A machine learning approach for predicting the reactivity power of hypervalent iodine compounds-Reference-Cited by-同舟云学术

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A machine learning approach for predicting the reactivity power of hypervalent iodine compounds

Published:2024-06 Issue:1 Volume:2 Page:100032
ISSN:2949-7477
Container-title:Artificial Intelligence Chemistry
language:en
Short-container-title:Artificial Intelligence Chemistry

Author:

Saini Vaneet^ORCID,Kataria Ramesh^ORCID,Rajput Shruti

Funder

India Ministry of Science & Technology Department of Science and Technology

Publisher

Elsevier BV

Reference52 articles.

1. Advances in synthetic applications of hypervalent iodine compounds;Yoshimura;Chem. Rev.,2016

2. Hypervalent iodine reactions utilized in carbon–carbon bond formations;Hyatt;Org. Biomol. Chem.,2019

3. Recent advances in hypervalent iodine(III)-catalyzed functionalization of alkenes;Li;Beilstein J. Org. Chem.,2018

4. Recent synthetic applications of hypervalent iodine reagents. A review in three installments: installment I;Sihag;Org. Prep. Proced. Int.,2022

5. Recent Synthetic Applications of Hypervalent Iodine Reagents. A Review in Three Installments: Installment II;Sihag;Org. Prep. Proced. Int.,2022

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predicting bond dissociation energies of cyclic hypervalent halogen reagents using DFT calculations and graph attention network model;Beilstein Journal of Organic Chemistry;2024-06-28

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