差异化电子密度特征基团对煤氮迁移转化的影响机理  

Mechanistic of the effect of differential electron density characteristic groups on the nitrogen migration transformation in coal

作　　者：王欣 张海 王凯[1] 范卫东[1] WANG Xin;ZHANG Hai;WANG Kai;FAN Weidong(School of Mechanical and Power Engineering,Shanghai Jiao Tong University,Shanghai 200240,China)

机构地区：[1]上海交通大学机械与动力工程学院,上海200240

出　　处：《洁净煤技术》2024年第11期24-32,共9页Clean Coal Technology

基　　金：国家重点研发计划资助项目(2023YFB4005700);国家自然科学基金面上资助项目(52276127);上海市自然科学基金面上资助项目(21ZR1434300)。

摘　　要：选择吡咯含氮杂环和吡啶含氮杂环为研究对象,在此基础上研究了煤热解氮组分迁移转化的官能团作用规律。首先,通过CBS-QB3方法对吡咯和吡啶热解生成HCN和NH_(3)的路径进行优化,获得了相应的反应势能面,其次,基于Pauling电负性计算了基团的键极指数加和值,将官能团分为给电子基团和吸电子基团,评估分析了28种不同类型官能团的性质,在此基础上优化了吡咯和吡啶衍生物的累计112条氮迁移转化路径。我们发现在吸电子基团作用下,热解反应需要更高的热量和能垒,而给电子基团则可以降低热解反应的热量和能垒,使热解更容易发生。最后,论文从DFT计算优化成功的结构中得到量子化学描述符,并通过比较皮尔逊相关系数筛选得到了12种合适的描述符,结合多元线性回归模型对煤氮迁移转化过程中的最高反应活化能进行了预测,所构建的MLR模型训练集决定系数为0.83,均方根误差为0.41,测试集的决定系数为0.92,均方根误差为0.29,其拟合和预测性能良好,可被用于预测活化能通过多元线性回归方程可以发现,基团类型的系数最大(0.71),其次是反应物的能隙(0.64)以及反应物和产物能隙的差(-0.59),进一步证实了基团类型对氮迁移转化的重要影响。本文的研究结论将有助于新型超低NOx燃烧技术的开发。The choice of pyrrole-and pyridine-containing nitrogen heterocycles as the subject of this paper was made in,and based on this,the mechanism and pattern of action of the influence of functional groups on the migration and transformation of nitrogen components of coal pyrolysis were studied.First,the CBS-QB3 was used to optimize the paths of pyrrole and pyridine pyrolysis to HCN and NH_(3),and the corresponding reaction potential energy surfaces were derived.Additionally,the accumulated 112 nitrogen migration conversion pathways of pyrrole and pyridine derivatives were optimized,the functional groups were divided into electron-donating(EDG)and electron-withdrawing groups(EWG),and the summation values of the bond polarity indices of the groups were calculated based on Pauling electronegativity.Finally,12 appropriate descriptors were screened by comparing Pearson correlation coefficients,which were derived from the structures effectively optimized by DFT calculations.By integrating multiple linear regression models,the greatest response activation energy in the coal-nitrogen migration conversion process was predicted,and the MLR model constructed had a coefficient of determination of 0.83,a root mean square error of 0.41 for the training set and a coefficient of determination of 0.92 and a root mean square error of 0.29 for the test set.The model could be used to estimate activation energy since it has high fitting and prediction ability.An in-depth analysis of the multiple linear regression equation of the model reveals that the coefficient of the group type is the largest(0.71),followed by the energy gap of the reactants(0.64)and the difference between the energy gaps of the reactants and products(-0.59),further confirming the significant influence of the group type on the nitrogen migration transformation.The findings of this paper can guide the mechanistic study of coal nitrogen migration conversion and aid in the creation of new ultra-low NOx combustion technologies.

关 键 词：模型煤 热解 官能团 密度泛函理论 活化能 氮氧化合物 

分 类 号：TK16[动力工程及工程热物理—热能工程]