Theoretical Design and Adsorption Properties of Molecularly Imprinted Polymers Obtained from Chloramphenicol and Acrylamide

Junbo Liu , Wensi Zhao , Shanshan Tang , Ruifa Jin

Chemical Research in Chinese Universities ›› 2020, Vol. 36 ›› Issue (5) : 915 -920.

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Chemical Research in Chinese Universities ›› 2020, Vol. 36 ›› Issue (5) : 915 -920. DOI: 10.1007/s40242-019-9267-2
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Theoretical Design and Adsorption Properties of Molecularly Imprinted Polymers Obtained from Chloramphenicol and Acrylamide

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Abstract

Molecular simulations are widely used to model molecularly imprinted polymers(MIPs) in order to enhance their adsorption and selectivity. In this study, chloramphenicol(CAP) and acrylamide(AM) were used as the template and functional monomer, respectively, and pentaerythritol triacrylate(PETA), ethylene glycol dimethacrylate (EGDMA), and trimethylolpropane trimethylacrylate(TRIM) were used as cross-linking agents. The ωB97XD/6-31G(d,p) density functional theory method was employed to simulate binding sites, binding energy, the number of hydrogen bonds, the imprinted molar ratio, which produced the most stable complex, and the interaction mechanism. The cross-linking agent was optimized based on the binding energy. The atoms in molecules theory were used to study the nature of the imprinting effects. The theoretical calculations revealed that CAP and AM formed ordered complexes via hydrogen bonding interactions when the molar ratio between CAP and AM was 1:7 using TRIM as the cross-linking agent. The CAP-AM complex(molar ratio 1:7) had the most stable structure, the largest number of hydrogen bonds, and the smallest ΔE. The experimental results indicate that the CAP-MIPs formed perfect microspheres with an average particle size of 314 nm. Scatchard plot analysis showed that the CAP-MIPs had only one type of binding site over the studied concentration ranges. The dissociation equilibrium constant and maximum apparent adsorption capacities were 1887.35 mg/L(5.84 mmol/L) and 155.56 mg/g(0.482 mmol/g), respectively.

Keywords

Chloramphenicol / Acrylamide / Molecularly imprinted polymer / Computer simulation / Adsorption

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Junbo Liu, Wensi Zhao, Shanshan Tang, Ruifa Jin. Theoretical Design and Adsorption Properties of Molecularly Imprinted Polymers Obtained from Chloramphenicol and Acrylamide. Chemical Research in Chinese Universities, 2020, 36(5): 915-920 DOI:10.1007/s40242-019-9267-2

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References

[1]

Chen H X, Ying J, Chen H, Huang J L, Liao L. Chromatogr., 2008, 68: 629.

[2]

Yusof N A, Rahman S K A, Hussein M Z, Ibrahim N A. Polymers, 2013, 5: 1215.

[3]

Douny C, Widart J, Pauw E D, Maghuin-Rogister G, Scippo M L. Food Anal. Methods, 2013, 6: 1458.

[4]

Xu Z X, Gao H J, Zhang L M, Chen X Q, Qian X G. J. Food Sci., 2015, 76: R69.

[5]

Liang W X, Hu H W, Guo P R, Ma Y F, Li P Y, Zheng W R, Zhang M J. Sci. Food Agr., 2014, 94: 1409.

[6]

Cheong W J, Yang S H, Ali F D. J. Sep. Sci., 2013, 36: 60.

[7]

Zhang Y, Qian L, Yin W, He B, Liu F M, Hou C J, Huo D Q, Fa H B. Chem. Res. Chinese Universities, 201, 32(5): 725.

[8]

Huang Y X, Lian H T, Sun XY, Liu B. Chem. Res. Chinese Universities, 2011, 27(1): 28.

[9]

Wulff G, Liu J Q. Acc. Chem. Res., 2012, 45: 239.

[10]

Liang D D, Wang Y, Li SY, Li Y Q, Zhang M L, Li Y, Tian W S, Liu J B, Tang S S, Li B, Jin R F. Int. J. Mol. Sci., 201, 17: 1750.

[11]

Liu J B, Shi Y, Tang S S, Jin R F. Struc. Chem., 201, 7: 897.

[12]

Liu J B, Wang Y, Su T T, Li B, Tang S S, Jin R F. Struc. Chem., 201, 7: 1135.

[13]

Liu J B, Wang Y, Tang S S, Gao Q, Jin R F. New J. Chem., 2017, 41: 13370.

[14]

Turiel E, Martínesteban A. Comput. Theor. Chem., 2017, 1108: 76.

[15]

Yu H, Koide H, Urakami T, Kanazawa H, Kodama T, Oku N, Shea K J. Comput. Theor. Chem., 2017, 1117: 130.

[16]

Zhu R, Zhao W H, Zhai M J, Wei F D, Cai Z, Sheng N, Hu Q. Anal. Chim. Acta, 2010, 658: 209.

[17]

Wang Y D, Wang E L, Dong H, Liu F, Wu Z M, Li H, Wang Y. Adsorpt. Sci. Technol., 2014, 32: 321.

[18]

Chen H Y, Ding L, Liu M L. Chem. J. Chinese Universities, 2015, 36(1): 67.

[19]

Frisch M J, Trucks G W, Schlegel H B, Scuseria G E, Robb M A, Cheeseman J R, Scalmani G, Barone V, Mennucci B, Petersson G A, Nakatsuji H, Caricato M, Li X, Hratchian H P, Izmaylov A F, Bloino J, Zheng G, Sonnenberg J L, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa J, Ishida M, Nakajima T, Honda Y, Kitao O, Nakai H, Vreven T, Montgomery J A Jr., Peralta J E, Ogliaro F, Bearpark M, Heyd J J, Brothers E, Kudin K N, Staroverov V N, Kobayashi R, Normand J, Raghavachari K, Rendell A, Burant J C, Iyengar S S, Tomasi J, Cossi M, Rega N, Millam J M, Klene M, Knox J E, Cross J B, Bakken V, Adamo C, Jaramillo J, Gomperts R, Stratmann R E, Yazyev O, Austin A J, Cammi R, Pomelli C, Ochterski J W, Martin R L, Morokuma K, Zakrzewski V G, Voth G A, Salvador P, Dannenberg J J, Dapprich S, Daniels A D, Farkas Ö, Foresman J B, Ortiz J V, Cioslowski J, Fox D J. Gaussian 09(Revision A.02), 2009, Wallingford CT: Gaussian, Inc.

[20]

Liu J B, Wang G Y, Tang S S, Gao Q, Liang D D, Jin R F. J. Sep. Sci., 2019, 42: 769.

[21]

Achary K R, Gowda D S S, Post M. Mat. Sci. Eng. C: Mater., 2013, 33: 189.

[22]

Steiner T. Angew. Chem. Int. Ed., 2002, 41: 49.

[23]

Jeffrey G A. Crystallogr. Rev., 2003, 9: 135.

[24]

Steiner T. Crystallogr. Rev., 2003, 9: 177.

[25]

Lipkowski P, Grabowski S J, Robinson T L, Leszczynski J. J. Phys. Chem. A, 2004, 108: 10865.

[26]

Rozas I, Alkorta A I, Elguero J. J. Am. Chem. Soc., 2000, 122: 11154.

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