Accurate bulk properties from approximate many-body techniques.

Area of Science:

• Computational Chemistry
• Materials Science
• Solid-State Physics

Background:

• Accurate electronic structure calculations are crucial for predicting material properties.
• Density functional theory (DFT) methods often struggle with electron correlation.
• The random-phase approximation (RPA) is proposed as a method to improve correlation energy calculations.

Purpose of the Study:

• To evaluate the effectiveness of the random-phase approximation (RPA) for ab initio electronic structure calculations.
• To assess RPA's performance in predicting key material properties like lattice constants and energies.
• To compare RPA with existing methods like DFT, diffusion Monte Carlo, and quantum chemical approaches.

Main Methods:

• Utilizing the random-phase approximation (RPA) to calculate the correlation energy in electronic structure computations.
• Performing ab initio calculations for lattice constants, atomization energies of solids, and adsorption energies on metal surfaces.
• Comparing computational results with experimental data.

Main Results:

• RPA calculations showed excellent agreement with experimental values for lattice constants.
• Atomization energies of solids and adsorption energies on metal surfaces were accurately predicted by RPA.
• The method demonstrated effectiveness across various bonding types, including ionic, metallic, and van der Waals systems.

Conclusions:

• The random-phase approximation (RPA) is a highly accurate and efficient method for ab initio electronic structure calculations.
• RPA offers a promising improvement over standard density functional theory (DFT) for various material properties.
• RPA provides a viable alternative to more computationally expensive methods like diffusion Monte Carlo.