Adsorption of Enzyme for Sulfur Mustard Decontamination by Mesocellular Foam

doi:10.15541/jim20180061

Abstract

Abstract:

With polyoxyethylene-polyoxypropylene-polyoxyethylene (P123) as template, 1,3,5-trimethylbenzene (TMB) as swelling agent and tetramethoxysilane (TEOS) as silica source, mesocellular foam (MCF) with three dimensional (3D) cage-like mesopores linked by windows was successfully synthesized by hydrothermal method. N₂ isothermal adsorption characterization indicated that the largest pore size was 17.3 nm, and the other structural parameters as window size, specific surface area and pore volume were 8.2 nm, 770.3 m²/g, 2.3 cm³/g, respectively. MCF was employed as carrier for adsorption of DhaA which is an enzyme for sulfur mustard decontamination. The effect of pH to saturated adsorption capacity of DhaA in MCF was studied and the results showed that the largest loading amount of DhaA was achieved at pH 6.5. The adsorption kinetics followed Elovich kinetic model very well, and rate-determining step of this adsorption process was intraparticle diffusion. Adsorption isotherm curve of DhaA matched Sips model. The catalytic activity and conformation of DhaA changed obviously after being adsorbed in MCF. The residual activity of DhaA was 12.4% after being adsorbed, and the intrinsic fluorescence spectrum was found red shift. From the experimental results it can be observed that the big pore size, large specific surface area, and 3D cage-like structure of MCF facilitated the adsorption of DhaA, The electrostatic repulsion between DhaA and MCF influenced the adsorption process, and the conformation change of DhaA was the major factor of the decreased catalytic activity.

Key words: mesocellular foam, enzyme for sulfur mustard decontamination, adsorption, conformation

CLC Number:

TQ174

ZHENG He, ZHONG Jin-Yi, LIU Jing-Quan, ZHANG Zhe, CUI Yan, ZHENG Yong-Chao. Adsorption of Enzyme for Sulfur Mustard Decontamination by Mesocellular Foam[J]. Journal of Inorganic Materials, 2018, 33(11): 1201-1207.

Figures/Tables 10

References 30

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Sample	BET surface area/(m²•g^-1)	Pore size /nm	Window size/nm	Pore volume /(cm³•g^-1)
MCF0	858.2	6.8	6.6	1.2
MCF1	538.4	8.5	6.8	0.9
MCF2	544.3	11.0	6.0	1.1
MCF3	507.3	12.9	4.9	1.3
MCF4	606.7	16.6	7.7	1.8
MCF5	770.3	17.3	8.2	2.3
MCF6	779.5	14.1	8.4	2.1

Sample	BET surface area/(m²•g^-1)	Pore size /nm	Window size/nm	Pore volume /(cm³•g^-1)
MCF0	858.2	6.8	6.6	1.2
MCF1	538.4	8.5	6.8	0.9
MCF2	544.3	11.0	6.0	1.1
MCF3	507.3	12.9	4.9	1.3
MCF4	606.7	16.6	7.7	1.8
MCF5	770.3	17.3	8.2	2.3
MCF6	779.5	14.1	8.4	2.1

Kinetic model		Parameters
Pseudo- first-order	\(\ln ({{q}_{e}}-{{q}_{t}})=ln({{q}_{e}})-{{k}_{1}}t\)	q_e=79.58(mg•g^-1), k₁=0.25(min^-1), R²=0.9300, RMSE=7.38
Pseudo- second-order	\(\frac{t}{{{q}_{t}}}=\frac{1}{{{k}_{2}}q_{e}^{2}}+\frac{t}{{{q}_{e}}}\)	q_e=83.41(mg•g^-1), k₂=0.01(mg•g^-1•min^-1), R²=0.9773, RMSE=4.10
Elovich	\({{q}_{t}}=\frac{\ln (\alpha \beta )}{\beta }+\frac{\ln t}{\beta }\)	α=33.52(mg•g^-1•min^-1), β=9.99(mg•g^-1), R²=0.9860, RMSE=3.18

Kinetic model		Parameters
Pseudo- first-order	\(\ln ({{q}_{e}}-{{q}_{t}})=ln({{q}_{e}})-{{k}_{1}}t\)	q_e=79.58(mg•g^-1), k₁=0.25(min^-1), R²=0.9300, RMSE=7.38
Pseudo- second-order	\(\frac{t}{{{q}_{t}}}=\frac{1}{{{k}_{2}}q_{e}^{2}}+\frac{t}{{{q}_{e}}}\)	q_e=83.41(mg•g^-1), k₂=0.01(mg•g^-1•min^-1), R²=0.9773, RMSE=4.10
Elovich	\({{q}_{t}}=\frac{\ln (\alpha \beta )}{\beta }+\frac{\ln t}{\beta }\)	α=33.52(mg•g^-1•min^-1), β=9.99(mg•g^-1), R²=0.9860, RMSE=3.18

Isotherm model	Equation	Parameters
Langmuir	\({{q}_{e}}=\frac{{{q}_{\max }}\times {{C}_{e}}}{{{K}_{\text{l}}}+{{C}_{e}}}\)	q_max=91.49(mg•g^-1), K_l=0.01(mL•mg^-1), R²=0.9800, RMSE=4.68
Freundlich	\({{q}_{e}}={{K}_{\text{f}}}\times C_{e}^{1/n}\)	K_f=102.58(mg•g^-1), n=0.11, R²=0.9436, RMSE=10.94
Tempkin	\({{q}_{e}}\text{=}\frac{RT}{{{b}_{T}}}\times \ln ({{A}_{\text{T}}}\times {{C}_{e}})\)	A_T=175388.80 (mL•mg^-1), b_T=295.93 (J•mol^-1), R²=0.9119, RMSE=9.8
Sips	\({{q}_{e}}=\frac{{{K}_{\text{s}}}C_{e}^{{{\beta }_{s}}}}{1+{{\alpha }_{\text{s}}}\times C_{e}^{{{\beta }_{s}}}}\)	K_s=236338.20(mL•mg^-1), β_s=1.26, α_s=2612.06, R²=0.9844, RMSE=4.13
Redlich- Peterson	\({{q}_{e}}=\frac{{{K}_{\text{R}}}\times {{C}_{e}}}{1+{{\alpha }_{\text{R}}}\times C_{e}^{g}}\)	K_R=39323.82(mL•mg^-1), α_R=449.02(mg^-1), g=1.03, R²=0.9832, RMSE=4.28