Critical Role of Thermal Fluctuations for CO Binding on Electrocatalytic Metal Surfaces

This work considers the evaluation of density functional theory (DFT) when comparing against experimental observations of CO binding trends on the strong binding Pt(111) and intermediate binding Cu(111) and for weak binding Ag(111) and Au(111) surfaces important in electrocatalysis. By introducing thermal fluctuations using appropriate statistical mechanical NVT and NPT ensembles, we find that the RPBE and B97M-rV DFT functionals yield qualitatively better metal surface strain trends and CO enthalpies of binding for Cu(111) and Pt(111) than found at 0 K, thereby correcting the overbinding by 0.2 to 0.3 eV to yield better agreement with the enthalpies determined from experiment. The importance of dispersion effects are manifest for the weak CO binding Ag(111) and Au(111) surfaces at finite temperatures in which the RPBE functional does not bind CO at all, while the B97M-rV functional shows that the CO-metal interactions are a mixture of chemisorbed and physisorbed species with binding enthalpies that are within similar to 0.05 eV of experiment. Across all M(111) surfaces, we show that the B97M-rV functional consistently predicts the correct atop site preference for all metals due to thermally induced surface distortions that preferentially favor the undercoordinated site. This study demonstrates the need to fully account for finite temperature fluctuations to make contact with the binding enthalpies from surface science experiments and electrocatalysis applications.

Automated summary

This study evaluates the performance of DFT in predicting CO binding trends on different metal surfaces by considering thermal fluctuations, with the B97M-rV functional showing better performance on all surfaces. Thermally induced surface distortions are shown to influence the accurate prediction of binding preferences on metal surfaces, highlighting the importance of accounting for finite temperature fluctuations in comparisons with experimental and application data.