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催化. 催化. 这就是催化. 评估计算的催化氨合成速率的可靠性

Andrew J Medford¹, Jess Wellendorff¹, Aleksandra Vojvodic²

¹SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA. SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA.

Science (New York, N.Y.)

|July 12, 2014

概括

我们开发了一种方法来估计密度函数理论 (DFT) 对材料性能计算的不确定性. 这种方法通过量化预测错误和评估催化剂性能概率来改善催化剂的发现.

科学领域:

计算材料科学计算材料科学
催化理论的催化理论
化学反应工程化学反应工程

背景情况:

密度函数理论 (DFT) 被广泛用于预测材料特性.
在DFT计算中量化不确定性对于可靠的预测至关重要,特别是在催化剂中.
氨合成是一个关键的工业过程,正在努力提高催化剂效率.

研究的目的:

开发一种用于估计DFT计算材料属性的不确定性的一般方法.
将这种方法应用于过渡金属催化剂上氨合成的催化速率.
通过结合不确定性,使催化剂选和发现更可靠.

主要方法:

在DFT中量化不确定性的一般框架.
在过渡金属催化剂上的氨合成反应速率的应用.
分析DFT计算中的错误相关性.

主要成果:

计算的催化速率的不确定性在很大程度上取决于反应条件和催化剂材料.
在计算利率中减少预测错误时,DFT错误之间的相关性很重要.
相对催化速率的预测比绝对速率更可靠.
引入了用于催化剂比较的概率方法.

结论:

开发的方法提供了一种可靠的方法来估计基于DFT的材料属性预测中的不确定性.
纳入不确定性对于准确的催化剂选和设计至关重要,特别是对于氨合成.
概率框架有助于用量化的信心识别优质催化剂.

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