Details

Autor(en) / Beteiligte

• Yao, Yonggang
• Liu, Zhenyu
• Xie, Pengfei
• Huang, Zhennan
• Li, Tangyuan
• Morris, David
• Finfrock, Zou
• Zhou, Jihan
• Jiao, Miaolun
• Gao, Jinlong
• Mao, Yimin
• Miao, Jianwei John
• Zhang, Peng
• Shahbazian-Yassar, Reza
• Wang, Chao
• Wang, Guofeng
• Hu, Liangbing

Titel

Computationally aided, entropy-driven synthesis of highly efficient and durable multi-elemental alloy catalysts

Ist Teil von

• Science advances, 2020-03, Vol.6 (11), p.eaaz0510-eaaz0510

Ort / Verlag

United States: AAAS

Erscheinungsjahr

2020

Quelle

Free E-Journal (出版社公開部分のみ）

Beschreibungen/Notizen

• Multi-elemental alloy nanoparticles (MEA-NPs) hold great promise for catalyst discovery in a virtually unlimited compositional space. However, rational and controllable synthesize of these intrinsically complex structures remains a challenge. Here, we report the computationally aided, entropy-driven design and synthesis of highly efficient and durable catalyst MEA-NPs. The computational strategy includes prescreening of millions of compositions, prediction of alloy formation by density functional theory calculations, and examination of structural stability by a hybrid Monte Carlo and molecular dynamics method. Selected compositions can be efficiently and rapidly synthesized at high temperature (e.g., 1500 K, 0.5 s) with excellent thermal stability. We applied these MEA-NPs for catalytic NH decomposition and observed outstanding performance due to the synergistic effect of multi-elemental mixing, their small size, and the alloy phase. We anticipate that the computationally aided rational design and rapid synthesis of MEA-NPs are broadly applicable for various catalytic reactions and will accelerate material discovery.