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响应面法优化钛白废酸还原浸出硫酸烧渣的条件研究

王青鸿 田从学 吴秀坤

王青鸿, 田从学, 吴秀坤. 响应面法优化钛白废酸还原浸出硫酸烧渣的条件研究[J]. 钢铁钒钛, 2024, 45(3): 107-113. doi: 10.7513/j.issn.1004-7638.2024.03.015
引用本文: 王青鸿, 田从学, 吴秀坤. 响应面法优化钛白废酸还原浸出硫酸烧渣的条件研究[J]. 钢铁钒钛, 2024, 45(3): 107-113. doi: 10.7513/j.issn.1004-7638.2024.03.015
Wang Qinghong, Tian Congxue, Wu Xiukun. Optimization of reduction leaching conditions for pyrite cinder using titanium dioxide waste acid by response surface methodology[J]. IRON STEEL VANADIUM TITANIUM, 2024, 45(3): 107-113. doi: 10.7513/j.issn.1004-7638.2024.03.015
Citation: Wang Qinghong, Tian Congxue, Wu Xiukun. Optimization of reduction leaching conditions for pyrite cinder using titanium dioxide waste acid by response surface methodology[J]. IRON STEEL VANADIUM TITANIUM, 2024, 45(3): 107-113. doi: 10.7513/j.issn.1004-7638.2024.03.015

响应面法优化钛白废酸还原浸出硫酸烧渣的条件研究

doi: 10.7513/j.issn.1004-7638.2024.03.015
基金项目: 攀西试验区第六批科技攻关项目(川财建 [2022] 390号 1-9);四川省科技成果转化示范项目(23ZHSF0237);四川省科技计划转移支付专项(22ZYZF-GG-02, 22ZYZF-GG-05);四川省科技服务业示范项目(2022KJFWYSF-1);四川省科技成果转移转化示范项目(24ZHSF0230)。
详细信息
    作者简介:

    王青鸿,2003年出生,男,四川达州人,大学本科,主要从事钛白废副的综合利用研究,E-mail:13158703883@163.com

    通讯作者:

    田从学,博士,教授,长期从事钛资源综合利用研发工作,E-mail:tcx7311@163.com

  • 中图分类号: X788,TF823

Optimization of reduction leaching conditions for pyrite cinder using titanium dioxide waste acid by response surface methodology

  • 摘要: 采用Box-Behnken设计的响应面法,选取铁粉用量、还原时间和浸出温度三个变量,研究并优化了钛白废酸还原浸出硫酸烧渣的浸出条件。建立了拟合效果较好的浸出条件的预测模型,以预测浸出率或优化浸出变量值。回归方程模型显著可靠,相关系数R2为0.9961。浸出条件对反应平衡、浸出物溶解度及反应体系性质等有重要影响,其中铁粉用量与浸出温度的协同交互作用影响最大。验证试验表明,在铁粉用量10.347 g、还原时间2 h、浸出温度88 ℃的最佳条件下,浸出率可达83.63%以上。
  • 图  1  浸出条件对浸出率的影响

    (a) 固定还原时间1.5 h,浸出温度89 ℃;(b) 固定还原铁粉用量12 g,浸出温度89 ℃;(c) 固定还原铁粉用量12 g,还原时间1.5 h

    Figure  1.  Effect of leaching conditions on leaching yield

    图  2  实际浸出率与预测值对比

    Figure  2.  Actual leaching yields vs. predicted values

    图  3  因素交互作用对浸出率影响的响应面3D图和等高线

    Figure  3.  Response surface plots and contour lines of interaction factors on the leaching yield

    图  4  烧渣还原浸出前后的XRD谱

    浸出还原条件:铁粉用量12 g,还原时间1.5 h,浸出温度89 ℃

    Figure  4.  XRD patterns for the pyrite cinder before and after reduction leaching

    图  5  烧渣还原浸取前的SEM和EDS面扫描

    Figure  5.  SEM images and EDS analysis for the raw pyrite cinder before reduction leaching

    图  6  烧渣还原浸取后的的SEM和EDS面扫描

    (浸出还原条件:铁粉用量12 g,还原时间1.5 h,浸出温度89 ℃)

    Figure  6.  SEM images and EDS analysis for the pyrite cinder after reduction leaching

    表  1  优化浸出条件的BBD试验因素和水平

    Table  1.   Factors and levels of BBD method for the optimized leaching conditions

    水平 因素
    还原铁粉用量/g
    (X1)
    还原时间 /h
    (X2)
    浸出温度/ ℃
    (X3)
    -1 10 1 86
    0 12 1.5 89
    1 14 2 92
    下载: 导出CSV

    表  2  烧渣浸出率的试验设计矩阵、试验结果及预测值

    Table  2.   Experimental design matrix, experimental leaching results and predicted values for pyrite cinder

    序号 X1/g X2/ h X3/ Y 试验值/% Y 预测值/%
    1 14 1.0 89 83.22 83.23
    2 12 1.5 89 84.01 83.96
    3 12 1.0 92 82.63 82.57
    4 10 1.5 86 82.69 82.64
    5 10 1.0 89 82.41 82.40
    6 14 1.5 86 82.41 82.34
    7 12 2.0 86 82.53 82.59
    8 12 1.5 89 83.89 83.96
    9 10 2.0 89 83.77 83.76
    10 12 1.0 86 81.15 81.21
    11 14 1.5 92 84.09 84.14
    12 14 2.0 89 83.91 83.92
    13 10 1.5 92 82.78 82.85
    14 12 1.5 89 83.97 83.96
    15 12 2.0 92 83.31 83.25
    下载: 导出CSV

    表  3  硫铁矿烧渣浸出率的响应面试验结果方差分析

    Table  3.   Variance analysis of response surface experimental results of the leaching yield

    平方和自由度(df )均方FP显著
    模型9.8891.1143.35< 0.0001**
    X10.4910.4963.990.0005**
    X22.1112.11275.71< 0.0001**
    X32.0312.03265.09< 0.0001**
    X1 X20.112210.112214.650.0123*
    X1 X30.63210.63282.530.0003**
    X2 X30.122510.1225160.0103*
    X1 ²0.001610.00160.20930.6665
    X2²1.3711.37178.42< 0.0001**
    X3 ²3.2913.29429.04< 0.0001**
    残差0.038350.0077
    失拟合0.030830.01032.750.2777
    纯误差0.007520.0037
    总计9.9214
    注:R²=0.9961, R 2 Adj =0.9892, R 2 Predj =0.9486。C.V= 0.1053%。
    *表示对结果有显著的影响(P < 0.05);**表示对结果有非常显著的影响(P < 0.01)。
    下载: 导出CSV

    表  4  验证测试结果

    Table  4.   Verification test results

    编号铁粉加量/g还原时间/h浸出温度/ ℃浸出率/%
    预测优化值10.347287.9883.673
    1610.34728883.64
    1710.34728883.66
    1810.34728883.63
    下载: 导出CSV
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  • 收稿日期:  2024-01-17
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