Are fragment-based quantum chemistry methods applicable to medium-sized water clusters?

Area of Science:

• Computational chemistry
• Quantum chemistry
• Theoretical chemistry

Background:

• Fragment-based quantum chemistry methods are crucial for large molecular systems.
• Two main approaches exist: many-body expansion and inclusion-exclusion principle.
• Comparing their performance is essential for selecting appropriate computational tools.

Purpose of the Study:

• To systematically evaluate and compare the performance of the generalized energy based fragmentation (GEBF) and electrostatically embedded many-body (EE-MB) methods.
• To assess their applicability for calculating ground-state energies of medium-sized water clusters ((H2O)n, n=10, 20, 30).
• To analyze the impact of basis set superposition error and fragmentation strategies on accuracy.

Main Methods:

• Calculated ground-state energies for low-energy isomers of water clusters (n=10, 20, 30) using GEBF and EE-MB methods.
• Employed various theoretical levels and basis sets, including those with diffuse functions.
• Investigated the effect of fragment size and cutoff distances on EE-MB accuracy.
• Analyzed the role of basis set superposition error (BSSE).

Main Results:

• GEBF consistently provided accurate ground-state energies for all water cluster isomers and theory levels.
• EE-MB (with single-molecule fragments and no cutoff) exhibited poor convergence for larger clusters ((H2O)20, (H2O)30) with diffuse basis sets.
• Neglecting BSSE minimally impacted GEBF accuracy but significantly reduced EE-MB accuracy.
• EE-MB accuracy improved substantially with a cutoff distance and two-molecule fragments.
• GEBF showed lower deviation (<0.001 hartree) than optimized EE-MB (~0.003 hartree) for (H2O)30 at comparable computational cost.

Conclusions:

• GEBF is a robust and accurate method for electronic structure calculations of water clusters, applicable with any basis set.
• EE-MB requires careful parameterization (fragment size, cutoff) and BSSE correction for reliable results.
• GEBF demonstrates superior performance and reliability compared to the standard EE-MB approach for the studied systems.