ABSTRACT
Electrocatalytic oxidation of formaldehyde (FOR) is an effective way to prevent the damage caused by formaldehyde and produce high-value products. A screening strategy of a single-layer MnO2-supported transition metal catalyst for the selective oxidation of formaldehyde to formic acid was designed by high-throughput density functional calculation. N-MnO2@Cu and MnO2@Cu are predicted to be potential FOR electrocatalysts with potential-limiting steps (PDS) of 0.008 and -0.009 eV, respectively. Electronic structure analysis of single-atom catalysts (SACs) shows that single-layer MnO2 can regulate the spin density of loaded transition metal and thus regulate the adsorption of HCHO (Ead), and Ead is volcanically distributed with the magnetic moment descriptor -|mM - mH|. In addition, the formula quantifies Ead and |mM - mH| to construct a volcano-type descriptor α describing the PDS [ΔG(*CHO)]. Other electronic and structural properties of SACs and α are used as input features for the GBR method to construct machine learning models predicting the PDS (R2 = 0.97). This study hopes to provide some insights into FOR electrocatalysts.
