A digital image correlation-integrated platform for force-controlled fatigue testing of PDMS thin films.
biomechanical · Level V
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- Record sourced from PubMed, PMID 42743709.
- Also identified by DOI 10.1016/j.jmbbm.2026.107611.
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Abstract
Force-controlled fatigue testing maintains constant stress amplitude and is better suited than displacement-controlled methods for elucidating viscoelastic behavior because it mitigates stress variations from machine compliance, accommodates cyclic softening, and reproduces realistic conditions for biomedical and wearable applications. Such experiments are seldom conducted on thin polydimethylsiloxane (PDMS) films. To address this, a Digital Image Correlation (DIC)-integrated platform characterizes the cyclic response of 150-μm-thick PDMS films with 0.1% strain resolution across 77 samples, of which 34 are studied under DIC, eliminating compliance error, resolving localized strain development, and measuring viscoelastic energy dissipation. DIC captures strain ratcheting often underestimated in displacement-controlled tests due to system compliance. With 10<sup>6</sup> cycles under 2 Hz taking one week, stress amplitudes of 2.5, 2.7, and 2.8 MPa produce ratcheting where higher amplitudes reach high strain earlier. Mean ratcheting strain increases from 0.137 to 0.151 at 2.5 MPa, 0.147 to 0.155 at 2.7 MPa for the 10th and 10<sup>6</sup>th cycles, and from 0.157 to 0.167 at 2.8 MPa for the 10th and 4×10<sup>5</sup>th cycles, respectively. Failure, defined as fracture within the gauge section during the first 10<sup>6</sup> cycles, is tracked across all tests. Decreasing hysteresis loop area indicates reduced viscous dissipation and cyclic softening. The force-controlled S-N curve, first in the literature, shows weak stress dependence, while cumulative failure distribution reveals strong stress sensitivity of failure probability, highlighting the need for probabilistic fatigue assessment. These results establish force-controlled fatigue testing with DIC as a robust framework for elastomer durability characterization in soft robotics and biomedical applications.