Abstract
Computational modeling has become an important tool for scientists to both predict the properties of materials and systems and to gain a better understanding of the underlying mechanisms. This chapter is a brief yet holistic introduction to computational modeling, focusing on density functional theoretical (DFT) methods. The different types of computational modeling methods, including molecular mechanics, semiempirical, and ab initio methods, as well as the different software available for computational calculations are discussed. A step-by-step guide is presented using Gaussian16 software to introduce the basics of computational modeling based on our work with biomimetic polymer beads. However, the guide presented here is not limited to this particular system; it can be applied to any computational modeling case. The computational modeling methods for the building of the structures are described, and the calculation parameters, such as basis sets and exchange-correlation functionals, are explained. The output data and results are presented and discussed. Two simulation features were the focus of this work: (1) the simulation of the Raman spectra and (2) the different solvation environments. While some researchers in the field believe that computational simulation should be performed before the lab experiments, in fact they should be done simultaneously. This is so that the output of the experimental data can be used as the input of the computational parameters, as a form of semiempirical modeling, in order to achieve more accurate results for predicting the behavior of future experiments and understanding the atomic forces and mechanisms.
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References
Mohamadi F, Richards NGJ, Guida WC et al (1990) Macromodel-an integrated software system for modeling organic and bioorganic molecules using molecular mechanics. J Comput Chem 11:440–467. https://doi.org/10.1002/jcc.540110405
Engler EM, Andose JD, Schleyer PVR (1973) Critical evaluation of molecular mechanics. J Am Chem Soc 95:8005–8025. https://doi.org/10.1021/ja00805a012
Burkert U, Norman A (1982) Molecular mechanics. Am Chem Soc 177. https://doi.org/10.1002/jcc.540040420
Ögretir C, Csizmadia IG (1991) Computational advances in organic chemistry: molecular structure and reactivity. Springer, Netherlands, Dordrecht
Szabo A, Ostlund NS (1989) Modern quantum chemistry: introduction to advanced electronic structure theory. McGrw-Hill, New York, NY
Foresman JB, Frisch A (2015) Exploring chemistry with electronic structure methods, 3rd edn. Gaussian, Inc., Wallingford, CT
Robert P, Yang W (1995) Density-functional theory of atoms and molecules. Oxford University Press, Oxford
Segall MD, Lindan PJD, Probert MJ et al (2002) First-principles simulation: ideas, illustrations and the CASTEP code. J Phys Condens Matter 14:2717–2744. https://doi.org/10.1088/0953-8984/14/11/301
Yu HS, Li SL, Truhlar DG (2016) Perspective: Kohn-Sham density functional theory descending a staircase. J Chem Phys 145:130901. https://doi.org/10.1063/1.4963168
From Wikipedia the Free Encyclopedia (2018) List of quantum chemistry and solid-state physics software. https://en.wikipedia.org/wiki/List_of_quantum_chemistry_and_solid-state_physics_software
Gameel KM, Sharafeldin IM, Abourayya AU et al (2018) Unveiling CO adsorption on Cu surfaces: new insights from molecular orbital principles. Phys Chem Chem Phys 20:25892–25900. https://doi.org/10.1039/C8CP04253E
Sharafeldin IM, Allam NK (2017) DFT insights into the electronic properties and adsorption of NO2 on metal-doped carbon nanotubes for gas sensing applications. New J Chem 41:14936–14944. https://doi.org/10.1039/C7NJ03109B
Clark SJ, Segall MD, Pickard CJ et al (2005) First principles methods using CASTEP. Zeitschrift für Krist 220:567–570. https://doi.org/10.1524/zkri.220.5.567.65075
Hafner J (2008) Ab-initio simulations of materials using VASP: density-functional theory and beyond. J Comput Chem 29:2044–2078. https://doi.org/10.1002/jcc.21057
Hehre WJ, Ditchfield R, Pople JA (1972) Self—consistent molecular orbital methods. XII. Further extensions of Gaussian—type basis sets for use in molecular orbital studies of organic molecules. J Chem Phys 56:2257–2261. https://doi.org/10.1063/1.1677527
Crescenzi O, D’Ischia M, Napolitano A (2017) Kaxiras’s porphyrin: DFT modeling of redox-tuned optical and electronic properties in a theoretically designed catechol-based bioinspired platform. Biomimetics 2:21. https://doi.org/10.3390/biomimetics2040021
Comba P, Rajaraman G, Rohwer H (2007) A density functional theory study of the reaction of the biomimetic Iron(II) complex of a tetradentate bispidine ligand with H2O2. Inorg Chem 46:3826–3838. https://doi.org/10.1021/ic061129y
Fitzgerald J, Sharafeldin I, Bravo-Vasquez JP, et al Microsensor based on cross-reactive, self-encoded polymer beads array
Jacob CR, Reiher M (2012) Spin in density-functional theory. Int J Quantum Chem 112:3661–3684. https://doi.org/10.1002/qua.24309
Jones RO, Gunnarsson O (1989) The density functional formalism, its applications and prospects. Rev Mod Phys 61:689–746. https://doi.org/10.1103/RevModPhys.61.689
Perdew JP, Wang Y (1992) Pair-distribution function and its coupling-constant average for the spin-polarized electron gas. Phys Rev B 46:12947–12954. https://doi.org/10.1103/PhysRevB.46.12947
Grossman JC, Mitas L, Raghavachari K (1995) Structure and stability of molecular carbon: importance of electron correlation. Phys Rev Lett 75:3870–3873. https://doi.org/10.1103/PhysRevLett.75.3870
Kohn W, Becke AD, Parr RG (1996) Density functional theory of electronic structure. J Phys Chem 100:12974–12980. https://doi.org/10.1021/jp960669l
Finocchi F (2011) Density functional theory for beginners-basic principles and practical approaches. Institut des NanoSciences de Paris (INSP) CNRS and University Pierre et Marie Curie, Paris
Lewars EG (2016) Computational chemistry-introduction to the theory and applications of molecular and quantum mechanics. Springer, Switzerland
Tomasi J, Mennucci B, Cammi R (2005) Quantum mechanical continuum solvation models. Chem Rev 105:2999–3094. https://doi.org/10.1021/cr9904009
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Sharafeldin, I.M., Fitzgerald, J.E., Fenniri, H., Allam, N.K. (2019). Computational Modeling for Biomimetic Sensors. In: Fitzgerald, J., Fenniri, H. (eds) Biomimetic Sensing. Methods in Molecular Biology, vol 2027. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9616-2_16
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DOI: https://doi.org/10.1007/978-1-4939-9616-2_16
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