This AI model effectively bridges fragmented material datasets, transforming the "needle-in-a-haystack" search for catalysts into a systematic, data-driven discovery process. It proves that the future of materials science lies in the algorithmic synthesis of cross-disciplinary knowledge rather than traditional trial-and-error.
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EMS AI News | AI, 다른 물질군 융합→최고 성능 촉매 찾았다 #ShortsHinzugefügt:
[music] [music] [music] >> I wanted to say it was wrong.
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The meeting ended [music] quietly.
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