兴奋剂
氨
钼
金属
选择(遗传算法)
氧化物
材料科学
组合化学
化学
计算机科学
无机化学
光电子学
有机化学
机器学习
作者
Dongwook Kwak,Henry J. Sokol,Bryan P. Moser,Heejeong Ryu,Kristie J. Koski,Radenka Marić,Liang Zhang,Yu Lei
标识
DOI:10.1109/sensors43011.2019.8956917
摘要
In this study, DFT simulation was employed to direct the selection of high-performance metal-doped MoO 3 for NH3 sensing. Sn-doped MoO 3 nanoribbons, predicted by the DFT simulation, were also synthesized and tested for NH 3 gas sensing with good sensing performance. This study indicates that DFT-simulation-directed selection of high-performance materials could play a significant role in future gas sensor development.
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