Density-BasedPartitioning Methods for Ground-StateMolecular Calculations.
Saved in:
| Title: | Density-BasedPartitioning Methods for Ground-StateMolecular Calculations. |
|---|---|
| Authors: | Nafziger, Jonathan1, Wasserman, Adam1 |
| Source: | Journal of Physical Chemistry A. Sep2014, Vol. 118 Issue 36, p7623-7639. 17p. |
| Subjects: | Ground state (Quantum mechanics), Molecular calculations & mathematical techniques, Electronic structure, Density functional theory, Diatomic molecules, Charge transfer |
| Abstract: | With the growing complexity of systemsthat can be treated withmodern electronic-structure methods, it is critical to develop accurateand efficient strategies to partition the systems into smaller, moretractable fragments. We review some of the various recent formalismsthat have been proposed to achieve this goal using fragment (ground-state)electron densities as the main variables, with an emphasis on partitiondensity-functional theory (PDFT), which the authors have been developing.To expose the subtle but important differences between alternativeapproaches and to highlight the challenges involved with density partitioning,we focus on the simplest possible systems where the various methodscan be transparently compared. We provide benchmark PDFT calculationson homonuclear diatomic molecules and analyze the associated partitionpotentials. We derive a new exact condition determining the strengthof the singularities of the partition potentials at the nuclei, establishthe connection between charge-transfer and electronegativity equalizationbetween fragments, test different ways of dealing with fractionalfragment charges and spins, and finally outline a general strategyfor overcoming delocalization and static-correlation errors in density-functionalcalculations. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Physical Chemistry A is the property of American Chemical Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
Be the first to leave a comment!