祝贺张伟进论文“A novel intelligent system based on machine learning for hydrochar multi-target prediction from the hydrothermal carbonization of biomass”被Biochar（IF：12.7）接收发表！
发布时间：2023-12-23
点击次数：
简介：Hydrothermal carbonization (HTC) is a thermochemical conversion technology to produce hydrochar from wet biomass without drying, but it is time-consuming and expensive to experimentally determine the optimal HTC operational conditions of specific biomass to produce desired hydrochar. Therefore, a machine learning (ML) approach was used to predict and optimize hydrochar properties. Specifically, the biochemical components (proteins, lipids, and carbohydrates) of biomass were predicted and analyzed first via elementary compositions. Then, the accurate single-biomass (no mixtures) basis ML multi-target models (average R2 = 0.93 and RMSE = 2.36) were built to predict and optimize the hydrochar properties (yield, elemental composition, elemental atomic ratio, and higher heating values). This study advances the field by integrating predictive modeling and mechanistic insights, offering a holistic approach to the precise control and optimization of hydrochar production through HTC.
是否译成外文：否
上一条： 祝贺孟凡悦论文“Biomimetic Mercury Immobilization by Selenium Functionalized Polyphenylene Sulfide Fabric”被Nature Communications（IF：16.6）接收发表！
下一条： 祝贺周军辉论文“Machine-learning-aided hydrochar production through hydrothermal carbonization of biomass by engineering operating parameters and/or biomass mixture recipes”被Energy（IF：9.0）接收发表！