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Item type:Publication, Access status: with files , Dirichlet-type absorbing boundary conditions for ordinary state-based peridynamicsWe present time-domain Dirichlet-type absorbing boundary conditions (ABCs) for 2D ordinary state-based peridynamics using the Linear Peridynamic Solid (LPS) model, aimed at efficiently truncating unbounded elastodynamic domains while retaining the flexibility of arbitrary Poisson ratios. The proposed ABCs are built from a semi-analytical far-field representation expressed as a finite superposition of plane-wave modes satisfying the discrete LPS dispersion relation, so that outgoing waves are absorbed consistently with the numerical P- and S-wave branches and their Poisson-ratio-dependent polarizations. A cloud-based collocation and least-squares procedure eliminates the unknown modal amplitudes locally and yields precomputable updating operators that prescribe boundary displacement and velocity directly within explicit time stepping, avoiding spatial derivatives, transform techniques, auxiliary evolution equations, and surface-correction procedures at truncated horizons. Unlike our earlier bond-based ABC formulations, the present work requires a new state based far-field theory, a new discrete dispersion operator with coupled P- and S-wave branches for general Poisson ratios, and an additional treatment of the nonlocal dilatation field. Numerical benchmarks show that the resulting ABCs strongly suppress nonphysical reflections over a broad range of material parameters, providing a simple and robust alternative to absorbing layers.Publicationtype: Journal Article20 17 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Surface and boundary corrections in peridynamics using optimized nodal influence weights(Wiley, 2026-07-14); ; ; ; Peridynamics (PD), similarly to some other nonlocal continuum theories, exhibits truncated interaction horizons near free surfaces, cracks, and voids in bounded domains. This loss of neighbors causes artificial surface effects and inconsistencies in the derivative and energy operators that persist under discretization refinement, limiting PD accuracy and robustness. First, the analysis and numerical isolation of the effects of horizon truncation on these operators are carried out, showing how it induces surface softening in bond‐based and stiffening/softening in state‐based PD formulations. Then, a purely PD‐based surface correction is proposed to restore full‐horizon behavior while preserving the original horizon radius and bond topology. Each node is assigned a scalar influence weight, and every bond is scaled by the average of the endpoint weights to maintain symmetry. The nodal influence weights are computed in a preprocessing optimization step enforcing agreement between truncated‐ and full‐horizon derivative and energy operators. Unlike existing approaches, the proposed method does not rely on ghost particles, variable horizons, or reference solutions from classical continuum mechanics (CCM). Benchmarks in one, two, and three dimensions, including a dynamic brittle fracture test, show that the optimized nodal influence weights reduce boundary‐induced surface effects, improve energy consistency, and accelerate convergence of PD solutions. Analytical evaluation of the calibration targets over full‐horizons also improves interior volume integration accuracy. The proposed scheme is simple to implement in existing PD codes, incurs only a modest preprocessing cost, performs robustly for flat and curved boundaries on both regular and irregular point sets, produces reliable crack paths, and applies to both bond‐based and ordinary state‐based PD formulations. An open‐source Python implementation, perifit, is provided.Publicationtype: Journal Article41 61 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Simultaneous learning of static and dynamic charges(Royal Society of Chemistry (RSC), 2026-06-01); ; ; Long-range interactions and electric response are essential for accurate modeling of condensed-phase systems, but capturing them efficiently remains a challenge for atomistic machine learning. Traditionally, these two phenomena can be represented by static charges that underlie Coulomb interactions between atoms, and dynamic charges such as atomic polar tensors—aka Born effective charges—describing the response to an external electric field. We critically compare different approaches to learn both types of charges within a single model architecture, taking bulk water and water clusters as paradigmatic examples: (1) learning them independently; (2) coupling static and dynamic charges based on their physical relationship with a single global coupling constant to account for dielectric screening; (3) coupled learning with a local, environment-dependent screening factor. In the coupled case, correcting for dielectric screening is essential, yet the common assumption of homogeneous, isotropic screening breaks down in heterogeneous systems such as water clusters. A learned, environment-dependent screening restores high accuracy for the dynamic charges. However, the accuracy gain over independent dynamic predictions is negligible, while the computational cost increases compared to using separate models for static and dynamic charges. This suggests that, despite the formal connection between the two charge types, modeling them independently is the more practical choice for both condensed-phase and isolated cluster systems.Publicationtype: Journal Article109 46 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Temperature-dependent capacitance of the electrical double layerWe use atomistic simulations to study the electrical double layer (EDL) at an electrode–electrolyte interface at different temperatures. For a constrained electrode charge, the potential drop over the EDL increases with temperature, a phenomenon known as the thermal voltage rise (TVR). Prior continuum models attributed TVR to expansion of the EDL