Inverse multi-principal element alloys design via conditional wasserstein generative adversarial network

Keyphrases

• Alloy Composition 20%
• Alloy Design 100%
• Conditional Generative Adversarial Network (cGAN) 40%
• Conditional Wasserstein Generative Adversarial Network 100%
• Data Scarcity 20%
• Data-limited 20%
• Design Approach 20%
• Elastic Modulus 20%
• Elemental Correlations 20%
• Enhanced Mechanical Performance 20%
• GAN Model 20%
• Generative Adversarial Networks 20%
• High-throughput Discovery 20%
• High-throughput Evaluation 20%
• Inverse Material Design 20%
• Limited Conditions 20%
• Machine Learning 20%
• Mechanical Properties 20%
• Multi-principal Element Alloys 100%
• Network Architecture 20%
• Network Framework 20%
• Predictive Model 20%
• Stable Training 20%
• Superior Performance 20%
• Targeting Property 20%
• Training Dynamics 20%

Material Science

• Alloy 33%
• Elastic Moduli 33%
• Materials Design 33%
• Mechanical Property 33%
• Multi-Principal Element Alloys 100%