Abstract
The catalytic decomposition of hydrazine using metallic nanoparticles has recently attracted considerable attention as this provides a promising means for highly efficient hydrogen release desired for a cleaner economy; however, the efficient catalytic nanoparticles model is still controversial. To shed further light on the optimal morphology of rhodium nanoparticles reported as the most efficient catalyst for this reaction, a more realistic nanocluster (Rhn) model is implemented here to compare the adsorption energies of hydrazine on these nanoclusters using the density functional theory. These nanoclusters (Rhn) comprise a varied number of Rh atom (n = 13–201), with their pre-constructed shapes but further defined by the highest energy optimization. Our calculations unravel that the vertex atoms of an Rhn nanocluster are the most favoured sites for N2H4 adsorption, in comparison with edge atoms or inner atoms of facets. Notably, the computed adsorption energies (Eads) clearly exhibit a linear dependence on their sizes effective particle diameter (r), with the equation Eads = − 1.30 + (− 0.24) r established. Further calculations on the introduction of adatoms to the regular nanoclusters demonstrated that the stepped facet plays a decisive role in determining the adsorption energy. Moreover, the electronic structure and charge transfer calculations revealed the dative-type binding nature of the N–Rh bond. These results highlight the importance of a more realistic particle model used for such adsorption studies and provide new insights into the design and development of nanocatalysts for the decomposition of hydrazine.
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Acknowledgements
This work is financially supported by the National Natural Science Foundation of China (21571119), Australian Research Council (DP180101581), the Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi (STIP) (2016174) and the Doctoral Scientific Research Foundation of Changzhi Medical College (BS15014).
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He, Y., Yu, J., Wu, H. et al. Defining the optimal morphology of Rhn nanoparticles for efficient hydrazine adsorption: a DFT-D3 study. J Mater Sci 54, 9533–9542 (2019). https://doi.org/10.1007/s10853-019-03579-5
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DOI: https://doi.org/10.1007/s10853-019-03579-5