Monte Carlo simulation of effect of MoO3 doping on Cu(Ⅱ) adsorption of silica

doi:10.11949/j.issn.0438-1157.20180968

CIESC Journal ›› 2019, Vol. 70 ›› Issue (1): 355-359.DOI: 10.11949/j.issn.0438-1157.20180968

• Material science and engineering, nanotechnology • Previous Articles Next Articles

Monte Carlo simulation of effect of MoO₃ doping on Cu(Ⅱ) adsorption of silica

Jiao WANG¹(),Zhejunyu JIN¹,Kaining DING³,Weiwei ZHAO¹,Xiaohua PU¹,Zongxiao LI^1,²()

1. College of Chemistry and Chemical Engineering, Baoji University of Arts and Sciences, Baoji 721013, Shaanxi, China
2. Xi an Traffic Engineering Institute, Xi an 710300, Shaanxi, China
3. Department of Chemistry, Research Institute of Photocatalysis, State Key Laboratory of Photocatalysis on Energy and Environment, Fuzhou University, Fuzhou 350116, Fujian, China

Received:2018-08-30 Revised:2018-10-08 Online:2019-01-05 Published:2019-01-05
Contact: Zongxiao LI

MoO₃掺杂对二氧化硅吸附Cu(Ⅱ)影响的Monte Carlo模拟

王姣¹(),金哲珺雨¹,丁开宁³,赵微微¹,蒲小华¹,李宗孝^1,²()

1. 宝鸡文理学院化学化工学院，陕西宝鸡 721013
2. 西安交通工程学院，陕西西安 710300
3. 福州大学光化学研究所化学系，能源与环境光催化国家重点实验室，福建福州 350116

通讯作者: 李宗孝
作者简介:王姣（1992—），女，硕士研究生，<email>18791869412@163.com</email>|李宗孝（1954—），男，教授，<email>mingtian8001@163.com</email>
基金资助:
国家自然科学基金青年基金项目(51702006);陕西省植物化学重点实验室项目(17JS009);陕西省科技计划项目(2018JQ2056);陕西省高校科协青年人才托举计划项目(20170707);宝鸡文理学院博士科研启动项目(ZK2017026);国家自然科学基金青年基金项目（51702006）；陕西省植物化学重点实验室项目（17JS009）；陕西省科技计划项目（2018JQ2056）；陕西省高校科协青年人才托举计划项目（20170707）；宝鸡文理学院博士科研启动项目（ZK2017026）

Abstract

Abstract:

The adsorption behavior of Cu(Ⅱ) on silica and molybdenum doped silica was simulated by Monte Carlo method. The results show that Cu(Ⅱ) is adsorbed on the surface of the nanomaterial and the interatomic space. It is found that adding a small amount of molybdenum oxide to silica does not significantly change the adsorption capacity of Cu(Ⅱ). At the same time, the generalized gradient approximation (GGA) density functional theory (DFT) was used to verify the process, and the adsorption behavior of Cu(Ⅱ) in water by silica and molybdenum doped silica was verified by microcalorimetry. It was found that the adsorption process had ΔH<0, ΔS<0, van der Waals force as the adsorption driving force, and the molecular simulation was consistent with the experimental results.

Key words: Monte Carlo simulation, Density Function theory, adsorption, Cu(Ⅱ), microcalorimetry

摘要：

利用Monte Carlo方法，分别模拟二氧化硅和钼掺杂二氧化硅对Cu(Ⅱ)的吸附行为。结果表明，Cu(Ⅱ)被吸附于该纳米材料的表面和原子间隙之中；模拟发现加入少量氧化钼于二氧化硅中不会显著改变对Cu(Ⅱ)的吸附能力。同时采用广义梯度近似(GGA)的密度泛函理论(DFT)对其过程进行验证，并通过微量热技术佐证了二氧化硅及钼掺杂二氧化硅对水中Cu(Ⅱ)的吸附行为，实验发现，吸附过程的ΔH<0，ΔS<0，范德华力为吸附驱动力，分子模拟与实验结果相吻合。

关键词: Monte Carlo模拟, 密度泛函理论, 吸附, Cu(Ⅱ), 微量热技术

CLC Number:

O 642.4

Jiao WANG, Zhejunyu JIN, Kaining DING, Weiwei ZHAO, Xiaohua PU, Zongxiao LI. Monte Carlo simulation of effect of MoO₃ doping on Cu(Ⅱ) adsorption of silica[J]. CIESC Journal, 2019, 70(1): 355-359.

王姣, 金哲珺雨, 丁开宁, 赵微微, 蒲小华, 李宗孝. MoO₃掺杂对二氧化硅吸附Cu(Ⅱ)影响的Monte Carlo模拟[J]. 化工学报, 2019, 70(1): 355-359.

Figures/Tables 5

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C/(mol/L)	n/mol	?Q/mJ	ΔH/(kJ/mol)	ΔS/((J·mol)/K)
2.14×10^?3	0.32×10^?7	141.08	?44.09	?108.76
4.05×10^?3	0.61×10^?7	312.12	?48.77	?107.52
6.35×10^?3	0.95×10^?7	446.72	?44.23	?107.02
8.11×10^?3	1.22×10^?7	580.83	?47.61	?110.09
10.25×10^?3	1.39×10^?7	898.14	?64.61	?99.37
12.12×10^?3	1.54×10^?7	1281.13	-84.31	-101.78
14.41×10^-3	2.16×10^-7	1014.13	-54.23	-110.93

C/(mol/L)	n/mol	?Q/mJ	ΔH/(kJ/mol)	ΔS/((J·mol)/K)
2.14×10^?3	0.32×10^?7	141.08	?44.09	?108.76
4.05×10^?3	0.61×10^?7	312.12	?48.77	?107.52
6.35×10^?3	0.95×10^?7	446.72	?44.23	?107.02
8.11×10^?3	1.22×10^?7	580.83	?47.61	?110.09
10.25×10^?3	1.39×10^?7	898.14	?64.61	?99.37
12.12×10^?3	1.54×10^?7	1281.13	-84.31	-101.78
14.41×10^-3	2.16×10^-7	1014.13	-54.23	-110.93

C/(mol/L)	n/mol	-Q /mJ	ΔH/(kJ/mol)	ΔS/(J·mol/K)
2.06×10^-3	0.31×10^-7	77.16	-24.89	-102.03
4.12×10^-3	0.62×10^-7	169.87	?27.37	?104.44
6.03×10^?3	0.91×10^?7	269.64	?29.63	?102.86
8.14×10^?3	1.22×10^?7	379.82	?31.13	?101.12
10.08×10^?3	1.51×10^?7	686.14	?45.44	?110.01
12.03×10^?3	1.81×10^?7	761.87	?42.09	?111.67
14.11×10^?3	2.12×10^?7	736.99	?34.76	?121.32

C/(mol/L)	n/mol	-Q /mJ	ΔH/(kJ/mol)	ΔS/(J·mol/K)
2.06×10^-3	0.31×10^-7	77.16	-24.89	-102.03
4.12×10^-3	0.62×10^-7	169.87	?27.37	?104.44
6.03×10^?3	0.91×10^?7	269.64	?29.63	?102.86
8.14×10^?3	1.22×10^?7	379.82	?31.13	?101.12
10.08×10^?3	1.51×10^?7	686.14	?45.44	?110.01
12.03×10^?3	1.81×10^?7	761.87	?42.09	?111.67
14.11×10^?3	2.12×10^?7	736.99	?34.76	?121.32