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Results for “configurational disorder”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Resolving Configurational Disorder for Impurities in a Low-Entropy Phase

Hematite (α-Fe 2 O 3 ) exerts a strong control over the transport of minor but critical metals in the environment and is used in multiple industrial applications; the photocatalysis community has explored the properties of hematite nanoparticles over a wide range of transition metal dopants. Nonetheless, simplistic assumptions are used to rationalize the local coordination environment of impurities in hematite. Here, we use ab initio molecular dynamics (AIMD)-guided structural analysis to model the extended X-ray absorption fine structure (EXAFS) of Cu 2+ - and Zn 2+ -doped hematite nanoparticles. Specific defect–impurity associations were identified, and the local coordination environments of Cu and Zn both displayed considerable configurational disorder that, in aggregate, approached Jahn–Teller-like distortion for Cu but, in contrast, maintained hematite-like symmetry for Zn. This study highlights the role of defects in accommodating impurities in a nominally low-entropy phase and the limits to traditional shell-by-shell fitting of EXAFS for dopants/impurities in unprecedented bonding environments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Probing configurational disorder in ZnGeN 2 using cluster-based Monte Carlo

ZnGeN 2 is sought as a semiconductor with comparable lattice constant to GaN and tunable band gap for integration in optoelectronic devices. Configurational disorder on the cation sublattice of ZnGeN 2 can strongly modify the electronic structure compared to the ordered material, and both ordered and disordered forms of ZnGeN 2 are candidates for light-emitting diodes and other emitters. The nonisovalent character of the disordered species (Zn 2+ and Ge 4+ ) subjects the cation ordering to strong short-range order effects. To model these effects, we use Monte Carlo (MC) simulations utilizing a cluster expansion to approximate formation enthalpy. Representative disordered configurations in 1024-atom supercells are relaxed in density functional theory calculations. From the MC structures, we extract a short-range order parameter (the N-cation coordination motif), and two long-range order parameters (Bragg-Williams and stretching parameters), and examine their correlations. We perform a thermodynamic integration to determine the mixing entropy and free energy. ZnGeN 2 exhibits a first-order phase transition with pronounced discontinuities in enthalpy and entropy, as well as in the structural order parameters. We discuss the relationship between the effective temperature used in the MC simulation and the growth temperatures in experiment in relation to the crossover from the nonequilibrium to the equilibrium growth regime. This work expands on current models of site disorder in ZnGeN 2 and provides atomic structure models with a systematic variation of the degree of cation disorder.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Towards accurate prediction of configurational disorder properties in materials using graph neural networks

Abstract The prediction of configurational disorder properties, such as configurational entropy and order-disorder phase transition temperature, of compound materials relies on efficient and accurate evaluations of configurational energies. Previous cluster expansion methods are not applicable to configurationally-complex material systems, including those with atomic distortions and long-range orders. In this work, we propose to leverage the versatile expressive capabilities of graph neural networks (GNNs) for efficient evaluations of configurational energies and present a workflow combining attention-based GNNs and Monte Carlo simulations to calculate the disorder properties. Using the dataset of face-centered tetragonal gold copper without and with local atomic distortions as an example, we demonstrate that the proposed data-driven framework enables the prediction of phase transition temperatures close to experimental values. We also elucidate that the variance of the energy deviations among configurations controls the prediction accuracy of disorder properties and can be used as the target loss function when training and selecting the GNN models. The work serves as a fundamental step toward a data-driven paradigm for the accelerated design of configurationally-complex functional material systems.

Chemistry↗
DOE OSTI2021

Cation-size mismatch as a predictive descriptor for structural distortion, configurational disorder, and valence-band splitting in II-IV-N2 semiconductors

The II-IV-N2 class of heterovalent ternary nitrides has gained significant interest as alternatives to the III-nitrides for electronic and optoelectronic applications. In this study, we apply first-principles calculations based on density functional theory to systematically investigate the effects of structural distortions due to cation size mismatch on the configurational disorder of the cation sublattice and the valence band structure in this class of materials. We find that larger size mismatch between the group-II and the group-IV cations results in stronger lattice distortions from the ideal hexagonal ratio, which in turn inhibits the propensity of these materials toward octet-rule violating cation disorder. We also demonstrate that the formation energy of a single cation antisite pair, which is fast and simple to calculate, is a strong indicator of a material's propensity toward disorder. Furthermore, the breaking of in-plane symmetry leads to a splitting of the top three valence bands at Γ, which is also directly related to the magnitude of structural distortions. Our work demonstrates that the structural and functional properties of the II-IV-N2 materials can be finely tuned through controllable structural distortions that stem from the choice of cations.

