Superconductor Science and Technology | 2019

Angular dependence of the upper critical field in randomly restacked 2D superconducting nanosheets

 

Abstract


Recently, Pan et al (2017 J. Am. Chem. Soc. 139 4623) reported that randomly restacked chemically exfoliated monolayers of TaS2 have enhanced superconducting transition temperatures of up to T c = 3 K, compared with T c = 0.8 K for the bulk 2 H-TaS2 compound. Ma et al (2018 NPJ Quantum Mater. 3 34) measured the angular dependence of the upper critical field, B c2(θ), for this material and employed several models to fit the experimental data, namely the three-dimensional Ginzburg–Landau (3D GL) model (Blatter et al 1994 Rev. Mod. Phys. 66 1125–1388), the two-dimensional Tinkham (2D Tinkham) model (Harper and Tinkham 1968 Phys. Rev. 172 441–450), and the modified 3D GL (Ma et al 2018 NPJ Quantum Mater. 3 34) model. However, differences between experimentally measured B c2(θ) and theoretical model values are large, showing a great enhancement of experimental B c2(θ) over a wide range of angles. The same result was obtained for 1T -MoS2 restacked nanosheets (Ma et al 2018 NPJ Quantum Mater. 3 34). Here we stress that the physical reason for enhanced superconductivity in these materials is the randomness in restacked monolayers (Pan et al 2017 J. Am. Chem. Soc. 139 4623; Ma et al 2018 NPJ Quantum Mater. 3 34). Based on this viewpoint (Pan et al 2017 J. Am. Chem. Soc. 139 4623; Ma et al 2018 NPJ Quantum Mater. 3 34), and despite the fact that the B c2(θ) of each individual monolayer will obey the 2D Tinkham model, the total B c2(θ) should mainly reflect the angular statistical distribution of the 2D nanosheets within the stack. Fits of the experimental B c2(θ) data using a statistical distribution model for the 2D nanosheets have excellent quality and the deduced parameters have meaningful values. We also propose that the angular dependences of the lower, B c1(θ), and thermodynamic, B c(θ), critical fields in randomly restacked 2D nanosheets should also obey statistical distribution models.

Volume 32
Pages 15013
DOI 10.1088/1361-6668/AAF025
Language English
Journal Superconductor Science and Technology

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