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A High‐Rate Li–CO 2 Battery Enabled by 2D Medium‐Entropy Catalyst

Abstract Lithium‐air batteries based on CO 2 reactant (Li–CO 2 ) have recently been of interest because it has been found that reversible Li/CO 2 electrochemistry is feasible. In this study, a new medium‐entropy cathode catalyst, (NbTa) 0.5 BiS 3 , that enables the reversible electrochemistry to operate at high rates is presented. This medium entropy cathode catalyst is combined with an ionic liquid‐based electrolyte blend to give a Li–CO 2 battery that operates at high current density of 5000 mA g −1 and capacity of 5000 mAh g −1 for up to 125 cycles, far exceeding reported values in the literature for this type of battery. The higher rate performance is believed to be due to the greater stability of the multi‐element (NbTa) 0.5 BiS 3 catalyst because of its higher entropy compared to previously used catalysts with a smaller number of elements with lower entropies. Evidence for this comes from computational studies giving very low surface energies (high surface stability) for (NbTa) 0.5 BiS 3 and transmission electron microscopystudies showing the structure being retained after cycling. In addition, the calculations indicate that Nb‐terminated surface promotes Li–CO 2 electrochemistry resulting in Li 2 CO 3 and carbon formation, consistent with the products found in the cell. These results open new direction to design and develop high‐performance Li–CO 2 batteries.

25 ENERGY STORAGE↗

Computational insights into hydrogen adsorption energies on medium-entropy oxides

High entropy oxides (HEOs) have emerged as promising catalysts for several important chemical transformations including alkane activation. Hydrogen adsorption energy (HAE) has been used as a key descriptor for many reactions including methane C–H activation and hydrogen evolution reactions. Hence, understanding the relationship between HAEs and the surface chemistry of HEO surfaces could lay the foundation for meaningful correlations among methane C–H activation, HAE, and the complex, local environment of HEO surfaces. Here, we used a medium-entropy oxide as a prototypical system – Mg 0.25 Ni 0.25 Cu 0.25 Zn 0.25 O with a rock-salt structure – to interrogate these relationships. We sampled 2000 different surfaces of its (100) plane and calculated the HAEs at randomly chosen surface O sites using density functional theory (DFT). Our analysis of the 2000 data points reveals that the HAEs at the surface O sites are significantly influenced by the local environment around the adsorption sites, particularly the nature of the metal atom directly below the surface O site where H adsorbs. After comparing several popular graph-neural-network-based machine learning models, we found that the DimeNet++ model performed best achieving satisfactory accuracy in predicting HAEs for both Mg 0.25 Ni 0.25 Cu 0.25 Zn 0.25 O and slightly varied compositions. Our work underscores the promise of such models and the need for further refinement to address the complexity of HEOs.

Song, Haohong [Vanderbilt Univ., Nashville, TN (Un↗