arXiv subjects

Vladyslav Turlo

Publications and source records attributed to Vladyslav Turlo.

18 recordsLinked to original sources

arXiv2026

Critical role of phase-dependent properties in modeling photothermal sintering of LiCoO2 cathodes

Photothermal (photonic) sintering crystallizes as-deposited amorphous LiCoO2 (LCO) cathodes for solid-state thin-film batteries using millisecond, surface-localized heating. However, process design often relies on 1D models with phase-averaged, temperature-independent properties, which can mispredict peak temperatures and thermal damage margins. Here we develop a multiscale, data-driven framework that provides phase- and grain size-resolved thermophysical inputs for stoichiometric LCO. We train an Allegro neural network potential with near-ab initio accuracy, enabling Green-Kubo calculations of thermal conductivity for crystalline and amorphous phases. The low, weakly density-dependent conductivity of amorphous LCO motivates its use as an effective intergranular phase in a thin-interface model that reproduces observed grain-size-dependent thermal transport. Combined with measured wavelength-resolved optical properties in 1D multiphysics simulations, we show amorphous LCO absorbs more strongly and reaches higher peak temperatures than crystalline LCO; thus crystalline, constant-property models systematically overestimate safe operating windows.

cond-mat.mtrl-sci↗

arXiv2026

OptiMat Alloys: a FAIR, living database of multi-principal element alloys enabled by a conversational agent

The FAIR principles have transformed how computational data and workflows are shared in materials research, yet existing repositories can only serve pre-computed entries -- broad coverage is perpetually incomplete and cannot adapt to new questions on demand. To address these challenges, we present OptiMat Alloys, a large language model-powered conversational agent for multi-principal element alloy exploration built on three pillars: a living database that stores every calculation with provenance, low-barrier accessibility through a web interface requiring zero programming expertise, and built-in uncertainty quantification via cross-potential and cross-configuration validation. Coupling foundational machine learning interatomic potentials covering near-all periodic table of elements with natural-language interaction, OptiMat Alloys enables targeted, on-demand computation guided by the user's domain knowledge-extending FAIR from pre-computed repositories to on-demand knowledge generation and making computational alloy screening accessible to any materials scientist.

cond-mat.mtrl-sci↗

arXiv2025

Hydroxylation-driven surface reconstruction at the origin of compressive-to-tensile stress transition in metal oxide nanoparticles

Experiments reveal negative (non-Laplacian) surface stresses in metal oxide nanoparticles, partly associated with humidity during fabrication and annealing. Using a neural network interatomic potential for MgO, we prove that water adsorption induces surface hydroxylation, shifting facets from {100} to {110} to {111} and switching the average surface stress from positive to negative. Predicted lattice strains versus nanoparticle size agree well with experiments, clarifying experimental correlations. The new framework informs broad applications in catalysis, sensors, batteries, and biomedicine.

cond-mat.mtrl-sci↗

arXiv2025

Refining interface stress measurement in nanomultilayers through layer corrugation and interface roughness corrections

We introduce new models that incorporate layer corrugation and interface roughness into standard approaches for measuring interface stress in nanomultilayers (NMLs). Applied to Cu/W NMLs, these models show that ignoring such features can inflate measured interface stress by up to 0.4 J/m^2. However, corrugation and roughness alone cannot account for the extreme stresses reported, suggesting that atomic-scale phenomena (e.g., intermixing and metastable phase formation at the interfaces) dominate. These findings highlight the importance of balancing bilayer counts and thickness-to-roughness ratios for reliable stress quantification, providing a practical pathway to designing and characterizing advanced nanocomposite coatings with improved accuracy.

cond-mat.mtrl-sci↗

arXiv2024

Bridging classical and quantum interpretation of chemical state analysis by XPS/HAXPES to resolve short-range order in amorphous alumina films

Probing the local structure and chemistry of wide-bandgap amorphous oxide thin films remains challenging due to the limitations of lab-based spectroscopy. This work integrates X-ray photoelectron spectroscopy (XPS), hard X-ray photoemission spectroscopy (HAXPES), molecular dynamics simulations using machine-learning interatomic potentials, density-functional theory (DFT) calculations, and classical electrostatic modeling of final-state core-ionization effects in Al atoms to uncover the structure and chemistry of amorphous alumina polymorphs made with atomic layer deposition (ALD). DFT calculations using the Delta Kohn-Sham method supported the interpretation of final-state effects and validated electrostatic model assumptions. Shifts in the measured Auger parameter were interpreted as extra-atomic relaxation energies, revealing sensitivity to the local coordination environment. Structural disorder and thermal fluctuations were found to govern the distribution of extra-atomic relaxation energies, suggesting that cryo-XPS can isolate and reveal intrinsic structural building blocks of amorphous oxides. Simulated heating and annealing demonstrated that Auger parameter shifts can serve as indicators of phase decomposition in H-supersaturated ALD amorphous alumina. These findings provide a pathway for comprehensive interpretation and predictive modeling of XPS spectra in amorphous wide-bandgap oxides.

