The Extension of Monomeric Computational Results to Polymeric Measurable Properties: An Introductory Computational Chemistry Experiment
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The Extension of Monomeric Computational Results to Polymeric Measurable Properties: An Introductory Computational Chemistry Experiment

Authors: Zhao Jing, Bai Yongqing, Shi Qiaofang, Zang Yang, Zhang Huaihao

Abstract:

Advances in software technology enable the computational chemistry to be commonly applied in various research fields, especially in pedagogy. Thus, in order to expand and improve experimental instructions of computational chemistry for undergraduates, we designed an introductory experiment—research on acrylamide molecular structure and physicochemical properties. Initially, students construct molecular models of acrylamide and polyacrylamide in Gaussian and Materials Studio software respectively. Then, the infrared spectral data, atomic charge and molecular orbitals of acrylamide as well as solvation effect of polyacrylamide are calculated to predict their physicochemical performance. At last, rheological experiments are used to validate these predictions. Through the combination of molecular simulation (performed on Gaussian, Materials Studio) with experimental verification (rheology experiment), learners have deeply comprehended the chemical nature of acrylamide and polyacrylamide, achieving good learning outcomes.

Keywords: Upper-division undergraduate, computer-based learning, laboratory instruction, amides, molecular modeling, spectroscopy.

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[1] Esselman, B.J.; Hill, N.J. Integration of Computational Chemistry into the Undergraduate Organic Chemistry Laboratory Curriculum. J. Chem. Educ. 2016, 93(5), 932-936.
[2] Monari, A. Computational Chemistry. Acta. Crystallogr. C. 2018, 74, 1781-1782.
[3] Bajorath, J. Pushing the boundaries of computational approaches: special focus issue on computational chemistry and computer-aided drug discovery. Future. Med. Chem. 2015, 7(18), 2415-2417.
[4] Bajorath, J. Computational chemistry publications in the Journal of Medicinal Chemistry. J. Med. Chem. 2008, 51(8), 2327-2327.
[5] Thiel, W.; Hummer, G. Chemistry methods for computational chemistry. Nature. 2013, 504(7478), 96-97.
[6] Stevens, J. Virtually going green: The role of quantum computational chemistry in reducing pollution and toxicity in chemistry. Physical Sciences Reviews. 2017, 2(7), UNSP 20170005.
[7] Alique, D.; Linares, M. The importance of rapid and meaningful feedback on computer-aided graphic expression learning. Education for Chemical Engineers. 2019, 27, 54-60.
[8] Sendlinger, S. C.; DeCoste, D. J.; Dunning, D. H.; Dummitt, D. A.; Jakobsson, E.; Mattson, D. R.; Wiziecki, E. N. Transforming chemistry education through computational science. Comput. Sci. Eng. 2008, 10(5), 34-39.
[9] Zendler, A.; Greiner, H. The effect of two instructional methods on learning outcome in chemistry education: The experiment method and computer simulation. Education for Chemical Engineers. 2020, 30, 9-19.
[10] Ruiz-Ramos, E.; Romero-Garcia, J. M.; Espinola, F.; Romero, I.; Hernandez, V.; Castro, E. Learning and researching based on local experience and simulation software for graduate and undergraduate courses in chemical and environmental engineering. Education for Chemical Engineers. 2017, 21, 50-61.
[11] Orenha, S. R.; Galembeck, S. E. Molecular orbitals of NO, NO+, and NO-: A computational quantum chemistry experiment. J. Chem. Educ. 2014, 91(7), 1064-1069.
[12] Marzzacco, C. J.; Baum, J. C. Computational chemistry studies on the carbene hydroxymethylene. J. Chem. Educ. 2011, 88(12), 1667-1671.
