Predicting superconducting transition temperature through advanced machine learning and innovative feature engineering

Predicting superconducting transition temperature through advanced machine learning and innovative feature engineering

Abstract Superconductivity is a remarkable phenomenon in condensed matter physics, which comprises a fascinating array of properties expected to revolutionize energy-related technologies and pertinent fundamental research. However, the field faces the challenge of achieving superconductivity at room...

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Detaylı Bibliyografya
Asıl Yazarlar: Hassan Gashmard, Hamideh Shakeripour, Mojtaba Alaei
Materyal Türü: Makale
Dil:English
Baskı/Yayın Bilgisi: Nature Portfolio 2024-02-01
Seri Bilgileri:Scientific Reports
Konular:
Fourth paradigms
Machine learning
Transition temperature
Superconductor
CatBoost
Jabir
Online Erişim:https://doi.org/10.1038/s41598-024-54440-y

Internet

https://doi.org/10.1038/s41598-024-54440-y

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