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Spectroscopy as a New Language for AI-Driven Materials Discovery

New framework treats spectroscopy as a 'physical language' for AI, enabling machine-readable spectra to accelerate materials discovery and self-driving labs.

This framework could revolutionize how scientists discover and design new materials by making spectroscopy machine-readable and actionable. It bridges the gap between physical laws and AI, enabling self-driving laboratories that autonomously design, synthesize, and test materials. By treating spectra as a language, researchers can leverage AI to interpret complex data and generate novel materials with desired properties, accelerating innovation in chemistry and materials science. The approach promises more efficient, interpretable, and creative scientific workflows, ultimately leading to faster breakthroughs in areas like energy, healthcare, and electronics.