arXiv subjects

Fritz Körmann

Publications and source records attributed to Fritz Körmann.

16 recordsLinked to original sources

arXiv2026

Impact of interstitial carbon on local lattice distortions in CoCrFeMnNi high-entropy alloys

Here, we explore component-dependent local lattice distortions in polycrystalline, equiatomic, face-centered cubic CrMnFeCoNi high-entropy alloys and their modifications induced by dilute interstitial carbon. Multi-edge extended X-ray absorption fine structure spectroscopy combined with reverse Monte Carlo analysis reveals that the Cr component experiences the most substantial local distortions, independent of the temperature of prolonged annealing treatments (993 K or 1373 K) and the nominal carbon content (0 to 0.8 at.%). The static disorder around Cr atoms was found to increase markedly and monotonically upon carbon alloying, whereas Mn, Fe, Co, and Ni demonstrate weaker and non-monotonic tendencies. The carbon-induced lattice distortions extend over several coordination shells, indicating the pronounced effect of the carbon presence on the local environment around Cr absorbers. First-principles density functional theory and finite-temperature molecular dynamics simulations confirm the greater impact of carbon on the local lattice distortions around Cr than around the other $3d$ constituent elements, based on the previous finding that carbon preferentially occupies Cr-rich interstitial sites. These results provide decisive hints towards the atomistic origin of the non-monotonic diffusion behavior previously reported for carbon-doped CrMnFeCoNi alloys, and are noticeable for understanding the carbon-induced phase transitions in compositionally complex systems.

cond-mat.mtrl-sci↗

arXiv2026

An Ontology for Machine Learning Interatomic Potentials

Machine learning interatomic potentials (MLIPs) approximate quantum-mechanical energies and forces---conventionally computed by density functional theory (DFT) or wave-function methods---at a fraction of the cost. The field encompasses a growing ecosystem of algorithms, training datasets, hyperparameters, and target materials, yet the metadata needed to systematically compare, reproduce, and build upon MLIP studies remains scattered across papers, scripts, and ad-hoc file formats. We present the MLIPs ontology, an OWL 2 DL ontology that captures the concepts needed to describe MLIP methods, their hyperparameters, training datasets with DFT provenance, and published benchmarks. The ontology is organized into three modules---Method, Training Data, and Benchmark---and connects existing ontologies in materials science (MDO, CMSO/ASMO) and machine learning (ML-Schema), complementing dataset-side schemas such as Croissant. It declares 27 formal axioms enforcing data completeness and consistency, including property chains that link trained models to their methods and training data. We demonstrate the ontology through a running example based on Moment Tensor Potentials and evaluate it through competency-question execution on a 20-paper seeded knowledge graph, OWL reasoning, and comparison with existing ontologies.

cs.AI↗

arXiv2026

Temperature dependence of the Gibbs energies of formation of point defects in B2 MoTa from ab initio calculations

Using B2 MoTa, the strongest B2 former among group V/VI refractory binaries, as a model system, we compute temperature-dependent Gibbs energies of formation of vacancies and antisites from ab initio calculations up to 3000 K at the stoichiometric composition. We explicitly account for thermal electronic excitations, vibrational anharmonicity, and electron-vibration coupling. The key finding is that the temperature dependence of the Gibbs energies of vacancy formation exhibits a pronounced sublattice asymmetry. Specifically, the Gibbs energy of formation of a Mo-site vacancy decreases by 1.1 eV from 0 to 3000 K, whereas the decrease for a Ta-site vacancy amounts to 2.1 eV, almost a factor of two larger. Two contributions of distinct origin govern the temperature dependence of this asymmetry: a quasiharmonic contribution associated with the chemical-potential imbalance set by the two antisite structures and an anharmonic contribution associated with the local vibrational response of the vacancy structures. The asymmetry in anharmonic vibrations is traced back to an enlarged local vibrational distribution of the first-nearest neighbors around the Ta-site vacancy. In contrast to the vacancies, the Gibbs energies of antisite formation vary only weakly with temperature.

