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arXiv Machine Learning By Jingyang Bai, Zijia Wang, Xiangyi Long, Marcos Millan, Binjian Nie, Mingyue Ding

From fragmented data to actionable design: Physics-calibrated learning for plastic upcycling

Read the original on arXiv Machine Learning →

arXiv:2608. 02402v1 Announce Type: new Abstract: Thermochemical upgrading of plastic waste is a key upcycling pathway, yet the experimental literature is fragmented by heterogeneous conditions and incomplete reporting.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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