Surface Spectroscopic Signatures of Mechanical Deformation in High-Density Polyethylene (HDPE)

Abstract

High-density polyethylene (HDPE) has been extensively studied, both as a model for semi-crystalline polymers and because of its own industrial utility. During cold drawing, crystalline regions of HDPE are known to break up and align with the direction of tensile load. Structural changes due to deformation should also manifest at the surface of the polymer, but until now, a detailed molecular understanding of how the surface responds to mechanical deformation has been lacking. This work establishes a precedent for using vibrational sum-frequency generation (VSFG) spectroscopy to investigate changes in the molecular-level structure of the surface of HDPE after cold drawing. X-ray diffraction (XRD) was used to confirm that the observed surface behavior corresponds to the expected bulk response. Before tensile loading, the VSFG spectra indicate that there is significant variability in the surface structure and tilt of the methylene groups away from the surface normal. After deformation, the VSFG spectroscopic signatures are notably different. These changes suggest that hydrocarbon chains at the surface of visibly necked HDPE are aligned with the direction of loading, while the associated methylene groups are oriented with the local C2 v symmetry axis roughly parallel to the surface normal. Small amounts of unaltered material are also found at the surface of necked HDPE, with the relative amount of unaltered material decreasing as the amount of deformation increases. Aspects of the nonresonant SFG response in the transition zone between necked and undeformed polymer provide additional insight into the deformation process and may provide the first indication of mechanical deformation. Nonlinear surface spectroscopy can thus be used as a noninvasive and nondestructive tool to probe the stress history of a HPDE sample in situations where X-ray techniques are not available or not applicable. Vibrational sum-frequency generation thus has great potential as a platform for material state awareness (MSA) and should be considered as part of a broader suite of tools for such applications.