水处理过程中的催化臭氧化催化剂的分子设计
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摘要
饮用水中难降解的微量有机物所造成的污染,是给水处理所面临的主要问题之一。金属催化臭氧化是近些年来发展起来的一种高级氧化技术,它是去除水中难降解有机物的有效方法之一,而高效催化臭氧化催化剂的研制是金属催化臭氧化技术的核心和难点。
本项研究以Al2O3为载体,采用浸渍法分别制备Cu、Mn、Fe、Ni、Co等五种金属催化臭氧化催化剂。催化剂活性实验结果表明:Cu系催化剂具有最好的催化效果。
在实验研究基础上,进行了催化剂分子设计的初步研究。使用Gaussian03量化计算软件建立了M2O2(M分别为Fe、Mn、Co、Ni、Cu )团簇分子顶位和桥位吸附模型,用密度泛函B3LYP/LANL2DZ方法,对于五种过渡金属催化臭氧化催化剂的氧化物团簇模型,进行了臭氧顶位和桥位吸附方式和吸附途径的研究。计算结果表明:Cu2O2团簇的吸附能最大,从而吸附活性最好,与实验结果相同。价层轨道和外层电子在O3吸附前后的计算结果表明:O-Cu吸附键的形成是由于被吸附点的d电子转移到了吸附点P轨道上,而吸附点P轨道上的极少部分电子反馈到被吸附点的d轨道上。Cu2O2团簇平行、垂直桥位吸附势能面扫描说明: O3分子更加容易垂直桥位吸附在Cu系催化剂上。
利用Materials Studio材料计算软件建立了CuO(110)(1×1)层状O3分子垂直吸附模型,PW91密度泛函优化结果表明:臭氧分子吸附后,它的S、P态密度都发生了较大的变化,能带发生连续;被吸附点Cu的d态密度也发生变化,能带范围变小。O-Cu吸附键的形成是O3的S、P与被吸附点的d态重叠和金属上的d电子转移到吸附点的S、P轨道上的结果。这与Gaussian03的计算结果相同。
应用典型相关分析筛选择变量,3层(M-N-1)BP人工神经网络方法对臭氧分子垂直、平行桥位吸附在Cu2O2团簇和臭氧分子垂直桥位吸附在Cu4O4团簇上的三种模型分别进行QSAR关系模拟。模拟结果得到BP神经网络期望值和输出值的相关系数都在0.9以上和QSAR关系为BP7-7-1。
The pollution of the drinker water, which is especially worked by minim contamination of organic evenlly, is one of the main problems in feedwater treatment. Catalytic ozonation of metals which is developing in recently is a efficiency method to treat contamination of organic of difficult settled.the preparation method of Catalytic ozonation of metals is not only a large work,but also is a small efficiency in tradition of search for.
Soaking method is used to make catalyst such as Cu/Al_2O_3、Mn/Al_2O_3、Fe/Al_2O_3、Ni/Al_2O_3 and Co/Al_2O_3. Removal rate of UV254 and TOC shows the activity of catalytic ozonation catalyst of Cu/Al_2O_3 is best.
It established cluster of M2O2 about model of bridge and tip adsorption, the M separate represent Fe、Mn、Co、Ni and Cu. Optimizing of cluster of M2O2 shows that energy of Cu2O2 is the largest, so its active of catalytic is best. this is the same as result of experiment. Their price orbit and deep electron in adsorbing O3 after show d electron of Cu transfer to p orbit of O, p orbit of O has small electron transferring to d orbit of Cu. It scans potential energy of cluster of Cu2O2,its result show O3 is easier adsorbed in vertical bridge than parallel bridge.
It established samdwich model of CuO(110)(1×1) in which O3 adsorbed with vertical way by using Materials Studio software. Its Optimizing of result shows that after O_3 adsorbed, S and P state density of O3 have large changes, energy strip appears concatenation. d state density of Cu has also change, but the bound of energy strip get smaller, the bond of adsorption O-Cu is because of d electron of Cu transfering to p and s orbit of O. this is the same as calculation of Gaussian 03.
Applying analyse of type correlation to choose variable and 3 layers (M-N-1) BP neural networks simulate QSAR to O_3 of vertical bridge adsorbing in the cluster of Cu2O2,to O_3 of parallel bridge adsorbing in the cluster of Cu2O2,and to O3 of vertical bridge adsorbing in the cluster of Cu4O4,respectively. The result of simulation makes know coefficient correlation of vaule of expectation and vaule of output about BP neural networks is larger 0.9,and the QSAR is BP7-7-1.
