34 research outputs found
ToF-SIMS and Machine Learning for Single-Pixel Molecular Discrimination of an Acrylate Polymer Microarray
© 2020 American Chemical Society. Combinatorial approaches to materials discovery offer promising potential for the rapid development of novel polymer systems. Polymer microarrays enable the high-throughput comparison of material physical and chemical properties - such as surface chemistry and properties like cell attachment or protein adsorption - in order to identify correlations that can progress materials development. A challenge for this approach is to accurately discriminate between highly similar polymer chemistries or identify heterogeneities within individual polymer spots. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) offers unique potential in this regard, capable of describing the chemistry associated with the outermost layer of a sample with high spatial resolution and chemical sensitivity. However, this comes at the cost of generating large scale, complex hyperspectral imaging data sets. We have demonstrated previously that machine learning is a powerful tool for interpreting ToF-SIMS images, describing a method for color-tagging the output of a self-organizing map (SOM). This reduces the entire hyperspectral data set to a single reconstructed color similarity map, in which the spectral similarity between pixels is represented by color similarity in the map. Here, we apply the same methodology to a ToF-SIMS image of a printed polymer microarray for the first time. We report complete, single-pixel molecular discrimination of the 70 unique homopolymer spots on the array while also identifying intraspot heterogeneities thought to be related to intermixing of the polymer and the pHEMA coating. In this way, we show that the SOM can identify layers of similarity and clusters in the data, both with respect to polymer backbone structures and their individual side groups. Finally, we relate the output of the SOM analysis with fluorescence data from polymer-protein adsorption studies, highlighting how polymer performance can be visualized within the context of the global topology of the data set
Exploring the Relationship between Polymer Surface Chemistry and Bacterial Attachment Using ToF-SIMS and Self-Organizing maps
Biofilm formation is a major cause of hospital-acquired infections. Research into biofilm-resistant materials is therefore critical to reduce the frequency of these events. Polymer microarrays offer a high-throughput approach to enable the efficient discovery of novel biofilm-resistant polymers. Herein, bacterial attachment and surface chemistry are studied for a polymer microarray to improve the understanding of Pseudomonas aeruginosa biofilm formation on a diverse set of polymeric surfaces. The relationships between time-of-flight secondary ion mass spectrometry (ToF-SIMS) data and biofilm formation are analyzed using linear multivariate analysis (partial least squares [PLS] regression) and a nonlinear self-organizing map (SOM). The SOM models revealed several combinations of fragment ions that are positively or negatively associated with bacterial biofilm formation, which are not identified by PLS. With these insights, a second PLS model is calculated, in which interactions between key fragments (identified by the SOM) are explicitly considered. Inclusion of these terms improved the PLS model performance and shows that, without such terms, certain key fragment ions correlated with bacterial attachment may not be identified. The chemical insights provided by the combination of PLS regression and SOM will be useful for the design of materials that support negligible pathogen attachment
Modeling of an industrial process of pleuromutilin fermentation using feed-forward neural networks
A sensitive and highly stable polypyrrole-based pH sensor with hydroquinone monosulfonate and oxalate co-doping
A polymer-based pH electrode has been successfully fabricated via a simple electropolymerization of pyrrole on stainless steel using a co-doping system. Hydroquinone monosulfonate (HQS) was selected as a functional dopant while oxalic acid was used as a co-dopant. A combination of cyclic voltammetry and X-ray photoelectron spectroscopy revealed that passive layers of iron oxalate and chromium oxalate formed on the stainless steel surface at the initial stage of electropolymerization. The potentiometric characteristics of the co-doped polypyrrole (PPy) electrode exhibited a response slope of -54.67 ± 0.70 mV/pH at 28 °C, a linearity range from pH 2 to 12 and correlation coefficient greater than 0.995. The open-circuit potential was stable in buffer solutions with a