arXiv subjects

Stefano Curtarolo

Publications and source records attributed to Stefano Curtarolo.

At least 19 recordsLinked to original sources

arXiv2026

Grain-Boundary Premelting in High-Entropy Transition Metal Carbides

Grain-boundary segregation and thermally induced interfacial disordering were investigated in four high-entropy transition metal carbides using Monte Carlo (MC) sampling and molecular dynamics (MD) with the universal MACE-OMAT-0 machine-learning interatomic potential. MC sampling segregated the group-VI element (Cr, Mo, or W) and Zr to grain boundaries, where the group-VI content reached approximately 45 at.%, consistent with STEM-EDS observations. During MD heating, the grain-boundary Lindemann index, a normalized measure of interatomic distance fluctuations, reached the liquid-like threshold of $\delta=0.15$ near $1390^{\circ}\mathrm{C}$ for the Cr-containing carbides, $1660^{\circ}\mathrm{C}$ for Mo, and $1890^{\circ}\mathrm{C}$ for W, while the grain interiors remained below the threshold. A chemically random (Cr,Hf,Ta,Ti,Zr)C reference crossed about $60^{\circ}\mathrm{C}$ later and showed less boundary-localized disorder, highlighting the role of interfacial chemistry in premelting. Species-resolved displacements showed enhanced grain-boundary mobility, particularly for carbon. Overall, Cr-rich interfaces showed the earliest and most extensive premelting-like response, followed by Mo- and W-containing boundaries.

cond-mat.mtrl-sci↗

arXiv2026

AFLOW-EMERALD: ElectroMagnetic modes EngineeRing in Advanced LayereD materials

Layered and periodically patterned heterostructures underpin advanced optical, photonic, and plasmonic (meta)materials, whose rational design demands electromagnetic solvers that are both numerically robust and tightly linked to the underlying material properties. Here, we present AFLOW-EMERALD (ElectroMagnetic modes EngineeRing in Advanced LayereD materials), an open-source, modular, Python-based computational framework for simulating electromagnetic wave propagation in finite and periodic layered (meta)materials. Built around a unified object-oriented architecture, AFLOW-EMERALD combines a numerically stable scattering-matrix method with plane-wave expansion and extends to rigorous coupled-wave analysis for laterally patterned structures such as gratings. The software computes optical spectra, spatial field distributions, and photonic band structures, including complex-k dispersion in lossy, dispersive media. A streamlined YAML workflow allows users to seamlessly import dielectric function datasets from experimental, literature, or first-principles sources. Owing to its modular design, AFLOW-EMERALD is readily extensible and suitable for integration into computational materials-design pipelines, providing a practical platform for the coupled material-geometry engineering of dielectric photonic crystals, plasmonic multilayers, hyperbolic metamaterials, and more complex architectures supporting, e.g., surface and volume plasmon-polariton modes.

physics.optics↗

arXiv2026

The AFLOW Library of Crystallographic Prototypes: Part 5

The AFLOW library of crystallographic prototypes has been updated to incorporate an additional 344 entries, which now reaches 2,127 prototypes. ICSD and CCDC numbers have been added to the website alongside improvements to the user interface. New tutorials covering the basics of crystallography in the context of materials science have also been added. Lastly, we covered the current known applications of AFLOW prototype labels and materials data across research software.