cond-mat.mtrl-sci↗

arXiv2024

Uncovering the origin of interface stress enhancement and compressive-to-tensile stress transition in immiscible nanomultilayers

The intrinsic stress in nanomultilayers (NMLs) is typically dominated by interface stress, which is particularly high in immiscible Cu/W NMLs. Here, atomistic simulations with a chemically-accurate neural network potential reveal the role of interfacial intermixing and metastable phase formation on the interface stress levels. These results rationalize an experimentally-reported compressive- to-tensile transition as a function of NML deposition conditions and the extremely high interface stresses under some conditions.

cond-mat.mtrl-sci↗

arXiv2024

Machine learning potential for the Cu-W system

Combining the excellent thermal and electrical properties of Cu with the high abrasion resistance and thermal stability of W, Cu-W nanoparticle-reinforced metal matrix composites and nano-multilayers (NMLs) are finding applications as brazing fillers and shielding material for plasma and radiation. Due to the large lattice mismatch between fcc Cu and bcc W, these systems have complex interfaces that are beyond the scales suitable for ab initio methods, thus motivating the development of chemically accurate interatomic potentials. Here, a neural network potential (NNP) for Cu-W is developed within the Behler-Parrinello framework using a curated training dataset that captures metallurgically-relevant local atomic environments. The Cu-W NNP accurately predicts (i) the metallurgical properties (elasticity, stacking faults, dislocations, thermodynamic behavior) in elemental Cu and W, (ii) energies and structures of Cu-W intermetallics and solid solutions, and (iii) a range of fcc Cu/bcc W interfaces, and exhibits physically-reasonable behavior for solid W/liquid Cu systems. As will be demonstrated in forthcoming work, this near-ab initio-accurate NNP can be applied to understand complex phenomena involving interface-driven processes and properties in Cu-W composites.

cond-mat.mtrl-sci↗

arXiv2023

Linear complexions directly modify dislocation motion in face-centered cubic alloys

Linear complexions are defect phases that form in the presence of dislocations and thus are promising for the direct control of plasticity. In this study, atomistic simulations are used to model the effect of linear complexions on dislocation-based mechanisms for plasticity, demonstrating unique behaviors that differ from classical dislocation glide mechanisms. Linear complexions impart higher resistance to the initiation and continuation of dislocation motion when compared to solid solution strengthening in all of the face-centered cubic alloys investigated here, with the exact strengthening level determined by the linear complexion type. Stacking fault linear complexions impart the most pronounced strengthening effect, as the dislocation core is delocalized, and initiation of plastic flow requires a dislocation nucleation event. The nanoparticle and platelet array linear complexions impart strengthening by acting as pinning sites for the dislocations, where the dislocations unpin one at a time through bowing mechanisms. For the nanoparticle arrays, this event occurs even though the obstacles do not cross the slip plane and instead only interact through modification of the dislocation's stress field. The bowing modes observed in the current work appear similar to traditional Orowan bowing around classical precipitates but differ in a number of important ways depending on the complexion type. As a whole, this study demonstrates that linear complexions are a unique tool for microstructure engineering that can allow for the creation of alloys with new plastic deformation mechanisms and extreme strength.

cond-mat.mtrl-sci↗

arXiv2023

Machine learning of twin/matrix interfaces from local stress field

Twinning is an important deformation mode in plastically deformed hexagonal close-packed materials. The extremely high twin growth rates at the nanoscale make atomistic simulations an attractive method for investigating the role of individual twin/matrix interfaces such as twin boundaries and basal-prismatic interfaces in twin growth kinetics. Unfortunately, there is no single framework that allows researchers to differentiate such interfaces automatically, neither in experimental in-situ transmission electron microscopy analysis images nor in atomistic simulations. Moreover, the presence of alloying elements introduces substantial noise to local atomic environments, making it nearly impossible to identify which atoms belong to which interface. Here, with the help of advanced machine learning methods, we provide a proof-of-concept way of using the local stress field distribution as an indicator for the presence of interfaces and for determining their types. We apply such an analysis to the growth of twin embryos in Mg-10 at.% Al alloys under constant stress and constant strain conditions, corresponding to two extremes of high and low strain rates, respectively. We discover that the kinetics of such growth is driven by high-energy basal-prismatic interfaces, in line with our experimental observations for pure Mg.

