摘要
目的
废弃电路板中有色金属含量约为40%,是天然矿石的40倍以上,堪称名副其实的“城市矿山”。为了实现废弃电路板的高效绿色回收,开发高效浸出电路板中有色金属的浸出体系。
方法
利用嗜酸性氧化亚铁硫杆菌(Acidithiobacillus ferrooxidans) MA-Y1构建电路板的生物浸出体系,并通过引入电场进一步强化铜和镍的浸出效率。
结果
最佳浸出工艺参数为:电路板浓度80.0 g/L,电路板粒径4.0 cm,液体流速2.0 L/min,电流70.0 mA。在此条件下,铜和镍的浸出率分别为84.0%和75.3%,与无电场生物浸出体系相比,分别提高了15.8%和17.1%。
结论
外加电场显著提升了A. ferrooxidans MA-Y1回收电路板中铜和镍的能力。
关键词
2025, 65(5): 2157-2174
电子行业的蓬勃发展带来一个日益严峻的环境挑战:电路板(printed circuit boards, PCBs)正以每年近20%的速度被淘汰,成为全球增长最快的废弃物之一。中国作为主要的电子垃圾处理中心,处理了全球70%的废弃电路板。目前我国每年产生的废弃电路板已达约200万
近年来,为了提高生物浸出的效率,大量研究在微生物改造、介质调控以及外场强化等方面进行了探索与优化,为开发高效、环保的金属回收技术提供了重要的理论与实践支
本研究利用A. ferrooxidans MA-Y1构建了电路板的生物浸出体系,研究电路板回收过程中参数(包括电路板浓度、粒径、溶液流速及温度)对铜和镍浸出率的影响。同时,通过引入电场,深入分析电场作用机制及其对微生物浸出行为的强化效应,为废弃电路板的高附加值绿色回收技术提供了新思路。
1 材料与方法
1.1 电路板样品
本研究所用的电路板为大庆某电脑城维修店的废弃电脑电路板。浸出前先利用钢丝钳、铁锤等工具拆除电路板表面的电子元器件,然后用切割机将电路板剪切成约2.0 cm×2.0 cm、3.0 cm×3.0 cm、4.0 cm×4.0 cm大小的方块。
1.2 主要试剂和仪器
硫酸亚铁,天津市永大化学试剂有限公司;总铜、总镍检验试剂盒,杭州陆恒生物科技有限公司。
pH计,上海仪电科学仪器股份有限公司;高斯计,长沙天恒测控技术有限公司;电场发生器,东莞市迈豪电子科技有限公司;多参数水质检测仪,杭州陆恒生物科技有限公司。
1.3 菌株及培养条件
本研究所用的菌株为Acidithiobacillus ferrooxidans MA-Y1,该菌株分离自马鞍山火山灰样品,在中国典型培养物保藏中心(CCTCC)的保藏编号为M 20211183。该细菌在改良的9K液体培养基中进行纯培养,培养基由A液和B液2部分组成。A液:(NH4)2SO4 2.4 g,KCl 0.1 g,K2HPO4 0.5 g,MgSO4·7H2O 0.5 g,Ca(NO3)2 0.1 g,蒸馏水700 mL;B液:FeSO4·7H2O 40.0 g,蒸馏水300 mL。A液和B液均用H2SO4调节 pH至2.0。A液在121 ℃灭菌15 min,B液通过0.22 μm滤膜过滤除菌后与A液混合,以防止Fe(II)氧化。
1.4 初始电路板中铜和镍含量的测定
称取0.1 g电路板样品,置于10 mL王水(浓盐酸与浓硝酸按体积比3:1混合)中,混匀后置于80 ℃水浴锅中反应4 h。待其冷却后,测定反应液中铜和镍的含量。
1.5 火山石固定化A.ferrooxidans MA-Y1
采用实验室前期建立的磁场强化火山石固定化工艺对A. ferrooxidans MA-Y1进行固

