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AI integrated with LCA for sustainable materials discovery

A new research paper proposes the ML-LCA framework to integrate artificial intelligence (AI) with life cycle assessment (LCA) for sustainable materials discovery. Current AI models for materials discovery optimize solely for structural stability and functional properties, neglecting environmental impact. The proposed ML-LCA framework aims to bridge this gap by incorporating environmental considerations directly into the AI design loop, addressing challenges like data scarcity and scale gaps. Case studies demonstrate the framework's feasibility across various materials. AI

IMPACT This framework could lead to the development of more environmentally friendly materials by integrating sustainability metrics directly into AI-driven discovery processes.

RANK_REASON The cluster contains an academic paper detailing a new framework for integrating AI with life cycle assessment. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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AI integrated with LCA for sustainable materials discovery

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The cluster contains an academic paper detailing a new framework for integrating AI with life cycle assessment. [lever_c_demoted from research: ic=1 ai=1.0]
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High
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102 days old
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Sajid Mannan, Rupert J. Myers, Rohit Batra, Rocio Mercado, Lothar Wondraczek, N. M. Anoop Krishnan ·

    Sustainable Materials Discovery in the Era of Artificial Intelligence

    arXiv:2601.21527v3 Announce Type: replace-cross Abstract: Artificial intelligence (AI) has transformed materials discovery, enabling rapid exploration of chemical space through generative models and surrogate screening. Yet current generative AI models for materials discovery, wh…