Related papers: Predicting new superconductors and their critical …
We employ interpretable explicit machine learning to analyze the material dependence of the magnetic transition temperature $T_c$ in ferromagnetic and ferrimagnetic Heusler compounds. For around 200 compounds, we consider both experimental…
The computational complexity of calculating phase diagrams for multi-parameter models significantly limits the ability to select parameters that correspond to experimental data. This work presents a machine learning method for solving the…
Machine learning methods are powerful in distinguishing different phases of matter in an automated way and provide a new perspective on the study of physical phenomena. We train a Restricted Boltzmann Machine (RBM) on data constructed with…
Predicting the Curie temperature ($T_\mathrm{C}$) of magnetic materials is crucial for advancing applications in data storage, spintronics, and sensors. We present a machine learning (ML) framework to predict $T_{\mathrm{C}}$ using a…
The discovery of novel high-temperature superconductor materials holds transformative potential for a wide array of technological applications. However, the combinatorially vast chemical and configurational search space poses a significant…
At this centenary of the discovery of superconductivity, the design of new and more useful superconductors remains as enigmatic as ever. These materials play crucial roles both for fundamental science and applications, and they hold great…
We perform calculations to obtain the $H_{c2}$ curve of high temperature superconductors (HTSC). We consider explicitly the fact that the HTSC possess intrinsic inhomogeneities by taking into account a non uniform charge density $\rho(r)$.…
Using the Ginzburg-Landau theory in very general terms, we develop a simple scaling procedure which allows to establish the temperature dependence of the upper critical field and the value of the superconducting critical temperature Tc of…
In anomaly detection, a prominent task is to induce a model to identify anomalies learned solely based on normal data. Generally, one is interested in finding an anomaly detector that correctly identifies anomalies, i.e., data points that…
We elucidate a recently emergent framework in unifying the two families of high temperature (high $T_c$) superconductors, cuprates and iron-based superconductors. The unification suggests that the latter is simply the counterpart of the…
We describe a simple AC susceptometer built in-house that can be used to make high-resolution measurements of the magnetic susceptibility of high-temperature superconductors in an undergraduate physics lab. Our system, cooled using liquid…
Iron-based superconductors, a cornerstone of low-temperature physics, have been the subject of numerous theoretical models aimed at deciphering their complex behavior. In this study, we present a comprehensive approach that amalgamates…
It is shown that the critical temperature of the superconductor is related to the Sommerfeld constant, i.e. it is determined by the Fermi energy for I-type superconductors. The estimation of properties of II-type superconductors reveals a…
Predictive materials synthesis is the primary bottleneck in realizing new functional and quantum materials. Strategies for synthesis of promising materials are currently identified by time-consuming trial and error approaches and there are…
The amplitude of ground state superconducting energy gap $\Delta(0)$ and relative jump in electronic specific heat at the transition temperature, $\Delta$$C$${/}$$\gamma$$T_c$, are primary fundamental parameters of any superconductor. There…
Inspired by nature, this study employs the Materials Genome Initiative to identify key components of HTSC superconductors. Integrating AI with high-throughput screening, we uncover crucial superconducting "genes". Through HTS techniques and…
We present a brief review of the present day situation with studies of high-temperature superconductivity in iron pnictides and chalcogenides. Recent discovery of superconductivity with T_c > 30 K in A_xFe_{2-x/2}Se_2 (A=K,Cs,Tl,...)…
Accurate thermal analysis of composites and porous media requires detailed characterization of local thermal properties in small scale. For some important applications such as lithium-ion batteries, changes in the properties during the…
Superconductor/ferromagnet bilayers are known to exhibit nontrivial dependence of the critical temperature T_c on the thickness d_f of the ferromagnetic layer. We develop a general method for investigation of T_c as a function of the…
We explore a class of holographic superconductors built using non-abelian condensates on probe branes in conformal and non-conformal backgrounds. These are shown to exhibit behaviour of the specific heat which resembles that of heavy…