Authors: Nikolaos Patsalidis | George Papamokos | George Floudas | Vagelis Harmandaris
Source: The Journal of Physical Chemistry C (article, 2022-09-27)
Field: Materials Science — Materials Chemistry

Understanding the Interaction between Polybutadiene and Alumina via Density Functional Theory Calculations and Machine-Learned Atomistic Simulations We provide a fundamental understanding of the interaction between cis-1,4-polybtadiene (PB) and the alumina (001) surface via a computational multi-stage methodology involving density functional theory (DFT) calculations and atomistic simulations. The latter were performed via newly derived, computationally efficient, pairwise-additive, parametric atomistic models using machine learning (ML) algorithms. First, DFT calculations that include van der Waals (vdW) interactions were performed to investigate the adsorption of cis-2-butene (i.e., the repeat unit of cis-1,4-PB) on the alumina surface. To obtain an accurate sampling of the complex cis-2-butene/alumina configurational space at the DFT level, we studied several systems in which alumina is modeled as (a) a small cluster, to quickly find the stable configurations of the system, and be used as a guide in (b) realistic periodic surface models. We found similar optimal (stable) structures in both models. We also performed a series of constrained DFT simulations to enhance the configurational space sampling between cis-2-butene and alumina for the periodic alumina (001). The atomistic model for the cis-2-butene/alumina interaction was developed using ML algorithms that find, using a specific functional representation, the optimum classical model parameters, which reproduce at the atomistic level the DFT-calculated adsorption energy. To examine the whole procedure, we developed atomistic models, using Lennard–Jones or Morse potential functions, in both all-atom and united-atom representations. Moreover, we provide a detailed statistical estimation of parametric uncertainty of the derived atomistic models by applying the Bootstrap method. We were able to fit the data with a mean absolute error below 1 kcal/mol, for all the models considered. As a last part of the proposed methodology, we performed molecular dynamics simulations, using the newly developed models, of a representative system of 30mer cis-1,4-PB chains confined between an infinite (periodic) alumina slab of thickness ≈1.114 nm at a temperature of 413 K and a pressure of 1 atm. We studied the molecular packing in the vicinity of the interface. The results demonstrate that the new atomistic models can accurately reproduce the structure of PB chains in the vicinity of the alumina substrate. In addition, we compared our results with atomistic simulations describing the PB/alumina interaction via standard mixing (Lorentz–Berthelot combination) rules. We demonstrate that the latter are inadequate in describing the complex interfacial polymer/solid interaction. Density functional theory ; van der Waals force ; Statistical physics ; Morse potential ; Materials science ; Adsorption ; Surface (topology) ; Computational chemistry ; Parametric statistics ; Configuration space ; Atom (system on chip) ; Thermodynamics ; Physics ; Chemistry ; Physical chemistry ; Molecule ; Computer science ; Mathematics ; Quantum mechanics ; Geometry Machine Learning in Materials Science ; Advanced Physical and Chemical Molecular Interactions ; Phase Equilibria and Thermodynamics