿Nb2O5品位显著下降。适宜的CYN-7用量为500 g/t，此时浮选精矿Nb2O5品位达到6.00%，Nb2O5作业回收率为92.37%。
3.2.2　铌浮选抑制剂种类和用量试验
铌浮选给矿中含有辉石-闪石、云母、白云石、方解石、磷灰石等多种不同性质脉石矿物，为实现多种脉石的抑制，抑制剂种类的选择尤为重要。捕收剂CYN-7用量500 g/t，抑制剂用量1 500 g/t，对比了氟硅酸铵、腐殖酸钠、草酸和CYD-2等多种抑制剂对铌浮选效果的影响，结果见图5。从图5可以看出，腐殖酸钠在铌矿物浮选过程中具有较强的抑制作用，但选择性较差；氟硅酸铵、草酸和CYD-2在铌矿物浮选中均具有较好的选择性抑制作用，其中CYD-2选择性抑制效果更好。选择CYD-2作为本次铌浮选的脉石抑制剂。
相同条件下，进行了抑制剂CYD-2用量试验，结果见图6。由图6可以看出：随着CYD-2用量增加，铌浮选粗精矿回收率逐渐降低，Nb2O5品位显著增加；CYD-2用量超过2 500 g/t后，再增加CYD-2用量，浮选铌粗精矿Nb2O5品位和回收率均降低。适宜的抑制剂CYD-2用量为2 500 g/t，此时浮选精矿Nb2O5品位达到13.30%，Nb2O5作业回收率为85.98%。
3.3　闭路试验
在条件试验基础上，进行了预选-铌浮选闭路流程试验，结果见表7，试验流程见图7。试验工艺条件为：磨矿细度－0.074 mm粒级占85%，弱磁选磁场强度0.15 T，强磁选磁场强度1.5 T；硫化矿浮选粗选丁基黄药用量150 g/t、Z-200用量50 g/t，硫化矿浮选精选丁基黄药用量100 g/t、Z-200用量50 g/t；铌浮选粗选CYN-7用量500 g/t、CYD-2用量2 500 g/t，铌精选1、精选2、精选3、精选4 CYD-2用量分别为500、300、200、100 g/t。闭路试验可以获得Nb2O5品位22.37%、回收率33.64%的铌精矿。
4　结论
收起
1）白云鄂博西矿区白云岩型铌矿石Nb2O5品位0.06%，铌主要以铌铁矿形式存在，铌矿物嵌布粒度细，与其伴生矿物共生紧密。
2）采用磁选-重选可预先抛除产率超过90%的尾矿；磁选-重选抛尾、反浮选脱硫、正浮选选铌闭路试验可获得Nb2O5品位22.37%、回收率33.64%的铌精矿。
基金
收起
  • 国家自然科学基金(92062223)
  • 国家重点研发计划(2020YFC1909103)
文献
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2025年第45卷第4期
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doi: 10.3969/j.issn.0253-6099.2025.04.011
  • 接收时间：2025-02-16
  • 首发时间：2026-03-05
  • 出版时间：2025-08-01
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  • 收稿日期：2025-02-16
基金
国家自然科学基金(92062223)
国家重点研发计划(2020YFC1909103)
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    长沙矿冶研究院有限责任公司，湖南　长沙　410012
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2种不同金属材料的力学参数
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Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
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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