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The Impact of Metal Centers in the M-MOF-74 Series on Formic Acid Production.

Dominika O WasikJose Manuel Vicent-LunaShima RezaieAzahara Luna-TrigueroThijs J H VlugtSofía Calero
Published in: ACS applied materials & interfaces (2024)
The confinement effect of porous materials on the thermodynamical equilibrium of the CO 2 hydrogenation reaction presents a cost-effective alternative to transition metal catalysts. In metal-organic frameworks, the type of metal center has a greater impact on the enhancement of formic acid production than the scale of confinement resulting from the pore size. The M-MOF-74 series enables a comprehensive study of how different metal centers affect HCOOH production, minimizing the effect of pore size. In this work, molecular simulations were used to analyze the adsorption of HCOOH and the CO 2 hydrogenation reaction in M-MOF-74, where M = Ni, Cu, Co, Fe, Mn, Zn. We combine classical simulations and density functional theory calculations to gain insights into the mechanisms that govern the low coverage adsorption of HCOOH in the surrounding of the metal centers of M-MOF-74. The impact of metal centers on the HCOOH yield was assessed by Monte Carlo simulations in the grand-canonical ensemble, using gas-phase compositions of CO 2 , H 2 , and HCOOH at chemical equilibrium at 298.15-800 K, 1-60 bar. The performance of M-MOF-74 in HCOOH production follows the same order as the uptake and the heat of HCOOH adsorption: Ni > Co > Fe > Mn > Zn > Cu. Ni-MOF-74 increases the mole fraction of HCOOH by ca. 10 5 times compared to the gas phase at 298.15 K, 60 bar. Ni-MOF-74 has the potential to be more economically attractive for CO 2 conversion than transition metal catalysts, achieving HCOOH production at concentrations comparable to the highest formate levels reported for transition metal catalysts and offering a more valuable molecular form of the product.
Keyphrases
  • metal organic framework
  • transition metal
  • molecular dynamics
  • monte carlo
  • density functional theory
  • aqueous solution
  • molecular dynamics simulations
  • healthcare
  • machine learning
  • heat stress