Polymer blends and copolymers are used in engineering applications where tribological and mechanical performance can be improved by 2D nanofillers like MXenes [1-3]. This study employs multiscale atomistic approaches, such as Density Functional Theory (DFT), with PBE-D3 dispersion correction, and Molecular Dynamics (MD), using the Orb-v3 machine-learning interatomic potential, to investigate matrix-reinforcement affinity of polypropylene/polyethylene (PP/PE) copolymers, polyethylene oxide (PEO), and polypropylene oxide (PPO) single chains in Ti3C2O2 MXene surface. We evaluate the system’s adsorption energies, conformations, friction and charge transfer. DFT reveals PP/PE copolymers exhibit higher adsorption energies than PEO and PPO, with helical PE monomers arrangements yielding stronger binding than planar zigzag configurations. Equilibrium distances (2.31-2.65 Å) and low adsorption energies (much lower than 1 eV) indicate physisorption, governed by van der Waals forces, dominates all systems, with a small contribution from hydrogen bonding, as showed by Bader charge analysis. However, PEO demonstrates adsorption site-region selectivity, transitioning to a coiled gauche-like structure, minimizing the system's energy, and leading to an adsorption energy approximately 4.6 times higher. Nanoscale friction calculations show negligible sliding energy barriers, highlighting solid lubricant potential especially for the PEO system. The MD diffusion results, despite the short simulation time (10 ps), are qualitatively consistent with the DFT calculations, and once again for PEO, despite its higher adsorption energy, a high flexibility of its chain is demonstrated through the change in dihedral angles and rotation behavior. Finally, electronic structure analysis confirms Ti3C2O2 MXene preserves its metallic character upon polymer adsorption, indicating also the potential of such materials for energy storage applications and electromagnetic interference (EMI) shielding.
[1] G. Barbosa et al, Surf. Coat. Technol. 512, 132424 (2025).
[2] R. Ronchi, F. Santos and R. Veiga, App. Surf. Science 609, 155344 (2023).
[3] R. Ronchi et al, Mater. Today Commun., 34, 105397 (2023).
Acknowledgement/Funding: The authors are very grateful to Exxon Mobil Corporation for the financial support of this research under ANP Project 24163-8. G. G. Barbosa acknowledges the research fellow from Exxon Mobil Corporation. The authors would also like to thank the Multi-user Computing Center (CCM/Propes) of Federal University of ABC (UFABC) for the computational resources.
Comissão Organizadora
Pedro Alves da Silva Autreto
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