arXiv subjects

Birger Horstmann

Publications and source records attributed to Birger Horstmann.

At least 19 recordsLinked to original sources

arXiv2026

Optimizing Subspace Expansion in Quantum Chemistry through Operator Selection and Reference State Choice

The Virtual Quantum Subspace Expansion (VQSE) extends the Variational Quantum Eigensolver (VQE) by leveraging additional measurements on the reference state to capture the influence of excluded virtual orbitals. This makes VQSE attractive for chemical applications where accurate energy differences along potential energy surfaces are crucial for modeling reaction rates and kinetics. In this work, we analyze VQSE performance on H$_2$ dissociation including references that use Hartree--Fock molecular orbitals with broken spin symmetry. We identify two mechanisms which affect accuracy: overlap of the reference state with the exact full configuration interaction (FCI) wavefunction and operator pool expressivity. We show these mechanisms are strongly co-dependent. When operators are restricted to act only from the active to the virtual space, results become highly sensitive to the reference, and enlarging the active space does not guarantee improved accuracy. In this case, prioritizing reference overlap over energy minimization is therefore essential. Adding single excitations and number operators within the active space recovers the accuracy of MR-CISD (multi-reference configuration interaction singles and doubles) regardless of the reference. In our noisy hardware experiments, we achieve chemical accuracy by adding additional operators and using strict regularization. These findings motivate careful co-design of reference fidelity, pool expressivity, and hardware constraints for practical VQSE deployment.

quant-ph↗

arXiv2026

Poly(1,4-anthraquinone) as an Organic Cathode Material: Simulation of Observable Bonding Properties to Li, Na, Mg, and Ca

Poly(1,4-anthraquinone) (P14AQ) has emerged as a promising cathode material, offering high capacity and good cycling stability, yet the atomic-scale mechanisms governing metal-ion binding and electrochemical behavior remain poorly understood. To address this, we investigate the binding mechanisms of Li, Na, Mg, and Ca to P14AQ using quantum mechanical methods, particularly DFT and DFTB. A key challenge lies in the material's structural complexity: multiple conformers of P14AQ are energetically similar but kinetically isolated due to significant energy barriers. To account for this, we develop an automated method to generate all unique P14AQ conformers for a periodic polymer chain without rotational duplicates through an orientation labeling scheme. For each conformer, we systematically place a metal atom adjacent to every oxygen site, enabling a complete exploration of binding configurations. We observe two structural motifs: a single metal-oxygen bond and coordination to two opposite oxygen atoms. While Li and Na exhibit continuous energy distributions, Mg and Ca show an energy gap between the two motifs, with a strong preference for the two-oxygen binding configuration. Galvanostatic measurements support these findings by showing lower gravimetric capacities for Ca and Mg than for Li and Na. For Na, the different numbers of metal-oxygen bonds are reflected in the two voltage plateaus observed experimentally. Overall, the combined computational and experimental results explain the higher capacity of monovalent ions in P14AQ: divalent ions cannot bind efficiently to a single oxygen site due to unfavorable energetics, and the conformational distribution of the polymer chain prevents optimal coordination.

physics.chem-ph↗

arXiv2026

Thermodynamically consistent modeling of ion exchange membranes in multi-ionic environments

Ion exchange membranes are useful for a wide range of applications, including water desalination, fuel cells, and aqueous batteries. Accordingly, a variety of models for ion exchange membranes has been proposed, each emphasizing different aspects that govern their static and dynamic properties. By reviewing these models, we identify key physical contributions and beneficial modeling strategies. Based on these insights, we derive a thermodynamically consistent model by combining mass-action site occupation with mean-field electrostatic interactions along the polymer backbone. In this derivation, we explicitly account for multicomponent electrolytes at elevated concentrations. The parameters of the resulting model relate closely to those of other models, but gain consistency and interpretability through the underlying derivation. A discussion of the model parameters highlights redundancies and linkages between quantities that are commonly treated independently. Comparison to experimental data shows that both static and dynamic membrane properties are reproduced with good accuracy by the presented model. This makes it a promising basis for theory-driven membrane optimization and supports the tailored design of ion exchange membranes for various technologies.

physics.chem-ph↗

arXiv2026

Physics-based modeling of cyclic and calendar aging of LIBs with Si-Gr composite anodes

Higher energy density and longer lifetime are the requirements for next-generation lithium-ion batteries. A promising anode material is silicon, which offers high specific capacity, but its significant volume change during lithiation and delithiation enormously reduces battery lifetime. A physical understanding of the processes degrading the battery is key to mitigate this effect and advance in the field. We develop a physics-based model to describe degradation during battery cycling under various protocols and storage conditions, with varying check-up (CU) frequencies. The model can disentangle basic degradation mechanisms, such as the growth of the Solid-Electrolyte Interphase (SEI), from silicon mechanisms, such as particle cracking, SEI growth on cracks, and loss of active material (LAM). We investigate the impact of CUs on the observed storage degradation and the reason behind the increased degradation in batteries, including silicon in the anode. Additionally, we relate the observed degradation to operating conditions, enabling future optimization of battery use and design.

