Low-dimensional lateral heterojunctions made of hexagonal boron nitride and carbon materials as efficient electrocatalysts for the chlorine evolution reaction: a study of DFT and machine learning

Abstract

Electrocatalytic oxidation of chlorine-rich wastewater, a byproduct of chemical production, to chlorine gas is an integral method for reintroducing chlorine atoms back into the chlorine cycle. However, the implementation of dimensionally stable anodes in industrial applications faces significant challenges due to their high cost and lackluster selectivity. To address these issues, we designed three heterojunctions with varying dimensions (D = 2, 1, 0) using hexagonal boron nitride (h-BN) and carbon-based materials such as graphene, nanotubes, and C₆₀. To explore the reactivity of these heterojunctions for the chlorine evolution reaction (CER), we conducted a systematic investigation under three surface coverage concentrations of Cl⁻ (c_Cl = 1, 2, 3) employing density functional theory (DFT) and machine learning (ML). The results indicate that reducing the catalyst's dimensionality while simultaneously increasing the surface coverage concentration of Cl⁻ can effectively facilitate the CER. Meanwhile, our results highlight that the zero-dimensional catalyst (D = 0), when subjected to a Cl⁻ surface coverage concentration of 3 (c_Cl = 3), can efficiently catalyze the CER, achieving an impressively low overpotential of 0.0026 V via the Cl* intermediate without necessitating the formation of ClO*. Additionally, the overpotential of the oxygen evolution reaction (OER) is 1.18 V, which promotes the selectivity of Cl₂ generation. Our research not only advances the usage of low-dimensional carbon composites in CER electrocatalysis, but also provides valuable insights for designing effective electrocatalysts to treat chlorine-laden wastewater across a broad range of Cl⁻ concentrations.