arXiv subjects

Christoph Scheurer

Publications and source records attributed to Christoph Scheurer.

14 recordsLinked to original sources

arXiv2026

Adaptive Slater Koster Parameters: Crossing Oxidation States with Density Functional Tight Binding

We propose to adapt the confined pseudo-atomic orbitals underpinning the precalculated Slater-Koster (SK) interaction tables in Density Functional Tight Binding (DFTB) to local atomic environments. We demonstrate significant improvement in electronic structure and energetics in the application to a partially oxidized Ni surface and Li insertion into graphite, where we assign optimal SK parameters to metal atoms in different oxidation states. Further analysis reveals the smoothness of the SK integrals across the varying oxidation states. Exploiting this, we introduce a site-resolved machine-learning scheme for fully adaptive DFTB. Using atomic descriptors and simple regression architectures already established in the context of machine-learning interatomic potentials, our scheme achieves 95% band-structure accuracy across all Ni-O binary compositions in the Materials Project.

cond-mat.mtrl-sci↗

arXiv2025

Multiscale Microscopy via Automation: Dual Magnification ESEM Imaging by Frame Alternation

In Environmental Scanning Electron Microscopy (ESEM) experiments, the acquisition parameters are generally kept constant throughout the collection of a data set. This limits data collection to one data set at a time, and frequent human interaction is required to maintain the image quality. Here, we use a custom-designed automation interface to minimize such supervision and allow for the collection of multiple interlaced data sets simultaneously. The oscillatory modes of an example catalytic system (hydrogen oxidation over Co foil) were employed as a tunable spatiotemporal test case. Using our automation interface, we can implement more advanced acquisition programs into the microscope that allow dual imaging - effectively bridging reaction monitoring between different length scales. By using automation to change the settings of the acquisition after each frame, we are able to capture alternating magnifications of the same process and sample location. Both a low magnification overview of the mesoscopic surface dynamics and a high magnification field of view of the ongoing structural changes of a selected surface motif were acquired. Using such truly correlative data captured with the dual magnification method, cross-scale correlations about catalytic systems including phase information can be established.

physics.ins-det↗

arXiv2025

Full Crystallographic Imaging of Hexagonal Boron Nitride Monolayers with Phonon-Enhanced Sum-Frequency Microscopy

Hexagonal boron nitride (hBN) is an important 2D material for van der Waals heterostructures, single photon emitters, and infrared nanophotonics. The optical characterization of mono- and few-layer samples of hBN however remains a challenge as the material is almost invisible optically. Here we introduce phase-resolved sum-frequency microscopy as a technique for imaging monolayers of hBN grown by chemical vapor deposition (CVD) and visualize their crystal orientation. A combination of femtosecond mid-infrared (IR) and visible laser pulses is used for sum-frequency generation (SFG), which is imaged in a wide-field optical microscope. The IR laser resonantly excites a phonon of hBN that leads to an ~800-fold enhancement of the SFG intensity, making it possible to image large 100x100 {\mu}m2 sample areas in less than 1 s. Implementing heterodyne detection in combination with azimuthal rotation of the sample further provides full crystallographic information. Through combined knowledge of topography and crystal orientation, we find that triangular domains of CVD-grown monolayer hBN have nitrogen-terminated zigzag edges. Overall, SFG microscopy can be used as an ultra-sensitive tool to image crystal structure, strain, stacking sequences, and twist angles, and is applicable to the wide range of van der Waals structures, where location and identification of monolayer regions and interfaces with broken inversion symmetry is of paramount importance.

cond-mat.mtrl-sci↗

arXiv2024

The Origin of Enhanced Conductivity and Structure Change in Defective Li4Ti5O12 or Blue-LTO : a study combined theoretical and experimental perspectives

