arXiv subjects

Lena Scholz

Publications and source records attributed to Lena Scholz.

5 recordsLinked to original sources

arXiv2026

Microstructural Insights into Fast Ion Transport in Solid Electrolytes via Multiscale Modeling

Improving solid electrolytes is critical for high-performance all-solid-state batteries, yet the microstructural features that enable fast ion transport remain poorly understood. Here, we use multiscale modeling to resolve polycrystalline ion transport from atomic-scale hopping at grain boundaries to continuum-scale percolation, thereby providing insights into realistic solid-electrolyte microstructures. Accurate lightweight machine-learning potentials -- developed via closed-loop active learning for exemplar argyrodites Li$_6$PS$_5$X, X $\in$ {Cl, Br, I} -- are employed to integrate molecular dynamics with finite element simulations. We find that diffusion barriers of the anion-ordered bulk scale linearly with anion radius. Grain boundaries exert opposite effects depending on the bulk: enhancing ion diffusion in low-diffusivity phases but suppressing it in fast-diffusing ones. Li$_6$PS$_5$I exhibits non-Arrhenius transport behavior consistent with experimental observations. Our results clarify the pivotal role of grain boundaries in ion transport and guide a priori microstructural design of advanced solid electrolytes.

cond-mat.mtrl-sci↗

arXiv2025

A collapsed interface approach to resolve grain boundaries in finite element simulations of polycrystalline diffusion

Atomic diffusion affects the properties of various engineering materials, which predominantly occur in the polycrystalline state. A rigorous description of polycrystalline diffusion must therefore account for crystallographic defects, especially grain boundaries (GBs), whose structure and volume fraction - and hence the effective grain size - govern mass transport. Experiments and atomistic simulations consistently show that GBs can accelerate diffusion by up to several orders of magnitude and that fluxes along and across the interface are generally anisotropic. Conventional mesoscale models either neglect GBs or invoke idealized analytical corrections. Fully resolved finite-element meshes are accurate but computationally infeasible when nanometer-thin GB layers are involved. We introduce a collapsed-interface finite element that integrates the GB thickness analytically and embeds the result in a two-dimensional surface element. The formulation (i) treats in-plane and through-plane diffusivity independently, (ii) couples to the surrounding grain matrix without the need for mesh manipulations, and (iii) parametrizes both grain size and GB volume fraction via simple affine scalings, allowing systematic variation without remeshing. Effective diffusivity tensors are extracted by linear computational homogenization. The new finite element reproduces three-dimensional GB transport phenomena - channeled fluxes, concentration discontinuities - at a fraction of the computational cost of explicit models. Parametric studies spanning multiple orders of magnitude in GB diffusivity reveal four distinct diffusion regimes and quantify their impact on the overall response. The framework thus connects atomistic data and continuum predictions, providing an efficient tool for diffusion-driven design and optimization of polycrystalline materials.

cond-mat.mtrl-sci↗

arXiv2024

Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li$_6$PS$_5$Cl using machine-learning interatomic potentials

Li$_6$PS$_5$Cl is a promising candidate for the solid electrolyte in all-solid-state Li-ion batteries. In applications, this material is in a polycrystalline state with grain boundaries (GBs) that can affect ionic conductivity. While atomistic modeling provides valuable information on the impact of GBs on Li diffusion, such studies face either high computational cost (\textit{ab initio} methods) or accuracy limitations (classical potentials) as challenges. Here, we develop a quality-level-based active learning scheme for efficient and systematic development of \textit{ab initio}-based machine-learning interatomic potentials, specifically moment tensor potentials (MTPs), for large-scale, long-time, and high-accuracy simulations of complex atomic structures and diffusion mechanisms as encountered in solid electrolytes. Based on this scheme, we obtain MTPs for Li$_6$PS$_5$Cl and investigate two tilt GBs, $\Sigma3(1\bar{1}2)[110]$, $\Sigma3(\bar{1}11)[110]$, and one twist GB, $\Sigma5(001)[001]$. All three GBs exhibit low formation energies of less than \SI{20}{meV/\angstrom\textsuperscript{2}}, indicating their high stability in polycrystalline Li$_6$PS$_5$Cl. Using the MTPs, diffusion coefficients of the anion-ordered and anion-disordered bulk, as well as the three GBs, are obtained from molecular dynamics simulations of atomistic models. At \SI{300}{\kelvin}, the GB diffusion coefficients fall between the ones of the anion-ordered bulk structure (\SI{0.012e-7}{cm^2/s}, corresponding ionic conductivity about \SI{0.2}{mS/cm}) and the anion-disordered bulk structure (\SI{50}{\percent} Cl/S-anion disorder; \SI{2.203e-7}{cm^2/s}, about \SI{29.8}{mS/cm}) of Li$_6$PS$_5$Cl. Experimental data fall between the Arrhenius-extrapolated diffusion coefficients of the investigated atomic structures.

cond-mat.mtrl-sci↗

arXiv2023

Systematic Comparison of Software Agents and Digital Twins: Differences, Similarities, and Synergies in Industrial Production

To achieve a highly agile and flexible production, it is envisioned that industrial production systems gradually become more decentralized, interconnected, and intelligent. Within this vision, production assets collaborate with each other, exhibiting a high degree of autonomy. Furthermore, knowledge about individual production assets is readily available throughout their entire life-cycles. To realize this vision, adequate use of information technology is required. Two commonly applied software paradigms in this context are Software Agents (referred to as Agents) and Digital Twins (DTs). This work presents a systematic comparison of Agents and DTs in industrial applications. The goal of the study is to determine the differences, similarities, and potential synergies between the two paradigms. The comparison is based on the purposes for which Agents and DTs are applied, the properties and capabilities exhibited by these software paradigms, and how they can be allocated within the Reference Architecture Model Industry 4.0. The comparison reveals that Agents are commonly employed in the collaborative planning and execution of production processes, while DTs typically play a more passive role in monitoring production resources and processing information. Although these observations imply characteristic sets of capabilities and properties for both Agents and DTs, a clear and definitive distinction between the two paradigms cannot be made. Instead, the analysis indicates that production assets utilizing a combination of Agents and DTs would demonstrate high degrees of intelligence, autonomy, sociability, and fidelity. To achieve this, further standardization is required, particularly in the field of DTs.

cs.SE↗

arXiv2021

An Energy-based, always Index $\le1$ and Structurally Amenable Electrical Circuit Model

Combining three themes: port-Hamiltonian energy-based modelling, structural analysis as used in the circuit world, and structural analysis of general differential-algebraic equations, we form a new model for electrical circuits, the compact port-Hamiltonian equations. They have remarkable simplicity and symmetry, and always have index at most 1 and other good numerical properties. The method has been implemented in Matlab. We give proofs and numerical results.

math.NA↗