cond-mat.mtrl-sci↗

arXiv2026

Hydrogen uptake and hydride formation in Al$_x$CoCrFeNi high-entropy alloys: First-principles, universal-potential, and experimental study

Hydrogen uptake in complex multicomponent alloys, including high-entropy alloys (HEAs), governs both hydrogen storage capacity and resistance to hydrogen-induced degradation. We combine high-pressure experiments, density-functional theory (DFT), and a GRACE universal interatomic potential to investigate hydrogen absorption in Al$_{0.3}$CoCrFeNi and Al$_3$CoCrFeNi HEAs. In H$_2$ as a pressure-transmitting medium, the FCC Al$_{0.3}$CoCrFeNi alloy forms hydrides at ambient temperature above 3 GPa, whereas the Al-rich B2 Al$_3$CoCrFeNi alloy shows no evidence of hydride formation even upon heating at pressures up to 50 GPa. Experiments and calculations show that aluminum suppresses hydrogen uptake by increasing solution energies and destabilizing interstitial sites. The universal potential, employed in the calculations and pretrained on large DFT databases, closely reproduces DFT energetics and demonstrates transferability from the dilute limit to the hydride-forming regime. Simulations further disentangle the roles of local ordering, volume changes, composition, and crystal structure. Overall, our results indicate that hydrogen solubility in Al-containing HEAs is governed primarily by composition, with Al-driven B2 ordering as a strong secondary effect.

cond-mat.mtrl-sci↗

arXiv2026

Microstructural origin of the simultaneous enhancements in strength and ductility of a nitrogen-doped high-entropy alloy

As one of the most abundant interstitial elements, nitrogen (N) is effective in improving yield strength of metallic materials, due to interstitial solid solution strengthening. Doping N can substantially enhance the yield strength but often leads to a decreased ductility, revealing a strength-ductility trade-off phenomenon. Here, we simultaneously enhance the strength and ductility in a non-equiatomic CrMnFeCoNi high-entropy alloy via N alloying and unravel the underlying microscopic mechanisms. The N-doped alloy (1 at.% N) shows an excellent combination of higher yield strength (104% increase) and larger ductility (38% increase), with a two-stage strain hardening behavior, compared to the N-free alloy. Detailed transmission electron microscopy (TEM) analysis reveals that N-doping introduces short-range order (SRO) domains within the microstructure, leads to pronounced planar slip, and promotes the formation of nano-spaced (6-15 nm) stacking faults and deformation twins. Continuous generation and interaction of the fine-spaced SFs act as a strong barrier for dislocation movement and provide ample room for dislocation storage. The interaction of SRO with dislocations and the evolution of SFs ascribe to the first strain hardening stage, and the disordering of the SRO along with the activation of deformation twins are attributed to the second strain hardening stage. Our work shows that N-doping is effective in simultaneously improving the strength-ductility synergy and provides novel insights into alloy design with slightly elevating the SFE, and manipulating the ordered structure within the HEA.

cond-mat.mtrl-sci↗

arXiv2026

Hydrogen diffusion in TiCr$_2$H$_x$ Laves phases: A combined ab initio and machine-learning-potential study

