Giampaolo Fabio, Cipullo Roberta, Cuomo Salvatore, Piccialli Francesco, Busico Vincenzo
Department of Mathematics and Applications "R. Caccioppoli", University of Naples Federico II, 80126 Naples, Italy.
Department of Chemical Sciences, University of Naples Federico II, 80126 Naples, Italy.
Anal Chem. 2025 Feb 4;97(4):2503-2510. doi: 10.1021/acs.analchem.4c06290. Epub 2025 Jan 21.
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 C NMR elucidations. High-temperature cryoprobes have dramatically shortened the acquisition time of 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 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.
聚烯烃在合成聚合物中独具特色,因为它们广泛的应用范围源于对烃链微观结构的精细控制,且不含任何独特的官能团。这妨碍了基于振动光谱的自动分选方法,需要更复杂的碳核磁共振(¹³C NMR)解析。高温低温探头极大地缩短了¹³C NMR谱图的采集时间,现在几分钟就足以用于聚烯烃分类;然而,传统的数据分析仍然既费力又耗时。在本文中,我们介绍了一种用于自动快速测定聚烯烃材料¹³C NMR微观结构的仪器,该仪器通过整合高通量实验和数据科学工具及方法实现。从科学角度来看,该方法的主要意义在于提出了解决如何快速表征统计分布分析物这一普遍问题的方案,其中合成聚合物是最重要的一类情况。实际上,该仪器是首个用于聚烯烃微观结构分析的自动化工具:它易于应用于单一材料,而扩展到包括消费后废物流在内的多材料分析是可行的,但仍需要一些工作。