[13] Miller, C. S.; Ellison, M. Walsh diagrams: molecular orbital and structure computational chemistry exercise for physical chemistry. J. Chem. Educ. 2015, 92(6), 1040-1043.
[14] Nassabeh, N.; Tran, M.; Fleming, P. E. Dissociation of the ethyl radical: An exercise in computational chemistry. J. Chem. Educ. 2014, 91(8), 1248-1253.
[15] Morales, C.; Chen, F. Exploration of substituent and isotope effects on reaction rates by a computational modeling experiment. J. Chem. Educ. 2019, 96(4), 792-796.
[16] Esselman, B. J.; Hofstetter, H.; Ellison, A. J.; Fry, C. G.; Hill, N. J. SN 1, E1, and E2 reactions of tert-amyl compounds: Improved analysis using computational chemistry and ASAP-HSQC NMR spectroscopy. J. Chem. Educ. 2020, 97(8), 2280-2285.
[17] Raters, M.; Matissek, R. 10 years Acrylamide - Retrospective and Status-quo. Deut. Lebensm-Rundsch. 2012, 108(4), 184-189.
[18] Sundaraganesan, N.; Puviarasan, N.; Mohan, S. Vibrational spectra, assignments and normal coordinate calculation of acrylamide. Talanta. 2001, 54(2), 233-241.
[19] Kozlovskii, A. A.; Gordon, D. A.; Bol'shakov, A. I.; Mikhailov, A. I. Low-temperature polymerization of acrylamide under the action of molecular chlorine. Polym. Sci. Ser. B. 2011, 53, 404-408.
[20] Chen, X. Y.; Zhang, Y.; Yu, F.; Wang, H. J. DFT calculations on hydrogen-bonded complexes formed between guanine and acrylamide. J. Solution. Chem. 2010, 39(9), 1341-1349.
[21] Wang, Y. S.; Lin, Y. D.; Chao, S. D. Hydrogen-bonding structures and energetics of acrylamide isomers, tautomers, and dimers: an ab initio study and spectral analysis. J. Chin. Chem. Soc-Taip. 2016, 63(12), 968-976.
[22] Permyakova, N. M.; Zheltonozhskaya, T. B.; Fedorchuk, S. V.; Zagdanskaya, N. E.; Syromyatnikov, V. G. Temperature effect on hydrogen bonds in triblock copolymers of poly(ethylene oxide) and polyacrylamide. Mol. Cryst. Liq. Cryst. 2007, 468, 405-413.
[23] Sharma, B. B.; Murli, C.; Sharma, S. M. Hydrogen bonds and polymerization in acrylamide under pressure. J. Raman. Spectrosc. 2013, 44(5), 785-790.
[24] Shirota, H.; Castner, E. W. Hydrogen-bond interactions and dynamics in aqueous polymers: Polyacrylamide. Abstracts of Papers of the American Chemical Society. 2000, 220, 422-PHYS.
[25] Ying, Z. R.; Wu, D. F.; Wang, Z. F.; Xie, W. Y.; Qiu, Y. X.; Wei, X. J. Rheological and mechanical properties of polylactide nanocomposites reinforced with the cellulose nanofibers with various surface treatments. Cellulose. 2018, 25, 3955-3971.
[26] Wu, D. F.; Yuan, L. J.; Laredo, E.; Zhang, M.; Zhou, W. D. Interfacial Properties, Viscoelasticity, and Thermal Behaviors of Poly(butylene succinate)/Polylactide Blend. Ing. Eng. Chem. Res. 2012, 51, 2290-2298.
[27] Vetcher, A. A.; Gearheart, R.; Morozov, V. N. Correlation of morphology of electrospun fibers with rheology of linear polyacrylamide solution. Polym. J. 2007, 39(8), 878-881.
[28] Ziegler, B. E. Theoretical hammett plot for the gas-phase ionization of benzoic acid versus phenol: A computational chemistry lab exercise. J. Chem. Educ. 2013, 90(5), 665-668.
[29] Perri, M. J.; Weber, S. H. Web-based job submission interface for the GAMESS computational chemistry program. J. Chem. Educ. 2014, 91(12), 2206-2208.
[30] Martini, S. R.; Hartzell, C. J. Integrating computational chemistry into a course in classical thermodynamics. J. Chem. Educ. 2015, 92(7), 1201-1203.
[31] Whisnant, D. M.; Lever, L. S.; Howe, J. J. Cl2O4 in the stratosphere: A collaborative computational chemistry project. J. Chem. Educ. 2000, 77(12), 1648-1649.
[32] Adams, W.; Sonntag, M. D. Vibrational spectroscopy of hexynes: A combined experimental and computational laboratory experiment. J. Chem. Educ. 2018, 95(7), 1205-1210.
[33] Daniel, P. M.; Adam, P.; Herbert, L.; Sarah, S.; Jochen, A.; Eva, Z. The computational design of two-dimensional materials. J. Chem. Educ. 2019, 96(10), 2308-2314.