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Machine learning-based discovery of vibrationally stable materials

Engineering and Technology

Machine learning-based discovery of vibrationally stable materials

S. A. Tawfik, M. Rashid, et al.

This paper presents a groundbreaking machine learning approach developed by Sherif Abdulkader Tawfik and colleagues to predict the vibrational stability of materials, a key aspect in material synthesizability. The classifier they created acts as a swift alternative to traditional computational methods, promising to enhance material database searches significantly.

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