arXiv subjects

Hendrik Heinz

Publications and source records attributed to Hendrik Heinz.

16 recordsLinked to original sources

arXiv2026

Stereochemical Vacuum Gap Explains Out-of-Plane Thermal Insulation in MXenes

Two-dimensional MXenes are promising materials for thermal management and spectral camouflage, combining low out-of-plane thermal conductivity with low infrared emissivity and mechanical robustness. Yet the near-order-of-magnitude spread in experimental out-of-plane thermal conductivity measurements (0.14-0.8 W/mK) and the systematic overestimation by simulations point to a fundamental gap in our understanding of heat transport in these materials. Here, we argue these differences originate in the overlooked role of heterogeneous surface terminations. Using Non-Equilibrium Molecular Dynamics simulations of Ti3C2Tx, we show that this discrepancy arises from a stereochemically induced vacuum gap between adjacent layers, formed when surface terminations of different sizes coexist. Even minor deviations from homogeneous terminations drastically suppress out-of-plane thermal conductivity, bringing simulated values into quantitative agreement with experiment. We also show that thermal conductivity scales strongly with the atomic density, and that introducing bulky surface terminations, including residual water, reduces the thermal conductivity to 0.3 W/mK, an order of magnitude below homogeneous termination values and below the minimum thermal conductivity limit predicted for disordered solids. Thus, we propose a chemistry-driven route to engineer thermal transport in MXenes.

cond-mat.mtrl-sci↗

arXiv2026

INTERFACE Force Field for Alumina with Validated Bulk Phases and a pH-Resolved Surface Model Database for Electrolyte and Organic Interfaces

Alumina and aluminum oxyhydroxides underpin chemical-engineering technologies from heterogeneous catalysis, corrosion protection, functional coatings, energy-storage devices, to biomedical components. Yet molecular models that predictively connect phase structure, pH-dependent surface chemistry, electrolyte organization, and adsorption across operating conditions remain limited. Here we introduce a unified INTERFACE Force Field (IFF) parameterization together with a curated, ready-to-use pH-resolved surface model database that provides the most accurate and transferable atomistic description of major alumina phases to date. The framework covers a-Al2O3, g-Al2O3, boehmite, diaspore, and gibbsite using a single, physically interpretable parameter set that is directly compatible with CHARMM, AMBER, OPLS-AA, CVFF, and PCFF. Across structural, thermodynamic, mechanical, and interfacial benchmarks, simulations reproduce experimental reference data with more than 95 percent accuracy, exceeding existing force fields and the reliability of current density-functional approaches. A key advance is the first transferable treatment of surface ionization and charge regulation across alumina phases over a broad range of pH values, enabling simulations of realistic solid electrolyte interfaces without phase-specific reparameterization. Quantitative reliability is demonstrated by reproducing trends in zeta potentials and pH-dependent adsorption of a corrosion inhibitor at alumina-water interfaces. Predicted adsorption free energies and surface contact times correlate with experiments across more than an order of magnitude. Relative to ML-DFT workflows, the speed 100 to 1000 times faster, reaching system sizes and time scales inaccessible to quantum methods. The results establish a predictive computational platform to design alumina-containing functional materials under realistic process conditions.

cond-mat.mtrl-sci↗

arXiv2025

Enhancing Dimensionality Prediction in Hybrid Metal Halides via Feature Engineering and Class-Imbalance Mitigation

We present a machine learning framework for predicting the structural dimensionality of hybrid metal halides (HMHs), including organic-inorganic perovskites, using a combination of chemically-informed feature engineering and advanced class-imbalance handling techniques. The dataset, consisting of 494 HMH structures, is highly imbalanced across dimensionality classes (0D, 1D, 2D, 3D), posing significant challenges to predictive modeling. This dataset was later augmented to 1336 via the Synthetic Minority Oversampling Technique (SMOTE) to mitigate the effects of the class imbalance. We developed interaction-based descriptors and integrated them into a multi-stage workflow that combines feature selection, model stacking, and performance optimization to improve dimensionality prediction accuracy. Our approach significantly improves F1-scores for underrepresented classes, achieving robust cross-validation performance across all dimensionalities.

