2018/07/04 by Flora D. Tsourtou, Stavros D. Peroukidis, Loukas D. Peristeras +1 · 12 citations
Chemistry · Engineering · Materials Science · Mathematics · Physics and Astronomy · #Chemical physics #Chemistry #Computational chemistry #Dihedral angle #Hydrogen bond #Machine Learning in Materials Science #Materials science #Mathematics #Molecular dynamics #Molecule #Monte Carlo method #Organic Electronics and Photovoltaics #Organic chemistry #Physics #Polymer crystallization and properties #Ring (chemistry) #Statistical physics #Thiophene #cond-mat.soft
paper · pdf · doi:10.1021/acs.macromol.8b01344
published in Macromolecules 51(21), 8406-8423 (American Chemical Society)
arxiv created 2018/07/04 · openalex created_date 2018/07/10 · openalex publication_date 2018/10/16 · arxiv updated 2019/03/06 · openalex updated_date 2026/08/05
We introduce a powerful Monte Carlo (MC) algorithm for the atomistic simulation of bulk models of oligo- and polythiophenes by redesigning MC moves originally developed for considerably simpler polymer structures and architectures, such as linear and branched polyethylene, to account for the ring structure of the thiophene monomer. Elementary MC moves implemented include bias reptation of an end thiophene ring, flip of an internal thiophene ring, rotation of an end thiophene ring, concerted rotation of three thiophene rings, rigid translation of an entire molecule, rotation of an entire molecule, and volume fluctuation. In the implementation of all moves we assume that thiophene ring atoms remain rigid and strictly coplanar; on the other hand, inter-ring torsion and bond bending angles are left fully flexible subject to suitable potential energy functions. Test simulations with the new algorithm of an important thiophene oligomer, α-sexithiophene (α-6T), at a high enough temperature (above its isotropic-to-nematic phase transition) using a new united atom model specifically developed for the purpose of this work provide predictions for the volumetric, conformational, and structural properties that are remarkably close to those obtained from detailed atomistic molecular dynamics (MD) simulations using an all-atom model. The new algorithm is particularly promising for addressing the rich (and largely unexplored) phase behavior and nanoscale ordering of very long (also more complex) thiophene-based polymers which cannot be accessed by conventional MD methods due to the extremely long relaxation times characterizing chain dynamics in these systems.