physics.chem-ph↗

arXiv2025

Combining Molecular Dynamics and Experimental Methods for the Parametrization of Binary Carbonate-Based Electrolytes

Modelling the ionic transport in battery cells requires precise parametrization of the involved electrolytes. For carbonate-based electrolytes, however, the evaluation of their parameters suffers from interphase effects between the bulk electrolyte and the Li metal electrode, commonly present in the usual electrochemical polarization experiments. In this work, we combine measurements on conductivity and concentration cells with molecular dynamic simulations, avoiding these difficulties and thus, allowing for a more accurate determination of the parameters. We determine the conductivity, the transference number, the thermodynamic factor and the salt diffusion coefficient for three different electrolytes, i.e mixtures of ethylene carbonate (EC), ethyl methyl carbonate (EMC), methyl propionate (MP), dimethyl carbonate (DMC) and propylene carbonate (PC), containing LiPF$_6$ at various concentrations and temperatures. In order to validate the simulated transference numbers, we employ electrophoretic Nuclear Magnetic Resonance spectroscopy (eNMR).

physics.chem-ph↗

arXiv2025

A Primer on Bayesian Parameter Estimation and Model Selection for Battery Simulators

Physics-based battery modelling has emerged to accelerate battery materials discovery and performance assessment. Its success, however, is still hindered by difficulties in aligning models to experimental data. Bayesian approaches are a valuable tool to overcome these challenges, since they enable prior assumptions and observations to be combined in a principled manner that improves numerical conditioning. Here we introduce two new algorithms to the battery community, SOBER and BASQ, that greatly speed up Bayesian inference for parameterisation and model comparison. We showcase how Bayesian model selection allows us to tackle data observability, model identifiability, and data-informed model development together. We propose this approach for the search for battery models of novel materials.

stat.ME↗

arXiv2025

Nested State and Degradation Estimation of a Satellite Battery with In-flight Data

Li-ion batteries are essential for the energy supply of satellites. The accurate estimation of their states is important for the reliable and safe operation in space. This paper introduces a new algorithm for the estimation of SOC and SOH. The multi-timescale algorithm combines Kalman filters and physics-based models for batteries. We use a P2D model combined with a degradation model that describes capacity fading due to SEI growth. The state estimation algorithm combines two extended Kalman filters for the two states evolving on different timescales, with one filter nested within the other one. We test the algorithm with synthetic data as well as with in-flight data from Japanese satellite REIMEI. The algorithm adequately estimates the SOC and SOH in both cases. Furthermore it gives insight into the reliability of the chosen model.

physics.chem-ph↗

arXiv2025

Modelling and Simulation of an Alkaline Ni/Zn Cell

Nickel/zinc (Ni/Zn) technology is a promising post-lithium battery type for stationary applications with respect to aspects such as safety, environmental compatibility and resource availability. Although this battery type has been known for a long time, the theoretical knowledge about the processes taking place in the battery is limited. In order to gain a deeper understanding of the general cycling behaviour and the underlying processes, but also specific phenomena intrinsic to zinc-based cells such as zinc shape change, we carry out simulations based on a thermodynamically consistent and volume-averaged continuum model. We use a Ni/Zn prototype cell as a reference framework to provide a basis for modelling, parameter estimation and systematic comparison between simulated and experimental cell behaviour to improve cyclability and performance.

physics.chem-ph↗

arXiv2025

Simulating Electron Transfer on Noisy Quantum Computers

While simple spin-boson models have been realized on quantum hardware, simulating extended electronic networks with local vibrational environments remains a fundamental challenge in the presence of non-equilibrium, long-lived electronic-vibrational (vibronic) coherence. We present a framework for the digital-analog simulation of open quantum systems governed by Hamiltonians with linear-vibronic coupling (LVC) and structured vibrational environments. Our approach exploits the intrinsic dissipation of qubits in near-term quantum hardware as a resource to emulate vibrational relaxation, combined with a model-specific error mitigation scheme to filter out noise sources incompatible with the target open system. We validate our strategy by resolving the vibronic transfer spectra of a one-dimensional donor-acceptor chain on IBM superconducting processors, reproducing non-Markovian dynamics and scaling the chain length up to 10 electronic sites, an unprecedented scale for chemical dynamics on quantum computers. Our model of vibronic electron transfer offers a portable, application-oriented benchmark for simulating long-lived entangled states on NISQ computers.