cs.LG↗

arXiv2025

Towards MatCore: A Unified Metadata Standard for Materials Science

The materials science community seeks to support the FAIR principles for computational simulation research. The MatCore Project was recently launched to address this need, with the goal of developing an overall metadata framework and accompanying guidelines. This paper reports on the MatCore goals and overall progress. Historical background context is provided, including a review of the principles underlying successful core metadata standards. The paper also presents selected MatCore examples and discusses future plans.

cond-mat.mtrl-sci↗

arXiv2024

Implementing Reactivity in Molecular Dynamics Simulations with Harmonic Force Fields

The simulation of chemical reactions and mechanical properties including failure from atoms to the micrometer scale remains a longstanding challenge in chemistry and materials science. Bottlenecks include computational feasibility, reliability, and cost. We introduce a method for reactive molecular dynamics simulations using a clean replacement of non-reactive classical harmonic bond potentials with reactive, energy-conserving Morse potentials, called the Reactive INTERFACE Force Field (IFF-R). IFF-R is compatible with force fields for organic and inorganic compounds such as IFF, CHARMM, PCFF, OPLS-AA, and AMBER. Bond dissociation is enabled by three interpretable Morse parameters per bond type and zero energy upon disconnect. Use cases for bond breaking in molecules, failure of polymers, carbon nanostructures, proteins, composite materials, and metals are shown. The simulation of bond forming reactions was included via template-based methods. IFF-R maintains the accuracy of the corresponding non-reactive force fields and is about 30 times faster than prior reactive simulation methods.

cond-mat.stat-mech↗

arXiv2022

Atomic-scale identification of the active sites of nanocatalysts

Alloy nanocatalysts have found broad applications ranging from fuel cells to catalytic converters and hydrogenation reactions. Despite extensive studies, identifying the active sites of nanocatalysts remains a major challenge due to the heterogeneity of the local atomic environment. Here, we advance atomic electron tomography to determine the 3D local atomic structure, surface morphology and chemical composition of PtNi and Mo-doped PtNi nanocatalysts. Using machine learning trained by density functional theory calculations, we identify the catalytic active sites for the oxygen reduction reaction from experimental 3D atomic coordinates, which are corroborated by electrochemical measurements. By quantifying the structure-activity relationship, we discover a local environment descriptor to explain and predict the catalytic active sites at the atomic level. The ability to determine the 3D atomic structure and chemical species coupled with machine learning is expected to expand our fundamental understanding of a wide range of nanocatalysts.

physics.chem-ph↗

arXiv2021

Prediction of Carbon Nanostructure Mechanical Properties and Role of Defects Using Machine Learning

Carbon fiber and graphene-based nanostructures such as carbon nanotubes (CNTs) and defective structures have extraordinary potential as strong and lightweight materials. A longstanding bottleneck has been lack of understanding and implementation of atomic-scale engineering to harness the theoretical limits of modulus and tensile strength, of which only a fraction is routinely reached today. Here we demonstrate accurate and fast predictions of mechanical properties for CNTs and arbitrary 3D graphitic assemblies based on a training set of over 1000 stress-strain curves from cutting-edge reactive MD simulation and machine learning (ML). Several ML methods are compared and show that our newly proposed hierarchically structured graph neural networks with spatial information (HS-GNNs) achieve predictions in modulus and strength for any 3D nanostructure with only 5-10% error across a wide range of possible values. The reliability is sufficient for practical applications and a great improvement over off-the shelf ML methods with up to 50% deviation, as well as over earlier models for specific chemistry with 20% deviation. The algorithms allow more than 10 times faster mechanical property predictions than traditional molecular dynamics simulations, the identification of the role of defects and random 3D morphology, and high-throughput screening of 3D structures for enhanced mechanical properties. The algorithms can be scaled to morphologies up to 100 nm in size, expanded for chemically similar compounds, and trained to predict a broader range of properties.

cond-mat.mtrl-sci↗

arXiv2020

ReaxFF reactive force field study of polymerization of polymer matrix in carbon nanotube-composite system

