Advances in machine learning-driven lignin valorization: from dissolution, characterization, to high-value conversion

Fuente: Green Chemistry
Green Chem., 2026, Accepted ManuscriptDOI: 10.1039/D6GC02374F, Tutorial ReviewWeilu Ding, Yongjiang Hu, Yumiao Lu, Ziqi Zhai, Kaixuan Li, Hongyan HeLignin is the most abundant renewable aromatic carbon resource on Earth, offering tremendous potential for the sustainable production of high-value chemicals and materials. Machine learning (ML) has demonstrated remarkable capabilities...The content of this RSS Feed (c) The Royal Society of Chemistry