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🧠 AI⚪ NeutralImportance 4/10
Sustainable Materials Discovery in the Era of Artificial Intelligence
arXiv – CS AI|Sajid Mannan, Rupert J. Myers, Rohit Batra, Rocio Mercado, Lothar Wondraczek, N. M. Anoop Krishnan||2 views
🤖AI Summary
Researchers propose ML-LCA framework to integrate machine learning-based materials discovery with lifecycle assessment for sustainable-by-design materials. The framework addresses the current inefficiency where environmental impacts are evaluated only after resources are invested in potentially unsustainable solutions.
Key Takeaways
- →Current AI materials discovery workflows optimize performance first and defer sustainability assessment until after synthesis.
- →The proposed ML-LCA framework integrates five components including materials-environment knowledge bases and multi-scale models.
- →Case studies across glass, cement, semiconductor photoresists, and polymers demonstrate both necessity and feasibility of the approach.
- →The framework enables simultaneous optimization of performance and sustainability rather than sequential assessment.
- →Implementation requires coordinated advances in data infrastructure, assessment methodologies, and regulatory alignment.
#artificial-intelligence#materials-discovery#machine-learning#sustainability#lifecycle-assessment#research#optimization#semiconductors#polymers
Read Original →via arXiv – CS AI
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