Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
October 18, 2018The Journal of Organic Chemistry

A Predictive Tool for Electrophilic Aromatic Substitutions Using Machine Learning

View Full Paper
Ask AI
Bookmark
Share

Authors

ATAnna TombergMJMagnus J. JohanssonPNPer‐Ola Norrby

Discussion

Loading...

Member takes

Overview

Key Points

Key points are not available for this paper at this time.

Cite This Study

Tomberg et al. (2018) studied this question.

synapsesocial.com/papers/6a1ba75f950e49a3ca0ca34ehttps://doi.org/10.1021/acs.joc.8b02270
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Intermolecular C(sp<sup>3</sup>)−H Amination of Complex Molecules2018 · 113 citations
  2. 2C–H Functionalization of Azines2017 · 579 citations
  3. 3GEPOL: An improved description of molecular surfaces II. Computing the molecular area and volume1991 · 252 citations
  4. 4Predicting reaction performance in C–N cross-coupling using machine learning2018 · 1,147 citations
  5. 5A Correlation of Reaction Rates1955 · 3,583 citations