The kinetics of hydrogen diffusion in C15 cubic and C14 hexagonal TiCr$_2$H$_x$ (0 < $x$ <= 4) Laves-phase hydrogen storage alloys is investigated with density functional theory (DFT) and machine learning interatomic potentials (MLIPs). Generalized solid-state nudged elastic band calculations are conducted based on DFT for all symmetrically inequivalent paths between the first-nearest-neighbor face-sharing interstitial sites. The hydrogen migration barriers are substantially higher for the paths that require breaking a Ti-H bond than for those that require breaking a Cr-H bond. Molecular dynamics (MD) simulations with the MLIPs also demonstrate that hydrogen migration occurs more frequently within the hexagonal rings made of the A$_2$B$_2$ interstitial paths, each requiring the breaking of Cr-H bonds, than along the inter-ring paths. The diffusion coefficients of hydrogen obtained from the MD simulations reveal a non-monotonic dependence on hydrogen concentration, which is more pronounced at lower temperatures. Time-averaged radial distribution functions of hydrogen further show that hydrogen avoids face-sharing positions during diffusion and that the hydrogen occupancy at the second-nearest-neighbor edge-sharing positions increases with increasing hydrogen concentration. The diffusion coefficients of hydrogen within 400-1000 K follow an Arrhenius relationship, with activation barriers consistent with most experimental values. One-order of magnitude overestimation of diffusion coefficients compared with some experiments suggests a substantial impact of hydrogen trapping by defects such as Cr vacancies and Ti anti-sites in non-stoichiometric TiCr$_2$ in experiments.

cond-mat.mtrl-sci↗

arXiv2025

Machine Learning Potentials for Hydrogen Absorption in TiCr$_2$ Laves Phases

The energetics of hydrogen absorption in C15 cubic and C14 hexagonal TiCr$_2$H$_x$ Laves phases is investigated for $0 < x \le 6$ with density functional theory (DFT) and machine learning interatomic potentials (MLIPs). The MLIPs are trained with configurations generated through a series of active-learning schemes. Basin-hopping Monte Carlo (BHMC) simulations based on the MLIPs predict minimum-energy hydrogen configurations, along with enthalpies of formation and hydrogen orderings. The obtained phase transformations at 0 K agree well with the experiments at low temperatures. The hydrogen solubility limits in the low-concentration $α$ phases at 0 K are predicted to be $x = 1.0$ and $x = 1.5$ for the C15 and the C14 phases, respectively. At these concentrations, C15 TiCr$_2$H shows the $Cc$ monoclinic symmetry, while C14 TiCr$_2$H$_{1.5}$ shows the $Ama2$ orthorhombic symmetry, both of which have not been reported for this system. The first and the second hydride phases, i.e., $β$ and $β'$, at 0 K are found around $x = 3$ and $x = 4$, respectively, for both the C15 and the C14 phases. In the second-hydride $β'$ phases, C15 TiCr$_2$H$_4$ shows the $I4_1/a$ tetragonal symmetry, while C14 TiCr$_2$H$_4$ shows the $R\bar3c$ rhombohedral symmetry. Hydrogen repulsion are found to extend to edge-sharing interstices, affecting the hydrogen ordering. Furthermore, the $6h_2$ A$_2$B$_2$ interstices are found to be energetically substantially more preferable for C14 TiCr$_2$H$_x$ than the other A$_2$B$_2$ interstices at low hydrogen concentrations, influencing the hydrogen-occupation trend.

cond-mat.mtrl-sci↗

arXiv2025

Lattice distortions and non-sluggish diffusion in BCC refractory high entropy alloys

Refractory high-entropy alloys (RHEAs) have emerged as promising candidates for extreme high-temperature applications, for example, in next-generation turbines and nuclear reactors. In such applications, atomic diffusion critically governs essential properties including creep resistance and microstructural stability. The present study systematically investigates impurity diffusion of Co, Mn, and Zn in single phase (BCC solid solution) HfTiZrNbTa and HfTiZrNbV RHEAs applying the radiotracer technique. A neutron total scattering technique is used to evaluate the pair distribution functions and element-specific lattice distortions in these alloys. \textit{Ab initio}-based calculations give access to lattice distortions and solubilities of the impurities under investigation, including the impact of short-range order. The diffusion results are discussed in relation to calculated substitutional and interstitial solution energies, local lattice distortions, and short-range order effects. Co diffusion is found to be dominated by the interstitial mechanism, exhibiting fast diffusion. These findings reveal important structure-property relationships between local atomic environments and diffusion kinetics in BCC RHEAs, providing critical insights for designing alloys with enhanced high-temperature performance through targeted control of impurity diffusion processes.

