arXiv subjects

Lorenz Romaner

Publications and source records attributed to Lorenz Romaner.

10 recordsLinked to original sources

arXiv2026

Interstitials as a key ingredient for P segregation to grain boundaries in polycrystalline $α$-Fe

Solute segregation to grain boundaries (GBs) significantly impacts material behavior, with most studies focusing on substitutional solute segregation while neglecting interstitial segregation due to its increased complexity. The site preference, interstitial or substitutional, for P segregation in $α$-Fe still remains under debate. This work investigates both substitutional and interstitial GB segregation in a polycrystalline model using classical interatomic potentials and machine learning. The method is validated with H and Ni, whose segregation behaviors are well understood. For P, we find segregation to both GB site types, with a preference for substitutional sites based on mean segregation energy. However, the abundance of interstitial sites means interstitial segregation also significantly contributes to the GB enrichment with P. This highlights the importance of considering interstitial P segregation alongside substitutional segregation. Additionally, obtaining a representative spectrum of segregation energies is crucial for accurate, experimentally aligned predictions.

cond-mat.mtrl-sci↗

arXiv2026

Intrinsic grain-size gradients upon grain growth near a free surface

Grain growth fundamentally shapes the microstructure of crystalline materials upon annealing, affecting their overall mechanical and functional properties. Recently, it has been rationalized that grain growth in polycrystals does not result solely from weighted curvature flow, but elastic effects (intrinsic stress) arised from shear coupling also need to be taken into account. We characterize and examine the effect of free surfaces on grain growth kinetics of high-purity, bulk polycrystalline nickel. By analyzing the microstructural evolution on cross sections of 1 mm thick specimens from the surface to the interior, as well as through in-plane investigations on specimens with varying thickness (1 mm, 40 $μ$m, and 10 $μ$m), an intrinsic grain-size gradient was identified, characterized by a gradual increase in grain size towards the interior. Interestingly, this grading was not restricted to the very surface but continued to depths of five to ten layers of grains, where effects from thermal grooves are considered negligible. We demonstrate that this behavior is significantly affected by elastic relaxation at the free surface, which alters the internal stress fields generated by shear-coupled grain boundary migration. These findings emphasize the relevance of free surfaces to the microstructural evolution of polycrystal.

cond-mat.mtrl-sci↗

arXiv2025

Towards predictive atomistic simulations of SiC crystal growth

Simulations of SiC crystal growth using molecular dynamics (MD) have become popular in recent years. They, however, simulate very fast deposition rates, to reduce computational costs. Therefore, they are more akin to surface sputtering, leading to abnormal growth effects, including thick amorphous layers and large defect densities. A recently developed method, called the minimum energy atomic deposition (MEAD), tries to overcome this problem by depositing the atoms directly at the minimum energy positions, increasing the time scale. We apply the MEAD method to simulate SiC crystal growth on stepped C-terminated 4H substrates with 4° and 8° off-cut angle. We explore relevant calculations settings, such as amount of equilibration steps between depositions and influence of simulation cell sizes and bench mark different interatomic potentials. The carefully calibrated methodology is able to replicate the stable step-flow growth, which was so far not possible using conventional MD simulations. Furthermore, the simulated crystals are evaluated in terms of their dislocations, surface roughness and atom mobility. Our methodology paves the way for future high fidelity investigations of surface phenomena in crystal growth.

cond-mat.mtrl-sci↗

arXiv2025

Accurate ab initio modeling of solid solution strengthening in high entropy alloys

High entropy alloys (HEA) represent a class of materials with promising properties, such as high strength and ductility, radiation damage tolerance, etc. At the same time, a combinatorially large variety of compositions and a complex structure render them quite hard to study using conventional methods. In this work, we present a computationally efficient methodology based on ab initio calculations within the coherent potential approximation. To make the methodology predictive, we apply an exchange-correlation correction to the equation of state and take into account thermal effects on the magnetic state and the equilibrium volume. The approach shows good agreement with available experimental data on bulk properties of solid solutions. As a particular case, the workflow is applied to a series of iron-group HEA to investigate their solid solution strengthening within a parameter-free model based on the effective medium representation of an alloy. The results reveal intricate interactions between alloy components, which we analyze by means of a simple model of local bonding. Thanks to its computational efficiency, the methodology can be used as a basis for an adaptive learning workflow for optimal design of HEA.

cond-mat.mtrl-sci↗

arXiv2025

Inversion of Dislocation-Impurity Interactions in $α$-Fe under Magnetic State Changes

In this work, we investigate the dislocation-impurity interaction energies and their profiles for various \textit{3d} elements \textemdash V, Cr, Mn, Cu, Ni, and Co \textemdash in and around $1/2\langle111\rangle$ screw dislocations in $α$-Fe using \textit{ab initio} methods. We consider the ferromagnetic and paramagnetic states, with the latter being modeled through both the disordered local moment model and a spin-wave approach. Our findings reveal that (1) magnetic effects are large compared to size misfit effects of substitutional impurities, and (2) dislocation-impurity interactions are dependent on the magnetic state of the matrix and thermal lattice expansion. In particular, Cu changes from core-attractive in the ferromagnetic state to repulsive in the paramagnetic state.

cond-mat.mtrl-sci↗

arXiv2025

Segregation to grain boundaries in disordered systems: an application to a Ni-based multi-component alloy

