Indices for predicting the quality of leaving groups

文献信息

发布日期 2005-04-05
DOI 10.1039/B500996K
影响因子 3.676
作者

Paul W. Ayers, James S. M. Anderson, Juan I. Rodriguez, Zobia Jawed


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摘要

The inherent quality of leaving groups in chemical reactions is related to their ionization potential and electron affinity using a quadratic model for the dependence of the energy on the number of electrons. A good leaving group for nucleophilic substitution/elimination reactions is one where the difference in energy between the system with the “optimum” number of electrons and the anion is small. Similarly, a good leaving group for electrophilic substitution/elimination reactions is one where the difference in energy between the system with the optimum number of electrons and the cation is small. This insight allows us to define indices for the quality of leaving groups in nucleophilic and electrophilic reactivity, which we term the nucleofugality and the electrofugality, respectively. These indices are useful not only for predicting the quality of leaving groups in organic reactions, but also for explaining the stability of carbocations, carbanions, and trends in pKa.

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来源期刊

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
自引率: 10.3%
年发文量: 3036

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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