中国电机工程学报2024，Vol.44Issue(24)：9743-9752,中插19,11.DOI:10.13334/j.0258-8013.pcsee.232015
一种预测Mn/Fe复合氧化物对燃煤烟气中砷、硒吸附特性的新方法
A New Method for Predicting the Adsorption Properties of Mn/Fe Binary Oxides for Arsenic and Selenium in Coal Flue Gas
摘要
Abstract
Mn/Fe binary oxides have gained significant attention due to their excellent adsorption potential for arsenic and selenium in coal-fired flue gas.However,their adsorption performance is influenced by both the preparation process of the adsorbent and the adsorption process itself,and experimental testing is characterized by high costs and lengthy cycles.A new predictive model is established based on the physicochemical properties of the adsorbent and its adsorption capacity.This model compares the surface structure differences of adsorbents with different molar ratios and calculates various parameters such as the conversion rate and activation energy of arsenic and selenium at different temperatures.Subsequently,the respective impact magnitudes of these factors are incorporated into the mathematical model,allowing the model to predict the adsorption efficiency of the adsorbent under different conditions.The results of the model calculations indicate that the maximum adsorption capacity for arsenic and selenium is achieved when the Mn/Fe molar ratio is 1:1.The optimal adsorption temperatures for arsenic and selenium are 750 and 600℃,respectively.The adsorption flux coefficients of arsenic and selenium show an initial increase followed by a decrease with increasing temperature.The adsorption flux coefficients are positively correlated with the morphological structure of the adsorbent at different temperatures.A comparative analysis between predicted values and experimental values confirms the accuracy of this method.This research provides a novel approach beyond experimental means for identifying efficient heavy metal adsorbents.关键词
燃煤烟气/吸附剂/砷/硒/预测模型Key words
coal flue gas/adsorbent/arsenic/selenium/prediction model分类
资源环境引用本文复制引用
王震,邢佳颖,袁潇,王春波..一种预测Mn/Fe复合氧化物对燃煤烟气中砷、硒吸附特性的新方法[J].中国电机工程学报,2024,44(24):9743-9752,中插19,11.基金项目
国家重点研发计划项目(2020YFB0606301) （2020YFB0606301）
国家自然科学基金项目(51976059).National Key R&D Program of China(2020YFB0606301) （51976059）
Project Supported by National Natural Science Foundation of China(51976059). （51976059）
