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Harnessing strong metal-support interactions via a reverse route.

Peiwen WuShuai TanJisue MoonZihao YanVictor FungNa LiShi-Ze YangYongqiang ChengCarter W AbneyZili WuAditya A SavaraAyyoub M MomenDe-En JiangDong SuHuaming LiWenshuai ZhuSheng DaiHuiyuan Zhu
Published in: Nature communications (2020)
Engineering strong metal-support interactions (SMSI) is an effective strategy for tuning structures and performances of supported metal catalysts but induces poor exposure of active sites. Here, we demonstrate a strong metal-support interaction via a reverse route (SMSIR) by starting from the final morphology of SMSI (fully-encapsulated core-shell structure) to obtain the intermediate state with desirable exposure of metal sites. Using core-shell nanoparticles (NPs) as a building block, the Pd-FeOx NPs are transformed into a porous yolk-shell structure along with the formation of SMSIR upon treatment under a reductive atmosphere. The final structure, denoted as Pd-Fe3O4-H, exhibits excellent catalytic performance in semi-hydrogenation of acetylene with 100% conversion and 85.1% selectivity to ethylene at 80 °C. Detailed electron microscopic and spectroscopic experiments coupled with computational modeling demonstrate that the compelling performance stems from the SMSIR, favoring the formation of surface hydrogen on Pd instead of hydride.
Keyphrases
  • machine learning
  • big data
  • deep learning
  • artificial intelligence
  • molecular dynamics simulations
  • transition metal