The spinel Li4Ti5O12 (LTO) has emerged as a promising anode material for the next generation of all-solid-state Li-ion batteries (ASSB), primarily due to its characteristic "zero strain" charge/discharge behavior and exceptional cycling stability, which significantly prolongs battery lifespan. Pristine LTO, however, is hindered by poor ionic and electronic conductivity. By employing tailored sintering protocols that create oxygen vacancies, a high-performing, blue LTO material is achieved. It has been proposed that the increased electronic conductivity could stem from vacancy-induced polarons. Yet, detailed insights into polaron stability, distribution, and dynamics within both the LTO bulk and surface have remained elusive due to limited information on structural changes. Utilizing Positron Annihilation Lifetime Spectroscopy (PALS) and Coincidence Doppler Broadening Spectroscopy (CDBS), in conjunction with Two Component Density Functional Theory (TCDFT) with the on-site Hubbard U correction, enables us to probe the depth profile of defect species introduced by sintering in a reductive environment. Our research provides direct evidence of oxygen vacancy formation within the subsurface region, an inference drawn from the observation of \ch{Ti^{3+}}. Our investigation into Li16d vacancy formation within the bulk region uncovers the interactions between mobile species, namely Li-ions and polarons. Furthermore, we delve into the polaron stability on the LTO surface, offering an explanation for the superior performance of the (100) facet exposed LTO nanoparticle, as compared to its (111) exposed counterpart.

cond-mat.mtrl-sci↗

arXiv2023

A Fuzzy Classification Framework to Identify Equivalent Atoms in Complex Materials and Molecules

The nature of an atom in a bonded structure -- such as in molecules, in nanoparticles or solids, at surfaces or interfaces -- depends on its local atomic environment. In atomic-scale modeling and simulation, identifying groups of atoms with equivalent environments is a frequent task, to gain an understanding of the material function, to interpret experimental results or to simply restrict demanding first-principles calculations. While routine, this task can often be challenging for complex molecules or non-ideal materials with breaks of symmetries or long-range order. To automatize this task, we here present a general machine-learning framework to identify groups of (nearly) equivalent atoms. The initial classification rests on the representation of the local atomic environment through a high-dimensional smooth overlap of atomic positions (SOAP) vector. Recognizing that not least thermal vibrations may lead to deviations from ideal positions, we then achieve a fuzzy classification by mean-shift clustering within a low-dimensional embedded representation of the SOAP points as obtained through multidimensional scaling. The performance of this classification framework is demonstrated for simple aromatic molecules and crystalline Pd surface examples.

physics.chem-ph↗

arXiv2022

The intrinsic electrostatic dielectric behaviour of graphite anodes in Li-ion batteries -- across the entire functional range of charge

Lithium-graphite intercalation compounds (Li-GICs) are the most common anode material for modern Li-ion batteries. However, the dielectric response of this material in the electrostatic limit (and its variation with the state of charge (SOC)) has not been investigated to a satisfactory degree, especially not for the higher SOC range. Nevertheless, said dielectric behaviour is a highly desired property, particularly as an input parameter for charged kinetic Monte Carlo simulations, one of the most promising modeling techniques for energy materials. In this work, we employ our recent DFTB parametrization for Li-GICs based on a machine-learned repulsive potential in order to overcome the computational hurdles of sampling the long-ranged Coulomb interactions within this material, as experienced by the charge carriers within. This approach is rather novel due to computational cost, but best suited for investigating our specific property of interest. For the first time, we discover a mostly linear dependency of the relative permittivity on the SOC, from ca. 7 at SOC 0% to ca. 25 at SOC 100%. In doing so, we also present a straightforward approach that can be used in future research for other intercalation compounds -- once sufficiently fast and long-ranged computational methods, e.g. linear-scaling DFT, a good DFTB parametrization, or atomic potentials with inbuilt electrostatics, become available. However, while the presented qualitative behaviour is robust and our results compare favourably with the few experimental studies available, we stress that quantitative results are strongly dependent on our estimation of the partial charge transfer from the intercalated Li-ion to the carbon host structure, and need to be verified by further experiments and calculations. Yet, our research shows that in principle, two measurements -- one at low and one at high SOC -- should suffice for that purpose.

