相关论文: Identification of High-Dielectric Constant Compoun…
Inorganic crystal materials have broad application potential due to excellent physical and chemical properties, with elastic properties (shear modulus, bulk modulus) crucial for predicting materials' electrical conductivity, thermal…
The analogy between magnetism and electricity has long been established by Maxwell in the 19th century, in spite of their subtle difference. While magnetic materials display paramagnetism, ferromagnetism, antiferromagnetism, and…
Owing to the fascinating physical characteristics of two-dimensional (2D) materials and their heterostructure, much effort has been devoted to exploring their basic physical properties as well as discovering other novel 2D materials.…
Sodium-ion batteries (SIBs) share similar electrochemistry with Li but offer several advantages, including high abundance in nature and low cost, as well as suitability for fast charging due to a Na-ion mobility higher than that of Li. The…
Data driven materials discovery and optimization requires databases that are error free and experimentally verified. Performing material measurements are time-consuming and often restricted by the fact that material sample preparations are…
Within 4 different crystal structures, 2280 ternary intermetallic configurations have been investigated via high-throughput density functional theory calculations in order to discover new semiconducting materials. The screening is…
Comparing with the conventional semiconductors, the choice of the two dimensional semiconductor (2DSC) materials is very limited. Based on proper electron counting, we propose a large family of 2DSCs, all adopting the same structure and…
Two-dimensional (2D) materials with zero band gap exhibit remarkable electronic properties with wide tunability. High harmonic generation (HHG) in such materials offers unique platforms to develop novel optoelectronic devices at nanoscale,…
Many transition-metal oxides show very large ("colossal") magnitudes of the dielectric constant and thus have immense potential for applications in modern microelectronics and for the development of new capacitance-based energy-storage…
To investigate the physical characteristics of the half-Heusler BaHgSn molecule, we used theoretical calculations within the Density Functional Theory (DFT) framework utilizing the LSDA+mBJ technique in this study. Using the optimal lattice…
Accurate prediction of dielectric tensors is essential for accelerating the discovery of next-generation inorganic dielectric materials. Existing machine learning approaches, such as equivariant graph neural networks, typically rely on…
Half-Heusler compounds have emerged as promising thermoelectric materials that offer huge compositional space to tune their thermoelectric performance. A class of stable half Heusler compounds formed from elements of three specific groups…
The paper proposes a simple and efficient method to study the dielectric properties of composite materials modeled using very large random resistor-capacitor (RC) networks. The algorithm is based on the Frank-Lobb reduction scheme and…
We compile data and machine learned models of solid Li-ion electrolyte performance to assess the state of materials discovery efforts and build new insights for future efforts. Candidate electrolyte materials must satisfy several…
This work demonstrates high-throughput screening of flexible magnetic materials for efficient transverse thermoelectric conversion based on the anomalous Nernst effect (ANE). The approach integrates automated annealing and contactless…
The conventional distinction between semiconductors and insulators is often based on the magnitude of the band gap, with materials exhibiting gaps wider than 3 eV typically classified as insulators. However, the emergence of…
We report a theoretical study of dielectric properties of models of amorphous Boron Nitride, using interatomic potentials generated by machine learning. We first perform first-principles simulations on small (about $100$ atoms in the…
It is well known that the high electric conductivity, large Seebeck coefficient, and low thermal conductivity are preferred for enhancing thermoelectric performance, but unfortunately, these properties are strongly inter-correlated with no…
Studying materials under extreme pressure in diamond anvil cells (DACs) is key to discovering new states of matter, yet no method currently allows the direct measurement of the electronic structure in this environment. Solid-state high…
We survey the landscape of binary hydrides across the entire periodic table from 10 to 500 GPa using a crystal structure prediction method. Building a critical temperature ($T_c$) model, with inputs arising from density of states…