Abstract
Polyolefins are unique among synthetic polymers because their wide application envelope originates from a finely controlled microstructure of hydrocarbon chains, lacking any distinctive functional groups. This hampers the methods of automated sorting based on vibrational spectroscopies and calls for much more complex (13)C NMR elucidations. High-temperature cryoprobes have dramatically shortened the acquisition time of (13)C NMR spectra, and few minutes are now enough for polyolefin classification purposes; however, conventional data analysis remains labor and time-consuming. In this paper, we introduce an instrument for automated fast determinations of the (13)C NMR microstructure on polyolefin materials, implemented by integrating High-Throughput Experimentation and Data Science tools and methods. From the scientific standpoint, the main interest of the approach is the solution proposed to address the general problem how to rapidly characterize statistically distributed analytes, of which synthetic polymers are a most important case. In practical terms, the instrument represents the first automated tool for microstructural polyolefin analysis: it is readily applicable to monomaterials, whereas extension to multimaterials, including postconsumer streams, is feasible but still requires some work.