Biobased Polymers Enable the Synergistic Tuning of Li+ Transport and Mechanical Robustness via Structural Design
JJ Qu and SQ Zhan and ZY Li and HH Zhao and LQ Zhang and J Liu, MACROMOLECULES, 58, 12931-12945 (2025).
DOI: 10.1021/acs.macromol.5c01856
As an eco-friendly alternative to traditional petroleum-based polymers,
biobased ion-conductive polymers derived from unsaturated biomass acids
exhibit tremendous potential. In this work, all-atom molecular dynamics
(MD) simulations were employed to investigate the structure-property
relationships of ferulate-based ion-conductive polymers. The systems
were constructed from polymer chains randomly copolymerized by ferulic
acid, 2-hydroxyethyl acrylate, and ethylene units, incorporated with
lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) at different mass
fractions. Lithium ions (Li+) coordinate primarily with oxygen atoms
from ester, carboxyl, and hydroxyl groups, maintaining stable local
coordination despite lithium salt concentration (phi) variations. The
study uncovers two conduction modes: direct Li+ hopping via decoupling
from -COO-/-COOH groups and coupled conduction with -OH groups in
polymer segments. Ionic conductivity exhibits a nonmonotonic trend,
optimized via the synergy between carrier density and mobility.
Mechanical properties of the systems were systematically characterized
via diverse approaches including uniaxial tension, tension recovery,
shear deformation, and fracture healing tests. After that, the MD data
set was expanded with representative metrics including conductivity,
tensile strength, viscoelasticity, and self-healing properties. Gaussian
process regression (GPR) was implemented for predictive modeling,
outlining parameter design directions to elevate both the electrical
conductivity and mechanical performance. Multiobjective optimization
maps the parameter space for peak performance, predicting an ionic
conductivity of 6.13 x 10-4 S
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