Human transport to Mars and deep space explorations demand the development of new materials with extraordinary high performance-to-mass ratios. Promising candidates to fulfill these requirements are ultrahigh strength lightweight (UHSL) materials, which consist of polymer matrices fortified by pristine carbon nanotubes (CNTs). Previous investigations have showed that with an increase in CNT diameter, its preferred configuration changes from a circular form to a flattened shape that can be obtained in high pressure or tension conditions. The ReaxFF reactive force field can reveal detailed chemical interactions at the atomistic scale. To enable ReaxFF simulations on CNT/polymer interfaces, we trained force field parameters to capture the proper structure of flattened carbon nanotubes (flCNTs), i.e. dumbbell-like shape CNTs, against available polymer consistent force field -- interface force field (PCFF-IFF) data which had good proximity to density functional theory (DFT) data. In this study we used accelerated ReaxFF molecular dynamics simulation using the optimized force field to study the polymerization of diglycidyl ether of bisphenol F (Bis F) and diethyltoluenediamine (DEDTA) molecules in vicinity of circular and flattened CNTs. Our results indicate that the flat regions of flCNT are more favorable spots for the polymers to settle compared to curved regions due to higher binding energies. Moreover, higher dimer generation around flCNT results in more effective coating of the CNT which leads to higher load transfer in compared to circular CNT. According to our results there is a high alignment between polymers and CNT surface which is due to strong pi-pi interactions of aromatic carbon rings in the polymers and CNTs. These ReaxFF simulations indicate the capability of this method to simultaneously observe the polymerization of monomers along with their interactions with CNTs.

physics.chem-ph↗

arXiv2019

Capturing Nucleation at 4D Atomic Resolution

Nucleation plays a critical role in many physical and biological phenomena ranging from crystallization, melting and evaporation to the formation of clouds and the initiation of neurodegenerative diseases. However, nucleation is a challenging process to study in experiments especially in the early stage when several atoms/molecules start to form a new phase from its parent phase. Here, we advance atomic electron tomography to study early stage nucleation at 4D atomic resolution. Using FePt nanoparticles as a model system, we reveal that early stage nuclei are irregularly shaped, each has a core of one to few atoms with the maximum order parameter, and the order parameter gradient points from the core to the boundary of the nucleus. We capture the structure and dynamics of the same nuclei undergoing growth, fluctuation, dissolution, merging and/or division, which are regulated by the order parameter distribution and its gradient. These experimental observations differ from classical nucleation theory (CNT) and to explain them we propose the order parameter gradient (OPG) model. We show the OPG model generalizes CNT and energetically favours diffuse interfaces for small nuclei and sharp interfaces for large nuclei. We further corroborate this model using molecular dynamics simulations of heterogeneous and homogeneous nucleation in liquid-solid phase transitions of Pt. We anticipate that the OPG model is applicable to different nucleation processes and our experimental method opens the door to study the structure and dynamics of materials with 4D atomic resolution.

cond-mat.mtrl-sci↗

arXiv2015

Accurate Force Field Parameters and pH Resolved Surface Models for Hydroxyapatite to Understand Structure, Mechanics, Hydration, and Biological Interfaces

Mineralization of bone and teeth involves interactions between biomolecules and hydroxyapatite. Associated complex interfaces and processes remain difficult to analyze at the 1 to 100 nm scale using current laboratory techniques, and prior models for atomistic simulations are limited in the representation of chemical bonding, surface chemistry, and interfacial interactions. This work introduces an accurate force field along with pH-resolved surface models for hydroxyapatite to represent chemical bonding, structural, surface, interfacial, and mechanical properties in quantitative agreement with experiment. The accuracy is orders of magnitude higher in comparison to earlier models to facilitate quantitative monitoring of inorganic-biological assembly. The force field is integrated into the CHARMM, AMBER, OPLS-AA, PCFF, and INTERFACE force fields to enable realistic simulations of apatite-biological systems of any composition and ionic strength. Specifically, the parameters reproduce lattice constants (<0.5% deviation), IR spectrum, cleavage energies, immersion energies in water (<5% deviation), and elastic constants (<10% deviation) of hydroxyapatite in comparison to experiment. Interactions between mineral, water, and organic compounds are represented by standard combination rules in the force field without additional adjustable parameters and shown to achieve quantitative accuracy. Surface models for common (001), (010), (020), (101) facets and nanocrystals are introduced as a function of pH on the basis of extensive experimental data. New insight into surface and immersion energies, the structure of aqueous interfaces, density profiles, and superficial dissolution is described. Mechanisms of specific binding of peptides, drugs, and mineralization can be analyzed and the force field is extensible to substituted and defective apatites as well as to other calcium phosphate phases.

