scispace - formally typeset
J

Johnpierre Paglione

Researcher at University of Maryland, College Park

Publications -  268
Citations -  10638

Johnpierre Paglione is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Superconductivity & Topological insulator. The author has an hindex of 51, co-authored 245 publications receiving 8901 citations. Previous affiliations of Johnpierre Paglione include University of California, San Diego & National Institute of Standards and Technology.

Papers
More filters
Journal ArticleDOI

High-temperature superconductivity in iron-based materials

TL;DR: The surprising discovery of high-temperature superconductivity in a material containing a strong magnet (iron) has led to thousands of publications as discussed by the authors, and it becomes clear what we know and where we are headed.
Journal ArticleDOI

Strong surface scattering in ultrahigh mobility Bi2Se3 topological insulator crystals

TL;DR: A comprehensive analysis of Shubnikov de Haas oscillations, Hall et al. as discussed by the authors showed that the measured electrical transport can be attributed solely to bulk states, even at 50 mK at low Landau level filling factor, and in the quantum limit.
Journal ArticleDOI

Surface conduction of topological Dirac electrons in bulk insulating Bi2Se3

TL;DR: In this paper, the bulk electrical conductivity of most topological insulators is relatively high, masking many of the important characteristics of its protected, surface conducting states, and counter-doping reduces the bulk conductivities of Bi2Se3 significantly, allowing these surface states and their properties to be clearly identified.
Journal ArticleDOI

Nearly ferromagnetic spin-triplet superconductivity.

TL;DR: The discovery of spin-triplet superconductivity in UTe2, featuring a transition temperature of 1.6 kelvin and a very large and anisotropic upper critical field exceeding 40 teslas, suggests that UTe1 is related to ferromagnetic superconductors such as UGe2, URhGe, and UCoGe, however, the lack of magnetic order and the observation of quantum critical scaling place U Te2 at the paramagnetic end of this ferrom
Journal ArticleDOI

Machine learning modeling of superconducting critical temperature

TL;DR: In this article, several machine learning schemes are developed to model the critical temperatures (Tc) of the 12,000+ known superconductors available via the SuperCon database.