cond-mat.mtrl-sci↗

arXiv2026

Grain Growth Kinetics in (Cr,Mo,Ta,V,W)C1-{\delta} High-Entropy Carbide Ceramics

Understanding grain-boundary mobility during spark plasma sintering can enable microstructure control in high-entropy carbides, yet quantitative grain-growth kinetics remain scarce. In this work, grain growth kinetics and densification behavior were investigated for single-phase fully dense (Cr,Mo,Ta,V,W)C1-{\delta} high-entropy carbide ceramics. Specimens were densified by spark plasma sintering for a constant dwell time of 10 min at temperatures between 1750 {\deg}C and 1950 {\deg}C to isolate the role of temperature on microstructural evolution. Increasing sintering temperature produced grain growth and increased lattice parameter, while maintaining a single-phase rock salt structure. Elemental mapping showed a progressive reduction of Ta segregation with increasing sintering temperature, suggesting enhanced chemical homogenization at elevated temperatures. Grain growth kinetics were analyzed using a normal grain growth model with an assumed growth exponent of n=3, physically reasonable for grain-boundary-controlled growth influenced by solute and vacancy pinning. Arrhenius analysis of the growth factor yielded an apparent activation energy of approximately 620 kJ mol-1, comparable to diffusion-controlled processes in refractory transition-metal carbides. Densification curves revealed rapid consolidation prior to reaching the peak temperature followed by temperature-dominated grain coarsening. These results establish quantitative relationships between densification temperature, grain growth, and diffusion kinetics in a carbide system, providing insight into the microstructural stability of high-entropy, ultra-high-temperature carbide ceramics.

cond-mat.mtrl-sci↗

arXiv2026

Disorder viscosity correction approach to calculate spinodal temperature and wavelength

Spinodal decomposition, a key mechanism to microstructure formation in materials, has long posed challenges for predictive modeling, due to the need for parameter-free approaches that accurately capture local energy landscapes. In this work, we propose an approach to predict spinodal behavior by introducing a disorder viscosity correction to bulk free energies computed from finite, small, representative cells. We approximate the energy penalty required to transition into a disordered state to enable the stabilization of locally concave bulk free energy regions - essential for interface formation - while suppressing long-range concentration fluctuations. This approximation circumvents the complexity of full ab initio parameterization of interfacial properties and is well-suited for high-throughput and machine-learning frameworks. Our approach captures the necessary physics underpinning spinodal kinetics, offering a scalable route to predict spinodal regions in compositionally complex and high-entropy materials.

cond-mat.mtrl-sci↗

arXiv2026

Terahertz volume plasmon-polariton modulation in all-dielectric hyperbolic metamaterials

The development of plasmonics and related applications in the terahertz range faces limitations due to the intrinsic high electron density of standard metals. All-dielectric systems are profitable alternatives, which allows for customized modulation of the optical response upon doping. Here we focus on plasmon-based hyperbolic metamaterials realized stacking doped III-V semiconductors that have been shown to be optically active in the terahertz spectral region. By using a multi-physics multi-scale theoretical approach, we unravel the role of doping and geometrical characteristics (e.g., thickness, composition, grating) in the modulation of high-k plasmon-polariton modes across the metamaterial.

physics.optics↗

arXiv2025

A Software Package for Generating Robust and Accurate Potentials using the Moment Tensor Potential Framework

We present the Plan for Robust and Accurate Potentials (PRAPs), a software package for training and using moment tensor potentials (MTPs) in concert with the Machine Learned Interatomic Potentials (MLIP) software package. PRAPs provides an automated workflow to train MTPs using active learning procedures, and a variety of utilities to ease and improve workflows when utilizing the MLIP software. PRAPs was originally developed in the context of crystal structure prediction, in which one calculates convex hulls and predicts low energy metastable and thermodynamically stable structures, but the potentials PRAPs develops are not limited to such applications. PRAPs produces two potentials, one capable of rough estimates of the energies, forces and stresses of almost any chemical structure in the specified compositional space -- the Robust Potential -- and a second potential intended to provide more accurate descriptions of ground state and metastable structures -- the Accurate Potential. We also present a Python library, mliputils, designed to assist users in working with the chemical structural files used by the MLIP package.

