祝贺李唐昊论文“Machine learning-aided prediction of nitrogen heterocycles in bio-oil from the pyrolysis of biomass”被Energy（IF：8.857）接收发表！

Release time:2023-06-03

Description of Publication:Nitrogen heterocyclic compounds in bio-oil (NH_Oil) made from biomass pyrolysis such as pyrroles, pyrazines, and indoles, have a relative content of 0–30%. NH_Oil is a NOx precursor if bio-oil is used as a fuel, but it has a high potential as a precursor for high-value chemicals. However, predicting and controlling NH_Oil are challenging because of the complexity of the pyrolysis reaction system. Machine learning (ML) shows significant potential for addressing this issue. In this study, the relative contents of NH_Oil, 5-membered NH_Oil, 6-membered NH_Oil, bio-oil yield, and the content of nitrogen in bio-oil were predicted using Random Forest and gradient boosting regression algorithms, with test regression coefficients values of 0.77–0.87 and 0.74–0.81, respectively. The optimization of pyrolysis parameters within ML models provides useful information for instructing experimental studies, indicating ML-aided bio-oil prediction and engineering show great promise.

Translated or Not:no