Related papers: Designing High-Tc Superconductors with BCS-inspire…
Monolayer transition metal dichalcogenides (TMDs) host deeply bound excitons interacting with itinerant electrons, and as such they represent an exciting new quantum many-body Bose-Fermi mixture. Here, we demonstrate that electrons…
We search for new superhard B-N-O compounds with an iterative machine learning (ML) procedure, where ML models are trained using sample crystal structures from evolutionary algorithm. We first use cohesive energy to evaluate the…
We design, from first principles calculations, a novel family of thallium halide-based compounds as candidates for new high temperature superconductors, whose superconductivity is mediated by the recently proposed mechanism of non-local…
Pursuit of superconductivity in light-element systems at ambient pressure is of great experimental and theoretical interest. In this work, we combine a machine learning (ML) method with first-principles calculations to efficiently search…
Accelerated discovery with machine learning (ML) has begun to provide the advances in efficiency needed to overcome the combinatorial challenge of computational materials design. Nevertheless, ML-accelerated discovery both inherits the…
Elemental materials provide clean and fundamental platforms for studying superconductivity. However, the highest superconducting critical temperature (Tc) yet observed in elements has not exceeded 30 K. Discovering elemental superconductors…
By drilling periodic thru-holes in a suspended film, the phonon system can be modified. Being motivated by the BCS theory, the technique, so-called phonon engineering, was applied to a niobium sheet. The newly emergent high-$T_{c}$…
As the most successful microscopic superconductivity theory, Bardeen-Cooper-Schrieffer(BCS) theory has a very peculiar prediction: at zero temperature, only a fraction of electrons within an energy shell form Cooper pair and condense, but…
A new two-dimensional material { Mg2B4C2, belonging to the family of the conventional superconductor MgB2, is theoretically predicted to exhibit superconductivity with critical temperature Tc estimated in the 47-48 K range (predicted using…
Superconducting microwave cavities have found applications in many areas including quantum computing, particle accelerators, and dark matter searches. Their extremely high quality factors translate to very narrow bandwidth, which makes them…
Magnetic cooling based on the magnetocaloric effect is a promising solid-state refrigeration technology for a wide range of applications in different temperature ranges. Previous studies have mostly focused on near room temperature (300 K)…
It is demonstrated that the transition temperature (Tc) of high-Tc superconductors is determined by their layered crystal structure, bond lengths, valency properties of the ions, and Coulomb coupling between electronic bands in adjacent,…
Superconductivity is one of the most amazing properties that metallic conductors exhibit. Electrical resistance is completely eliminated below the critical temperature (Tc), which is the most important parameter in superconductivity. Since…
A novel phenomenological framework for an efficient estimation of the thermo-electric properties at room temperature and elevated temperatures of body-centered cubic (BCC) transition metal concentrated alloys is proposed in this work. The…
The frequency-dependent complex optical conductivity reflects key properties of superconductors, such as the energy gap in the density of states (DOS) and the superfluid density. For disordered superconductors, the optical conductivity…
Developing inverse design methods for functional materials with specific properties is critical to advancing fields like renewable energy, catalysis, energy storage, and carbon capture. Generative models based on diffusion principles can…
First principles computational methods can predict the superconducting critical temperature $T_{\mathrm{c}}$ of conventional superconductors through the electron-phonon spectral function. Full convergence of this quantity requires Brillouin…
In this Letter we present resonance properties in terahertz metamaterials consisting of a split-ring resonator array made from high temperature superconducting films. By varying the temperature, we observed efficient metamaterial resonance…
Inspired by the first boron-carbon (B-C) clathrate SrB$_3$C$_3$ and the ternary borohydride KB$_2$H$_8$ [Miao et al., Phys. Rev. B 104 L100504 (2021)], we have performed first-principles density functional theory calculations of the…
Deep learning models are widely used for the data-driven design of materials based on atomic force microscopy (AFM) and other scanning probe microscopy. These tools enhance efficiency in inverse design and characterization of materials.…