NH3Cu+Cu-CHA,

Reisel Millan1,2, Estefanía Bello-Jurado2, Manuel Moliner2

  • 1Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.

ACS central science
|November 30, 2023
PubMed
概括

机器学习潜力使铜交换热石的大规模模拟成为可能,揭示了配对和氨度影响铜离子的移动性. 这一发现对于优化 NOx 选择性催化降解等反应中的催化剂至关重要.