fig5

Smart design of Rh-based hydrogen evolution electrocatalysts: integrating DFT, machine learning, and structural optimization for sustainable hydrogen energy

Figure 5. (A) Synthesis process and the coordination environment of single Rh atom on metal nodes of PCN. (B) LSV curves of various catalysts in 0.5 M H2SO4 at 1,600 rpm. Inset: HAADF-STEM images of PCN-Rh15.9. (C) Comparative analysis of overpotentials at 10 mA cm-2 and Tafel slopes of PCN-Rh15.9/KB with different reported HER catalysts, (A-C) are reproduced from Ref.[100]. with permission, Copyright 2023, Wiley. (D) DFT-optimized atomic models depicting the geometry of each catalyst configuration. (E) LSV curves of Rh-TiO2/CNF, TiO2/CNF, Pt/C, and CNF. (D and E) are reproduced from Ref.[40]. with permission, Copyright 2024, Wiley. (F) Electrocatalytic HER performance in alkaline medium (1.0 M KOH): iR-compensated LSV curves for NixMoOy nanorod arrays (NRs), Rh SAs-Mo2C NSs, Mo2C/3D-NRs, Rh SAs-Mo2C/3D-NRs, and Pt/C. Reproduced from Ref.[73]. with permission, Copyright 2023, Wiley.

Energy Materials
ISSN 2770-5900 (Online)
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