AI-Aided Crystallization Elution Fractionation (CEF) Assessment of Polyolefin Resins
Artificial Intelligence (AI) tools and methods are dramatically innovating the application protocols of most polymer characterization techniques. In this paper, we demonstrate that, with the aid of custom-made and properly trained machine learning algorithms, analytical Crystallization Elution Fractionation (aCEF) can be changed from an ancillary to a standalone approach usable to identify and categorize commercially relevant polyolefin materials without any prior information. The proposed protocols are fully operational for monomaterials, whereas for multimaterials, integration with AI-aided <sup>13</sup>C NMR is a realistic intermediate step.
Authors
- Giuseppe Antinucci (ORCID: https://orcid.org/0000-0003-1258-6363)
- Vincenzo Busico (ORCID: https://orcid.org/0000-0001-7079-1651)
- Roberta Cipullo (ORCID: https://orcid.org/0000-0003-3846-1999)
- Lorenzo Brighel
- Gabriella Maria Lucia Scuotto
Institutions
- Dutch Polymer Institute (NL)
- University of Naples Federico II (IT)
Publication Details
- Journal
- Polymers
- Published
- 2025-06-07
- DOI
- https://doi.org/10.3390/polym17121597
- Citations
- 2
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 1.04