Accurate density functional theory (DFT) protocol for screening and designing chain transfer and branching agents for LDPE systems. Issue 1 (29th November 2017)

• Record Type: Journal Article
• Authors: Konstantinov, Ivan; Ewart, Sean; Brown, Hayley; Eddy, Christopher; Mendenhall, Jonathan; Munjal, Sarat
• Is Part Of: Molecular Systems Design and Engineering. Volume 3:Issue 1(2018)
• Page Start: 228
• Page End: 242
• Publication Date: 2017-11-29
• Subjects: Chemistry -- Molecular aspects -- Periodicals; Chemical engineering -- Molecular aspects -- Periodicals; Nanotechnology -- Periodicals; 620.5
• DOI: 10.1039/c7me00087a
• Languages: English
• ISSNs: 2058-9689

Abstract

Abstract : This work emphasizes the importance of considering multiple reaction pathways when estimating the rate parameters for free radical polymerization using DFT. Abstract : In this work, a density functional theory (DFT) methodology was developed and validated against experimental data for relative hydrogen abstraction ( C s ) and monomer reactivity ratio ( r 1 ) parameters associated with free radical polymerization. For hydrogen abstraction, we considered ethane, cyclohexane, 2-butanone, propylene, isobutene, isobutane and propanal while methyl methacrylate, vinyl acetate, 1-butene, propylene and isobutene were the molecules of choice for benchmarking r 1 . It was shown that the M06-2X/6-311+G(3df, 2p)//B3LYP/6-31+G(d, p) level of theory along with the counterpoise correction for the basis set superposition error (BSSE) produced estimated values in excellent agreement with experimental data. The calculated parameters were within a factor of 1.5 from the experimental values. This translated into a maximum error of 0.32 kcal mol −1 in Gibbs free energy of activation difference. The only exception was C s for ethane with an experimental-to-calculated ratio of 3.0. Even then, the DFT estimate was within the experimental error. Furthermore, the approach managed to capture a wide range of empirical parameters as well as distinguish between monomers with close values. This robust and computationally inexpensive method can be applied to elucidate the reactivity of much larger species of industrial importance and rationally design the next generation of branching and chain-transfer agents for low density polyethylene (LDPE) systems.