quant-ph↗

arXiv2025

Workflows and Principles for Collaboration and Communication in Battery Research

Interdisciplinary collaboration in battery science is required for rapid evaluation of better compositions and materials. However, diverging domain vocabulary and non-compatible experimental results slow down cooperation. We critically assess the current state-of-the-art and develop a structured data management and interpretation system to make data curation sustainable. The techniques we utilize comprise ontologies to give a structure to knowledge, database systems tenable to the FAIR principles, and software engineering to break down data processing into verifiable steps. To demonstrate our approach, we study the applicability of the Galvanostatic Intermittent Titration Technique on various electrodes. Our work is a building block in making automated material science scale beyond individual laboratories to a worldwide connected search for better battery materials.

cs.DB↗

arXiv2025

Stress-driven whisker formation in lithium metal batteries

Lithium metal batteries are promising for next-generation high-energy-density batteries, especially when lithium is directly plated on a current collector. However, lithium whiskers can form in the early stages of electroplating. These whiskers lead to low Coulombic efficiency due to isolated lithium formation during stripping. The mechanism of whisker formation is not fully understood, and different mechanisms are proposed in the literature. Herein, we computationally explore a stress-driven extrusion mechanism through cracks in the solid-electrolyte-interphase (SEI), which explains the experimentally observed root growth of lithium whiskers. We model the extrusion as a flow of a power-law Herschel-Bulkley fluid parametrized by the experimental power-law creep behavior of lithium, which results in the typical one-dimensional whisker shape. Consequently, in competition with SEI self-healing, SEI cracking determines the emergence of whiskers, giving a simple rule of thumb to avoid whisker formation in liquid electrolytes.

physics.chem-ph↗

arXiv2024

Physics-based inverse modeling of battery degradation with Bayesian methods

To further improve Lithium-ion batteries (LiBs), a profound understanding of complex battery processes is crucial. Physical models offer understanding but are difficult to validate and parameterize. Therefore, automated machine-learning methods (ML) are necessary to evaluate models with experimental data. Bayesian methods, e.g., Bayesian optimization for likelihood-free inference (EP-BOLFI), stand out as they capture uncertainties in models and data while granting meaningful parameterization. An important topic is prolonging battery lifetime, which is limited by degradation, such as the solid-electrolyte interphase (SEI) growth. As a case study, we apply EP-BOLFI to parametrize SEI growth models with synthetic and real degradation data. EP-BOLFI allows for incorporating human expertise in the form of suitable feature selection, which improves the parametrization. We show that even under impeded conditions, we achieve correct parameterization with reasonable uncertainty quantification, needing less computational effort than standard Markov chain Monte Carlo methods. Additionally, the physically reliable summary statistics show if parameters are strongly correlated and not unambiguously identifiable. Further, we investigate Bayesian alternately subsampled quadrature (BASQ), which calculates model probabilities, to confirm electron diffusion as the best theoretical model to describe SEI growth during battery storage.

physics.chem-ph↗

arXiv2024

Elliptical Silicon Nanowire Covered by the SEI in a 2D Chemo-Mechanical Simulation

Understanding the mechanical interplay between silicon anodes and their surrounding solid-electrolyte interphase (SEI) is essential to improve the next generation of lithium-ion batteries. We model and simulate a 2D elliptical silicon nanowire with SEI via a thermodynamically consistent chemo-mechanical continuum ansatz using a higher order finite element method in combination with a variable-step, variable-order time integration scheme. Considering a soft viscoplastic SEI for three half cycles, we see at the minor half-axis the largest stress magnitude at the silicon nanowire surface, leading to a concentration anomaly. This anomaly is caused by the shape of the nanowire itself and not by the SEI. Also for the tangential stress of the SEI, the largest stress magnitudes are at this point, which can lead to SEI fracture. However, for a stiff SEI, the largest stress magnitude inside the nanowire occurs at the major half-axis, causing a reduced concentration distribution in this area. The largest tangential stress of the SEI is still at the minor half-axis. In total, we demonstrate the importance of considering the mechanics of the anode and SEI in silicon anode simulations and encourage further numerical and model improvements.

physics.app-ph↗

arXiv2024

Modeling the Influence of Solvation on the Electrochemical Double Layer of Salt / Solvent Mixtures

Modelling electrolytes accurately on both a nanoscale and cell level can contribute to improving battery chemistries.[Armand and Tarascon, Nature, 2008, 451, 652-657] We previously presented a thermodynamic continuum model for electrolytes.[arXiv:2010.14915] In this paper we include solvation interactions between the ions and solvent, which alter the structure of the electochemical double layer (EDL). We are able to combine a local solvation model -- permitting examination of the interplay between electric forces and the ion-solvent binding -- with a full electrolyte model. Using this, we can investigate double layer structures for a wide range of electrolytes, especially including highly concentrated solutions. We find that some of the parameters of our model significantly affect the solvent concentration at the electrode surface, and thereby the rate of solvent decomposition. Firstly, an increased salt concentration weakens the solvation shells, making it possible to strip the solvent in the EDL before the ions reach the surface. The strength of the ion-solvent interaction also affects at which potential difference the solvation shells removed. We are therefore able to qualitatively predict EDL structures for different electrolytes based on parameters like molecule size, solvent binding energy and salt concentration.

