Related papers: Data-Driven Prediction of Complex Crystal Structur…
Uncontrollable dendrites growth during electrochemical cycles leads to low Coulombic efficiency and critical safety issues in Li metal batteries. Hence, a comprehensive understanding of the dendrite formation mechanism is essential for…
The prediction of crystal properties plays a crucial role in the crystal design process. Current methods for predicting crystal properties focus on modeling crystal structures using graph neural networks (GNNs). Although GNNs are powerful,…
Metal-insulator transition (MIT) materials are a useful platform for emerging microelectronic, optoelectronic, and neuromorphic devices, but their discovery is hindered by the high computational cost of electronic structure modeling, the…
Solid-state electrolyte batteries are expected to replace liquid electrolyte lithium-ion batteries in the near future thanks to their higher theoretical energy density and improved safety. However, their adoption is currently hindered by…
A porous electrode resulting from unregulated Li growth is the major cause of the low Coulombic efficiency and potential safety hazards of rechargeable Li metal batteries. Strategies aiming to achieve large granular Li deposits have been…
Lithium abundances in open clusters are a very effective probe of mixing processes, and their study can help to understand the large depletion of lithium in the Sun. Due to its age and metallicity, the open cluster M67 is especially…
Machine learning potentials (MLPs) have significantly advanced global crystal structure prediction by enabling efficient and accurate property evaluations. In this study, global structure searches are performed for 11 bismuth-based binary…
The metal-semiconductor-metal transition in dense lithium is considered as an archetype of interplay between interstitial electron localization and delocalization induced by compression, which leads to exotic electride phases. In this work,…
The electronic structure of the lithium atom in a strong magnetic field 0 <= gamma <= 10 is investigated. Our computational approach is a full configuration interaction method based on a set of anisotropic Gaussian orbitals that is…
We introduce a simple and efficient model to describe the potential energy surface of lithium diffusing in a solid-state ionic conductor. First, we assume that the Li atoms are fully ionized and we neglect the weak dependence of the…
Context: Lithium is a fragile element, which is easily destroyed in the stellar interior. The existence of lithium-rich giants still represents a challenge for stellar evolution models. Aims: We have collected a large database of…
We introduce machine learning (ML) models that predict the electronic structure of materials across a wide temperature range. Our models employ neural networks and are trained on density functional theory (DFT) data. Unlike most other ML…
Two-dimensional (2D) layered magnetic materials are generating a great amount of interest for the next generation of electronic devices thanks to their remarkable properties associated to spin dynamics. The recently discovered layered…
Hydrogen and lithium, along with their compounds, are crucial materials for nuclear fusion research. High-pressure studies have revealed intricate structural transitions in all these materials. However, research on lithium hydrides beyond…
Under pressure, metals exhibit increasingly shorter interatomic distances. Intuitively, this response is expected to be accompanied by an increase in the widths of the valence and conduction bands and hence a more pronounced…
Machine learning (ML) models utilizing structure-based features provide an efficient means for accurate property predictions across diverse chemical spaces. However, obtaining equilibrium crystal structures typically requires expensive…
Cubic spinel Li$_{\rm 1+x}$Ti$_2$O$_4$ is a promising electrode material as it exhibits a high lithium diffusivity and undergoes minimal changes in lattice parameters during lithiation and delithiation, thereby ensuring favorable…
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…
A new superstructure of layered pristine LiNiO2 (LNO) was obtained optimizing a large supercell of the 166 space group, the one observed experimentally by XRD, and relaxing both cell parameters and internal positions. The crystal structure…
We have determined Li abundances in 55 metal-poor (3.6 < [Fe/H] < -0.7) stars with extreme orbital kinematics. We find the Li abundance in the Li-plateau stars and examine its decrease in low-temperature, low-mass stars. The Li observations…