Related papers: Predicting new superconductors and their critical …
Recent research on compressed binary hydrides have unveiled the potential for achieving superconductivity at near-room-temperature. Nevertheless, the available decision-making procedures standing behind the selection of constituent elements…
Predicting the transition temperature, Tc, of a superconductor from Periodic Table normal state properties is regarded as one of the grand challenges of superconductivity. By studying the correlations of Periodic Table properties with known…
Cuprates, a member of high-Tc superconductors, have been on the long-debate on their superconducting mechanism, so that predicting the critical temperature of cuprates still remains elusive. Herein, using machine learning and first…
High critical temperature (T$_c$) superconductor has a great potential in many industrial applications. However, discovering a compound having high T$_c$ is still remaining a big challenge for experimental approach due to time-consuming and…
Recently a relationship between the Debye temperature $\Theta_D$ and the superconducting transition temperature $T_c$ of conventional superconductors has been proposed [npj Quantum Materials $\mathbf{3}$, 59 (2018)]. The relationship…
In this work we used unsupervised machine learning methods in order to find possible clustering structures in superconducting materials data sets. We used the SuperCon database, as well as our own data sets complied from literature, in…
Technologies that function at room temperature often require magnets with a high Curie temperature, $T_\mathrm{C}$, and can be improved with better materials. Discovering magnetic materials with a substantial $T_\mathrm{C}$ is challenging…
There currently exist no quantitative methods to determine the appropriate conditions for solid-state synthesis. This not only hinders the experimental realization of novel materials but also complicates the interpretation and understanding…
The discovery of new superconducting materials, particularly those exhibiting high critical temperature ($T_c$), has been a vibrant area of study within the field of condensed matter physics. Conventional approaches primarily rely on…
Seven distinct families of superconductors with critical temperatures at ambient pressure that equal or surpass the historic 23 K limit for Nb3Ge have been discovered in the last 25 years. Each family is reviewed briefly and their common…
The application of superconducting materials is becoming more and more widespread. Traditionally, the discovery of new superconducting materials relies on the experience of experts and a large number of "trial and error" experiments, which…
This chapter gives an overview of the progress in the field of computational superconductivity. Following the MgB2 discovery (2001), there has been an impressive acceleration in the development of methods based on Density Functional Theory…
The prediction of transition temperatures can be regarded in several ways, either as an exacting test of theory, or as a tool for identifying theoretical rules for defining new homology models. Popular "first principle" methods for…
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…
Recently, machine learning has emerged as an alternative, powerful approach for predicting quantum-mechanical properties of molecules and solids. Here, using kernel ridge regression and atomic fingerprints representing local environments of…
Even though superconductivity has been studied intensively for more than a century, the vast majority of superconductivity research today is carried out in nearly the same manner as decades ago. That is, each study tends to focus on only a…
Despite having been discovered more than three decades ago, High Temperature Superconductors (HTSs) lack both an explanation for their mechanisms and a systematic way to search for them. To aid this search, this project proposes ScGAN, a…
First-principles computations are the driving force behind numerous discoveries of hydride-based superconductors, mostly at high pressures, during the last decade. Machine-learning (ML) approaches can further accelerate the future…
Using the Eliashberg strong coupling theory with vertex correction, we calculate maps of transition temperatures (T$_{c}$) of electron-phonon superconductors in full parameter space. The maximums of transition temperatures for…
We develop a multi-step workflow for the discovery of conventional superconductors, starting with a Bardeen Cooper Schrieffer inspired pre-screening of 1736 materials with high Debye temperature and electronic density of states. Next, we…