New Computing Method Speeds Up Discovery of Renewable Energy Materials
新計算方法加速再生能源材料的發現
The transition to renewable energy hinges on finding advanced materials for batteries and solar cells.
向再生能源的過渡取決於為電池與太陽能電池尋找先進材料。
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By leveraging Artificial Intelligence (AI) and machine learning, researchers can now screen thousands of chemical candidates computationally.
透過利用人工智慧（AI）和機器學習，研究人員現在可以在計算上篩選數千種化學候選物。
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This approach uses high-throughput virtual screening and Density Functional Theory (DFT) to model atomic structures with high precision.
這種方法使用高通量虛擬篩選與密度泛函理論（DFT）來高精度地建模原子結構。
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Furthermore, 'self-driving' labs, which combine AI with robotics, can test these materials 24/7 without human intervention.
此外，將AI與機器人技術結合的「自主駕駛」實驗室，能夠不間斷地在二十四小時內測試這些材料，且無需人工干預。
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