ToF-SIMS and Machine Learning for Single-Pixel Molecular Discrimination of an Acrylate Polymer Microarray was written by Gardner, Wil;Hook, Andrew L.;Alexander, Morgan R.;Ballabio, Davide;Cutts, Suzanne M.;Muir, Benjamin W.;Pigram, Paul J.. And the article was included in Analytical Chemistry (Washington, DC, United States) in 2020.Related Products of 4074-88-8 This article mentions the following:
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 phys. and chem. properties-such as surface chem. 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 chem. associated with the outermost layer of a sample with high spatial resolution and chem. 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 methodol. to a ToF-SIMS image of a printed polymer microarray for the first time. We report complete, single-pixel mol. 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 anal. with fluorescence data from polymer-protein adsorption studies, highlighting how polymer performance can be visualized within the context of the global topol. of the data set. In the experiment, the researchers used many compounds, for example, Diethyleneglycoldiacrylate (cas: 4074-88-8Related Products of 4074-88-8).
Diethyleneglycoldiacrylate (cas: 4074-88-8) belongs to alcohols. A strong base can deprotonate an alcohol to yield an alkoxide ion (R鈥昈鈭?. For example, sodamide (NaNH2), a very strong base, abstracts the hydrogen atom of an alcohol. Converting an alcohol to an alkene requires removal of the hydroxyl group and a hydrogen atom on the neighbouring carbon atom. Dehydrations are most commonly carried out by warming the alcohol in the presence of a strong dehydrating acid, such as concentrated sulfuric acid.Related Products of 4074-88-8
Referemce:
Alcohol – Wikipedia,
Alcohols – Chemistry LibreTexts