Inhibition of Lithium Dendrite Growth with Highly Concentrated Ions: Cellular Automaton Simulation and Surrogate Model with Ensemble Neural Networks

We have developed a lattice Monte Carlo (MC) simulation based on the diffusion-limited aggregation model that accounts for the effect of the physical properties of small ions such as inorganic...

Off-Lattice Monte-Carlo Approach for Studying Nucleation and Evaporation Phenomena at the Molecular Scale

Droplet nucleation and evaporation are ubiquitous in nature and many technological applications, such as phase-change cooling and boiling heat transfer. So far, the description of these phenomena at the molecular scale has posed challenges for modelling with most of the models being implemented on a lattice. Here, we propose an off-lattice Monte-Carlo approach combined with a grid that can be used for the investigation of droplet formation and evaporation. We provide the details of the model, its implementation as Python code, and results illustrating its dependence on various parameters. The method can be easily extended for any force-field (e.g., coarse-grained, all-atom models, and external fields, such as gravity and electric field). Thus, we anticipate that the proposed model will offer opportunities for a wide range of studies in various research areas involving droplet formation and evaporation and will also form the basis for further method developments for the molecular modelling of such phenomena.

Numerical and Experimental Evaluation of Thermal Conductivity: An Application to Al-Sn Alloys

Evaluation of thermal conductivity of composite materials is extremely important to control material performance and stability in thermal applications as well as to study transport phenomena. In this paper, numerical simulation of effective thermal conductivity of Al-Sn miscibility gap alloys is validated with experimental results. Lattice Monte-Carlo (LMC) method is applied to two-phase and three-phase materials, allowing to estimate effective thermal conductivity from micrographs and individual phase properties. Numerical results are compared with literature data for cast Al-Sn alloys for the two-phase model and with a specifically produced powder metallurgy Al-10vol%Sn, tested using laser flash analysis, for a three-phase simulation. A good agreement between numerical and experimental data was observed. Moreover, LMC simulations confirmed the effect of phase morphology as well as actual phase composition on thermal conductivity of composite materials.

Partial deconfinement at strong coupling on the lattice

We provide evidence for partial deconfinement — the deconfinement of a SU(M) subgroup of the SU(N) gauge group — by using lattice Monte Carlo simulations. We take matrix models as concrete examples. By appropriately fixing the gauge, we observe that the M × M submatrices deconfine. This gives direct evidence for partial deconfinement at strong coupling. We discuss the applications to QCD and holography.

Designing 2D covalent networks with lattice Monte Carlo simulations: precursor self-assembly

Theoretical calculations predicted multiple outputs of the surface-confined self-assembly of metal–organic precursors comprising naphthalene monomeric units with differently distributed halogen atoms.

Impurity lattice Monte Carlo for hypernuclei

We consider the problem of including $$\varLambda $$ Λ hyperons into the ab initio framework of nuclear lattice effective field theory. In order to avoid large sign oscillations in Monte Carlo simulations, we make use of the fact that the number of hyperons is typically small compared to the number of nucleons in the hypernuclei of interest. This allows us to use the impurity lattice Monte Carlo method, where the minority species of fermions in the full nuclear Hamiltonian is integrated out and treated as a worldline in Euclidean projection time. The majority fermions (nucleons) are treated as explicit degrees of freedom, with their mutual interactions described by auxiliary fields. This is the first application of the impurity lattice Monte Carlo method to systems where the majority particles are interacting. Here, we show how the impurity Monte Carlo method can be applied to compute the binding energies of the light hypernuclei. In this exploratory work we use spin-independent nucleon–nucleon and hyperon–nucleon interactions to test the computational power of the method. We find that the computational effort scales approximately linearly in the number of nucleons. The results are very promising for future studies of larger hypernuclear systems using chiral effective field theory and realistic hyperon–nucleon interactions, as well as applications to other quantum many-body systems.