Vibrational Fingerprints of Strained Polymers: A Spectroscopic Pathway to Mechanical State Prediction

• URL: http://arxiv.org/abs/2509.16266v2
• Date: Wed, 24 Sep 2025 11:37:29 GMT
• Title: Vibrational Fingerprints of Strained Polymers: A Spectroscopic Pathway to Mechanical State Prediction
• Authors: Julian Konrad, Janina Mittelhaus, David M. Wilkins, Bodo Fiedler, Robert Meißner,
• Abstract summary: vibrational response of polymer networks under load provides a sensitive probe of molecular deformation.<n>We show that machine-learned force fields reproduce these spectroscopic fingerprints with quantum-level fidelity in realistic epoxy thermosets.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The vibrational response of polymer networks under load provides a sensitive probe of molecular deformation and a route to non-destructive diagnostics. Here we show that machine-learned force fields reproduce these spectroscopic fingerprints with quantum-level fidelity in realistic epoxy thermosets. Using MACE-OFF23 molecular dynamics, we capture the experimentally observed redshifts of para-phenylene stretching modes under tensile load, in contrast to the harmonic OPLS-AA model. These shifts correlate with molecular elongation and alignment, consistent with Badger's rule, directly linking vibrational features to local stress. To capture IR intensities, we trained a symmetry-adapted dipole moment model on representative epoxy fragments, enabling validation of strain responses. Together, these approaches provide chemically accurate and computationally accessible predictions of strain-dependent vibrational spectra. Our results establish vibrational fingerprints as predictive markers of mechanical state in polymer networks, pointing to new strategies for stress mapping and structural-health diagnostics in advanced materials.

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