-
Amorphous alloys are meta-stable materials with long-range disordered atomic structure, which have excellent catalytic degradation performance and are also susceptible to crystallization, but the mechanism of the effect of crystallization on their catalytic properties has not been clarified. Therefore, the effect of the annealing crystallization process on the microstructure of Fe-Si-B-Cu-Nb industrial amorphous ribbons and their catalytic degradation properties for acid orange 7 are investigated in this work. It is found that the catalytic degradation performance of the ribbons decreases dramatically after having been annealed at 460–580 ℃ , and its reaction rate constant is less than 0.01 min–1. The main reason is the formation of ɑ-Fe precipitation phase in the ribbons after having been annealed at high temperatures and the destruction of the substable amorphous structure. These reduce the rate of hydroxyl radical formation. In contrast, the catalytic degradation performance of the 650–700 ℃ annealed ribbons increases significantly, which increases to 3.77 times the degradation rate of the as-cast ribbons. The decolorization rate of acid orange 7 by the annealed ribbons reaches 99.22% within 15 min, which is 1.12 times that of the as-cast ribbons. The improvement of the catalytic degradation performance is attributed to the primary cell effect between the crystalline phase and the metal compounds and the substitution reaction between the Cu-enriched clusters and zero-valent iron. In this study, the influence mechanism of annealing crystallization on the performance of Fe-Si-B-Cu-Nb industrial amorphous ribbons for degrading azo dyes is revealed, which provides theoretical and experimental support for using aged iron-based amorphous ribbons to purify printing and dyeing waste-water and achieve “purification of waste-water by using alloy waste”.
-
Keywords:
- Fe-based amorphous ribbons /
- industrial ribbons /
- annealed crystallization /
- catalytic degradation
-
图 1 Fe-Si-B-Cu-Nb工业条带的(a) XRD和(b) DSC图谱
Figure 1. (a) XRD spectrum and (b) DSC spectrum of Fe-Si-B-Cu-Nb industrial ribbon.
图 2 Fe-Si-B-Cu-Nb工业条带不同温度退火后的XRD图谱
Figure 2. XRD patterns of Fe-Si-B-Cu-Nb industrial ribbons after annealing at different temperatures.
图 3 工业非晶条带及其经不同温度退火20 min后降解酸性橙7的紫外光谱图 (a) 工业非晶条带; (b) 460℃; (c) 520 ℃; (d) 580 ℃; (e) 650 ℃; (f)700 ℃
Figure 3. UV spectra of industrial amorphous ribbons and their degraded acid orange 7 after annealing at different temperatures for 20 min: (a) Industrial amorphous ribbon; (b) 460℃; (c) 520 ℃; (d) 580 ℃; (e) 650 ℃; (f) 700 ℃.
图 4 Fe-Si-B-Cu-Nb工业非晶条带及其经不同温度退火后对酸性橙7的降解 (a) Ct/C0归一曲线; (b)染料脱色率; (c) －ln函数; (d)反应速率常数柱状图
Figure 4. Degradation of acid orange II processed by Fe-Si-B-Cu-Nb industrial amorphous ribbons in the as-cast state and after different annealing temperatures: (a) Ct/C0 normalized graph; (b) dye decolorization rate graph; (c) variation of the －ln function graph; (d) histogram of reaction rate constants.
图 5 不同温度退火条带降解酸性橙7后的表面SEM图 (a)—(d)未退火; (e)—(h)580 ℃退火; (i)—(l) 700 ℃退火
Figure 5. SEM images of the alloy surface after degrading the acid orange II: (a)–(d) As-cast alloys without annealing; (e)–(h) after annealing at 580 °C; (i)–(l) after annealing at 700 °C.
图 6 700 ℃退火20 min后条带表面 (a) SEM图像及对应的(b) Cu, (c) O, (d) C, (e) Fe和(f) Si元素分布图像
Figure 6. SEM images of Fe-Si-B-Cu-Nb alloy after annealing at 700 ℃ for 20 min (a); the corresponding elemental distribution maps of (b) Cu, (c) O, (d) C, (e) Fe, and (f) Si.
表 1 用于偶氮染料催化降解的典型非晶合金比较
Table 1. Comparison of typical amorphous alloys for catalytic degradation of azo dyes.