with increasing temperature; conversely, our simulations with aqueous, organic, and ionic liquids show that the EDL does not expand but that the TVR is caused by a decrease in interfacial permittivity with increasing temperatures.Publicationtype: Journal Article57 60 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Interfacial ion hydration and electrostatics govern salt precipitation and crystal morphology(2025-12-28); ; ; Salt precipitation, a phenomenon central to processes such as soil salinization, water treatment, and energy storage, is dictated by nanoscale hydration and electrostatic interactions at crystal interfaces. Understanding how their interplay gives rise to salt-specific growth behaviors and morphologies remains a critical challenge. Combining large-scale molecular dynamics simulations with free energy calculations, we investigate the precipitation behavior of three common salts, namely, NaCl, KCl, and Na2SO4, on their respective crystal surfaces. While all crystals grow steadily under controlled supersaturation, their surface morphologies differ markedly. KCl grows in a nearly ideal layer-by-layer mode, whereas NaCl and Na2SO4 develop increasingly rough, defect-rich surfaces. This roughening is accompanied by an early-stage charge imbalance at the crystal surface, characterized by preferential cation adsorption. The resulting local electrostatic environment modifies the structuring and dynamics of interfacial water, which in turn facilitates the premature growth of subsequent layers. We further find that ion adsorption is strongly defect-dependent: kinks provide stabilizing environments, whereas steps are energetically unfavorable due to their distinct hydration. Our study offers molecular-level insight into the coupled roles of ion-specific adsorption and interfacial hydration in shaping crystal morphology for different salts.Publicationtype: Journal Article61 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Intermittent molecular motion and first passage statistics for the NMR relaxation of confined waterThe structure and dynamics of fluids confined in nanoporous media differ from those in bulk, which can be probed using NMR relaxation measurements. We here show, using atomistic molecular dynamics simulations of water in a slit nanopore, that the behavior of the NMR relaxation rate, R_{1}, with varying surface interaction and confinement strength can be estimated from the exchange statistics of fluid molecules between the adsorbed surface layer and the bulk region. In detail, we test the applicability of intermittent molecular water dynamics, a theoretical framework that relates NMR relaxation to the statistics of molecular exchange between these two states. We confront this framework with the direct evaluation of dipolar NMR relaxation rates from atomistic molecular dynamics simulations of water confined in a slit nanopore, allowing to assess its accuracy across varying surface interactions. We employ first return passage time calculations to quantify the molecular exchange statistics, thereby linking microscopic parameters of the confined fluid-such as adsorption time, pore size, and diffusion coefficient-to the NMR relaxation rate. Our results show that the theoretical framework proposed by Levitz et al. captures the qualitative trends of NMR relaxation rates observed in our molecular simulations. This approach allows to predict, interpret, and analyze the molecular relaxation of fluids at interfaces using merely concepts of statistical mechanics that can be generalized to closed and open geometries and thus yields direct insights into the experimental study of NMR relaxation with varying surface chemistry or confinement strength.Publicationtype: Journal Article29 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Effect of anion hydrophobicity on the oxidation of ferrocene-terminated monolayersSelf-assembled monolayers (SAMs) terminated with ferrocene ((Formula presented.)) moieties are a popular model system for electron transfer processes at solid-liquid interfaces. Numerous experimental studies have found a correlation between the hydrophobicity of anions in the electrolyte and the redox potential. In this computational study, the redox potential is calculated for various anion species and SAM configurations using classical molecular dynamics. Thermodynamic integration and the constrained charge method are used to determine the redox potential as the free energy change associated with electron transfers from the (Formula presented.) moieties to the electrodes. The results show the anticipated lower redox potentials for hydrophobic anions and allow the study of changes at the solid-liquid interface at the atomistic level.Publicationtype: Journal Article57 53 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Efficient treatment of long-range electrostatics in charge equilibration approaches(American Institute of Physics (AIP), 2025-05-07); ; ; ; A charge equilibration method based on real-space Gaussians as charge densities is presented. The implementation is part of the Electrode package available in the Large-scale Atomic/Molecular Massively Parallel Simulator and benefits from its efficient particle-mesh Ewald approach. A simple strategy required to switch from the previously used Slater-type orbital (STO) shielding to Gaussians is provided by fitting the Coulomb energy of two Gaussian charge distributions to the repulsion between two STOs. Their widths were optimized for O, Si, and Ti species, obtaining results consistent with previous studies using STOs in the case of SiO2 polymorphs. In the limit of sufficiently narrow Gaussians, it is shown that the implementation converges to electronegativity equalization method results for the case of Ti/TiOx interfaces. The method presented is implemented in a way that is potentially beneficial for the application of modern machine-learning force fields that include long-range electrostatic interactions.Publicationtype: Journal Article36 74