Related papers: Predicting Lattice Phonon Vibrational Frequencies …
We develop a polycrystal graph neural network (PGNN) model for predicting the effective properties of polycrystalline materials, using the Li7La3Zr2O12 ceramic as an example. A large-scale dataset with >5000 different three-dimensional…
We present a graph-based deep learning framework for predicting the magnetic properties of quasi-one-dimensional Ising spin systems. The lattice geometry is encoded as a graph and processed by a graph neural network (GNN) followed by fully…
We study the lattice dynamics of iron superconductor FeSe, and address the fundamental question of how important is proper description of fluctuating magnetic moments in metallic systems for phonon dispersion and phonon density of states.…
As the length-scales of materials decrease, heterogeneities associated with interfaces approach the importance of the surrounding materials. Emergent electronic and magnetic interface properties in superlattices have been studied…
We present a vibrational dynamical mean-field theory (VDMFT) of the dynamics of atoms in solids with anharmonic interactions. Like other flavors of DMFT, VDMFT maps the dynamics of a periodic anharmonic lattice of atoms onto those of a…
Atomic vibrations in perfect, slightly defective or mixed crystals are to a large extent well understood since many decades. Theoretical descriptions are thus in excellent agreement with the experiments. As a consequence, phonon-related…
Determining the stability of chemical compounds is essential for advancing material discovery. In this study, we introduce a novel deep neural network model designed to predict a crystal's formation energy, which identifies its stability…
The coherent lattice vibrations significantly impact physical and chemical processes in solids, such as heat transfer, displacive phase transitions, and thermal conductivity. Thus, probing lattice dynamics in real-space and real-time is…
Ultrasound detection is one of the most important nondestructive subsurface characterization tools of materials, whose goal is to laterally resolve the subsurface structure with nanometer or even atomic resolution. In recent years, graphene…
Moir\'e superlattices in two-dimensional (2D) materials exhibit rich quantum phenomena, but ab initio modelling of these systems remains computationally prohibitive. Existing machine learning methods for accelerating density-functional…
We develop a formalism for the calculation of the frequency band structure of a phononic crystal consisting of non-overlapping elastic spheres, characterized by Lam\'e coefficients which may be complex and frequency dependent, arranged…
The probing of coherent lattice vibrations in solids has been conventionally carried out using time-resolved transient spectroscopy where only the relative oscillation amplitude can be obtained. Using time-resolved X-ray techniques,…
While Bernal stacked bilayer graphene bears two distinct atom types in its lattice, there exists no analytical framework addressing the number of atomic environments that emerge in twisted bilayer graphene superlattices. Here, we…
Classical thermal transport theories that preserve rotational symmetry, predict strong anharmonic scattering of out-of-plane lattice vibrational modes called flexural phonons in flat suspended graphene sheets. Such strong scattering…
In order to make accurate predictions of material properties, current machine-learning approaches generally require large amounts of data, which are often not available in practice. In this work, an all-round framework is presented which…
The primary issue in inverse halftoning is removing noisy dots on flat areas and restoring image structures (e.g., lines, patterns) on textured areas. Hence, a new structure-aware deep convolutional neural network that incorporates two…
We have performed extensive ab initio calculations to investigate phonon dynamics and their possible role in superconductivity in BaFe2As2 and related systems. The calculations are compared to inelastic neutron scattering data that offer…
In the design of engineered components, rigorous vibration testing is essential for performance validation and identification of resonant frequencies and amplitudes encountered during operation. Performing this evaluation numerically via…
We use a method based on optical coherent transients to study the vibrational coherence lifetimes of atoms trapped in the potential wells of a near-resonant optical lattice in the oscillating regime. The dependence of the positions and…
While the vibrational thermodynamics of materials with small anharmonicity at low temperatures has been understood well based on the harmonic phonons approximation; at high temperatures, this understanding must accommodate how phonons…