Abstract
The complexity of hyperspectral time of flight secondary ion mass spectrometry (ToF-SIMS) datasets makes their subsequent analysis and interpretation challenging, and is often an impasse to the identification of trends and differences within large sample-sets. The application of multivariate data analysis has become a routine method to successfully deconvolute and analyze objectively these datasets. The advent of high-resolution large area ToF-SIMS imaging capability has enlarged further the data handling challenges. In this work, a modified multivariate curve resolution image analysis of a polymer microarray containing 70 different poly(meth)acrylate type spots (over a 9.2 × 9.2 mm area) is presented. This analysis distinguished key differences within the polymer library such as the differentiation between acrylate and methacrylate polymers and variance specific to side groups. Partial least squares (PLS) regression analysis was performed to identify correlations between the ToF-SIMS surface chemistry and the protein adsorption. PLS analysis identified a number of chemical moieties correlating with high or low protein adsorption, including ions derived from the polymer backbone and polyethylene glycol side-groups. The retrospective validation of the findings from the PLS analysis was also performed using the secondary ion images for those ions found to significantly contribute to high or low protein adsorption.
Highlights
The application of time of flight secondary ion mass spectrometry (ToF-SIMS) analysis has been successfully applied throughout a range of scientific disciplines for the analysis of both inorganic and organic sample types.1–3,6 For chemical analysis by ToF-SIMS, hyperspectral images are produced where each individual pixel contains a full mass spectrum
Partial least squares (PLS) analysis identified a number of chemical moieties correlating with high or low protein adsorption, including ions derived from the polymer backbone and polyethylene glycol side-groups
A large area hyperspectral image ToF-SIMS dataset acquired from a poly(meth)acrylate polymer microarray has been successfully deconvoluted using a modified multivariate curve resolution (MCR) analysis approach
Summary
The application of time of flight secondary ion mass spectrometry (ToF-SIMS) analysis has been successfully applied throughout a range of scientific disciplines for the analysis of both inorganic and organic sample types. For chemical analysis by ToF-SIMS, hyperspectral images are produced where each individual pixel contains a full mass spectrum. The potential of employing high-performance computing to undertake multivariate curve resolution (MCR) image analysis has been previously demonstrated by the authors, as applied to ToF-SIMS data of eight polymer microarray printed spots combined to form a single composite hyperspectral image (consisting of a 524 288 pixel area). In this present study, a modified MCR imaging analysis approach has allowed the successful deconvolution of a polymer microarray consisting of 70 distinct polymer chemistries without a need for postacquisition data binning or a reduction in the acquired spatial resolution. For the wider uptake of this method, this modified approach can be performed using a high-specification (8–16 GB, multicore) desktop computer in addition to a high performance compute cluster
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
