Atomic doping in catalysts is an effective strategy for adjusting their catalytic activity, which has recently been applied to promote sulfur reduction reactions (SRRs) on the cathode of lithium-sulfur (Li-S) batteries. Herein, the electrocatalytic SRR mechanism of eight metal atom (Ca, Ti, V, Cr, Mn, Fe, Co or Ni) doped Chevrel phase MoSe were investigated using density functional theory (DFT) calculations. The results reveal that the interaction between polysulfides and the catalyst mainly originates from the coupling of d and d orbitals of doped metals and the 3p orbitals of S. The Ti-doped MoSe system significantly reduces the overpotential of the SRR to only 0.21 V. After analyzing SRR processes over doped and undoped MoSe, no scalar relationship was found between the adsorption energies () of various polysulfides. Instead, a linear relationship is established between 4 - and overpotential. Finally, a linear relationship between overpotential and descriptors was established based on a machine learning (ML) method, which can accurately predict the overpotential of the SRR over the MoSe catalyst. This work provides new theoretical insights into the SRR mechanism over metal-selenides and the rational design of a catalyst for Li-S batteries.
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http://dx.doi.org/10.1039/d3nr06009h | DOI Listing |
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