cond-mat.mtrl-sci↗

arXiv2025

Ultrastrong and ductile CoNiMoAl medium-entropy alloys enabled by L12 nanoprecipitate-induced multiple deformation mechanisms

L12 precipitates are known to significantly enhance the strength and ductility of single-phase face-centered cubic (FCC) medium- or high-entropy alloys (M/HEAs). However, further improvements in mechanical properties remain untapped, as alloy design has historically focused on systems with specific CrCoNi- or FeCoCrNi-based FCC matrix and Ni3Al L12 phase compositions. This study introduces novel Co-Ni-Mo-Al alloys with L12 precipitates by systematically altering Al content, aiming to bridge this research gap by revealing the strengthening mechanisms. The (CoNi)81Mo12Al7 alloy achieves yield strength of 1086 MPa, tensile strength of 1520 MPa, and ductility of 35 %, demonstrating an impressive synergy of strength, ductility, and strain-hardening capacity. Dislocation analysis via transmission electron microscopy, supported by generalized stacking fault energy (GSFE) calculations using density functional theory (DFT), demonstrates that Mo substitution for Al in the L12 phase alters dislocation behavior, promoting the formation of multiple deformation modes, including stacking faults, super-dislocation pairs, Lomer-Cottrell locks, and unusual nano-twin formation even at low strains. These behaviors are facilitated by the low stacking fault energy (SFE) of the FCC matrix, overlapping of SFs, and dislocation dissociation across anti-phase boundaries (APBs). The increased energy barrier for superlattice intrinsic stacking fault (SISF) formation compared to APBs, due to Mo substitution, further influences dislocation activity. This work demonstrates a novel strategy for designing high-performance M/HEAs by expanding the range of FCC matrix and L12 compositions through precipitation hardening.

cond-mat.mtrl-sci↗

arXiv2022

Modelling Surface Segregation in Compositionally Complex Alloys with Ab-Initio Accuracy

Compositionally complex alloys or concentrated solid solutions are the latest frontier in catalyst design, but mixing different elements in one catalyst may result in surface segregation. Atomistic simulations can predict segregation patterns, but standard approaches based on mean-field models, cluster expansion, or classical interatomic potentials are often limited for the description of multicomponent alloys. We present machine learning potentials that can describe surface segregation with near DFT accuracy. The method is used to study a complex Co-Cu-Fe-Mo-Ni quinary alloy. For this alloy, an unexpected segregation of Co, which has a relatively high surface energy, is observed. We rationalize this surprising mechanism in terms of simple transition-metal chemistry.

cond-mat.mtrl-sci↗

arXiv2022

Machine learning-enabled high-entropy alloy discovery

High-entropy alloys are solid solutions of multiple principal elements, capable of reaching composition and feature regimes inaccessible for dilute materials. Discovering those with valuable properties, however, relies on serendipity, as thermodynamic alloy design rules alone often fail in high-dimensional composition spaces. Here, we propose an active-learning strategy to accelerate the design of novel high-entropy Invar alloys in a practically infinite compositional space, based on very sparse data. Our approach works as a closed-loop, integrating machine learning with density-functional theory, thermodynamic calculations, and experiments. After processing and characterizing 17 new alloys (out of millions of possible compositions), we identified 2 high-entropy Invar alloys with extremely low thermal expansion coefficients around 2*10-6 K-1 at 300 K. Our study thus opens a new pathway for the fast and automated discovery of high-entropy alloys with optimal thermal, magnetic and electrical properties.

cond-mat.mtrl-sci↗

arXiv2019

Impact of lattice relaxations on phase transitions in a high-entropy alloy studied by machine-learning potentials