cond-mat.mtrl-sci↗

arXiv2015

Three-dimensional coordinates of individual atoms in materials revealed by electron tomography

Crystallography, the primary method for determining the three-dimensional (3D) atomic positions in crystals, has been fundamental to the development of many fields of science. However, the atomic positions obtained from crystallography represent a global average of many unit cells in a crystal. Here, we report, for the first time, the determination of the 3D coordinates of thousands of individual atoms and a point defect in a material by electron tomography with a precision of ~19 picometers, where the crystallinity of the material is not assumed. From the coordinates of these individual atoms, we measure the atomic displacement field and the full strain tensor with a 3D resolution of ~1nm^3 and a precision of ~10^-3, which are further verified by density functional theory calculations and molecular dynamics simulations. The ability to precisely localize the 3D coordinates of individual atoms in materials without assuming crystallinity is expected to find important applications in materials science, nanoscience, physics and chemistry.

cond-mat.mtrl-sci↗

arXiv2006

Calculation of local pressure tensors in systems with many-body interactions

Local pressures are important in the calculation of interface tensions and in analyzing micromechanical behavior. The calculation of local pressures in computer simulations has been limited to systems with pairwise interactions between the particles, which is not sufficient for chemically detailed systems with many-body potentials such as angles and torsions. We introduce a method to calculate local pressures in systems with n-body interactions (n=2,3,4, . . .) based on a micromechanical definition of the pressure tensor. The local pressure consists of a kinetic contribution from the linear momentum of the particles and an internal contribution from dissected many-body interactions by infinitesimal areas. To define dissection by a small area, respective n-body interactions are divided into two geometric centers, effectively reducing them to two-body interactions. Consistency with hydrodynamics-derived formulas for systems with two-body interactions (J. H. Irving and J. G. Kirkwood, J. Chem. Phys. 18, 817 (1950)), for average cross-sectional pressures (B. D. Todd, D. J. Evans, and P. J. Daivis, Phys. Rev. E 52, 1627 (1995)), and for volume averaged pressures (virial formula) is shown. As a simple numerical example, we discuss liquid propane in a cubic box. Local, crosssectional,and volume-averaged pressures as well as relative contributions from two-body and three-body forces are analyzed with the proposed method, showing full numerical equivalence with the existing approaches. The method allows computing local pressures in the presence of many-body interactions in atomistic simulations of complex materials and biological systems.

cond-mat.stat-mech↗

arXiv2003

Simple and Accurate Computations of Solvatochromic Shifts in pi -> pi* Transitions of Aromatic Chromophors

A new approach is introduced for calculating the spectral shifts of the most bathochromic pi -> pi* transition of an aromatic chromophore in apolar environments. As an example, perylene in solid and liquid n-alkane matrices was chosen, and all shifts are calculated relative to one well-defined solid-inclusion system. It is shown that a simple two-level treatment of the solute using Huckel theory yields spectral shifts in excellent agreement with experimental results for the most prominent inclusion sites of perylene in solid n-alkane surroundings and for the dilute solutions in liquid n-alkanes. The idea is general enough to be applied to any aromatic chromophore in a nonpolar solvent matrix. In contrast to earlier treatments, this approach is based on geometry-dependent polarizabilities, employs a r^-4 dependence for the dispersion energy, is conceptually simple and computationally efficient. Different simple models based on our general approach to compute the UV spectral shifts due to solvation indicate that the dispersive part of the van-der-Waals energy, which stabilizes the LUMO of perylene more than the HOMO, falls off with a distance dependence of r^-4 in a range up to ~1 nm and not as r^-6, as has been assumed for a long time. This finding corresponds to the interpretation of temporary dipoles as being equivalent to weak permanent dipoles with fluctuating orientation.

