arXiv subjects

Erich Wimmer

Publications and source records attributed to Erich Wimmer.

5 recordsLinked to original sources

arXiv2026

Unveiling and quantifying the topology-dependent pre-melting of nanoparticles

The melting of metallic nanoparticles is governed by surface premelting, a phenomenon traditionally modeled as the isotropic growth of a uniform liquid shell. Challenging this classical view, we report facet-dependent premelting in hexagonal close-packed Co nanoparticles, arising from the structural heterogeneity of their surface. In molecular dynamics simulations (587 to 13047 atoms), the onset of surface mobility is observed as low as 20% of the bulk melting point, driven by the early disordering of stepped $\{01\bar{1}1\}$ facets. These facets consistently melt nearly 150 K below flat $\{0001\}$ facets, regardless of particle size. We show that both surface and facet melting temperatures scale with nanoparticle size through the Gibbs-Thomson effect, and determine a size-dependent critical liquid layer thickness that triggers complete melting of the nanoparticle, which saturates near three atomic layers. Our results confirm recent experimental observations of surface premelting and extend the framework to anisotropic particles with facet-orientation-dependent behavior.

cond-mat.mtrl-sci↗

arXiv2024

A dual-cutoff machine-learned potential for condensed organic systems obtained via uncertainty-guided active learning

Machine-learned potentials (MLPs) trained on ab initio data combine the computational efficiency of classical interatomic potentials with the accuracy and generality of the first-principles method used in the creation of the respective training set. In this work, we implement and train a MLP to obtain an accurate description of the potential energy surface and property predictions for organic compounds, as both single molecules and in the condensed phase. We devise a dual descriptor, based on the atomic cluster expansion (ACE), that couples an information-rich short-range description with a coarser long-range description that captures weak intermolecular interactions. We employ uncertainty-guided active learning for the training set generation, creating a dataset that is comparatively small for the breadth of application and consists of alcohols, alkanes, and an adipate. Utilizing that MLP, we calculate densities of those systems of varying chain lengths as a function of temperature, obtaining a discrepancy of less than 4% compared with experiment. Vibrational frequencies calculated with the MLP have a root mean square error of less than 1 THz compared to DFT. The heat capacities of condensed systems are within 11% of experimental findings, which is strong evidence that the dual descriptor provides an accurate framework for the prediction of both short-range intramolecular and long-range intermolecular interactions.

physics.chem-ph↗

arXiv2024

Polyvalent Machine-Learned Potential for Cobalt: from Bulk to Nanoparticles

We present the development and applications of a quadratic Spectral Neighbor Analysis Potential (q-SNAP) for ferromagnetic cobalt. Trained on Density Functional Theory calculations using the Perdew-Burke-Ernzerhof (DFT-PBE) functional, this machine-learned potential enables simulations of large systems over extended time scales across a wide range of temperatures and pressures at near DFT accuracy. It is validated by closely reproducing the phonon dispersions of hexagonal close-packed (hcp) and face-centered cubic (fcc) Co, surface energies, and the relative stability of nanoparticles of various shapes. An important feature of this novel potential is its numerical stability in long molecular dynamics simulations. This robustness is exploited to compute the heat capacity of nanoparticles containing up to 9201 atoms, showing convergence to less than 2 J.K-1.mol-1 after 100 ns. Computations of the melting temperature of nanoparticles as a function of their size revealed a convergence to the bulk limit in excellent agreement with the experimental value. Thus, the new, highly accurate machine-learned potential for Co opens exciting opportunities for further applications such as the dynamics of nanoparticles in catalytic reactions.

cond-mat.mtrl-sci↗

arXiv2015

Structure, Energy, and Thermal Transport Properties of Si-SiO$_2$ Nanostructures using an Ab initio based Parameterization of a Charge-Optimized Many-Body Forcefield

In an effort to extend the reach of current ab initio calculations to simulations requiring millions of configurations for complex systems such as heterostructures, we have parameterized the third-generation Charge Optimized Many-Body (COMB3) potential using solely ab initio total energies, forces, and stress tensors as input. The quality and the predictive power of the new forcefield is assessed by computing properties including the cohesive energy and density of SiO$_2$ polymorphs, surface energies of alpha-quartz, and phonon densities of states of crystalline and amorphous phases of SiO$_2$. Comparison with data from experiments, ab initio calculations, and molecular dynamics simulations using published forcefields including BKS (van Beest, Kramer, and van Santen), ReaxFF, and COMB2 demonstrate an overall improvement of the new parameterization. The computed temperature dependence of the thermal conductivity of crystalline alpha-quartz and the Kapitza resistance of the interface between crystalline Si(001) and amorphous silica are in excellent agreement with experiment, setting the stage for simulations of complex nanoscale heterostructures.

cond-mat.mtrl-sci↗

arXiv2006

Structure and optical properties of alpha- and gamma-cerium sesquisulfide

Structural and electronic properties of the alpha- and gamma-phases of cerium sesquisulfide, Ce2S3, are examined by first-principles calculations using the GGA+U extension of density functional theory. The strongly correlated f-electrons of Ce are described by a Hubbard-type on-site Coulomb repulsion parameter. A single parameter of $U^/prime$=4 eV yields excellent results for crystal structures, band gaps, and thermodynamic stability for both Ce2S3 allotropes. This approach gives insights in the difference in color of brownish-black alpha-Ce2S3 and dark red gamma-Ce2S3. The calculations predict that both Ce2S3 modifications are insulators with optical gaps of 0.8 eV (alpha-phase) and 1.8 eV (gamma-phase). The optical gaps are determined by direct electronic excitations at k=Gamma from localized and occupied Ce 4f-orbitals into empty Ce 5d-states. The f-states are situated between the valence and conduction bands. The difference of 1 eV between the optical gaps of the two Ce2S3 modifications is explained by different coordinations of the cerium cations by sulfur anions. For both Ce2S3 modifications the calculations yield an effective local magnetic moment of 2.6 $mu_B$ per cerium cation, which is in agreement with measurements. The electronic energy of the alpha-phase is computed to be 6 kJ/mol lower than that of the gamma-phase, which is consistent with the thermodynamic stability of the two allotropes.

cond-mat.mtrl-sci↗