|
|
|
|
|
|
| Theoretical Study on the Structures and IR Spectra of Hydration of Arsenates and Iron Arsenates |
| LI Hui-ji1, LI Yan-wen1, YU Wei-wei2, HUANG Ru-meng1, SUN Hai-jie1*, PENG Zhi-kun3* |
1. School of Chemistry and Chemical Engineering, Zhengzhou Normal University, Zhengzhou 450044, China
2. Huadian Zhengzhou Machinery Design and Research Institute Co., Ltd., Zhengzhou 450046, China
3. Henan Institutes of Advanced Technology, Zhengzhou University, Zhengzhou 450003, China
|
|
|
|
|
Abstract Arsenic pollution has aroused widespread concern worldwide, and the removal of arsenic has immediately become a problem to be solved. The toxicity of trivalent arsenic is far higher than that of pentavalent arsenic. Arsenic mainly exists in groundwater with trivalent arsenic. The removal of arsenic in water is closely related to its hydration characteristics. However, there are few studies on the hydration characteristics around different protonated arsenite [HmAsO3]m-3(m=2, 3), let alone the infrared spectral characteristics of [HmAsO3]m-3(m=2, 3) hydration layer. In this paper, the B3LYP/6-311G(d, p) method was used to optimize and calculate the hydration energy of [HmAsO3(H2O)12]m-3(m=3, 2). The type, location and intensity of interaction between water molecules and [HmAsO3]m-3(m=3, 2) species were analyzed by using a reduced density gradient function colorimetric isosurface. The IR characteristics of [HmAsO3(H2O)12]m-3(m=3, 2) hydrated clusters were analyzed in detail. The results show that HmAsO3 tends to be distributed on the surface of [HmAsO3(H2O)12]m-3(m=3, 2) hydrated clusters. H3AsO3 has a lower hydration capacity than H2AsO-3. Interestingly, the first hydration layer of H3AsO3 forms a deformed six-membered ring through a hydrogen bonds, with an average bond length of 1.79 Å. However, the first hydration layer of H2AsO-3 forms a deformed five-membered ring through hydrogen bond, and the average bond length of hydrogen bond is also 1.79 Å. In the infrared spectrum, the As—OP (proton-O) stretching vibration peaks of [H3AsO3(H2O)12]0 are 701 and 637 cm-1, which are consistent with the FTIR spectra, while the As—OP stretching vibration peaks of [H2AsO3(H2O)12]- are 573, 562 and 449 cm-1. The As—ON (unprotonated O) stretching vibration peak is 798 cm-1. In [H3AsO3(H2O)12]0, the independent OP—H stretching vibration peaks are 3 696 cm-1, and the OP—H stretching vibration peaks in OP—H…OW are 3 598 and 3 105 cm-1. The independent OP—H stretching vibration peak in [H2AsO3(H2O)12]- is 3 678 cm-1, and the OP—H…OW stretching vibration peak is 3 576 cm-1. The OW—HW characteristic stretching vibration peaks of OW—HW…OW in the six-membered ring composed of the first hydration layer of H3AsO3 are 3 233 and 2 911 cm-1, and the bending vibration peak is 1 606 cm-1. When the water in the first hydration layer forms a hydrogen bond with H or OP in H3AsO3, both OW—HW stretching vibration peak and bending vibration peak shift blue. The OW—HW characteristic stretching vibration peak of OW—HW…OW in the five-member ring composed of the first hydration layer is 3 383 cm-1, and the OW—HW bending vibration peaks are 1 680, 1 674, and 1 660 cm-1. When the water in the first hydration layer of H2AsO-3 forms HW—OW…H with H of H2AsO-3, the OW—HW stretching vibration peak shifts blue, and the bending vibration peak shifts red. When the water in the first hydration layer forms a hydrogen bond with OP or ON of H2AsO-3, the OW—HW stretching vibration peak shifts red and the bending vibration peak shifts blue. Compared with the infrared characteristics of the first hydration layer of H3AsO3, the OW—HW stretching and bending vibration peaks for the first hydration layer of H2AsO-3 have a blue shift.
|
|
Received: 2021-11-16
Accepted: 2022-06-22
|
|
|
|
Corresponding Authors:
SUN Hai-jie, PENG Zhi-kun
E-mail: sunhaijie406@163.com; pengzhikun@zzu.edu.cn
|
|
[1] Song Z Y, Li P H, Yang M, et al. Chemical Communications, 2021, 57(31): 3820.
[2] Zhang G, Zhang D, Yuan Z, et al. Environmental Science: Nano, 2019, 6(7): 2228.
[3] Wang Y, Lv C, Xiao L, et al. Environmental Technology, 2019, 40(13): 1714.
[4] Wu D, Zong Y, Tian Z, et al. Chemical Engineering Journal, 2019, 368: 980.
[5] Loehr T M, Plane R A. Inorganic Chemistry, 1968, 7(9): 1708.
[6] Cassone G, Chille D, Foti C, et al. Physical Chemistry Chemical Physics, 2018, 20(36): 23272.
[7] Canaval L R, Lutz O M, Weiss A K, et al. Inorganic Chemistry, 2014, 53(22): 11861.
