Hammett's Sigma Constants in Certain Electrophilic Reactions

“…found that there is a linear relationship that accommodates the various sets of a+-values (38, 39,66,67,180,191,196,197). Using the Brown and Okamoto set as standards (a+), as in equation 51 U + = u + ?…”

Section: (119)mentioning

confidence: 98%

Linear Free Energy Relationships.

Wells¹

1963

Chem. Rev.

531

313

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“…The values of the substituent constants are highly dependent on the choice of reference reaction and may not be reliable for other reactions. [238][239][240] Hammett's method also easily overfits towards the reference reaction, meaning its predictions will be good for the reference reaction, but poorer for others. Thus, it was the work of Bragato et al 148 to form a new Hammett method such that the substituent constants could become more transferable and the overall model be made more reliable for different reactions.…”

Section: δ-Ml For Activation Energy Predictionmentioning

confidence: 99%

“…However, Hammett's original method is saddled with some significant disadvantages. The values of the substituent constants are highly dependent on the choice of reference reaction and may not be reliable for other reactions 238–240 . Hammett's method also easily overfits towards the reference reaction, meaning its predictions will be good for the reference reaction, but poorer for others.…”

Section: For Activation Energiesmentioning

confidence: 99%

Machine learning activation energies of chemical reactions

Lewis‐Atwell

Townsend

Grayson

2021

WIREs Comput Mol Sci

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Application of machine learning (ML) to the prediction of reaction activation barriers is a new and exciting field for these algorithms. The works covered here are specifically those in which ML is trained to predict the activation energies of homogeneous chemical reactions, where the activation energy is given by the energy difference between the reactants and transition state of a reaction. Particular attention is paid to works that have applied ML to directly predict reaction activation energies, the limitations that may be found in these studies, and where comparisons of different types of chemical features for ML models have been made. Also explored are models that have been able to obtain high predictive accuracies, but with reduced datasets, using the Gaussian process regression ML model. In these studies, the chemical reactions for which activation barriers are modeled include those involving small organic molecules, aromatic rings, and organometallic catalysts. Also provided are brief explanations of some of the most popular types of ML models used in chemistry, as a beginner's guide for those unfamiliar.

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Hammett's Sigma Constants in Certain Electrophilic Reactions

Cited by 44 publications

References 11 publications

The Question of Hyperconjugation or of Bulk Effect in the Beckmann Rearrangement

The Question of Hyperconjugation or of Bulk Effect in the Beckmann Rearrangement

Linear Free Energy Relationships.

Machine learning activation energies of chemical reactions

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