cond-mat.mtrl-sci↗

arXiv2021

Revisiting the storage capacity limit of graphite battery anodes: spontaneous lithium overintercalation at ambient pressure

The market quest for fast-charging, safe, long-lasting and performant batteries drives the exploration of new energy storage materials, but also promotes fundamental investigations of materials already widely used. Presently, revamped interest in anode materials is observed -- primarily graphite electrodes for lithium-ion batteries. Here, we focus on the upper limit of lithium intercalation in the morphologically quasi-ideal highly oriented pyrolytic graphite (HOPG), with a LiC$_6$ stoichiometry corresponding to 100\% state of charge (SOC). We prepared a sample by immersion in liquid lithium at ambient pressure and investigated it by static $^7$Li nuclear magnetic resonance (NMR). We resolved unexpected signatures of superdense intercalation compounds, LiC$_{6-x}$. These have been ruled out for decades, since the highest geometrically accessible composition, LiC$_2$, can only be prepared under high pressure. We thus challenge the widespread notion that any additional intercalation beyond LiC$_6$ is not possible under ambient conditions. We monitored the sample upon calendaric aging and employed ab initio calculations to rationalise the NMR results. The computed relative stabilities of different superdense configurations reveal that non-negligible overintercalation does proceed spontaneously beyond the currently accepted capacity limit.

cond-mat.mtrl-sci↗

arXiv2021

Interface between graphene and liquid Cu from molecular dynamics simulations

Controllable synthesis of defect-free graphene is crucial for applications since the properties of graphene are highly sensitive to any deviations from the crystalline lattice. We focus here on the emerging use of liquid Cu catalysts, which has high potential for fast and efficient industrial-scale production of high-quality graphene. The interface between graphene and liquid Cu is studied using force field and ab initio molecular dynamics, revealing a complete or partial embedding of finite-sized flakes. By analyzing flakes of different sizes we find that the size-dependence of the embedding can be rationalized based on the energy cost of embedding versus bending the graphene flake. The embedding itself is driven by the formation of covalent bonds between the under-coordinated edge C atoms and the liquid Cu surface, which is accompanied by a significant charge transfer. In contrast, the central flake atoms are located around or slightly above 3 Å from the liquid Cu surface and exhibit weak vdW-bonding and much lower charge transfer. The structural and electronic properties of the embedded state revealed in our work provides the atomic-scale information needed to develop effective models to explain the special growth observed in experiments where various interesting phenomena such as flake self-assembly and rotational alignment, high growth speeds and low defect densities in the final graphene product have been observed.

cond-mat.mtrl-sci↗

arXiv2020

DFTB modelling of lithium intercalated graphite with machine-learned repulsive potential

Lithium ion batteries have been a central part of consumer electronics for decades. More recently, they have also become critical components in the quickly arising technological fields of electric mobility and intermittent renewable energy storage. However, many fundamental principles and mechanisms are not yet understood to a sufficient extent to fully realize the potential of the incorporated materials. The vast majority of concurrent lithium ion batteries make use of graphite anodes. Their working principle is based on intercalation---the embedding and ordering of (lithium-) ions in the two-dimensional spaces between the graphene sheets. This important process---it yields the upper bound to a battery's charging speed and plays a decisive role for its longevity---is characterized by multiple phase transitions, ordered and disordered domains, as well as non-equilibrium phenomena, and therefore quite complex. In this work, we provide a simulation framework for the purpose of better understanding lithium intercalated graphite and its behaviour during use in a battery. In order to address the large systems sizes and long time scales required to investigate said effects, we identify the highly efficient, but semi-empirical Density Funtional Tight Binding (DFTB) as a suitable approach and combine particle swarm optimization (PSO) with the machine learning (ML) procedure Gaussian Process Regression (GPR) to obtain the necessary parameters. Using the resulting parametrization, we are able to reproduce experimental reference structures at a level of accuracy which is in no way inferior to much more costly ab initio methods. We finally present structural properties and diffusion barriers for some exemplary system states.

