🔋 Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models
📝 این مقاله چارچوبی مبتنی بر مدلهای بزرگ هوش مصنوعی مانند MLIP و LLM برای کشف خودکار الکترولیتهای جامد و رفع موانع داده و شبیهسازی ارائه میدهد.
📚 Journal: Advanced Materials #AdvancedMaterials
📅 Date: 2026-10-13
💭 Perspective | 🔓 Open Access | 📥 PDF
💡 Novelty & Significance:
This work proposes a framework for autonomous solid electrolyte discovery using large AI models—MLIPs and LLMs—integrated into closed-loop cycles spanning literature mining, hypothesis generation, multiscale simulation, and experimental validation. Its novelty lies in shifting SE research from intuition-guided exploration to self-improving, data-informed systems, addressing fragmented data and slow iteration. Significance: design principles for autonomous solid-state battery laboratories.
🔗 10.1002/adma.75354
🏷 solid electrolyte · large AI models · machine learning potentials · autonomous discovery · solid-state batteries
Post #15211
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