cond-mat.mtrl-sci↗

arXiv2023

Atomistic simulations of the crystalline-to-amorphous transformation of gamma-Al2O3 nanoparticles: delicate interplay between lattice distortions, stresses, and space charges

The size-dependent phase stability of gamma-Al2O3 was studied by large-scale molecular dynamics simulations over a wide temperature range from 300 to 900 K. For the gamma-Al2O3 crystal, a bulk transformation to alpha-Al2O3 by an FCC-to-HCP transition of the O sublattice is still kinetically hindered at 900 K. However, local distortions of the FCC O-sublattice by the formation of quasi-octahedral Al local coordination spheres become thermally activated, as driven by the partial covalency of the Al-O bond. On the contrary, spherical gamma-Al2O3 NPs (with sizes of 6 and 10 nm) undergo a crystalline-to-amorphous transformation at 900 K, which starts at the reconstructed surface and propagates into the core through collective displacements of anions and cations, resulting in the formation of 7- and 8-fold local coordination spheres of Al. In parallel, the reconstructed Al-enriched surface is separated from the stoichiometric core by a diffuse Al-depleted transition region. This compositional heterogeneity creates a disbalance of charges inside the NP, which induces a net attractive Coulombic force that is strong enough to reverse the initial stress state in the NP core from compressive to tensile. These findings disclose the delicate interplay between lattice distortions, stresses, and space-charge regions in oxide nanosystems. A fundamental explanation for the reported expansion of metal-oxide NPs with decreasing size is provided, which has significant implications for e.g. heterogeneous catalysis, NP sintering, and additive manufacturing of NP-reinforced metal matrix composites.

cond-mat.mtrl-sci↗

arXiv2020

Interdependent linear complexion structure and dislocation mechanics in Fe-Ni

Using large-scale atomistic simulations, dislocation mechanics in the presence of linear complexions are investigated in an Fe-Ni alloy, where the complexions appear as nanoparticle arrays along edge dislocation lines. When mechanical shear stress is applied to drive dislocation motion, a strong pinning effect is observed where the defects are restricted by their own linear complexion structures. This pinning effect becomes weaker after the first dislocation break-away event, leading to a stress-strain curve with a profound initial yield point, similar to the static strain ageing behavior observed experimentally for Fe-Mn alloys with the same type of linear complexions. The existence of such a response can be explained by local diffusion-less and lattice distortive transformations corresponding to L10-to-B2 phase transitions within the linear complexion nanoparticles. As such, an interdependence between linear complexion structure and dislocation mechanics is found.

cond-mat.mtrl-sci↗

arXiv2020

Dislocation-induced Y segregation at basal-prismatic interfaces in Mg

Solute segregation at twin boundaries in Mg has been widely investigated, yet this phenomenon has not been studied at the equally important basal-prismatic interfaces. To fill this critical gap, this work investigates the segregation behavior of Y at basal-prismatic interfaces with various structures using atomistic simulations. The calculated interfacial energies show that short coherent interfaces and long semi-coherent interfaces containing disconnections and dislocations are more energetically stable than disordered interfaces, which is supported by our experimental observations. The segregation energy of Y at these lowest energy basal-prismatic interfaces shows a clear correlation with the atomic hydrostatic stress, highlighting the importance of local compressive stresses for segregation. In addition, sites around dislocations at the semi-coherent basal-prismatic interfaces demonstrate lower segregation energy, indicating that local defects such as interfacial dislocations can further enhance the segregation. In its entirety, this study indicates that the segregation of solutes can be affected by a number of different aspects of the local structure at complex interfaces in Mg alloys.

cond-mat.mtrl-sci↗

arXiv2020

Embracing the chaos: Alloying adds stochasticity to twin embryo growth

High-throughput atomistic simulations reveal the unique effect of solute atoms on twin variant selection in Mg-Al alloys. Twin embryos first undergo a stochastic incubation stage when embryos choose which twin variant to adopt, and then a deterministic growth stage when embryos expand without changing the selected twin variant. An increase in Al composition promotes the stochastic incubation behavior on the atomic level due to nucleation and pinning of interfacial disconnections. At compositions above a critical value, disconnection pinning results in multiple twin variant selection.

