Abstract
Time-of-flight secondary ion mass spectrometry (TOF-SIMS) was used in a high-throughput fashion to obtain mass spectra from the surfaces of 576 novel acrylate-based polymers, synthesized using a combinatorial approach and in a micropatterned format. To identify variations in surface chemistry within the library, principal component analysis (PCA) was used. PCA clearly identified surface chemical commonality and differences within the library. The TOF-SIMS spectra were also used to determine the relationship between water contact angle (WCA) and the surface chemistry of the polymer library using partial least-squares regression (PLS). A good correlation between the TOF-SIMS data from the novel polymers and water contact angle was obtained. Examination of the PLS regression vector allowed surface moieties that correlate with high and low WCA to be identified. This in turn provided an insight into molecular structures that significantly influence wettability. This study demonstrates that multivariate analysis can be successfully applied to TOF-SIMS data from a large library of samples and highlights the potential of these techniques for building complex surface property/chemistry models.
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