Abstract
A new and robust statistical approach is explored with the objective to derive quantitative and reliable information on the molecular dynamics within distinct domains (crystalline, intermediate and amorphous domains) of ultra-high molecular weight polyethylene (UHMWPE). The method consists of a critical evaluation of the free induction decay (FID) model, which is used to generate synthetic FID with a predefined signal-to-noise ratio by Monte Carlo simulations. The application of the method is demonstrated for three UHMWPE samples. A subsequent model fitting of their synthetic FIDs revealed a unique correlation between the error, i.e., standard deviation, of the derived parameters and the FID signal-to-noise ratio (SNRFID). Moreover, it was found that the method can be used to estimate the minimum required sampling time to obtain reliable parameter estimation of the FID model to experimental data.
Highlights
Polyethylene (PE) possesses a semi-crystalline complex topology composed of crystalline and disordered amorphous regions
The main topic in this work will be dedicated to the model fitting of both experimental and synthetic free induction decay (FID) of typical ultra-high molecular weight polyethylene (UHMWPE) samples, with the objective to explore the reproducibility and inherent error (95% confidence interval) in the derived domain fractions and their corresponding relaxation time characteristics
The results presented in this work rely on quantitative sampling of the FID, which is dictated by the longest spin–lattice relaxation time (T1) within the sample
Summary
Polyethylene (PE) possesses a semi-crystalline complex topology composed of crystalline and disordered amorphous regions. The main topic in this work will be dedicated to the model fitting of both experimental and synthetic FIDs of typical UHMWPE samples, with the objective to explore the reproducibility and inherent error (95% confidence interval) in the derived domain fractions (crystalline, intermediate and amorphous domains) and their corresponding relaxation time characteristics. For this purpose, we have explored three samples exposed to significantly different processing conditions
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