[8] Canche-Tello J, Vargas M C, Hérnandez-Cobos J, et al. Journal of Physical Chemistry A, 2014, 118(46): 10967.
[9] Ramírez-Solís A, Amaro-Estrada J I, León-Pimentel C I, et al. Physical Chemistry Chemical Physics, 2018, 20(24): 16568.
[10] Tkachenko N V, Tkachenko A A, Kulyukin V A, et al. Journal of Physical Chemistry A, 2021, 125(40): 8899.
[11] LI Hui-ji, SUN Hai-jie, LIU Na, et al(李会吉, 孙海杰, 刘 娜, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2021, 41(7): 2071.
[12] Hunter K M, Shakib F A, Paesani F. Journal of Physical Chemistry B, 2018, 122(47): 10754.
|
| [1] |
CHENG Jia-wei1, 2，LIU Xin-xing1, 2*，ZHANG Juan1, 2. Application of Infrared Spectroscopy in Exploration of Mineral Deposits: A Review[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 15-21. |
| [2] |
LI Jie, ZHOU Qu*, JIA Lu-fen, CUI Xiao-sen. Comparative Study on Detection Methods of Furfural in Transformer Oil Based on IR and Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 125-133. |
| [3] |
GAO Feng1, 2, XING Ya-ge3, 4, LUO Hua-ping1, 2, ZHANG Yuan-hua3, 4, GUO Ling3, 4*. Nondestructive Identification of Apricot Varieties Based on Visible/Near Infrared Spectroscopy and Chemometrics Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 44-51. |
| [4] |
LIU Jia, ZHENG Ya-long, WANG Cheng-bo, YIN Zuo-wei*, PAN Shao-kui. Spectra Characterization of Diaspore-Sapphire From Hotan, Xinjiang[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 176-180. |
| [5] |
BAO Hao1, 2，ZHANG Yan1, 2*. Research on Spectral Feature Band Selection Model Based on Improved Harris Hawk Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 148-157. |
| [6] |
YANG Cheng-en1, 2, LI Meng3, LU Qiu-yu2, WANG Jin-ling4, LI Yu-ting2*, SU Ling1*. Fast Prediction of Flavone and Polysaccharide Contents in
Aronia Melanocarpa by FTIR and ELM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 62-68. |
| [7] |
GUO Ya-fei1, CAO Qiang1, YE Lei-lei1, ZHANG Cheng-yuan1, KOU Ren-bo1, WANG Jun-mei1, GUO Mei1, 2*. Double Index Sequence Analysis of FTIR and Anti-Inflammatory Spectrum Effect Relationship of Rheum Tanguticum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 188-196. |
| [8] |
LI Xiao-dian1, TANG Nian1, ZHANG Man-jun1, SUN Dong-wei1, HE Shu-kai2, WANG Xian-zhong2, 3, ZENG Xiao-zhe2*, WANG Xing-hui2, LIU Xi-ya2. Infrared Spectral Characteristics and Mixing Ratio Detection Method of a New Environmentally Friendly Insulating Gas C5-PFK[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3794-3801. |
| [9] |
HU Cai-ping1, HE Cheng-yu2, KONG Li-wei3, ZHU You-you3*, WU Bin4, ZHOU Hao-xiang3, SUN Jun2. Identification of Tea Based on Near-Infrared Spectra and Fuzzy Linear Discriminant QR Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3802-3805. |
| [10] |
LIU Xin-peng1, SUN Xiang-hong2, QIN Yu-hua1*, ZHANG Min1, GONG Hui-li3. Research on t-SNE Similarity Measurement Method Based on Wasserstein Divergence[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3806-3812. |
| [11] |
SUN Wei-ji1, LIU Lang1, 2*, HOU Dong-zhuang3, QIU Hua-fu1, 2, TU Bing-bing4, XIN Jie1. Experimental Study on Physicochemical Properties and Hydration Activity of Modified Magnesium Slag[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3877-3884. |
| [12] |
BAI Xue-bing1, 2, SONG Chang-ze1, ZHANG Qian-wei1, DAI Bin-xiu1, JIN Guo-jie1, 2, LIU Wen-zheng1, TAO Yong-sheng1, 2*. Rapid and Nndestructive Dagnosis Mthod for Posphate Dficiency in “Cabernet Sauvignon” Gape Laves by Vis/NIR Sectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3719-3725. |
| [13] |
WANG Qi-biao1, HE Yu-kai1, LUO Yu-shi1, WANG Shu-jun1, XIE Bo2, DENG Chao2*, LIU Yong3, TUO Xian-guo3. Study on Analysis Method of Distiller's Grains Acidity Based on
Convolutional Neural Network and Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3726-3731. |
| [14] |
DANG Rui, GAO Zi-ang, ZHANG Tong, WANG Jia-xing. Lighting Damage Model of Silk Cultural Relics in Museum Collections Based on Infrared Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3930-3936. |
| [15] |
LUO Li, WANG Jing-yi, XU Zhao-jun, NA Bin*. Geographic Origin Discrimination of Wood Using NIR Spectroscopy
Combined With Machine Learning Techniques[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3372-3379. |
|
|
|
|