physics.comp-ph↗

arXiv2020

IrO2 Surface Complexions Identified Through Machine Learning and Surface Investigations

A Gaussian Approximation Potential (GAP) was trained using density-functional theory data to enable a global geometry optimization of low-index rutile IrO2 facets through simulated annealing. Ab initio thermodynamics identifies (101) and (111) (1x1)-terminations competitive with (110) in reducing environments. Experiments on single crystals find that (101) facets dominate, and exhibit the theoretically predicted (1x1) periodicity and X-ray photoelectron spectroscopy (XPS) core level shifts. The obtained structures are analogous to the complexions discussed in the context of ceramic battery materials.

cond-mat.mtrl-sci↗

arXiv2020

Mobile Small Polarons Explain Conductivity in Lithium Titanium Oxide Battery Electrodes

Lithium titanium oxide Li$_4$Ti$_5$O$_{12}$ (LTO) is an intriguing anode material promising particularly long lived batteries, due to its remarkable phase stability during (dis)charging of the cell. However, its usage is limited by its low intrinsic electronic conductivity. Introducing oxygen vacancies can be one method to overcome this drawback, possibly by altering the charge carrier transport mechanism. We use Hubbard corrected density-functional theory (DFT+U) to show that polaronic states in combination with a possible hopping mechanism can play a crucial role in the experimentally observed increase of electronic conductivity. To gauge polaronic charge mobility, we compute relative stabilities of different localization patterns and estimate polaron hopping barrier heights. With this we finally show how defect engineering can indeed raise the electronic conductivity of LTO up to the level of its ionic conductivity, thereby explaining first experimental results for reduced LTO.

cond-mat.mtrl-sci↗

arXiv2018

Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects

We first briefly report on the status and recent achievements of the ELPA-AEO (Eigenvalue Solvers for Petaflop Applications - Algorithmic Extensions and Optimizations) and ESSEX II (Equipping Sparse Solvers for Exascale) projects. In both collaboratory efforts, scientists from the application areas, mathematicians, and computer scientists work together to develop and make available efficient highly parallel methods for the solution of eigenvalue problems. Then we focus on a topic addressed in both projects, the use of mixed precision computations to enhance efficiency. We give a more detailed description of our approaches for benefiting from either lower or higher precision in three selected contexts and of the results thus obtained.

physics.comp-ph↗

arXiv2016

Unexpected red shift of C-H vibrational band of Methyl benzoate

The C-H vibrational bands become more and more important in the structural determination of biological molecules with the development of CARS microscopy and 2DIR spectroscopy. Due to the congested pattern, near degeneracy, and strong anharmonicity of the C-H stretch vibrations, assignment of the C-H vibrational bands are often misleading. Anharmonic vibrational spectra calculation with multidimensional potential energy surface interprets the C-H vibrational spectra more accurately. In this article we have presented the importance of multidimensional potential energy surface in anharmonic vibrational spectra calculation and discuss the unexpected red shift of C-H vibrational band of Methyl benzoate.

physics.chem-ph↗

arXiv2014

Vibrational Spectroscopy of Methyl benzoate

Methyl benzoate (MB) is studied as a model compound for the development of new IR pulse schemes with possible applicability to biomolecules. Anharmonic vibrational modes of MB are calculated on different level (MP2, SCS, CCSD(T) with varying basis sets) ab-initio PESs using the vibrational self-consistent field (VSCF) method and its correlation corrected extensions. Dual level schemes, combining different quantum chemical methods for diagonal and coupling potentials, are systematically studied and applied successfully to reduce the computational cost. Isotopic substitution of β-hydrogen by deuterium is studied to obtain a better understanding of the molecular vibrational coupling topology.

physics.chem-ph↗