Recently, high-entropy alloys (HEAs) have attracted wide attention due to their extraordinary materials properties. A main challenge in identifying new HEAs is the lack of efficient approaches for exploring their huge compositional space. Ab initio calculations have emerged as a powerful approach that complements experiment. However, for multicomponent alloys existing approaches suffer from the chemical complexity involved. In this work we propose a method for studying HEAs computationally. Our approach is based on the application of machine-learning potentials based on ab initio data in combination with Monte Carlo simulations. The high efficiency and performance of the approach are demonstrated on the prototype bcc NbMoTaW HEA. The approach is employed to study phase stability, phase transitions, and chemical short-range order. The importance of including local relaxation effects is revealed: they significantly stabilize single-phase formation of bcc NbMoTaW down to room temperature. Finally, a so-far unknown mechanism that drives chemical order due to atomic relaxation at ambient temperatures is discovered.

cond-mat.mtrl-sci↗

arXiv2019

Ab initio vibrational free energies including anharmonicity for multicomponent alloys

A density-functional-theory based approach to efficiently compute numerically exact vibrational free energies - including anharmonicity - for chemically complex multicomponent alloys is developed. It is based on a combination of thermodynamic integration and a machine-learning potential. We demonstrate the performance of the approach by computing the anharmonic free energy of the prototypical five-component VNbMoTaW refractory high entropy alloy.

cond-mat.mtrl-sci↗

arXiv2018

Anomalous phonon lifetime shortening in paramagnetic CrN caused by magneto-lattice coupling: A combined spin and ab initio molecular dynamics study

We study the mutual coupling of spin fluctuations and lattice vibrations in paramagnetic CrN by combining atomistic spin dynamics and ab initio molecular dynamics. The two degrees of freedom are dynamically coupled leading to non-adiabatic effects. Those effects suppress the phonon life times at low temperature compared to an adiabatic approach. The here identified dynamic coupling provides an explanation for the experimentally observed unexpected temperature dependence of the thermal conductivity of magnetic semiconductors above the magnetic ordering temperature.

cond-mat.mtrl-sci↗

arXiv2017

Temperature-dependent phonon spectra of magnetic random solid solutions

A first-principles-based method for computing phonons of magnetic random solid solutions including thermal magnetic fluctuations is developed. The method takes fluctuations of force constants (FCs) due to magnetic excitations as well as due to chemical disorder into account. The developed approach correctly predicts the experimentally observed unusual phonon hardening of a transverse acoustic mode in Fe-Pd an Fe-Pt Invar alloys with increasing temperature. This peculiar behavior, which cannot be explained within a conventional, harmonic picture, turns out to be a consequence of thermal magnetic fluctuations.

cond-mat.mtrl-sci↗

arXiv2014

Structural stability and thermodynamics of CrN magnetic phases from ab initio and experiment

The dynamical and thermodynamic phase stabilities of the stoichiometric compound CrN including different structural and magnetic configurations are comprehensively investigated using a first-principles density-functional-theory (DFT) plus U approach in conjunction with experimental measurements of the thermal expansion. Comparing DFT and DFT+U results with experimental data reveals that the treatment of electron correlations using methods beyond standard DFT is crucial. The non-magnetic face-centered cubic B1-CrN phase is both, elastically and dynamically unstable, even under high pressure, while CrN phases with non-zero local magnetic moments are predicted to be dynamically stable within the framework of the DFT+U scheme. Furthermore, the impact of different treatments for the exchange-correlation (xc)-functional is investigated by carrying out all computations employing the local density approximation and generalized gradient approximation. To address finite-temperature properties, both, magnetic and vibrational contributions to the free energy have been computed employing our recently developed spin-space averaging method. The calculated phase transition temperature between low-temperature antiferromagnetic and high-temperature paramagnetic (PM) CrN variants is in excellent agreement with experimental values and reveals the strong impact of the choice of the xc-functional. The temperature-dependent linear thermal expansion coefficient of CrN is experimentally determined by the wafer curvature method from a reactive magnetron sputter deposited single-phase B1-CrN thin film with dense film morphology. A good agreement is found between experimental and ab initio calculated linear thermal expansion coefficients of PM B1-CrN. Other thermodynamic properties, such as the specific heat capacity, have been computed as well and compared to previous experimental data.

cond-mat.mtrl-sci↗