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

Analysis and prediction of defects in UV photo-initiated polymer microarrays.
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DOI:
10.1039/c2tb00379a
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发表时间:
2013-02-21
期刊:
Journal of materials chemistry. B
影响因子:
--
通讯作者:
Alexander MR
Alexander MR
中科院分区:
其他
文献类型:
--
作者:
Hook AL;Scurr DJ;Burley JC;Langer R;Anderson DG;Davies MC;Alexander MR

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使用基于分子描述符的PLS回归模型,在85%的情况下成功预测了聚合物中的缺陷发生。聚合物微阵列是发现新材料的关键技术。通过扩展数组上表示的组合空间,可以进一步增强该技术。然而,并非所有材料都与微阵列格式兼容,在材料发现调查之前,必须对材料进行筛选,以评估其与微阵列制造方法的适用性。在这项研究中,通过光学显微镜、原子力显微镜和飞行时间二次离子质谱法对微阵列格式表达的材料库进行了评估,以识别具有缺陷的成分,这些缺陷导致聚合物斑点表现出与光滑、圆形、化学均匀的“正常”斑点明显不同的表面特性。结果表明,基于聚合物单体组分的分子描述符,使用偏最小二乘回归模型可以预测85%的情况下这些缺陷的存在。这可以使潜在的有缺陷的材料在形成之前就被识别出来。PLS回归模型的分析突出了影响缺陷形成的一些化学性质,特别是表明混合甲基丙烯酸酯和丙烯酸酯单体和/或混合具有长而线性或短而笨重的垂基团的单体将防止缺陷的形成。这些结果对聚合物微阵列的形成很有意义,也可能为印刷聚合物材料的配方提供信息。
Defect occurrence within polymers was successfully predicted in 85% of cases using a PLS regression model based upon molecular descriptors. 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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