Energies and structures in biradical chemistry from the parametric two-electron reduced-density matrix method: applications to the benzene and cyclobutadiene biradicals
文献信息
Alison L. McManus, Erik P. Hoy, David A. Mazziotti
The treatment of biradical chemistry presents a challenge for electronic structure theory, especially single-reference methods, as it requires the description of varying degrees and kinds of electron correlation. In this work we assess the ability of the parametric two-electron reduced-density matrix (p2-RDM) method to describe biradical chemistry through application to the benzene and cyclobutadiene biradicals. The relative energy of o- and m-benzynes predicted by the p2-RDM method is consistent with Wenthold et al.'s experimental determinations, while the more difficult relative energy prediction of the more multi-referenced p-benzyne is within 1.4 kcal mol−1 of the experimental value [P. G. Wenthold et al., J. Am. Chem. Soc., 1998, 120, 5279], which is significantly better than traditional single-reference methods. We observe that the degree of multireference correlation in the biradicals depends upon the distance between their radical centers, with the largest radical separation displaying the largest degree of multireference correlation. In addition to relative and absolute electronic energies, we report molecular geometries, natural orbitals, and natural-orbital occupations for the benzene and cyclobutadiene biradicals.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.











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