physics.chem-ph↗

arXiv2025

Composition/structure directed search for new chalcogenide compounds

This work presents a simple scheme for finding new crystalline compounds by adapting structure types from neighbor atoms compounds. The approach is demonstrated for the selenide and sulfide families of binary compounds. It predicts ten new compounds that are not currently included in the inorganic crystal structure database (ICSD). The compounds primarily originated from a small search domain that includes near neighbors. Comparison with extended searches that include structures from binary systems of more remote atoms in the periodic table demonstrate the relative efficiency of near neighbor screening. This points at the possibility of using similar directed searches as a heuristic rule for efficiently finding new stable compounds in additional compound families.

cond-mat.mtrl-sci↗

arXiv2025

Variable-Temperature Plasmonic High-Entropy Carbides

Effective thermal management at variable and extreme temperatures face limitations for the development of novel energy and aerospace applications. Plasmonic approaches, shown to be capable of tailoring black-body emission, could be effective if materials with high-temperature and tunable plasmonic-resonance were available. Here, we report a synergy between experimental and theoretical results proving that many high-entropy transition-metal carbides, consisting of four or more metals at equal molar ratio, have plasmonic resonance at room, high (>1000C) and variable temperatures. We also found that these high-entropy carbides can be tuned and show considerable plasmonic thermal cycling stability. This paradigm-shift approach could prove quite advantageous as it facilitates the accelerated rational discovery and manufacturability of optically highly-optimized high-entropy carbides with ad-hoc properties.

cond-mat.mtrl-sci↗

arXiv2025

AFLOW4: heading toward disorder

AFLOW4 is the latest iteration of the AFLOW toolkit, specifically tailored to study high-entropy disordered materials. This upgrade includes innovative features like the Soliquidy module, based on the Euclidean transport cost between disordered and ordered material states. AFLOW4 can calculate dielectric functions to understand optical and electronic properties of disordered ceramics. The newly introduced human-readable data export feature ensures the uncomplicated incorporation of AFLOW4 in diverse automated workflows. Features relevant to high-entropy research, like prototype identification, partial occupation method, convex hull calculation, and enthalpy corrections based on local atomic environments, have been improved and exhibit substantial speed-up. Together, these enhancements represent a step forward for AFLOW as a valuable tool for research of high-entropy materials.

cond-mat.mtrl-sci↗

arXiv2025

Computational Study of Density Fluctuation-Induced Shear Bands Formation in Bulk Metallic Glasses

Seemingly identical Bulk Metallic Glasses (BMG) often exhibit strikingly different mechanical properties despite having the same composition and fictive temperature. A postulated mechanism underlying these differences is the presence of "defects". Here we investigate this hypothesis through the study of the effect of density fluctuations on shear band formation under an applied stress. We find that the critical shear stress is strongly dependent on the magnitude and size of the fluctuations. This finding also elucidates why, historically, critical shear stresses obtained in simulations have differed so much from those found experimentally, as typical simulations setups might favor unrealistically uniform geometries.

cond-mat.dis-nn↗

arXiv2025

Soliquidy: a descriptor for atomic geometrical confusion

Tailoring material properties often requires understanding the solidification process. Herein, we introduce the geometric descriptor Soliquidy, which numerically captures the Euclidean transport cost between the translationally disordered versus ordered states of a materials. As a testbed, we apply Soliquidy to the classification of glass-forming metal alloys. By extending and combining an experimental library of metallic thin-films (glass/no-glass) with the aflow.org computational database (geometrical and energetic information of mixtures) we found that the combination of Soliquity and formation enthalpies generates an effective classifier for glass formation. Such classifier is then used to tackle a public dataset of metallic glasses showing that the glass-agnostic assumptions of Soliquity can be useful for understanding kinetically-controlled phase transitions.

cond-mat.mtrl-sci↗

arXiv2024

Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange

The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the upcoming v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development.

