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This paper investigates the optimization of exchange-correlation (XC) functionals in density functional theory (DFT) specifically for surface binding energies and their implications for surface reaction barriers. The authors demonstrate that while tuning XC functionals can enhance binding energy predictions, it may inadvertently degrade the accuracy of reaction barrier estimates if key physical exact conditions are not satisfied. Their findings highlight the delicate balance required in XC functional optimization, emphasizing the importance of maintaining physical fidelity in DFT calculations for heterogeneous catalysis.
Optimizing exchange-correlation functionals for better binding energy predictions can paradoxically worsen reaction barrier accuracy if physical exact conditions are ignored.
Density functional theory (DFT) often is the method of choice for simulating the electronic properties of extended solids and surfaces from first principles due to a favorable compromise between accuracy and computational cost. In the field of heterogeneous catalysis, DFT is indispensable for deriving mechanistic insights and understanding trends in surface reactivity. The accuracy of DFT for surface reaction energetics depends strongly on the exchange-correlation (XC) approximation. We show here that optimization of such XC functionals for surface binding energies can lead to a worse description of surface reaction barriers, unless important physical exact conditions are fulfilled.
