pKa: Heterolytic bond dissociation energies (pKa) are one of the most important properties for organic molecules, which play very import rules in chemistry, biology, medicine, and geology. We provided a fast pKa prediction platform free of charge herein, which was based on two different machine learning methods. The pKa training set included more than 19,000 experimental data published so far. Xxperimental data comes from the sub-database of iBonD, for more details please click http://ibond.nankai.edu.cn.
BDE: Bond dissociation energy (BDE), which involves the homolysis of chemical bonds, is a basic thermodynamic property of molecule. It is very important for understanding the chemical reactivity, chemical properties and chemical transformations. The BDE training set included more than 290000 calculation BDEs and 4000 experimental BDEs. Experimental data comes from the sub-database of iBonD, for more details please click http://ibond.nankai.edu.cn.
Note: The bond energy prediction platform are only free of charge for non-profit making academic use. Whenever applicable, the users are requested to cite this website in their publication/presentation as follows: pKa prediction platform (link1, link2, link3, link4). We thank iBonD and Dr. Jindong Yang for his comments and suggestions. All rights are reserved by Luo group in Department of Chemistry, Tsinghua University.
Nucleophilicity and electrophilicity: Attaining the kinetic reactivities of nucleophiles and electrophiles has generated considerable research interest for a long time. Based on the Mayr equation [log k20°C = sN (N + E)], a quantitative reactivity scale was established and had been extensively applied to several reaction systems. By using machine learning protocols, we developed a holistic and accurate reactivity parameters prediction model. The training set included 1115 nucleophilicity parameters and 285 electrophilicity parameters published so far. The experimental data comes from the Mayr’s Database of Reactivity Parameters, for more details please refer to Mayr's Database.