Related papers: A first-principles machine-learning force field fo…
The organization of water molecules and ions between charged mineral surfaces determines the stability of colloidal suspensions and the strength of phase-separated particulate gels. In this article we assemble a density functional that…
A heat exchange interface at subzero temperature in a water vapor environment, exhibits high probability of frost formation due to freezing condensation, a factor that markedly decreases the heat transfer efficacy due to the considerable…
As one of the most fascinating confined water/ice phenomena, two-dimensional square ice has been extensively studied and experimentally confirmed in recent years. Apart from the unidirectional homogeneous square icing patterns considered in…
We examine to what extent the inferred surface temperature of magnetars in quiescence can constrain the presence of a superfluid in the neutron star core and the role of magnetic field decay in the core. By performing detailed simulations…
Crystallization from a supercooled liquid initially proceeds via the formation of a small solid embryo (nucleus), which requires surmounting an activation barrier. This phenomenon is most easily studied by numerical simulation, using…
First-principles alloy theory is used to establish the $\gamma$-surface of Fe-Cr-Ni alloys as function of chemical composition and temperature. The theoretical stacking fault energy (SFE) versus chemistry and temperature trends agree well…
We report an investigation of the suitability of quantum embedding for modeling the effects of the environment on the X-ray photoelectron spectra of hydrogen chloride and the chloride ions adsorbed on ice surfaces, as well as of chloride…
Machine-learned interatomic potentials are revolutionising atomistic materials simulations by providing accurate and scalable predictions within the scope covered by the training data. However, generation of an accurate and robust training…
The surface diffusion potential landscape plays an essential role in a number of physical and chemical processes such as self-assembly and catalysis. Diffusion energy barriers can be calculated theoretically for simple systems, but there is…
Recent theoretical studies have suggested that a magnetic field may play a crucial role in the first star formation in the universe. However, the influence of the magnetic field on the first star formation has yet to be understood well. In…
The simulation and analysis of the thermal stability of nanoparticles, a stepping stone towards their application in technological devices, require fast and accurate force fields, in conjunction with effective characterisation methods. In…
Machine-learning-based parameterizations (i.e. representation of sub-grid processes) of global climate models or turbulent simulations have recently been proposed as a powerful alternative to physical, but empirical, representations,…
Diffusion models have emerged as state-of-the-art generative methods for image synthesis, yet their potential as general-purpose feature encoders remains underexplored. Trained for denoising and generation without labels, they can be…
Machine learning has proven to be a valuable tool to approximate functions in high-dimensional spaces. Unfortunately, analysis of these models to extract the relevant physics is never as easy as applying machine learning to a large dataset…
The first off-lattice Monte Carlo kinetics model of interstellar dust-grain surface chemistry is presented. The positions of all surface particles are determined explicitly, according to the local potential minima resulting from the…
FePt nanoparticles are known to exhibit reduced L1$_0$ order with decreasing particle size. The reduction in order reduces the magnetic anisotropy and the thermal stability of the direction of magnetization of the particle. The phenomenon…
Uranium mononitride (UN) is a promising accident-tolerant fuel because of its high fissile density and high thermal conductivity. In this study, we developed the first machine learning interatomic potentials for reliable atomic-scale…
The formation and growth of ice particles, particularly on the surfaces of spherical water droplets, bear profound implications for localized weather systems and global climate. Herein, we develop a theoretical framework for ice nucleation…
Interstellar magnetic fields influence all stages of the process of star formation, from the collapse of molecular cloud cores to the formation of protostellar jets. This requires us to have a full understanding of the physical properties…
Ferrogels, i.e., hydrogels loaded with magnetic nanoparticles, have the ability to deform in external magnetic fields. The precise shape of deformation and the alignment of the gel in the field, however, depend on the interplay of several…