physics.atm-clus↗

arXiv2003

Surface Structure of Organoclays

The properties of organically modified clay minerals determine essentially the quality of polymer-clay nanocomposites. We investigate alkylammonium-micas with different alkyl chain length by molecular dynamics simulation as homogeneous mixtures and separated island structures on the mica surface (80 percent alkali exchange, 20 percent of the alkali ions remain), including a detailed model of the Si --> Al...K charge defects on the surface of phyllosilicates. By comparison with experiment, we find that long chains (C18) lead to a mixed phase of alkali ions and organic ions on the surface, while chains of a medium length (~C12) give rise to phase separation. Very short chains, by thermodynamical arguments, prefer again a homogeneously mixed surface. We explain this interesting observation with a basic free energy model and present a diagram of the phase behaviour as a function of surface saturation with alkyl chains and the chain length. Besides, an order-disorder transition of the tethered alkyl chains is found on heating when ~20 percent of the torsional angles along the hydrocarbon backbones are gauche. At higher temperature, also rearrangements of the ammonium headgroups on the surface are possible, which lead to metastable structures after quenching.

cond-mat.mtrl-sci↗

arXiv2003

Structure and Phase Transitions of Alkyl Chains on Mica

We use molecular dynamics as a tool to understand the structure and phase transitions [Osman et. al. J. Phys. Chem. B 2000, 104, 4433; 2002, 106, 653] in alkylammonium micas. The consistent force field 91 is extended for accurate simulation of mica and related minerals. We investigate mica sheets with 12 octadecyltrimethylammonium (C18) ions or 12 dioctadecyldimethylammonium (2C18) ions, respectively, as single and layered structures at different temperatures with periodicity in the xy plane by NVT dynamics. The alkylammonium ions reside preferably above the cavities in the mica surface with an aluminum-rich boundary. The nitrogen atoms are 380 to 390 pm distant to the superficial silicon-aluminum plane. With increasing temperature, rearrangements of C18 ions on the mica surface are found, while 2C18 ions remain tethered due to geometric restraints. We present basal-plane spacings in the duplicate structures, tilt angles of the alkyl chains, and gauche-trans ratios to analyze the chain conformation. Also, the individual phase transitions of the two systems on heating are explained. Where experimental data are available, the agreement is very good. We propose a geometric parameter lamba for the saturation of the surface with alkyl chains, which determines the preferred self-assembly pattern, i.e., islands, intermediate, or continuous. Lambda also determines the tilt angles in continuous layers on mica or other surfaces. The thermal decomposition appears to be a Hofmann elimination with mica as a base-template.

cond-mat.mtrl-sci↗

arXiv2003

Analysis of the Phase Transitions in Alkyl- Mica by Density and Pressure Profiles

In a previous work [H. Heinz, H. J. Castelijns, U. W. Suter, J. Am. Chem. Soc. 115, 9500 (2003)], we developed an accurate force field and simulated the phase transitions in C18-mica (octadecyltrimethylammonium-mica) as well as the absence of such transitions in 2C18-mica (dioctadecyldimethylammonium-mica) between room temperature and 100 deg C. Here we analyze (i) average z coordinates of the carbon atoms and interdigitation of the hydrocarbon bilayers, (ii) density profiles and (iii) pressure profiles of the structures along all Cartesian axes. In C18-mica, the standard deviation in the z coordinate for the chain atoms is high and more than doubles in the disordered phase. The order-disorder transition is accompanied by a change in the orientation of the ammonium headgroup, as well as decreasing tensile and shear stress in the disordered phase. In 2C18-mica, the standard deviation in the z coordinate for the chain atoms is low and does not increase remarkably on heating. The backbones display a highly regular structure, which is slightly obscured by rotations in the C18 backbones and minor headgroup displacements at 100 deg C. Close contacts between the bulky headgroups with sidearms cause significant local pressure which is in part not relieved at 100 deg C. An increase of the basal-plane spacing at higher temperature is found in both systems due to larger separation between the two hydrocarbon layers and an increased z spacing between adjacent chain atoms (=decreased tilt of the chains relative to the surface normal), and, in C18-mica only, a stronger upward orientation of the C18 chain at the ammonium headgroup. The likelihood for chain interdigitation between the two hydrocarbon layers is 0.24 to 0.30 for C18-mica,and 0.65 to 0.26 for 2C18-mica (for 20 deg C to 100 deg C).

cond-mat.soft↗