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Using data mining technology in screening potential additives to Ni/Al2O3 catalysts for methanation
Catalysis Science & Technology ( IF 5 ) Pub Date : 2017-11-07 00:00:00 , DOI: 10.1039/c7cy01634d
Xiaoxia Han 1, 2, 3, 4 , Chaofan Zhao 1, 2, 3, 4 , Haixia Li 3, 4, 5, 6 , Shusen Liu 3, 4, 5, 6 , Yahong Han 3, 4, 5, 6 , Zhilei Zhang 3, 4, 5, 6 , Jun Ren 3, 4, 5, 6
Affiliation  

In order to improve the catalytic activity, the screening of optimal potential additives to Ni/Al2O3 catalysts for CO methanation was performed by data mining techniques with a combination of principal component analysis, K-means algorithm and Gaussian process regression (GPR). Based on a tremendous amount of data from previous studies, 63 elements excluding gaseous, poisonous and radioactive ones were selected as initial candidates. After the screening by element clustering, the activities of Ni/Al2O3 catalysts promoted by 9 representative elements including Na, Ca, Cr, B, La, Ru, Cu, Zn, and In were measured, and the catalytic activity was analyzed in terms of T50, which represents the temperature at a CO conversion rate of 50%. The activities and physicochemical properties of the nine elements were used to construct regression models by GPR. The regression models predicted that as a potential additive, Re promotes the activity; we experimentally verified that the T50 dropped by 78 °C relative to that of the unmodified Ni/Al2O3 catalyst. It can be considered to be the most effective one of all additives. The advantages of using data mining techniques in catalyst research are that they reduce the number of catalysts to be empirically analyzed and they accelerate the discovery of new catalysts.

中文翻译:

使用数据挖掘技术筛选Ni / Al 2 O 3催化剂中潜在的甲烷化添加剂

为了提高催化活性,通过数据挖掘技术结合主成分分析,K-均值算法和高斯过程回归(GPR),筛选了用于CO甲烷化的Ni / Al 2 O 3催化剂的最佳潜在添加剂。。根据先前研究的大量数据,选择了63种不包括气态,有毒和放射性元素的元素作为初始候选元素。通过元素聚类筛选后,测定了以Na,Ca,Cr,B,La,Ru,Ru,Cu,Zn和In等9种代表性元素促进的Ni / Al 2 O 3催化剂的活性,并对其催化活性进行了分析。根据T 50,代表CO转换率为50%时的温度。通过GPR,利用这9种元素的活性和理化性质构建了回归模型。回归模型预测,作为潜在的添加剂,Re可以促进活性。我们通过实验验证了相对于未改性的Ni / Al 2 O 3催化剂,T 50下降了78°C 。它可以被认为是所有添加剂中最有效的一种。在催化剂研究中使用数据挖掘技术的优势在于,它们减少了需要进行经验分析的催化剂的数量,并加速了新催化剂的发现。
更新日期:2017-11-17
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