Department of Chemistry, Brown University, Providence, Rhode Island 02912, United States.
School of Engineering, Brown University, Providence, Rhode Island 02912, United States.
J Am Chem Soc. 2020 Nov 11;142(45):19209-19216. doi: 10.1021/jacs.0c08962. Epub 2020 Oct 30.
Tuning the performance of nanoparticle (NP) catalysts by controlling the NP surface strain has evolved as an important strategy to optimize NP catalysis in many energy conversion reactions. Here, we present our new study on using an eigenforce model to predict and experiments to verify the strain-induced catalysis enhancement of the oxygen reduction reaction (ORR) in the presence of L1-CoMPt NPs (M = Mn, Fe, Ni, Cu, Ni). The eigenforce model allowed us to predict anisotropic (that is, two-dimensional) strain levels on distorted Pt(111) surfaces. Experimentally, by preparing a series of 5 nm L1-CoMPt NPs, we could push the ORR catalytic activity of these NPs toward the optimum region of the theoretical two-dimensional volcano plot predicted for L1-CoMPt. The best ORR catalyst in the alloy NP series we studied is L1-CoNiPt, which has a mass activity of 3.1 A/mg and a specific activity of 9.3 mA/cm at room temperature with only 15.9% loss of mass activity after 30 000 cycles at 60 °C in 0.1 M HClO.
通过控制纳米颗粒 (NP) 表面应变来调整 NP 催化剂的性能，已成为优化许多能量转换反应中 NP 催化作用的重要策略。在这里，我们介绍了一项新的研究，该研究使用本征力模型来预测和实验来验证 L1-CoMPt NPs（M = Mn、Fe、Ni、Cu、Ni）存在时氧还原反应 (ORR) 的应变诱导催化增强。本征力模型使我们能够预测扭曲 Pt(111) 表面的各向异性（即二维）应变水平。实验上，通过制备一系列 5nm 的 L1-CoMPt NPs，我们可以将这些 NPs 的 ORR 催化活性推向 L1-CoMPt 的二维火山图理论最优区域。在我们研究的合金 NP 系列中，最佳的 ORR 催化剂是 L1-CoNiPt，其在室温下的质量活性为 3.1 A/mg，比活性为 9.3 mA/cm，在 60°C 的 0.1 M HClO 中循环 30000 次后，质量活性仅损失 15.9%。