图1 固定化装置(A)和生化两级反应器(B)
Figure 1 Immobilization device (A) and biochemical dual-chamber reactor (B).
1.6 不同因素对A. ferrooxidansMA-Y1浸出电路板中铜和镍的影响
火山石固定化完成后,使用9K培养基缓慢清洗火山石表面。随后,将清洗后的火山石转移至新的固定化装置中,继续培养至Fe(II)氧化率超过90.0%,以用作生物反应器。培养结束后,将生物反应器与化学反应器连接,形成生化两级反应器(
以铜和镍的浸出率为指标,探究电路板浓度、电路板粒径、反应器液体交换流速及反应器运行温度对浸出效果的影响。在反应结束后检测浸出液中铜和镍的浓度,并依据
(1) |
(2) |
式中:C0为初始浸出液中总铜(镍)的浓度(mg/L),Ct为反应结束后浸出液中总铜(镍)的浓度(mg/L)。
1.7 A.ferrooxidans MA-Y1浸出电路板中铜和镍的响应面优化
根据单因素试验结果,使用Design-Expert 13.0软件中的Box-Behnken程序进行响应面设计。以电路板浸出过程中影响最显著的3个因素作为自变量,金属浸出率作为响应值,进一步优化金属的浸出条件。响应面因素与编码见
Code | Factors | Levels | ||
---|---|---|---|---|
-1 | 0 | 1 | ||
A | c(PCBs)/(g/L) | 60.0 | 80.0 | 100.0 |
B | Particle size (cm) | 2.0 | 3.0 | 4.0 |
C | Liquid velocity (L/min) | 1.2 | 2.4 | 3.6 |
1.8 电流强度对铜和镍浸出的影响
在响应面优化得到的浸出条件下,在化学反应器中放置2个石墨电极,正、负电极分别位于反应器的上部和下部。通过电场发生器产生不同电流强度(0.0-150.0 mA)以刺激生物浸出。待反应结束后,记录浸出液中铜和镍的含量。
1.9 浸出过程中电路板表征观测
取经过0、3、5、7和9 d浸出的电路板,通过X射线光电子能谱(X-ray photo-electron spectroscopy, XPS)、傅里叶变换红外光谱(Fourier transform infrared spectroscopy, FTIR)、能量色散X射线谱(X-ray energy dispersive spectrometry, EDS)和扫描电子显微镜(scanning electron microscope, SEM)观察电路板的特性。
1.10 总铜和总镍的测定方法
使用总铜和总镍检验试剂
1.11 数据处理
数据的显著性分析通过SPSS 19.0完成,P<0.05为显著,P<0.01为极显著。响应面设计及分析通过Design-Expert 13.0完成。其余实验数据及图表制作通过Origin 8.0完成。
2 结果与分析
2.1 单因素对A. ferrooxidans MA-Y1浸出电路板中金属浸出的影响
如

图2 电路板浓度(A)、电路板粒径(B)、流速(C)和温度(D)对金属浸出率的影响
Figure 2 The effect of PCBs dosages (A), particle size (B), liquid velocity (C) and temperature (D) on metal bioleaching ratios. Distinct lowercase letters indicate statistically significant differences (P<0.05).
如

