High throughput discovery of thermo-responsive materials using water contact angle measurements and time-of-flight secondary ion mass spectrometry

Microfluidic High-Throughput Platforms for Discovery of Novel Materials

High-throughput screening is a potent technique to accelerate the discovery and development of new materials. By performing massive synthesis and characterization processes in parallel, it can rapidly discover materials with desired components, structures and functions. Among the various approaches for high-throughput screening, microfluidic platforms have attracted increasing attention. Compared with many current strategies that are generally based on robotic dispensers and automatic microplates, microfluidic platforms can significantly increase the throughput and reduce the consumption of reagents by several orders of magnitude. In this review, we first introduce current advances of the two types of microfluidic high-throughput platforms based on microarrays and microdroplets, respectively. Then the utilization of these platforms for screening different types of materials, including inorganic metals, metal alloys and organic polymers are described in detail. Finally, the challenges and opportunities in this promising field are critically discussed.

ToF-SIMS analysis of a polymer microarray composed of poly(meth)acrylates with C6 derivative pendant groups

Surface analysis plays a key role in understanding the function of materials, particularly in biological environments. Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) provides highly surface sensitive chemical information that can readily be acquired over large areas and has, thus, become an important surface analysis tool. However, the information‐rich nature of ToF‐SIMS complicates the interpretation and comparison of spectra, particularly in cases where multicomponent samples are being assessed. In this study, a method is presented to assess the chemical variance across 16 poly(meth)acrylates. Materials are selected to contain C₆ pendant groups, and ten replicates of each are printed as a polymer microarray. SIMS spectra are acquired for each material with the most intense and unique ions assessed for each material to identify the predominant and distinctive fragmentation pathways within the materials studied. Differentiating acrylate/methacrylate pairs is readily achieved using secondary ions derived from both the polymer backbone and pendant groups. Principal component analysis (PCA) is performed on the SIMS spectra of the 16 polymers, whereby the resulting principal components are able to distinguish phenyl from benzyl groups, mono‐functional from multi‐functional monomers and acrylates from methacrylates. The principal components are applied to copolymer series to assess the predictive capabilities of the PCA. Beyond being able to predict the copolymer ratio, in some cases, the SIMS analysis is able to provide insight into the molecular sequence of a copolymer. The insight gained in this study will be beneficial for developing structure–function relationships based upon ToF‐SIMS data of polymer libraries. © 2016 The Authors Surface and Interface Analysis Published by John Wiley & Sons Ltd.

Bacterial attachment to polymeric materials correlates with molecular flexibility and hydrophilicity

A new class of material resistant to bacterial attachment has been discovered that is formed from polyacrylates with hydrocarbon pendant groups. In this study, the relationship between the nature of the hydrocarbon moiety and resistance to bacteria is explored, comparing cyclic, aromatic, and linear chemical groups. A correlation is shown between bacterial attachment and a parameter derived from the partition coefficient and the number of rotatable bonds of the materials' pendant groups. This correlation is applicable to 86% of the hydrocarbon pendant moieties surveyed, quantitatively supporting the previous qualitative observation that bacteria are repelled from poly(meth)acrylates containing a hydrophilic ester group when the pendant group is both rigid and hydrophobic. This insight will help inform and predict the further development of polymers resistant to bacterial attachment.

Detection of surface mobility of poly (2, 3, 4, 5, 6-pentafluorostyrene) films by in situ variable-temperature ToF-SIMS and contact angle measurements

Poly (2, 3, 4, 5, 6-pentafluorostyrene) (5FPS) was prepared by bulk radical polymerization. The spin-cast films of this polymer were analyzed using time-of-flight secondary ion mass spectrometry (ToF-SIMS) at various temperatures ranging from room temperature to 120°C. Principal component analysis (PCA) of the ToF-SIMS data revealed a transition temperature (T(T)) at which the surface structure of 5FPS was rearranged. A comparison between the results of the PCA of ToF-SIMS spectra obtained on 5FPS and polystyrene (PS) indicate that the pendant groups of 5FPS and PS moved in exactly opposite directions as the temperature increased. More pendant groups of 5FPS and PS migrated from the bulk to the surface and verse versa, respectively, as the temperature increased. These results clearly support the view that the abrupt changes in the normalized principal component 1 value was caused by the surface reorientation of the polymers and not by a change in the ion fragmentation mechanism at temperatures above the T(T). Contact angle measurement, which is another extremely surface sensitive technique, was used to monitor the change in the surface tension as a function of temperature. A clear T(T) was determined by the contact angle measurements. The T(T) values determined by contact angle measurements and ToF-SIMS were very similar.

Thermally switchable polymers achieve controlled Escherichia coli detachment

The thermally triggered release of up to 96% of attached uropathogenic E. coli is achieved on two polymers with opposite changes in surface wettability upon reduction in temperature. This demonstrates that the bacterial attachment to a surface cannot be explained in terms of water contact angle alone; rather, the surface composition of the polymer plays the key role.

Chemically diverse polymer microarrays and high throughput surface characterisation: a method for discovery of materials for stem cell culture†Electronic supplementary information (ESI) available. See DOI: 10.1039/c4bm00054dClick here for additional data file

Chemically diverse polymer microarrays as a powerful screening tool for the discovery of new materials for a variety of applications.

Materials discovery provides the opportunity to identify novel materials that are tailored to complex biological environments by using combinatorial mixing of monomers to form large libraries of polymers as micro arrays. The materials discovery approach is predicated on the use of the largest chemical diversity possible, yet previous studies into human pluripotent stem cell (hPSC) response to polymer microarrays have been limited to 20 or so different monomer identities in each study. Here we show that it is possible to print and assess cell adhesion of 141 different monomers in a microarray format. This provides access to the largest chemical space to date, allowing us to meet the regenerative medicine challenge to provide scalable synthetic culture ware. This study identifies new materials suitable for hPSC expansion that could not have been predicted from previous knowledge of cell-material interactions.

Discovery of novel materials with broad resistance to bacterial attachment using combinatorial polymer microarrays

A new class of bacteria-attachment-resistant materials is discovered using a multi-generation polymer microarray methodology that reduces bacterial attachment by up to 99.3% compared with a leading commercially available silver hydrogel anti-bacterial material. The coverage of three bacterial species, Pseudomonas aeruginosa, Staphylococcus aureus, and uropathogenic Escherichia coli is assessed.

Strategies for MCR image analysis of large hyperspectral data-sets

Polymer microarrays are a key enabling technology for high throughput materials discovery. In this study, multivariate image analysis, specifically multivariate curve resolution (MCR), is applied to the hyperspectral time of flight secondary ion mass spectroscopy (ToF-SIMS) data from eight individual microarray spots. Rather than analysing the data individually, the data-sets are collated and analysed as a single large data-set. Desktop computing is not a practical method for undertaking MCR analysis of such large data-sets due to the constraints of memory and computational overhead. Here, a distributed memory High-Performance Computing facility (HPC) is used. Similar to what is achieved using MCR analysis of individual samples, the results from this consolidated data-set allow clear identification of the substrate material; furthermore, specific chemistries common to different spots are also identified. The application of the HPC facility to the MCR analysis of ToF-SIMS hyperspectral data-sets demonstrates a potential methodology for the analysis of macro-scale data without compromising spatial resolution (data 'binning'). Copyright © 2012 John Wiley & Sons, Ltd.

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 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.