Thermophysical properties of adsorbates with beyond-DFT accuracy from DFT data through error cancellation.

Area of Science:

• Computational chemistry
• Surface science
• Catalysis

Background:

• Predictive multiscale modeling of catalytic reactions relies on accurate adsorbate enthalpies.
• Standard density functional theory (DFT) methods with generalized gradient approximation (GGA) functionals yield inaccurate enthalpies.
• High-accuracy electronic structure methods are computationally prohibitive for these systems.

Purpose of the Study:

• To develop a computational method for accurate adsorbate formation enthalpies.
• To improve the predictive power of multiscale models for heterogeneous catalysis.
• To enable more accurate insights into catalytic reaction mechanisms.

Main Methods:

• An error-cancellation approach based on the connectivity-based hierarchy (CBH) was developed.
• Reactions were constructed to conserve electronic configurations between target and reference species, enabling error cancellation.
• The method was applied to adsorbates on Pt(111), Ni(111), and MgO(100) surfaces.

Main Results:

• The CBH method yields adsorbate formation enthalpies with beyond-DFT accuracy.
• Results show excellent agreement with experimental measurements across various GGA functionals and adsorbates.
• The CBH method outperforms conventional referencing approaches in accuracy.

Conclusions:

• The CBH method provides highly accurate adsorbate formation enthalpies, crucial for multiscale modeling.
• This approach enhances the predictive capabilities of catalytic reaction models.
• Accurate thermochemical data derived from CBH facilitates deeper understanding of catalytic processes.