图3 电路板浓度(A)、电路板粒径(B)、流速(C)和温度(D)对金属浸出速率的影响
Figure 3 The effect of PCBs dosages(A), particle size (B), liquid velocity (C) and temperature (D) on metal bioleaching rates. Distinct lowercase letters indicate statistically significant differences (P<0.05).
2.2 电路板金属浸出响应面分析
基于响应面Box-Behnken设计,铜和镍的响应面实验结果见
Run | c(PCBs)/(g/L) | Particle size (cm) | Liquid velocity (L/min) | Cu bioleaching ratio (%) | Ni bioleaching ratio (%) |
---|---|---|---|---|---|
1 | 60.0 | 2.0 | 3.6 | 53.9 | 48.8 |
2 | 60.0 | 3.0 | 2.4 | 51.9 | 49.5 |
3 | 60.0 | 3.0 | 2.4 | 51.9 | 49.5 |
4 | 60.0 | 3.0 | 1.2 | 59.3 | 51.1 |
5 | 80.0 | 2.0 | 2.4 | 55.8 | 50.5 |
6 | 60.0 | 2.0 | 2.4 | 67.3 | 51.3 |
7 | 80.0 | 2.0 | 3.6 | 56.9 | 51.7 |
8 | 80.0 | 4.0 | 1.2 | 50.5 | 51.7 |
9 | 100.0 | 2.0 | 2.4 | 47.2 | 44.7 |
10 | 100.0 | 3.0 | 3.6 | 54.2 | 46.9 |
11 | 100.0 | 3.0 | 1.2 | 66.6 | 51.8 |
12 | 80.0 | 4.0 | 2.4 | 68.9 | 58.4 |
13 | 80.0 | 2.0 | 1.2 | 54.9 | 50.5 |
14 | 60.0 | 3.0 | 3.6 | 54.2 | 46.9 |
15 | 100.0 | 4.0 | 1.2 | 55.5 | 50.7 |
16 | 60.0 | 3.0 | 1.2 | 54.3 | 50.4 |
17 | 60.0 | 4.0 | 3.6 | 49.2 | 50.7 |
18 | 60.0 | 3.0 | 1.2 | 63.2 | 53.4 |
19 | 80.0 | 3.0 | 2.4 | 61.6 | 48.6 |
20 | 100.0 | 4.0 | 2.4 | 68.8 | 58.4 |
Source | Sum of squares | Degree of freedom | Mean square | F-value | P-value |
---|---|---|---|---|---|
Model | 0.067 5 | 9 | 0.007 5 | 4.84 | 0.010 8 |
A | 0.053 5 | 1 | 0.053 5 | 34.46 | 0.000 2 |
B | 0.000 4 | 1 | 0.000 4 | 0.26 | 0.623 0 |
C | 0.002 8 | 1 | 0.002 8 | 1.79 | 0.210 9 |
AB | 0.005 1 | 1 | 0.005 1 | 3.28 | 0.100 2 |
AC | 0.004 3 | 1 | 0.004 3 | 2.75 | 0.128 5 |
BC | 0.000 0 | 1 | 0.000 0 | 0.05 | 0.831 6 |
| 0.053 0 | 1 | 0.053 0 | 34.12 | 0.000 2 |
| 0.000 0 | 1 | 0.000 0 | 0.00 | 0.999 2 |
| 0.005 3 | 1 | 0.005 3 | 3.43 | 0.093 6 |
Residual | 0.015 5 | 10 | 0.001 6 | ||
Lack of fit | 0.012 9 | 5 | 0.002 6 | 4.87 | 0.053 6 |
Pure error | 0.002 6 | 5 | 0.000 5 | ||
Cor total | 0.083 1 | 19 |
Source | Sum of squares | Degree of freedom | Mean square | F-value | P-value |
---|---|---|---|---|---|
Model | 0.019 8 | 9 | 0.002 2 | 25.99 | <0.000 1 |
A | 0.007 5 | 1 | 0.007 5 | 88.51 | <0.000 1 |
B | 0.000 3 | 1 | 0.000 3 | 3.27 | 0.100 5 |
C | 0.000 2 | 1 | 0.000 2 | 1.91 | 0.197 5 |
AB | 0.002 4 | 1 | 0.002 4 | 28.38 | 0.000 3 |
AC | 0.000 3 | 1 | 0.000 3 | 3.26 | 0.101 4 |
BC | 0.000 1 | 1 | 0.000 1 | 0.65 | 0.439 7 |
| 0.009 3 | 1 | 0.009 3 | 110.42 | <0.000 1 |
| 0.001 0 | 1 | 0.001 0 | 12.22 | 0.005 8 |
| 0.000 6 | 1 | 0.000 6 | 7.53 | 0.020 7 |
Residual | 0.000 8 | 10 | 0.000 1 | ||
Lack of fit | 0.000 6 | 5 | 0.000 1 | 2.08 | 0.221 0 |
Pure error | 0.000 3 | 5 | 0.000 1 | ||
Cor total | 0.0206 | 19 |

图4 电路板浓度、电路板粒径、流速对铜浸出率影响的等高线图(A、C、E)和3D图(B、D、F)
Figure 4 Contour (A, C, E) and 3D diagrams (B, D, F) of the effects of PCBs dosages, particle size, and liquid velocity on Cu bioleaching ratio.