本项研究以Al2O3为载体,采用浸渍法分别制备Cu、Mn、Fe、Ni、Co等五种金属催化臭氧化催化剂。催化剂活性实验结果表明:Cu系催化剂具有最好的催化效果。
在实验研究基础上,进行了催化剂分子设计的初步研究。使用Gaussian03量化计算软件建立了M2O2(M分别为Fe、Mn、Co、Ni、Cu )团簇分子顶位和桥位吸附模型,用密度泛函B3LYP/LANL2DZ方法,对于五种过渡金属催化臭氧化催化剂的氧化物团簇模型,进行了臭氧顶位和桥位吸附方式和吸附途径的研究。计算结果表明:Cu2O2团簇的吸附能最大,从而吸附活性最好,与实验结果相同。价层轨道和外层电子在O3吸附前后的计算结果表明:O-Cu吸附键的形成是由于被吸附点的d电子转移到了吸附点P轨道上,而吸附点P轨道上的极少部分电子反馈到被吸附点的d轨道上。Cu2O2团簇平行、垂直桥位吸附势能面扫描说明: O3分子更加容易垂直桥位吸附在Cu系催化剂上。
利用Materials Studio材料计算软件建立了CuO(110)(1×1)层状O3分子垂直吸附模型,PW91密度泛函优化结果表明:臭氧分子吸附后,它的S、P态密度都发生了较大的变化,能带发生连续;被吸附点Cu的d态密度也发生变化,能带范围变小。O-Cu吸附键的形成是O3的S、P与被吸附点的d态重叠和金属上的d电子转移到吸附点的S、P轨道上的结果。这与Gaussian03的计算结果相同。
应用典型相关分析筛选择变量,3层(M-N-1)BP人工神经网络方法对臭氧分子垂直、平行桥位吸附在Cu2O2团簇和臭氧分子垂直桥位吸附在Cu4O4团簇上的三种模型分别进行QSAR关系模拟。模拟结果得到BP神经网络期望值和输出值的相关系数都在0.9以上和QSAR关系为BP7-7-1。
The pollution of the drinker water, which is especially worked by minim contamination of organic evenlly, is one of the main problems in feedwater treatment. Catalytic ozonation of metals which is developing in recently is a efficiency method to treat contamination of organic of difficult settled.the preparation method of Catalytic ozonation of metals is not only a large work,but also is a small efficiency in tradition of search for.
Soaking method is used to make catalyst such as Cu/Al_2O_3、Mn/Al_2O_3、Fe/Al_2O_3、Ni/Al_2O_3 and Co/Al_2O_3. Removal rate of UV254 and TOC shows the activity of catalytic ozonation catalyst of Cu/Al_2O_3 is best.
It established cluster of M2O2 about model of bridge and tip adsorption, the M separate represent Fe、Mn、Co、Ni and Cu. Optimizing of cluster of M2O2 shows that energy of Cu2O2 is the largest, so its active of catalytic is best. this is the same as result of experiment. Their price orbit and deep electron in adsorbing O3 after show d electron of Cu transfer to p orbit of O, p orbit of O has small electron transferring to d orbit of Cu. It scans potential energy of cluster of Cu2O2,its result show O3 is easier adsorbed in vertical bridge than parallel bridge.
It established samdwich model of CuO(110)(1×1) in which O3 adsorbed with vertical way by using Materials Studio software. Its Optimizing of result shows that after O_3 adsorbed, S and P state density of O3 have large changes, energy strip appears concatenation. d state density of Cu has also change, but the bound of energy strip get smaller, the bond of adsorption O-Cu is because of d electron of Cu transfering to p and s orbit of O. this is the same as calculation of Gaussian 03.
Applying analyse of type correlation to choose variable and 3 layers (M-N-1) BP neural networks simulate QSAR to O_3 of vertical bridge adsorbing in the cluster of Cu2O2,to O_3 of parallel bridge adsorbing in the cluster of Cu2O2,and to O3 of vertical bridge adsorbing in the cluster of Cu4O4,respectively. The result of simulation makes know coefficient correlation of vaule of expectation and vaule of output about BP neural networks is larger 0.9,and the QSAR is BP7-7-1.
引文
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