Ab Initio Calculations of the Interaction Potential of the N 2 O-N 2 O Dimer: Strength of the Intermolecular Interactions and Physical Insights.

N 2 O, or nitrous oxide, is an important greenhouse gas with a significant impact on global warming and climate change. To accurately model the behavior of N 2 O in the atmosphere, precise representations of its intermolecular force fields are required. First principles quantum mechanical calculations followed by appropriate fitting are commonly used to establish such force fields. However, fitting such force fields is challenging due to the complex mathematical functions that describe the molecular interactions of N 2 O. As such, ongoing research is focused on improving our understanding of N 2 O and developing more accurate models for use in climate modeling and other applications. In this study, we investigated the strength of the intermolecular interactions in the N 2 O-N 2 O dimer using the coupled-cluster theory with single, double, and perturbative triple excitation [CCSD(T)] method with the def2-QZVPP basis set. Our calculations provided a detailed understanding of the intermolecular forces that govern the stability and structure of the N 2 O dimer. We found that the N 2 O-N 2 O dimer is stabilized by a combination of van der Waals forces and dipole-dipole interactions. The calculated interaction energy between the two N 2 O molecules in the dimer was found to be -5.09 kcal/mol, which is in good agreement with previous theoretical and experimental results. Additionally, we analyzed the molecular properties of the N 2 O-N 2 O dimer, including its geometry and charge distribution. Our calculations provide a comprehensive understanding of the intermolecular interactions in the N 2 O-N 2 O dimer using the CCSD(T) method with the def2-QZVPP basis set by using the improved Lennard-Jones interaction potential method. These results can be used to improve our understanding of atmospheric chemistry and climate modeling, as well as to aid in the interpretation of experimental data.