Preparation and infrared/raman classification of 630 spectroscopically encoded styrene copolymers

The barcoded resins (BCRs) were introduced recently as a platform for encoded combinatorial chemistry. One of the main challenges yet to be overcome is the demonstration that a large number of BCRs could be generated and classified with high confidence. Here, we describe the synthesis and classification of 630 polystyrene-based copolymers prepared from the combinatorial association of 15 spectroscopically active styrene monomers. Each of the 630 copolymers displayed a unique vibrational fingerprint (infrared and Raman), which was converted into a spectral vector. To each of the 630 copolymers, a vector of the known (reference) composition was assigned. Unknown (prediction) vectors were decoded using multivariate data analysis. From the inner product of the reference and prediction vectors, a correlation map comparing 396 900 copolymer pairs (630 x 630) was generated. In 100% of the cases, the highest correlation was obtained for polymer pairs in which the reference and prediction vectors correspond to copolymers prepared from identical styrene monomers, thus demonstrating the high reliability of this encoding strategy. We have also established that the spectroscopic barcodes generated from the Raman and infrared spectra are independent of the copolymers' morphology (beaded versus bulk polymers). Besides the demonstration of the generality of the polymer barcoding strategy, the analytical methods developed here could in principle be extended to the investigation of the composition and purity of any other synthetic polymer and biopolymer library, or even scaffold-based combinatorial libraries.