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Hook AL, Scurr DJ, Burley JC, et al. Analysis and prediction of defects in UV photo-initiated polymer microarrays. J Mater Chem B. 2012;1(7):1035-1043doi: 10.1039/c2tb00379a.
Hook, A. L., Scurr, D. J., Burley, J. C., Langer, R., Anderson, D. G., Davies, M. C., & Alexander, M. R. (2013). Analysis and prediction of defects in UV photo-initiated polymer microarrays. Journal of materials chemistry. B, 1(7), 1035-1043. https://doi.org/10.1039/c2tb00379a
Hook, Andrew L, et al. "Analysis and prediction of defects in UV photo-initiated polymer microarrays." Journal of materials chemistry. B vol. 1,7 (2013): 1035-1043. doi: https://doi.org/10.1039/c2tb00379a
Hook AL, Scurr DJ, Burley JC, Langer R, Anderson DG, Davies MC, Alexander MR. Analysis and prediction of defects in UV photo-initiated polymer microarrays. J Mater Chem B. 2013 Feb 21;1(7):1035-1043. doi: 10.1039/c2tb00379a. Epub 2012 Dec 20. PMID: 25798286; PMCID: PMC4357255.
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J Mater Chem B. 2013 Feb 21;1(7):1035-1043. doi: 10.1039/c2tb00379a. Epub 2012 Dec 20.

Analysis and prediction of defects in UV photo-initiated polymer microarrays.

Journal of materials chemistry. B

Andrew L Hook, David J Scurr, Jonathan C Burley, Robert Langer, Daniel G Anderson, Martyn C Davies, Morgan R Alexander

Affiliations

  1. Laboratory of Biophysics and Surface Analysis , University of Nottingham , UK NG7 2RD . Email: [email protected] ; ; Tel: +44 (0)1159515119.
  2. David H. Koch Institute for Integrative Cancer Research , Massachusetts Institute of Technology , USA 02139.

PMID: 25798286 PMCID: PMC4357255 DOI: 10.1039/c2tb00379a

Abstract

Polymer microarrays are a key enabling technology for the discovery of novel materials. This technology can be further enhanced by expanding the combinatorial space represented on an array. However, not all materials are compatible with the microarray format and materials must be screened to assess their suitability with the microarray manufacturing methodology prior to their inclusion in a materials discovery investigation. In this study a library of materials expressed on the microarray format are assessed by light microscopy, atomic force microscopy and time-of-flight secondary ion mass spectrometry to identify compositions with defects that cause a polymer spot to exhibit surface properties significantly different from a smooth, round, chemically homogeneous 'normal' spot. It was demonstrated that the presence of these defects could be predicted in 85% of cases using a partial least square regression model based upon molecular descriptors of the monomer components of the polymeric materials. This may allow for potentially defective materials to be identified prior to their formation. Analysis of the PLS regression model highlighted some chemical properties that influenced the formation of defects, and in particular suggested that mixing a methacrylate and an acrylate monomer and/or mixing monomers with long and linear or short and bulky pendant groups will prevent the formation of defects. These results are of interest for the formation of polymer microarrays and may also inform the formulation of printed polymer materials generally.

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