Minimum energy pathways via quantum Monte Carlo.

Area of Science:

• Computational Chemistry
• Quantum Mechanics
• Chemical Physics

Background:

• Accurate prediction of chemical reaction pathways is crucial for understanding chemical processes.
• Density functional theory (DFT) is widely used but has limitations in accuracy for certain systems.
• High-level quantum chemistry methods are computationally expensive for larger systems.

Purpose of the Study:

• To evaluate the performance of quantum Monte Carlo (QMC) calculations for determining minimum energy pathways of chemical reactions.
• To compare QMC results with those from DFT and high-level quantum chemistry methods.
• To assess the viability of QMC for challenging chemical reactions and larger systems.

Main Methods:

• Quantum Monte Carlo (QMC) calculations were employed.
• Minimum energy pathways, geometries, and reaction barriers were computed.
• Results were compared against density functional theory (DFT) and other quantum chemistry methods.

Main Results:

• QMC calculations generally demonstrated significantly higher accuracy than DFT.
• QMC successfully treated cases where DFT failed to locate transition states or yielded inaccurate results.
• The employed QMC wave function form is simple and transferable to larger systems.

Conclusions:

• QMC is a viable and useful computational approach for chemical reactions where DFT is inaccurate.
• QMC offers a promising alternative for studying larger chemical systems beyond the reach of traditional high-level quantum chemistry methods.