cond-mat.mtrl-sci↗

arXiv2020

Disconnection-mediated twin embryo growth in Mg

While deformation twinning in hexagonal close-packed metals has been widely studied due to its substantial impact on mechanical properties, an understanding of the detailed atomic processes associated with twin embryo growth is still lacking. Conducting molecular dynamics simulations on Mg, we show that the propagation of twinning disconnections emitted by basal-prismatic interfaces controls the twin boundary motion and is the rate-limiting mechanism during the initial growth of the twin embryo. The time needed for disconnection propagation is related to the distance between the twin tips, with widely spaced twin tips requiring more time for a unit twin boundary migration event to be completed. Thus, a phenomenological model, which unifies the two processes of disconnection and twin tip propagation, is proposed here to provide a quantitative analysis of twin embryo growth. The model fits the simulation data well, with two key parameters (twin tip velocity and twinning disconnection velocity) being extracted. In addition, a linear relationship between the ratio of twinning disconnection velocity to twin tip velocity and the applied shear stress is observed. Using an example of twin growth in a nanoscale single crystal from the recent literature, we find that our molecular dynamics simulations and analytical model are in good agreement with experimental data.

cond-mat.mtrl-sci↗

arXiv2019

Prediction of a wide variety of linear complexions in face centered cubic alloys

Linear complexions are defect states that have been recently discovered along dislocations in body centered cubic Fe-based alloys. In this work, we use atomistic simulations to extend this concept and explore segregation-driven structural transitions at dislocations in face centered cubic alloys. We identify a variety of stable, nanoscale-size structural and chemical states, which are confined near dislocations and can be classified as linear complexions. Depending on the alloy system and thermodynamic conditions, such new states can preserve, partially modify, or completely replace the original defects they were born at. By considering different temperatures and compositions, we construct linear complexion diagrams that are similar to bulk phase diagrams, defining the important conditions for complexion formation while also specifying an expected complexion size and type. Several notable new complexion types were predicted here: (1) nanoparticle arrays comprised of L12 phases in Ni-Fe, Ni-Al, and Al-Zr, (2) replacement of stacking faults with layered complexions comprised of (111) planes from the Cu5Zr intermetallic phase in Cu-Zr, (3) platelet arrays comprised of two-dimensional Guinier-Preston zones in Al-Cu, and finally (4) coexistence of multiple linear complexions containing both Guinier-Preston zones and L12 phases in ternary Al-Cu-Zr. All of these new complexion states are expected to alter material properties and affect the stability of the dislocations themselves, offering a unique opportunity for future materials design.

cond-mat.mtrl-sci↗

arXiv2019

Linear complexions: Metastable phase formation and coexistence at dislocations

The unique three-phase coexistence of metastable B2-FeNi with stable L10-FeNi and L12-FeNi3 is discovered near edge dislocations in body-centered cubic Fe-Ni alloys using atomistic simulations. Stable nanoscale precipitate arrays, formed along the compression side of dislocation lines and defined as linear complexions, were observed for a wide range of compositions and temperatures. By analyzing the thermodynamics associated with these phase transitions, we are able to explain the metastable phase formation and coexistence, in the process defining new research avenues for theoretical and experimental investigations.

cond-mat.mtrl-sci↗

arXiv2018

Dislocation-assisted linear complexion formation driven by segregation

Atomistic simulations are used to study linear complexion formation at dislocations in a body-centered cubic Fe-Ni alloy. Driven by Ni segregation, precipitation of the metastable B2-FeNi and stable L10-FeNi phases occurs along the compression side of edge dislocations. If the Ni segregation is not intense enough to ensure precipitate growth and coalescence along the dislocation lines, linear complexions in the form of stable nanoscale precipitate arrays are observed. Critical conditions such as global composition and temperature are defined for both linear complexion formation and dislocation-assisted precipitation.

cond-mat.mtrl-sci↗

arXiv2018

Grain boundary complexions and the strength of nanocrystalline metals: Dislocation emission and propagation

Grain boundary complexions have been observed to affect the mechanical behavior of nanocrystalline metals, improving both strength and ductility. While an explanation for the improved ductility exists, the observed effect on strength remains unexplained. In this work, we use atomistic simulations to explore the influence of ordered and disordered complexions on two deformation mechanisms which are essential for nanocrystalline plasticity, namely dislocation emission and propagation. Both ordered and disordered grain boundary complexions in Cu-Zr are characterized by excess free volume and promote dislocation emission by reducing the critical emission stress. Alternatively, these complexions are characterized by strong dislocation pinning regions that increase the flow stress required for dislocation propagation. Such pinning regions are caused by ledges and solute atoms at the grain-complexion interfaces and may be dependent on the complexion state as well as the atomic size mismatch between the matrix and solute elements. The trends observed in our simulations of dislocation propagation align with the available experimental data, suggesting that dislocation propagation is the rate-limiting mechanism behind plasticity in nanocrystalline Cu-Zr alloys.

cond-mat.mtrl-sci↗