cond-mat.mtrl-sci↗

arXiv2024

Materials Design for Hypersonics

Hypersonic vehicles must withstand extreme conditions during flights that exceed five times the speed of sound. These systems have the potential to facilitate rapid access to space, bolster defense capabilities, and create a new paradigm for transcontinental earth-to-earth travel. However, extreme aerothermal environments create significant challenges for vehicle materials and structures. This work addresses the critical need to develop resilient refractory alloys, composites, and ceramics. We will highlight key design principles for critical vehicle areas such as primary structures, thermal protection, and propulsion systems; the role of theory and computation; and strategies for advancing laboratory-scale materials to flight-ready components.

cond-mat.mtrl-sci↗

arXiv2024

The AFLOW Library of Crystallographic Prototypes: Part 4

The AFLOW Library of Crystallographic Prototypes has been updated to include an additional 683 entries, which now reaches 1,783 prototypes. We have also made some changes to the presentation of the entries, including a more consistent definition of the AFLOW-prototype label and a better explanation of our choice of space group when the experimental data is ambiguous. A method is presented for users to submit new prototypes for the Encyclopedia. We also include a complete index linking to all the prototypes currently in the Library.

cond-mat.mtrl-sci↗

arXiv2024

Machine Learned Interatomic Potentials for Ternary Carbides trained on the AFLOW Database

Large density functional theory (DFT) databases are a treasure trove of energies, forces and stresses that can be used to train machine learned interatomic potentials for atomistic modeling. Herein, we employ structural relaxations from the AFLOW database to train moment tensor potentials (MTPs) for four carbide systems: HfTaC, HfZrC, MoWC and TaTiC. The resulting MTPs are used to relax ~6300 random symmetric structures, and are subsequently improved via active learning to generate robust potentials (RP) that can relax a wide variety of structures, and accurate potentials (AP) designed for the relaxation of low-energy systems. This protocol is shown to yield convex hulls that are indistinguishable from those predicted by AFLOW for the HfTaC, HfZrC and TaTiC systems, and in the case of the MoWC system to predict thermodynamically stable structures that are not found within AFLOW, highlighting the potential of the employed protocol within crystal structure prediction. Relaxation of over three hundred Mo$_{1-x}$W$_x$C stoichiometry crystals first with the RP then with the AP yields formation enthalpies that are in excellent agreement with those obtained via DFT.

cond-mat.mtrl-sci↗

arXiv2023

Magnetic Transparent Conductors for Spintronic Applications

Transparent Conductors (TCs) exhibit optical transparency and electron conductivity, and are essential for many opto-electronic and photo-voltaic devices. The most common TCs are electron-doped oxides, which have few limitations when transition metals are used as dopants. Non-oxides TCs have the potential of extending the class of materials to the magnetic realm, bypass technological bottlenecks, and bring TCs to the field of spintronics. Here we propose new functional materials that combine transparency and conductivity with magnetic spin polarization that can be used for spintronic applications, such as spin filters. By using high-throughput first-principles techniques, we identified a large number of potential TCs, including non-oxides materials. Our results indicate that proper doping with transition metals introduces a finite magnetization that can provide spin filtering up to 90% in the electrical conductivity, still maintaining a transparency greater than 90%.

cond-mat.mtrl-sci↗

arXiv2023

A priori procedure to establish spinodal decomposition in alloys

Spinodal decomposition can improve a number of essential properties in materials, especially hardness. Yet, the theoretical prediction of the onset of this phenomenon (e.g., temperature) and its microstructure (e.g., wavelength) often requires input parameters coming from costly and time-consuming experimental efforts, hindering rational materials optimization. Here, we present a procedure where such parameters are not derived from experiments. First, we calculate the spinodal temperature by modeling nucleation in the solid solution while approaching the spinode boundary. Then, we compute the spinodal wavelength self-consistently using a few reasonable approximations. Our results show remarkable agreement with experiments and, for NiRh, the calculated yield strength due to spinodal microstructures surpasses even those of Ni-based superalloys. We believe that this procedure will accelerate the exploration of the complex materials experiencing spinodal decomposition, critical for their macroscopic properties.

cond-mat.mtrl-sci↗