response time less than 10 s, regardless of the age of electrode. The co-doped PPy electrode could be used as a multi-use pH sensor up to 60 days without any effect to the potentiometric response. Interferences from most of common ions are acceptably small. In comparison with a HQS-doped PPy electrode, the co-doped PPy electrode provides a superior pH measurement in solution due to the higher pH sensitivity and longer lifetime. Co-doping results in an improvement in the adhesion strength of the co-doped PPy film with the stainless steel electrode. Easy fabrication and the low production cost of the co-doped PPy electrodes offer an alternative to pH sensors having a comparable potentiometric performance with commercial glass electrodes.</p
A novel pH sensor based on hydroquinone monosulfonate-doped conducting polypyrrole
Functionalized polypyrrole (PPy) with hydroquinone monosulfonate (HQS) incorporated as the dopant has been prepared by a simple one-step electropolymerization of pyrrole at a stainless steel electrode from aqueous solution. Potentiometric pH responses of the HQS-doped PPy electrodes showed a response slope of -50.54 ± 1.67 mV/pH (28 °C), a linear working range of pH 2-12 and a response time less than 100 s. The electrode stability was maintained over the period of a month. Compared with other PPy-based pH electrodes reported previously, the HQS-doped PPy electrode shows significantly improved potentiometric response slope, response time, reproducibility and stability. Interference studies with several ions showed minimal effects on the potentiometric response of the modified electrode. A combination of X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary-ion mass spectrometry (ToF-SIMS) was performed to investigate the surface composition and characteristics of the electrodes, including the chemical basis of the electrode performance. Cyclic voltammetry revealed the expected electrochemical response of the HQS, which was electroactive in response to pH changes. HQS-doped PPy shows excellent potential as a novel pH sensor, incorporating both the electroactive species and conducting support in an integrated form, for a variety of applications requiring pH monitoring.</p
Adhesion of polymers
Most industrially applied polymer resins and composites have low surface free energy and lack polar functional groups on their surface, resulting in inherently poor adhesion properties. A strong research momentum to understand polymer adhesion in the last decade has been motivated by the growing needs of the automotive and aerospace industries for better adhesion of components and surface coatings. This paper reviews the recent research efforts on polymer adhesion with a special focus on adhesion mechanisms. It starts with an introduction to adhesion with explanatory notes on adhesion phenomena. Recent research on the adhesion mechanisms of mechanical coupling, chemical bonding and thermodynamic adhesion is then discussed. The area of adhesion promoters is reviewed with the focus on plasma and chemical treatments, along with direct methods for adhesion measurement. The topics of polymer blends and reactive polymerization are considered and the interactions with adhesion mechanisms are reported. The concluding section provides recommendations regarding future research on the contentious aspects of currently accepted adhesion mechanisms and on strategies for enhancing polymer adhesion strength.<br /
Interpretable Machine Learning Models for Phase Prediction in Polymerization-Induced Self-Assembly
ToF-SIMS investigation of epoxy resin curing reaction at different resin to hardener ratios
Time-of-flight secondary ion mass spectrometry (ToF-SIMS) and principal components analysis (PCA) were used to analyze diglycidyl ether of bisphenol A (DGEBA) and diglycidyl ether of bisphenol F (DGEBF) epoxy resin blend cured with isophorone diamine (IPD) hardener at different resin to hardener ratios. The aim was to establish correlations between the hardener concentration and the nature and progress of the crosslinking reaction. Insights into the cured resin structure revealed using ToF-SIMS are discussed. Three sets of significant secondary ions have been identified by PCA. Secondary ions such as C14H7O+, CHO+, CH3O+, and C21H24O4+ showed variance related to the completion of the curing reaction. Relative intensities of CxHyNz+ ions in the cured resin samples are indicative of the un-reacted and partially reacted hardener molecules, and are found to be proportional to the resin to hardener mixing ratio. The relative ion intensities of the aliphatic hydrocarbon ions are shown to relate to the cured resin crosslinking density