Fe-Based Superconducting Transition Temperature Modeling through Gaussian Process Regression
- PDF / 1,762,866 Bytes
- 14 Pages / 439.37 x 666.142 pts Page_size
- 79 Downloads / 204 Views
Fe‑Based Superconducting Transition Temperature Modeling through Gaussian Process Regression Yun Zhang1 · Xiaojie Xu1 Received: 21 April 2020 / Accepted: 27 October 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Extensive research has been conducted to find new superconducting materials that exhibit high critical temperature T c , in order to fulfill the needs of practical applications with liquid-helium-free refrigeration or even at room temperature. Iron-based superconductors show high T c and high upper critical field. The research, however, requires significant manpower for materials synthesis and characterization, and costly equipment and facilities. Computational approaches have contributed greatly to investigate the properties of solid-state matter in many fields, which can be integrated to machine learning and big-data analysis. In this work, the Gaussian process regression model is developed to predict Fe-based superconductor critical temperature based on lattice parameters. This modeling approach demonstrates a high degree of accuracy and stability that lead to the statistical relationship between the lattice parameters and T c . The results disclosed by this work can also lead to a better understanding of the origin of superconductivity in these materials. Keywords Critical temperature · Gaussian process regression · High-temperature superconductors · Iron-based superconductors · Lattice parameters
1 Introduction In 1911, Kamerlingh Onnes observed a sudden loss of electrical resistance to the flow of DC current in mercury near 4 K, which marked the discovery of superconductivity [1]. Two properties are fundamental to superconductors, zero-resistivity, and perfect diamagnetism [2]. Below critical temperature, T c , current can flow within the material without noticeable energy dissipation. In the superconducting phase, the conduction electron fluid is in a more strongly ordered state than it is * Yun Zhang [email protected] Xiaojie Xu [email protected] 1
North Carolina State University, Raleigh, NC 27695, USA
13
Vol.:(0123456789)
Journal of Low Temperature Physics
in the normal state, and the diamagnetism in the Meissner state is an equilibrium property of this ordered state. The nature of this ordering process became clear when the BCS theory was developed by Bardeen, Cooper, and Schrieffer in 1957 [3, 4]. The BCS theory indicated that an attractive interaction between electrons, due to local distortion of lattice (phonon exchange), results in the formation of electron pairs–Cooper pairs. Cooper pairs undergo a form of Bose condensation, which is associated with superfluidity. The formation of the electron-pair condensate gives rise to the rigidity of the superconducting wavefunction. However, the maximum critical temperature for this type of superconductor was very low, and it has greatly limited practical applications of superconductors. Since then, researchers have been conducting an extensive search for novel superconductors, especially those with hi
Data Loading...
