首页|Harbin Institute of Technology Reports Findings in Machine Learning (Promotion of anaerobic biodegradation of azo dye RR2 by different biowaste-derived biochars: Characteristics and mechanism study by machine learning)
Harbin Institute of Technology Reports Findings in Machine Learning (Promotion of anaerobic biodegradation of azo dye RR2 by different biowaste-derived biochars: Characteristics and mechanism study by machine learning)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
New research on Machine Learning is the subject of a report. According to news reporting originating from Harbin, People's Republic of China, by NewsRx correspondents, research stated, "The addition of biochar resulted in a 31.5 % to 44.6 % increase in decolorization efficiency and favorable decolorization stability. Biochar promoted extracellular polymeric substances (EPS) secretion, especially humic-like and fulvic-like substances." Our news editors obtained a quote from the research from the Harbin Institute of Technology, "Additionally, biochar enhanced the electron transfer capacity of anaerobic sludge and facilitated surface attachment of microbial cells. 16S rRNA gene sequencing analysis indicated that biochar reduced microbial species diversity, enriching fermentative bacteria such as Trichococcus. Finally, a machine learning model was employed to establish a predictive model for biochar characteristics and decolorization efficiency. Biochar electrical conductivity, H/C ratio, and O/C ratio had the most significant impact on RR2 anaerobic decolorization efficiency."
HarbinPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
