Logotipo del repositorio
  • English
  • Español
  • Français
  • Português
  • Iniciar sesión
    ¿Has olvidado tu contraseña?
Logotipo del repositorio
  • Comunidades
  • Listar por
  • English
  • Español
  • Français
  • Português
  • Iniciar sesión
    ¿Has olvidado tu contraseña?
  1. Inicio
  2. Examinar por materia

Examinando por Materia "electrochemical reduction of CO2"

Mostrando 1 - 1 de 1
Resultados por página
Opciones de ordenación
  • No hay miniatura disponible
    Ítem
    A Semiempirical Method to Detect and Correct DFT-Based Gas-Phase Errors and Its Application in Electrocatalysis
    (AMER CHEMICAL SOC, 2020-06-19) Granda-Marulanda, Laura P.; Rendon-Calle, Alejandra; Builes, Santiago; Illas, Francesc; Koper, Marc T. M.; Calle-Vallejo, Federico; Universidad EAFIT. Departamento de Ingeniería de Procesos; Desarrollo y Diseño de Procesos
    Computational models of adsorption at metal surfaces are often based on DFT and make use of the generalized gradient approximation. This likely implies the presence of sizable errors in the gas-phase energetics. Here, we take a step closer toward chemical accuracy with a semiempirical method to correct the gas-phase energetics of PBE, PW91, RPBE, and BEEF-vdW exchange-correlation functionals. The proposed two-step method is tested on a data set of 27 gas-phase molecules belonging to the carbon cycle: first, the errors are pinpointed based on formation energies, and second, the respective corrections are sequentially applied to ensure the progressive lowering of the data set's mean and maximum errors. We illustrate the benefits of the method in electrocatalysis by a substantial improvement of the calculated equilibrium and onset potentials for CO2 reduction to CO on Au, Ag, and Cu electrodes. This suggests that fast and systematic gas-phase corrections can be devised to augment the predictive power of computational catalysis models.

Vigilada Mineducación

Universidad con Acreditación Institucional hasta 2026 - Resolución MEN 2158 de 2018

Software DSpace copyright © 2002-2025 LYRASIS

  • Configuración de cookies
  • Enviar Sugerencias