Machine Learning Models for Catalytic Asymmetric Reactions of Simple Alkenes: From Enantioselectivity Predictions to Chemical Insights

Ajnabiul Hoque; Nupur Jain; Divya R. Chenna; Raghavan B. Sunoj

doi:10.1039/d5dd00483g

January 1, 2025Digital DiscoveryOpen Access

Machine Learning Models for Catalytic Asymmetric Reactions of Simple Alkenes: From Enantioselectivity Predictions to Chemical Insights

View Full Paper

Ask AI

Bookmark

Share

Key Points

This research investigates how machine learning can predict outcomes of catalytic asymmetric reactions involving simple alkenes.
Utilized machine learning algorithms for predicting enantioselectivity in chemical reactions.
Analyzed high-throughput experimentation datasets to enhance model accuracy.
Evaluated performance of various ML models in predicting reaction outcomes.
Machine learning models demonstrated a significant ability to predict enantioselectivity.
Some models outperformed traditional methods in accuracy and reliability.
The work provides chemical insights that could improve future catalytic processes.

Implication

Observational study explores enantioselectivity predictions in chemical catalysis using machine learning, suggesting valuable insights.

Abstract

Increasing number of applications of machine learning (ML) in chemical catalysis has engendered considerable confidence in predicting reaction outcomes. Despite the successful applications of ML to high-throughput experimentation (HTE) datasets,...

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Hoque et al. (2025) studied this question.

synapsesocial.com/papers/69ada8c2bc08abd80d5bbf97 https://doi.org/10.1039/d5dd00483g

View Full Paper

Ask AI

Bookmark

Share

Machine Learning Models for Catalytic Asymmetric Reactions of Simple Alkenes: From Enantioselectivity Predictions to Chemical Insights

Key Points

Implication

Abstract

Discussion

Cite This Study

Machine Learning Models for Catalytic Asymmetric Reactions of Simple Alkenes: From Enantioselectivity Predictions to Chemical Insights

Key Points

Implication

Abstract

Discussion

Cite This Study

Keep reading

Keep reading