图5 电路板浓度、电路板粒径、流速对镍浸出率影响的等高线图(A、C、E)和3D图(B、D、F)
Figure 5 Contour (A, C, E) and 3D diagrams (B, D, F) of the effects of PCBs dosages, particle size, and liquid velocity on Ni bioleaching ratio.
2.3 电流强度对A. ferrooxidans MA-Y1浸出电路板中铜和镍的影响
电流强度对浸出性能的影响如

图6 电流强度对铜、镍浸出率(A)和浸出速率(B)的影响
Figure 6 Effect of electric current on bioleaching ratios (A) and rates (B) of Cu and Ni. Distinct lowercase letters indicate statistically significant differences (P<0.05).
2.4 电路板在浸出过程中的表征

图7 第0、3、5、7和9天电路板浸出后的FTIR光谱
Figure 7 FTIR spectra of PCBs after bioleaching for 0, 3, 5, 7, and 9 days.
SEM-EDS结果如

图8 不同时期电路板残渣的SEM-EDS分析
Figure 8 SEM-EDS analysis of residues from PCBs after bioleaching at different stages. A: 0 d; B: 3 d; C: 5 d; D: 7 d; E: 9 d.
通过XPS谱图分析了电路板残渣表面的化学组成。如

图9 不同浸出时期电路板Cu 2p (A)和Ni 2p (B)的XPS谱图
Figure 9 XPS spectra of Cu 2p (A) and Ni 2p (B) on PCBs before and after the bioleaching process.
3 讨论与结论
单因素实验结果显示(
通过对响应面数据(
在确定最佳生物浸出工艺条件后,本研究探讨了电场对铜和镍浸出效率的影响。在电流为70.0 mA时,铜的浸出率达到最高值;而在电流为110.0 mA时,镍的浸出率达到峰值。此外,与无电场条件相比,在70.0 mA电流时,铜和镍的生物浸出效率显著提高。这主要归因于电场能够加速铜和镍在阴极表面的沉积过程。该现象可通过电流作用下在正极[反应式(1)和反应式(2)]和负极[反应式(3)和反应式(4)]处发生的电催化反应进行解释。这些反应通过增强电子转移效率,显著促进了整体生物浸出过程[反应式(5)-反应式(7)]。
正极:
(1) |
(2) |
负极:
(3) |
(4) |
生物反应:
(5) |
(6) |
(7) |
A. ferrooxidans MA-Y1可以通过生物催化[反应式(5)]将Fe(II)氧化为Fe(III),或者利用正极[反应式(2)]还原反应产生的Fe(II)作为生长所需的能量。此外,A. ferrooxidans MA-Y1还能直接利用负极氧化反应产生的Fe(III),将铜和镍转化为C
本研究中,铜浸出率提升了15.8%,与其他研究方
Method | Pulp density (g/L) | Increasing ratio (%) | Bioleaching ratio (%) | Reference |
---|---|---|---|---|
Microbial fuel cells assisted | 100.0 | Cu (24.0) | Cu (79.7) |
[ |
Electrode modified with N-doped carbon nanotube | 20.0 | Cu (20.0) | Cu (99.0) |
[ |
Metal-tolerance strain | 10.0 | Cu (64.0), Ni (15.0) | Cu (94.0), Ni (45.0) |
[ |
Physical fragmentation | 100.0 | Cu (20.4), Ni (14.1) | Cu (94.3), Ni (90.7) |
[ |
The addition of lemon juice | 7.5 | Cu (5.0), Ni (12.0) | Cu (94.0), Ni (81.0) |
[ |
Electrochemically assisted | 80.0 | Cu (15.8), Ni (17.1) | Cu (84.0), Ni (75.3) | This study |
通过对生物浸出前后的电路板残渣进行FTIR、SEM-EDS和XPS分析,结果如图
通过SEM-EDS对电路板残渣进行了深入分析。如
XPS是分析样品表面成分不可或缺的技
本研究发现,外加电场可以显著强化生物浸出。在70.0 mA的电流时,铜和镍的浸出率分别为84.0%和75.3%,较未加电场分别提升了15.8%和17.1%。通过FTIR、SEM-EDS和XPS分析监测了浸出过程中电路板的形态、结构和组成的变化,结果表明电路板表面崩解并附着铜盐和镍盐。综上所述,外加电场显著提升了A. ferrooxidans MA-Y1回收电路板中的铜和镍的能力,为生物浸出在工业生产中的应用提供了新的技术支持。
作者贡献声明
王事成:实验设计、数据收集、建模、结果分析、论文撰写;杨健:实验材料准备、数据分析、图表制作、研究现状分析;张爽:理论指导、实验方案优化、结果解释、论文审阅;刘涛:软件模拟、数据可视化、项目协调、投稿准备;盛亚男:实验执行、数据验证;晏磊:统计分析、模型验证、论文修改。
利益冲突
公开作者声明不存在任何可能会影响本文所报告工作的已知经济利益或个人关系。声明
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