A novel intelligent system based on machine learning for hydrochar multi-target prediction from the hydrothermal carbonization of biomass

被引:0
作者
Weijin Zhang
Junhui Zhou
Qian Liu
Zhengyong Xu
Haoyi Peng
Lijian Leng
Hailong Li
机构
[1] Central South University,School of Energy Science and Engineering
[2] Xiangjiang Laboratory,undefined
[3] Hunan Modern Environmental Technology Co.,undefined
[4] LTD.,undefined
来源
Biochar | / 6卷
关键词
Biomass; Hydrothermal carbonization; Hydrochar; Machine learning; Intelligent prediction system;
D O I
暂无
中图分类号
学科分类号
摘要
Biochemical components of biomass were first predicted by elemental composition.The multi-target ML model accurately predicted hydrochar with R2 = 0.93.The ash, T, N, and C were the most critical factors affecting hydrochar properties.An online intelligent system based on optimal models was posted and verified.
引用
收藏
相关论文
共 156 条
[1]  
Buss W(2019)Synergies between BECCS and biochar—maximizing carbon sequestration potential by recycling wood ash ACS Sustain Chem Eng 7 4204-4209
[2]  
Jansson S(2022)Automated machine learning structure-composition-property relationships of perovskite materials for energy conversion and storage Energy Mater 1 100006-719
[3]  
Wurzer C(2013)Hydrothermal processing of duckweed: effect of reaction conditions on product distribution and composition Bioresour Technol 135 710-745
[4]  
Mašek O(2018)Integration of hydrothermal liquefaction and supercritical water gasification for improvement of energy recovery from algal biomass Energy 155 734-356
[5]  
Deng Q(1956)Colorimetric method for determination of sugars and related substances Anal Chem 28 350-1810
[6]  
Lin B(2022)Process optimization of biomass gasification with a Monte Carlo approach and random forest algorithm Energy Convers Manag 264 1802-297
[7]  
Duan P(2022)Predicting crop root concentration factors of organic contaminants with machine learning models J Hazard Mater 424 271-488
[8]  
Chang Z(2022)Process water recirculation for catalytic hydrothermal carbonization of anaerobic digestate: water-energy-nutrient nexus Bioresour Technol 361 482-1889
[9]  
Xu Y(2022)Catalytic co-hydrothermal carbonization of food waste digestate and yard waste for energy application and nutrient recovery Bioresour Technol 344 1883-1809
[10]  
Duan PG(2011)Hydrothermal carbonization (HTC) of lignocellulosic biomass Energy Fuels 25 1786-114