合金成分 样品
状态染料种类 反应速率常数(kobs) 循环次数 参考
文献Fe83Si5B8P4 条带 亚甲基蓝 0.514 — [13] (Fe78Si9B13)99Zr1 条带 亚甲基蓝 0.24 — [14] Fe84B16 条带 直接蓝6 0.110 — [16] Fe78Si9B13 条带 甲基蓝 0.085 — [17] Fe78Si11B9P2 条带 酸性橙7 0.082 17 [20] Fe80P13C7 条带 亚甲基蓝 0.56 23 [21] Cu46Zr44.5Al7.5Gd2 条带 酸性橙7 0.48 80 [28] Mg65Cu25Y10 粉末 直接蓝6 0.585 — [29] Co65Mo15B20 非晶丝 直接蓝6 2.31 20 [30] Cu47.5Zr46Al6.5 条带 酸性橙7 0.165 10 [31] Co78Si8B14 粉末 酸性橙7 — 8 [32] FeSiBCuNb 条带 酸性橙7 0.094 50 本工作 FeSiBCuNb (700℃退火后) 条带 酸性橙7 0.36 — 本工作 
DownLoad: CSV
表 2 α-Fe晶粒尺寸计算结果
Table 2. Calculation results of α-Fe grain size.
温度/℃ 460 520 580 650 700 βhkl/(°) 0.80 0.71 0.66 0.27 0.21 Dhkl/nm 11.54 12.68 13.72 33.74 42.52 (hkl) (220) (220) (220) (220) (220)
DownLoad: CSV
-
[1] 杨卫明, 刘海顺, 敦超超, 赵玉成, 窦林名 2012 物理学报 61 106802
Yang W M, Liu H S, Dun C C, Zhao Y C, Dou L M 2012 Acta Phys. Sin. 61 106802
[2] 柳延辉 2017 物理学报 66 176106
Google Scholar
Liu Y H 2017 Acta Phys. Sin. 66 176106
Google Scholar
[3] 柯海波, 蒲朕, 张培, 张鹏国, 徐宏扬, 黄火根, 刘天伟, 王英敏 2017 物理学报 66 176104
Google Scholar
Ke H B, Pu Z, Zhang P, Zhang P G, Xu H Y, Huang H G, Liu T W, Wang Y M, 2017 Acta Phys. Sin. 66 176104
Google Scholar
[4] Lai L M, Liu T H, Cai X H, Wang M, Zhang S B, Chen W, Guo S F 2021 Scripta Mater 203 114095
Google Scholar
[5] 孙奕韬, 王超, 吕玉苗, 胡远超, 罗鹏, 刘明, 咸海杰, 赵德乾, 丁大伟, 孙保安, 潘明祥, 闻平, 白海洋, 柳延辉, 汪卫华 2018 物理学报 67 126101
Google Scholar
Sun Y T, Wang C, Lu Y M, Hu Y C, Luo P, Liu M, Xian H J, Zhao D Q, Ding D W, Sun B A, Pan M X, Wen P, Bai H Y, Liu Y H, Wang W H 2018 Acta Phys. Sin. 67 126101
Google Scholar
[6] 姚可夫, 施凌翔, 陈双琴, 邵洋, 陈娜, 贾蓟丽 2018 物理学报 67 016101
Google Scholar
Yao K F, Shi L X, Chen S Q, Shao Y, Chen N, Jia J L 2018 Acta Phys. Sin. 67 016101
Google Scholar
[7] Ge Y, Cheng J, Mo J, Xue L, Zhang B, Hong S, Wu Y, Liang X, Zhang X 2024 J. Alloy Compd. 976 173173
Google Scholar
[8] Liu H, Jiang Y, Yang D, Jiang Q, Yang W 2023 J. Mat. Res. Technol. 26 3070
Google Scholar
[9] Li X, Wang J G, Ke H B, Yang C, Wang W H 2022 Mater. Today Phys. 27 100782
Google Scholar
[10] 邵梓桥, 毕恒昌, 谢骁, 万能, 孙立涛 2018 物理学报 67 167802
Google Scholar
Shao Z Q, Bi H C, Xie R, Wan N, Sun L T 2018 Acta Phys. Sin. 67 167802
Google Scholar
[11] Qiao J C, Wang Q, Pelletier J M, Kato H, Casalini R, Crespo D, Pineda E, Yao Y, Yang Y 2019 Prog. Mater. Sci. 104 250
Google Scholar
[12] Liang S X, Jia Z, Zhang W C, Li X F, Wang W M, Lin H C, Zhang L C 2018 Appl. Catal. B-Environ. 221 108
Google Scholar
[13] Zuo M Q, Yi S H, Choi J 2021 J. Environ. Sci. 105 116
Google Scholar