Segregation to defects, in particular to grain boundaries (GBs), is an unavoidable phenomenon leading to changed material behavior over time. With the increase of available computational power, unbiased quantum-mechanical predictions of segregation energies, which feed classical thermodynamics models of segregation (e.g., McLean isotherm), become available. In recent years, huge progress towards predictions closely resembling experimental observations was made by considering the statistical nature of the segregation process due to competing segregation sites at a single GB and/or many different types of co-existing GBs. In the present work, we further expand this field by explicitly showing how compositional disorder, present in real engineering alloys (e.g. steels or Ni-based superalloys), gives rise to a spectrum of segregation energies. With the example of a $Σ5$ GB in a Ni-based model alloy (Ni-Co-Cr-Ti-Al), we show that the segregation energies of Fe, Mn, W, Nb, and Zr are significantly different from those predicted for pure elemental Ni. We further use the predicted segregation energy spectra in a statistical evaluation of GB enrichment, which allows for extracting segregation enthalpy and segregation entropy terms related to the chemical complexity in multi-component alloys.

cond-mat.mtrl-sci↗

arXiv2024

Ab initio framework for deciphering trade-off relationships in multi-component alloys

While first-principles methods have been successfully applied to characterize individual properties of multi-principal element alloys (MPEA), their use to search for optimal trade-offs between competing properties is hampered by high computational demands. In this work, we present a novel framework to explore Pareto-optimal compositions by integrating advanced ab initio-based techniques into a Bayesian multi-objective optimization workflow complemented with a simple analytical model providing straightforward analysis of trends. We benchmark the framework by applying it to solid solution strengthening and ductility of refractory MPEAs, with the parameters of the strengthening and ductility models being efficiently computed using a combination of the coherent-potential approximation method, accounting for finite-temperature effects, and actively-learned moment-tensor potentials parameterized with ab initio data. Properties obtained from ab initio calculations are subsequently used to extend predictions of all relevant material properties to a large class of refractory alloys with the help of the analytical model validated by the data and relying on a few element-specific parameters and universal functions that describe bonding between elements. Our findings offer new crucial insights into the traditional strength-vs-ductility dilemma of refractory MPEAs. The proposed framework is versatile and can be extended to other materials and properties of interest, enabling a predictive and tractable high-throughput screening of Pareto-optimal MPEAs over the entire composition space.

cond-mat.mtrl-sci↗

arXiv2022

Interstitial segregation has the potential to mitigate liquid metal embrittlement in iron

The embrittlement of metallic alloys by liquid metals leads to catastrophic material failure and severely impacts their structural integrity. The weakening of grain boundaries by the ingress of liquid metal and preceding segregation in the solid are thought to promote early fracture. However, the potential of balancing between the segregation of cohesion-enhancing interstitial solutes and embrittling elements inducing grain boundary decohesion is not understood. Here, we unveil the mechanisms of how boron segregation mitigates the detrimental effects of the prime embrittler, zinc, in a $Σ5\,[0\,0\,1]$ tilt grain boundary in $α-$Fe ($4~at.\%$ Al). Zinc forms nanoscale segregation patterns inducing structurally and compositionally complex grain boundary states. Ab-initio simulations reveal that boron hinders zinc segregation and compensates for the zinc induced loss in grain boundary cohesion. Our work sheds new light on how interstitial solutes intimately modify grain boundaries, thereby opening pathways to use them as dopants for preventing disastrous material failure.

cond-mat.mtrl-sci↗

arXiv2022

On Strong-Scaling and Open-Source Tools for High-Throughput Quantification of Material Point Cloud Data: Composition Gradients, Microstructural Object Reconstruction, and Spatial Correlations

Characterizing microstructure-material-property relations calls for software tools which extract point-cloud- and continuum-scale-based representations of microstructural objects. Application examples include atom probe, electron, and computational microscopy experiments. Mapping between atomic- and continuum-scale representations of microstructural objects results often in representations which are sensitive to parameterization; however assessing this sensitivity is a tedious task in practice. Here, we show how combining methods from computational geometry, collision analyses, and graph analytics yield software tools for automated analyses of point cloud data for reconstruction of three-dimensional objects, characterization of composition profiles, and extraction of multi-parameter correlations via evaluating graph-based relations between sets of meshed objects. Implemented for point clouds with mark data, we discuss use cases in atom probe microscopy that focus on interfaces, precipitates, and coprecipitation phenomena observed in different alloys. The methods are expandable for spatio-temporal analyses of grain fragmentation, crystal growth, or precipitation.

cond-mat.mtrl-sci↗

arXiv2021

Aluminum depletion induced by complex co-segregation of carbon and boron in a Σ 5 [3 1 0] bcc-iron grain boundary

The local variation of grain boundary atomic structure and chemistry caused by segregation of impurities influences the macroscopic properties of poylcrystalline materials. Here, the effect of co-segregation of carbon and boron on the depletion of aluminum at a $Σ5\,(3\,1\,0\,) [0\,0\,1]$ tilt grain boundary in a $α-$Fe-$4~at.~\%$Al bicrystal was studied by combining atomic resolution scanning transmission electron microscopy, atom probe tomography and density functional theory calculations. The atomic grain boundary structural units mostly resemble kite-type motifs and the structure appears disrupted by atomic scale defects. Atom probe tomography reveals that carbon and boron impurities are co-segregating to the grain boundary reaching levels of >1.5 at.\%, whereas aluminum is locally depleted by approx. 2~at.\%. First-principles calculations indicate that carbon and boron exhibit the strongest segregation tendency and their repulsive interaction with aluminum promotes its depletion from the grain boundary. It is also predicted that substitutional segregation of boron atoms may contribute to local distortions of the kite-type structural units. These results suggest that the co-segregation and interaction of interstitial impurities with substitutional solutes strongly influences grain boundary composition and with this the properties of the interface.

cond-mat.mtrl-sci↗