Prediction of higher-selectivity catalysts by computer-driven workflow and machine learning

Keyphrases

• High Selectivity 100%
• Machine Learning 100%
• Cheminformatics 100%
• Workflow Learning 100%
• Highly Accurate 50%
• Electronic Properties 50%
• Training Set 50%
• Predictive Modeling 50%
• Molecular Descriptors 50%
• Catalyst Design 50%
• Machine Learning Techniques 50%
• Support Vector Machine 50%
• Reaction Development 50%
• Agnostic 50%
• Machine Learning Algorithms 50%
• Chiral Catalyst 50%
• Empiricism 50%
• Thiol Addition 50%
• Asymmetric Reaction 50%
• Catalyst Selection 50%
• Deep Feedforward Neural Network 50%
• N-acylimines 50%
• Predictive Model 50%
• Steric Properties 50%

Chemistry

• Catalyst 100%
• Chemoinformatics 66%
• Electronic Property 33%
• Catalyst Design 33%
• N-Acylimine 33%
• Thiol 33%

Chemical Engineering

• Learning System 100%
• Feedforward Neural Network 50%
• Support Vector Machine 50%
• Machine Learning Algorithm 50%