physics.chem-ph↗

arXiv2024

Slow Voltage Relaxation of Silicon Nanoparticles with a Chemo-Mechanical Core-Shell Model

Silicon presents itself as a high-capacity anode material for lithium-ion batteries with a promising future. The high ability for lithiation comes along with massive volume changes and a problematic voltage hysteresis, causing reduced efficiency, detrimental heat generation, and a complicated state-of-charge estimation. During slow cycling, amorphous silicon nanoparticles show a larger voltage hysteresis than after relaxation periods. Interestingly, the voltage relaxes for at least several days, which has not been physically explained so far. We apply a chemo-mechanical continuum model in a core-shell geometry interpreted as a silicon particle covered by the solid-electrolyte interphase to account for the hysteresis phenomena. The silicon core (de)lithiates during every cycle while the covering shell is chemically inactive. The visco-elastoplastic behavior of the shell explains the voltage hysteresis during cycling and after relaxation. We identify a logarithmic voltage relaxation, which fits with the established Garofalo law for viscosity. Our chemo-mechanical model describes the observed voltage hysteresis phenomena and outperforms the empirical Plett model. In addition to our full model, we present a reduced model to allow for easy voltage profile estimations. The presented results support the mechanical explanation of the silicon voltage hysteresis with a core-shell model and encourage further efforts into the investigation of the silicon anode mechanics.

cond-mat.mtrl-sci↗

arXiv2024

Nonlinear dynamics as a ground-state solution on quantum computers

For the solution of time-dependent nonlinear differential equations, we present variational quantum algorithms (VQAs) that encode both space and time in qubit registers. The spacetime encoding enables us to obtain the entire time evolution from a single ground-state computation. We describe a general procedure to construct efficient quantum circuits for the cost function evaluation required by VQAs. To mitigate the barren plateau problem during the optimization, we propose an adaptive multigrid strategy. The approach is illustrated for the nonlinear Burgers equation. We classically optimize quantum circuits to represent the desired ground-state solutions, run them on IBM Q System One and Quantinuum System Model H1, and demonstrate that current quantum computers are capable of accurately reproducing the exact results.

quant-ph↗

arXiv2024

Electro-Chemo-Mechanical Model for Polymer Electrolytes

Polymer electrolytes (PEs) are promising candidates for use in next-generation high-voltage batteries, as they possess advantageous elastic and electrochemical properties. However, PEs still suffer from low ionic conductivity and need to be operated at higher temperatures. Furthermore, the wide variety of different types of PEs and the complexity of the internal interactions constitute challenging tasks for progressing towards a systematic understanding of PEs. Here, we present a continuum transport theory which enables a straight-forward and thermodynamically consistent method to couple different aspects of PEs relevant for battery performance. Our approach combines mechanics and electrochemistry in non-equilibrium thermodynamics, and is based on modeling the free energy, which comprises all relevant bulk properties. In our model, the dynamics of the polymer-based electrolyte are formulated relative to the highly elastic structure of the polymer. For validation, we discuss a benchmark polymer electrolyte. Based on our theoretical description, we perform numerical simulations and compare the results with data from the literature. In addition, we apply our theoretical framework to a novel type of single-ion conducting PE and derive a detailed understanding of the internal dynamics.

physics.chem-ph↗

arXiv2024

Silicon Nanowires as Anodes for Lithium-Ion Batteries: Full Cell Modeling

Silicon (Si) anodes attract a lot of research attention for their potential to enable high energy density lithium-ion batteries (LIBs). Many studies focus on nanostructured Si anodes to counteract deterioration. In this work, we model LIBs with Si nanowire (NW) anodes in combination with an ionic liquid (IL) electrolyte. On the anode side, we allow for elastic deformations to reflect the large volumetric changes of Si. With physics-based continuum modeling we can provide insight into usually hardly accessible quantities like the stress distribution in the active material. For the IL electrolyte, our thermodynamically consistent transport theory includes convection as relevant transport mechanism. We present our volume-averaged 1d+1d framework and perform parameter studies to investigate the influence of the Si anode morphology on the cell performance. Our findings highlight the importance of incorporating the volumetric expansion of Si in physics-based simulations. Even for nanostructured anodes - which are said to be beneficial concerning the stresses - the expansion influences the achievable capacity of the cell. Accounting for enough pore space is important for efficient active material usage.

physics.chem-ph↗