Independent gradient model based on Hirshfeld partition: A new method for visual study of interactions in chemical systems

The powerful independent gradient model (IGM) method has been increasingly popular in visual analysis of intramolecular and intermolecular interactions in recent years. However, we frequently observed that there is an evident shortcoming of IGM map in graphically studying weak interactions, that is its isosurfaces are usually too bulgy; in these cases, not only the graphical effect is poor, but also the color on some areas on the isosurfaces is inappropriate and may lead to erroneous analysis conclusions. In addition, the IGM method was originally proposed based on promolecular density, which is quite crude and does not take actual electronic structure into account. In this article, we propose an improvement version of IGM, namely IGM based on Hirshfeld partition of molecular density (IGMH), which replaces the free-state atomic densities involved in the IGM method with the atomic densities derived by Hirshfeld partition of actual molecular electron density. This change makes IGM have more rigorous physical background. A large number of application examples in this article, including molecular and periodic systems, weak and chemical bond interactions, fully demonstrate the important value of IGMH in intuitively understanding interactions in chemical systems. Comparisons also showed that the IGMH usually has markedly better graphical effect than IGM and overcomes known problems in IGM. Currently IGMH analysis has been supported in our wavefunction analysis code Multiwfn (). We hope that IGMH will become a new useful method among chemists for exploring interactions in wide variety of chemical systems.

Automated summary

The powerful independent gradient model (IGM) method has limitations in graphically studying weak interactions. In this article, an improved version of IGM, called IGM based on Hirshfeld partition (IGMH), is proposed to overcome the shortcomings. The rigorous physical background of IGMH is demonstrated through various application examples, showcasing its important value in intuitively understanding interactions in chemical systems.