祝贺张伟进论文“Machine learning prediction of nitrogen heterocycles in bio-oil produced from hydrothermal liquefaction of biomass”被Bioresource Technology（IF：11.889）接收发表！

Release time:2022-08-13

Description of Publication:Hydrothermal liquefaction (HTL) of high-moisture biomass or biowaste to produce bio-oil is a promising technology. However, nitrogen-heterocycles (N-H) presence in bio-oil is a bottleneck to the upgrading and utilization of bio-oil. The present study applied the machine learning (ML) method (random forest) to predict and help control the bio-oil N-H, bio-oil yield, and N content of bio-oil (N_oil). The results indicated that the predictive performance of the yield and N_oil were better than previous studies. Acceptable predictive performance for the prediction of N-H was also achieved. The feature importance analysis, partial dependence, and Shapely value were used to interpret the prediction models and study the N-H formation mechanisms and behavior. Then, forward optimization of N-H was implemented based on optimal predictive models, indicating the high potential of ML-aided bio-oil production and engineering.

Translated or Not:no