相关论文: Finite-Temperature Ferroelectric Phase Transitions…
Machine-learning force fields (MLFF) should be accurate, computationally and data efficient, and applicable to molecules, materials, and interfaces thereof. Currently, MLFFs often introduce tradeoffs that restrict their practical…
The molecular-to-atomic liquid-liquid transition (LLT) in high-pressure hydrogen is a fundamental topic touching domains from planetary science to materials modeling. Yet, the nature of the LLT is still under debate. To resolve it,…
Specific forms of the exchange correlation energy functionals in first-principles density functional theory-based calculations, such as the local density approximation (LDA) and generalized-gradient approximations (GGA), give rise to…
Understanding collective phenomena in quantum materials from first principles is a promising route toward engineering materials properties on demand and designing new functionalities. This work examines the quantum paraelectric state, an…
The investigation of the structural phase transition in the vicinity of the Curie temperature $T_c$ of LiNb$_{1-x}$Ta$_x$O$_3$ crystals is motivated by the expected combination of advantageous high-temperature properties of LiNbO$_3$ and…
Machine learning thermodynamic perturbation theory (MLPT) is a promising approach to compute finite temperature properties when the goal is to compare several different levels of ab initio theory and/or to apply highly expensive…
Recent materials research has advanced the maximum ferromagnetic transition temperature in semiconductors containing magnetic elements toward room temperature. Reaching this goal would make information technology applications of these…
Manganese telluride (MnTe) has garnered strong interest recently for its antiferromagnetic semiconductor properties, which are promising for applications in spintronics, data storage, and quantum computing. In this study, we discovered that…
Optical spectroscopy, X-ray diffraction measurements, density functional theory (DFT) and density functional theory + embedded dynamical mean field theory (DFT+eDMFT) have been used to characterize structural and electronic properties of…
Composition-temperature phase diagrams are crucial for designing ferroelectric materials, however predicting them accurately remains challenging due to limited phase transformation data and the constraints of conventional methods. Here, we…
Mesoscale patterns as observed, e.g., in ferromagnets, ferroelectrics, superconductors, mono-molecular films, or block-copolymers, reflect spatial variations of a pertinent order parameter at length- and time-scales that may be described…
We use phase field simulations to study composites made of two different ferroelastics (e.g., two types of martensite). The deformation of one material due to a phase transformation can elastically affect the other constituent and induce it…
In multiferroic BiFeO3 thin films grown on highly mismatched LaAlO3 substrates, we reveal the coexistence of two differently distorted polymorphs that leads to striking features in the temperature dependence of the structural and…
Molecular-dynamics simulations of KNbO$_3$ reveal preformed dynamic chain-like structures, present even in the paraelectric phase, that are related to the softening of phonon branches over large regions of the Brillouin zone. The phase…
Efficient molecular dynamics (MD) simulation is vital for understanding atomic-scale processes in materials science and biophysics. Traditional density functional theory (DFT) methods are computationally expensive, which limits the…
Melting is a high temperature process that requires extensive sampling of configuration space, thus making melting temperature prediction computationally very expensive and challenging. Over the past few years, I have built two methods to…
Molecular dynamics (MD) simulations are performed to investigate the thermal and mass accommodation coefficients (TAC and MAC, respectively) for the combination of iron(-oxide) and air. The obtained values of TAC and MAC are then used in a…
We perform first-principles path integral Monte Carlo (PIMC) and density functional theory molecular dynamics (DFT-MD) calculations to explore warm dense matter states of LiF. Our simulations cover a wide density-temperature range of…
The present work addresses the simulation of pore emptying during the drying of battery electrodes. For this purpose, a model based on the multiphase-field method (MPF) is used, since it is an established approach for modeling and…
Identifying phase transitions is one of the key challenges in quantum many-body physics. Recently, machine learning methods have been shown to be an alternative way of localising phase boundaries also from noisy and imperfect data and…