Related papers: Materials Design for New Superconductors

Interfacial superconductivity is observed in a variety of heterostructures composed of different materials including superconducting and nonsuperconducting (at appropriate doping and temperatures) cuprates and iron-based pnictides. The…

Generative models such as AlphaFold and MatterGen can directly generate novel material structures with desired properties, accelerating the new materials discovery and revolutionizing the material design paradigm from traditional…

In cuprate high-temperature superconductors the doping level is fixed during synthesis, hence the charge carrier density per CuO$_2$ plane cannot be easily tuned by conventional gating, unlike in 2D materials. Strain engineering has…

Carbon-based materials like nanotubes and graphene are heavily investigated as future CMOS-like devices and in interconnect applications. While much of the interest has been devoted to the device aspects in competition to conventional CMOS…

The issue of the mechanism of high-Tc superconductivity remains open. In this contribution, we propose a new scenario for the mechanism of superconductivity in cuprates based on analysis of experimental data, mainly tunneling, neutron…

While topological superconductors are predicted to provide building blocks for fault-tolerant quantum computing, one of the remaining challenges is to find a convenient experimental platform that would allow patterning of circuits. We find…

A growing number of papers are published in the area of superconducting materials science. However, novel text and data mining (TDM) processes are still needed to efficiently access and exploit this accumulated knowledge, paving the way…

Over the past six years, superconductivity at high temperatures has been reported in a variety of hydrogen-rich compounds under high pressure. That high-temperature superconductivity should exist in these materials is expected according to…

Discovering new superionic materials is essential for advancing solid-state batteries, which offer improved energy density and safety compared to the traditional lithium-ion batteries with liquid electrolytes. Conventional computational…

Enhancing the temperature at which superconductivity is observed is a long-standing objective for materials scientists. Recent tantalizing experiments suggest a possible route for achieving this.

During the CERN Accelerator School 'Superconductivity for accelerators', the students were divided into 18 groups, and 6 different exercises (case studies), involving the design and analysis of superconducting magnets and RF cavities, were…

Using a systematic ab initio quantum many-body approach that goes beyond low-energy models, we directly compute the superconducting pairing order and estimate the pairing gap of several doped cuprate materials and structures within a purely…

Since the discovery of superconductivity in a high-entropy alloy (HEA) Ti-Zr-Nb-Hf-Ta in 2014, the community of superconductor science has explored new HEA superconductors to find the merit of the HEA states on superconducting properties.…

To synthesize a new superconductor which has a critical temperature, Tc, exceeding the room temperature, one needs to know what chemical components to start with. This chapter presents analysis of experimental data which allow one to draw a…

Less than two years after the discovery of high temperature superconductivity in oxypnictide LaFeAs(O,F) several families of superconductors based on Fe layers (1111, 122, 11, 111) are available. They share several characteristics with…

Cuprates and iron-based superconductors are two classes of unconventional high Tc superconductors based on 3d transition elements. Recently, two principles, correspondence principle and magnetic selective pairing rule, have been emerged to…

Over the past decade a large family of spintronic devices have been proposed as candidates for replacing CMOS for future digital logic circuits. Using the recently developed Modular Approach framework, we investigate and identify the…

Materials discovery is a computationally intensive process that requires exploring vast chemical spaces to identify promising candidates with desirable properties. In this work, we propose using quantum-enhanced machine learning algorithms…

A proper understanding of the mechanism for cuprate superconductivity can emerge only by comparing materials in which physical parameters vary one at a time. Here we present a variety of bulk, resonance, and scattering measurements on the…

Advanced engineering materials design involves the exploration of massive multidimensional feature spaces, the correlation of materials properties and the processing parameters derived from disparate sources. The search for alternative…