Machine learning assisted design for active cathode materials

Keyphrases

• Machine Learning 100%
• Active Cathode Material 100%
• Assisted Design 100%
• Material Design 66%
• Crystal System 66%
• Training Data 66%
• Property Prediction 66%
• Electrical Properties 33%
• Material Properties 33%
• Measurement Simulation 33%
• Mean Squared Error 33%
• Volume Change 33%
• Property Change 33%
• Oxygen Content 33%
• Tree Algorithm 33%
• Computational Simulation 33%
• Random Tree 33%
• Regression Model 33%
• Limited Datasets 33%
• Machine Learning Techniques 33%
• Promising Solutions 33%
• Random Forest 33%
• Coefficient of Determination 33%
• Machine Learning Algorithms 33%
• Random Forest Algorithm 33%
• System Classification 33%
• System Learning 33%
• Gravity Change 33%
• Monte Carlo Validation 33%
• Feature Importance Score 33%

Material Science

• Cathode 100%
• Cathode Material 100%
• Materials Design 50%
• Materials Property 50%

Chemical Engineering

• Learning System 100%