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Page 2 of 18 Li et al. J. Mater. Inf. 2025, 5, 29 https://dx.doi.org/10.20517/jmi.2024.103

INTRODUCTION
Polymer materials, especially rubber materials, have a significant presence in the Chinese market and are
widely utilized in diverse fields. However, aging problems are inevitable, with oxygen-participating aging
being commonly observed. Research on aging mechanisms is carried out through multiple methods,
including experimental characterization, theoretical models, simulation-based approaches, and data-driven
methods.

Experimental characterization focuses on detecting various changes during the aging process across four
main aspects: chemical composition, microstructure, surface morphology, and macroscopic properties. For
chemical composition and elemental analysis, techniques such as X-ray photoelectron spectroscopy (XPS)
[1-3]
are used to analyze the elemental composition and chemical structure , while infrared spectroscopy (IR)
helps measure the content of specific functional groups , revealing alterations in the types and amounts of
[4-6]
chemical elements and compounds. In terms of microstructure analysis, changes in the spatial structure,
such as the distortion or rearrangement of polymer chains in three-dimensional space, are examined with
[7-9]
X-ray diffraction (XRD) . XRD serves as a valuable technique to assess the crystalline structure and
analyze the degree of aging by evaluating changes in peak positions, intensities, and crystallinity, offering
insights into how aging impacts the material’s microstructure. Surface morphology analysis involves
studying changes such as roughness, cracks, or deformations on the material’s surface. Atomic force
microscopy (AFM) is commonly used for high-resolution imaging of surface topography, enabling the
detection of subtle changes in surface features such as roughness and cracking [10-14] . Additionally,
macroscopic property analysis, including measurements of mechanical strength, flexibility, and color,
provides essential data for understanding aging mechanisms. For example, dynamic mechanical analysis
(DMA) can be used to examine changes in the viscoelastic properties of the material [15,16] , while tensile
property measurements offer insights into changes in strength and elasticity [17,18] , which help in
understanding how aging affects the material’s overall performance. These comprehensive analyses allow
for a deeper understanding of the material’s degradation process, aiding in the prediction of its service life
under various conditions.

Theoretical models are proposed to better understand and predict the aging behavior of materials . The
[19]
Arrhenius equation is a typical example, which is used to calculate reaction rate constants. By considering
factors such as temperature and activation energy, it reveals the relationship between reaction rates and
aging time. This equation helps in predicting how the rate of aging will change under different
environmental conditions and provides a basis for estimating the lifespan of the material .
[20]
Simulation calculations are another important type of method to describe the aging process. Molecular
dynamics (MD) simulations track molecular movement and interaction over time to show how molecular
changes affect macroscopic properties, such as how polymer chain rearrangement due to stress alters
material stiffness or elasticity . The diffusion of small gas molecules in rubber materials can affect the aging
[21]
of the materials. MD can simulate the diffusion behavior of small molecules in rubber to obtain the most
likely aging sites and degrees of rubber materials . It can also be used to simulate the hygrothermal aging
[22]
of fiber materials . Quantum mechanics (QM) methods precisely describe electronic structures to study
[23]
electronic effects in aging, such as how light/heat-induced electron excitation leads to reactions such as free
radical formation and chain scission .
[24]
Data-driven approaches combine simulation calculations with experimental data. Image data generated
during aging can be classified to identify specific material change features. Spectral data, such as infrared or
nuclear magnetic resonance (NMR) spectra, can be used to construct feature vectors that reflect material