[14] Miao F, Wang Q Q, Di S Y, Yun L, Zhou J, Shen B L 2020 Jmst 53 163
[15] Chen Q, Yan Z C, Zhang H, Zhang L C, Ma H J, Wang W L, Wang W M 2020 Materials 13 3694
Google Scholar
[16] Tang Y, Shao Y, Chen N, Yao K F 2015 Rsc Adv. 5 6215
Google Scholar
[17] Jia Z, Duan X G, Qin P, Zhang W C, Wang W M, Yang C, Sun H Q, Wang S B, Zhang L C 2017 Adv. Funct. Mat. 27 1702258
Google Scholar
[18] Liang S X, Wang X Q, Zhang W C, Liu Y J, Wang W M, Zhang L C 2020 Appl. Mat. Today 19 100543
Google Scholar
[19] Wang X Q, Zhang Q Y, Liang S X, Jia Z, Zhang W C, Wang W M, Zhang L C 2020 Catalysts 10 48
Google Scholar
[20] Ji L, Chen J W, Zheng Z G, Qiu Z G, Peng S Y, Zhou S H, Zeng D C 2020 J. Phys. Chem. Solids 145 109546
Google Scholar
[21] Wang Q Q, Chen M X, Lin P H, Cui Z Q, Chu C L, Shen B L 2018 J. Mat. Chem. A 6 10686
Google Scholar
[22] Hou L, Wang Q Q, Fan X D, Miao F, Yang W M, Shen B L 2019 New J. Chem. 43 6126
Google Scholar
[23] Chen S Q, Li M, Ji Q M, Chen X, Lan S, Feng T, Yao K F 2021 J. Non-Cryst. Solids 571 121070
Google Scholar
[24] Tan L, Wang X Y, Wang S K, Qin X R, Xiao L F, Li C L, Sun S Q, Hu S Q 2023 New J. Chem. 47 11723
Google Scholar
[25] Wei J, Zheng Z G, Zhao L, Qiu Z G, Zeng D C 2023 Colloid Surface A 666 131227
Google Scholar
[26] Lassoued A, Li J F 2023 J. Phys. Chem. Solids 180 111475
Google Scholar
[27] Yang W M, Wang Q Q, Li W Y, Xue L, Liu H S, Zhou J, Mo J Y, Shen B L 2019 Mat. Design 161 136
Google Scholar
[28] Zheng K L, Qin X D, Zhu Z W, Zheng S J, Li H L, Fu H M, Zhang H F 2020 J. Mat. Chem. A 8 10855
Google Scholar
[29] Luo X K, Li R, Zong J Y, Zhang Y, Li H F, Zhang T 2014 Appl. Surf. Sci. 305 314
Google Scholar
[30] Tang M F, Lai L M, Ding D Y, Liu T H, Kang W Z, Guo N, Song B, Guo S F 2022 J. Non-Cryst. Solids 576 121282
Google Scholar
[31] Zhao B W, Zhu Z W, Qin X D, Li Z K, Zhang H F 2020 J. Mat. Sci. Technol. 46 88
Google Scholar
[32] Qin X D, Zhu Z W, Liu G, Fu H. M, Zhang H W, Wang A M, Li H, Zhang H F, 2015 Sci. Rep. 5 18226
Google Scholar
[33] Xie S H, Huang P, Kruzic J J, Zeng X, Qian H 2016 Sci. Rep. 6 21947
Google Scholar
[34] Jia Z, Duan X G, Qin P, Zhang W C, Wang W C, Yang C, Sun H Q, Wang S B, Zhang L C 2017 Adv. Funct. Mat. 27 1702258
Google Scholar
[35] 陈双琴 2018博士学位论文(北京: 清华大学)
Chen S Q 2018 Ph. D Dissertation (Beijing: Tsinghua University
[36] Xie S H, Xie Y L, Jamie J, Gu K M, Yang H P, Deng Y M, Zeng X R 2020 Chemcatchem 12 750
Google Scholar
DownLoad:
Metrics
- Abstract views: 811
- PDF Downloads: 19
- Cited By: 0
