COMPUTATIONAL STUDY OF DUAL-METAL DOPING IN Fe-N-C SINGLE-ATOM CATALYSTS FOR ENHANCED CO2 ELECTROCHEMICAL REDUCTION

Abstract

The electrochemical reduction of carbon dioxide (CO2RR) offers a promising approach to transform CO2 into valuable chemical products, tackling both environmental issues and sustainable energy challenges. Nevertheless, the effectiveness, specificity, and durability of electrocatalysts continue to be significant hurdles. This investigation utilizes Density Functional Theory (DFT) to methodically examine the impact of incorporating two metal elements and sulfur functionalization in Fe-N-C single-atom catalysts, with the aim of improving their catalytic efficiency. The study investigates how secondary metal additives (Ni, Pd, Pt, and Fe) alter the electronic configuration, charge transfer dynamics, and adsorption energetics of crucial CO2 reduction intermediates. Furthermore, the research analyzes the effect of sulfur incorporation at various levels (single sulfur (1S) and dual sulfur (2S)) to evaluate its influence on intermediate stabilization and catalytic performance. The findings suggest that FeNi-NC offers the optimal combination of electronic reactivity and stability, making it the most efficient catalyst for reducing CO2 to carbon monoxide (CO). While FePd-NC exhibits high catalytic activity due to strong electronic interactions, it shows reduced stability. In contrast, FePt-NC ensures long-lasting durability with stronger CO binding. FeFe-NC demonstrates strong reactivity but faces issues related to excessive CO adsorption, potentially impeding catalytic turnover. The introduction of sulfur doping significantly improves catalytic performance by adjusting electronic properties and stabilizing intermediates. Although 2S doping achieves the highest catalytic activity through substantial electronic modifications, it may introduce structural distortions. On the other hand, 1S doping provides a balanced enhancement, improving activity while maintaining stability. This study's computational findings offer a crucial framework for steering the development of advanced CO2RR catalysts. Through a methodical assessment of dual-metal doping and sulfur functionalization effects, this research establishes an approach to enhance catalytic efficiency via electronic structure manipulation. The capability to forecast essential catalytic characteristics, including adsorption energies, charge transfer dynamics, and stability, enables a more focused method in catalyst creation. These results highlight the broader significance of computational chemistry in expediting materials discovery, providing fundamental insights that can influence future progress in sustainable carbon conversion technologies.