纳米催化剂活性中心的原子尺度识别
Atomic-scale identification of the active sites of nanocatalysts
摘要：
合金纳米催化剂在燃料电池、催化转化器和加氢反应等领域有着广泛的应用。尽管进行了广泛的研究，但由于局部原子环境的异质性，确定纳米催化剂的活性位点仍然是一个重大挑战。在这里，我们先进的原子电子断层扫描，以确定三维局部原子结构，表面形貌和化学组成的PtNi和Mo掺杂的PtNi纳米催化剂。使用通过密度泛函理论计算训练的机器学习，我们从实验的3D原子坐标中识别出氧还原反应的催化活性位点，并通过电化学测量证实。通过量化构效关系，我们发现了一个局部环境描述符，可以在原子水平上解释和预测催化活性中心。确定3D原子结构和化学物种的能力与机器学习相结合，有望扩大我们对各种纳米催化剂的基本理解。
英文摘要：
Alloy nanocatalysts have found broad applications ranging from fuel cells to catalytic converters and hydrogenation reactions. Despite extensive studies, identifying the active sites of nanocatalysts remains a major challenge due to the heterogeneity of the local atomic environment. Here, we advance atomic electron tomography to determine the 3D local atomic structure, surface morphology and chemical composition of PtNi and Mo-doped PtNi nanocatalysts. Using machine learning trained by density functional theory calculations, we identify the catalytic active sites for the oxygen reduction reaction from experimental 3D atomic coordinates, which are corroborated by electrochemical measurements. By quantifying the structure-activity relationship, we discover a local environment descriptor to explain and predict the catalytic active sites at the atomic level. The ability to determine the 3D atomic structure and chemical species coupled with machine learning is expected to expand our fundamental understanding of a wide range of nanocatalysts.
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