Analysis and prediction of defects in UV photo-initiated polymer microarrays
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...
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| Format: | Article |
| Language: | en_US |
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Royal Society of Chemistry
2014
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| Online Access: | http://hdl.handle.net/1721.1/91249 https://orcid.org/0000-0001-5629-4798 https://orcid.org/0000-0003-4255-0492 |
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| author | Hook, Andrew L. Scurr, David J. Burley, Jonathan C. Anderson, Daniel Griffith Davies, Martyn C. Alexander, Morgan R. Langer, Robert S |
| author2 | Massachusetts Institute of Technology. Department of Chemical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Chemical Engineering Hook, Andrew L. Scurr, David J. Burley, Jonathan C. Anderson, Daniel Griffith Davies, Martyn C. Alexander, Morgan R. Langer, Robert S |
| author_sort | Hook, Andrew L. |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T15:02:19Z |
| format | Article |
| id | mit-1721.1/91249 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:02:19Z |
| publishDate | 2014 |
| publisher | Royal Society of Chemistry |
| record_format | dspace |
| spelling | mit-1721.1/912492022-10-02T00:10:25Z Analysis and prediction of defects in UV photo-initiated polymer microarrays Hook, Andrew L. Scurr, David J. Burley, Jonathan C. Anderson, Daniel Griffith Davies, Martyn C. Alexander, Morgan R. Langer, Robert S Massachusetts Institute of Technology. Department of Chemical Engineering Koch Institute for Integrative Cancer Research at MIT Langer, Robert Anderson, Daniel Griffith 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. Burroughs Wellcome Fund (grant number 085245) Royal Society (Great Britain) (Wolfson Research Merit Award) 2014-10-31T14:15:57Z 2014-10-31T14:15:57Z 2013 2012-11 Article http://purl.org/eprint/type/JournalArticle 2050-750X 2050-7518 http://hdl.handle.net/1721.1/91249 Hook, Andrew L., David J. Scurr, Jonathan C. Burley, Robert Langer, Daniel G. Anderson, Martyn C. Davies, and Morgan R. Alexander. “Analysis and Prediction of Defects in UV Photo-Initiated Polymer Microarrays.” Journal of Materials Chemistry B 1, no. 7 (2013): 1035. https://orcid.org/0000-0001-5629-4798 https://orcid.org/0000-0003-4255-0492 en_US http://dx.doi.org/10.1039/c2tb00379a Journal of Materials Chemistry B Creative Commons Attribution-NonCommercial 3.0 Unported License http://creativecommons.org/licenses/by-nc/3.0 application/pdf Royal Society of Chemistry Royal Society of Chemistry |
| spellingShingle | Hook, Andrew L. Scurr, David J. Burley, Jonathan C. Anderson, Daniel Griffith Davies, Martyn C. Alexander, Morgan R. Langer, Robert S Analysis and prediction of defects in UV photo-initiated polymer microarrays |
| title | Analysis and prediction of defects in UV photo-initiated polymer microarrays |
| title_full | Analysis and prediction of defects in UV photo-initiated polymer microarrays |
| title_fullStr | Analysis and prediction of defects in UV photo-initiated polymer microarrays |
| title_full_unstemmed | Analysis and prediction of defects in UV photo-initiated polymer microarrays |
| title_short | Analysis and prediction of defects in UV photo-initiated polymer microarrays |
| title_sort | analysis and prediction of defects in uv photo initiated polymer microarrays |
| url | http://hdl.handle.net/1721.1/91249 https://orcid.org/0000-0001-5629-4798 https://orcid.org/0000-0003-4255-0492 |
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