| Autor: |
Koyale, Pramod A., Patil, Amruta D., Dongale, Tukaram D., Thorat, Parth S., Sutar, Santosh S., Parale, Vinayak G., Hyung-Ho Park, Panda, Dillip K., Delekar, Sagar D. |
| Zdroj: |
Journal of Materials Chemistry C; 8/28/2024, Vol. 12 Issue 32, p12499-12509, 11p |
| Abstrakt: |
The present investigation focuses on the designing of photoanodes for photoelectrochemical (PEC) water splitting. For this, metal-organic framework (MOF)-derived Zn-doped ceria (CeO2) nanobars (NBs) are modified herein using reduced graphene oxide (rGO). The bare CeO2 NBs and Zn-CeO2 nanocomposites (NCs) are synthesized through calcination of the respective MOFs, while a simple sonochemical treatment is used to create ternary Zn-CeO2/rGO (ZCR-3) NCs with 1 wt% rGO content. The primary goal of integrating rGO and Zn2+ ion doping is to enhance the PEC performance of CeO2 NBs by increasing conductivity, and stability, and facilitating well-organized charge transfer, owing to synergistic effects between the components. The high surface area with increased oxygen vacancies within ZCR-3 NCs is studied using N2 adsorption-desorption isotherms and electron spin resonance (ESR) analysis. This is further perceived by PEC testing of the synthesized samples, revealing the highest current density of 2.228 mA cm-2 at 1.23 V vs. reversible hydrogen electrode (RHE) for the ternary ZCR-3 NC-based photoanode, which is almost 2 and 6 times greater than that of Zn-CeO2 NCs and bare CeO2 NB-based photoanodes, respectively. Additionally, the stability of the photoanodes is evaluated under prolonged water splitting conditions and modeled using a machine learning-based recurrent neural network (RNN) with a long short-term memory (LSTM) algorithm. The results of this study suggest that rGO integration with MOF-derived CeO2 nanostructures holds significant potential for developing efficient and stable photoanodes for water splitting applications. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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