Machine learning investigates the overlooked organic excitation effects in the UV/PS system by UV185
|更新时间:2025-04-10
|
Machine learning investigates the overlooked organic excitation effects in the UV/PS system by UV185
“In the field of pollutant degradation, researchers have combined machine learning and DFT calculations to explore the mechanism of UV185 in vacuum ultraviolet persulfate systems, providing new ideas for improving pollutant degradation efficiency.”
Journal of Civil and Environmental EngineeringPages: 1-10(2025)
作者机构:
重庆大学 三峡库区生态环境教育部重点实验室,重庆 400045
作者简介:
brief: LUO Jingyao (2000- ), main research interest: advanced oxidation, E-mail: 15828569492@139.com.
LUO Jingyao,ZHEN Peng,LIU Yudan,et al.Machine learning investigates the overlooked organic excitation effects in the UV/PS system by UV185[J].Journal of Civil and Environmental Engineering,
LUO Jingyao,ZHEN Peng,LIU Yudan,et al.Machine learning investigates the overlooked organic excitation effects in the UV/PS system by UV185[J].Journal of Civil and Environmental Engineering,DOI:10.11835/j.issn.2096-6717.2025.014.
Machine learning investigates the overlooked organic excitation effects in the UV/PS system by UV185
Prediction of CO2 adsorption performance in porous biochar based on machine learning
Multi-objective optimization design method of modular steel frame structure in cold regions
Machine learning method for overall stability of welded constant section box columns made of high strength steel
Review and prospect of machine learning method in shield tunnel construction
Efficient interpolation method for 2D non-stationary CPT data using Gibbs sampling and compressive sampling
Related Author
QIN Yinghong
WANG Junsong
TAN Kanghao
ZHANG Xiaoqing
CHEN Yifei
MA Guowei
ZHANG Yufen
DONG Wei
Related Institution
School of Civil Engineering and Architecture; Key Laboratory of Disaster Prevention and Engineering Safety of Guangxi, Guangxi University
State Key Laboratory of Subtropical Building Science, South China University of Technology
School of Civil and Transportation Engineering; Hebei University of Technology
a. School of Mechanics and Civil Engineering; 1b. Jiangsu Key Laboratory of Environmental Disaster and Structural Reliability of Civil Engineering, China University of Mining and Technology, Xuzhou 221116, Jiangsu, P. R. China; 2. South Branch of China Construction Eighth Engineering Bureau Co., Ltd, Shenzhen 518035, Guangdong, P. R. China; 3. College of Civil Engineering, Southwest Jiaotong University, Chendu