Kute, Malhar (ORCID:0000000214364564)↗
DOE OSTI2021

Deep potential generation scheme and simulation protocol for the Li 10 GeP 2 S 12 -type superionic conductors

We report solid-state electrolyte materials with superior lithium ionic conductivities are vital to the next-generation Li-ion batteries. Molecular dynamics could provide atomic scale information to understand the diffusion process of Li-ion in these superionic conductor materials. Here, we implement the deep potential generator to set up an efficient protocol to automatically generate interatomic potentials for Li 10 GeP 2 S 12 -type solid-state electrolyte materials (Li 10 GeP 2 S 12 , Li 10 SiP 2 S 12 , and Li 10 SnP 2 S 12 ). The reliability and accuracy of the fast interatomic potentials are validated. With the potentials, we extend the simulation of the diffusion process to a wide temperature range (300 K–1000 K) and systems with large size (~1000 atoms). Important technical aspects such as the statistical error and size effect are carefully investigated, and benchmark tests including the effect of density functional, thermal expansion, and configurational disorder are performed. The computed data that consider these factors agree well with the experimental results, and we find that the three structures show different behaviors with respect to configurational disorder. Our work paves the way for further research on computation screening of solid-state electrolyte materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

High Entropy Oxide Relaxor Ferroelectrics

Relaxor ferroelectrics are important in technological applications due to strong electromechanical response, energy storage capacity, electrocaloric effect, and pyroelectric energy conversion properties. Current efforts to discover and design materials in this class generally rely on substitutional doping as slight changes to local compositional order can significantly affect the Curie temperature, morphotropic phase boundary, and electromechanical responses. In this work, we demonstrate that moving to the strong limit of compositional complexity in an ABO 3 perovskite allows stabilization of relaxor responses that do not rely on a single narrow phase transition region. Entropy-assisted synthesis approaches are utilized to synthesize single-crystal Ba(Ti 0.2 Sn 0.2 Zr 0.2 Hf 0.2 Nb 0.2 )O 3 [Ba(5B)O] films. The high levels of configurational disorder present in this system are found to influence dielectric relaxation, phase transitions, nanopolar domain formation, and Curie temperature. Temperature-dependent dielectric, Raman spectroscopy, and second-harmonic generation measurements reveal multiple phase transitions, a high Curie temperature of 570 K, and the relaxor ferroelectric nature of Ba(5B)O films. The first-principles theory calculations are used to predict possible combinations of cations to design relaxor ferroelectrics and quantify the relative feasibility of synthesizing these highly disordered single-phase perovskite systems. Further, the ability to stabilize single-phase perovskites with various cations on the B-sites offers possibilities for designing high-performance relaxor ferroelectric materials for piezoelectric, pyroelectric, and electrocaloric applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Ice-rule driven vertex frustration in a stretched pentagonal spin ice

We introduce the stretched pentagonal spin ice and study low-energy configurations achieved after thermal annealing. Using synchrotron-based photoemission electron microscopy, we reveal highly disordered configurations dominated by short-range order. Real-space observations reveal that an adherence to local order, in the form of a strict ice-rule obedience, acts as a main factor in enforcing vertex frustration and hindering long-range order. Our results open up pathways to create forms of frustrated systems that have seemed elusive thus far. Published by the American Physical Society 2024

Crater, Davis (ORCID:0009000168933822)↗
DOE OSTI2023

Active Learning Framework

Machine learning (ML) of interatomic potentials show great promise to accelerate scientific simulation, e.g., by emulating expensive computations at a high accuracy but much reduced computational cost. Training datasets are calculated from computationally expensive ab initio quantum mechanics methods, density functional theory (DFT). Trained on this data, an ML model can be very successful in predicting energy and forces for new atomic configurations. A critical factor is the quality and diversity of the training dataset. Thus, a highly automated approach to dataset construction based on active learning framework is designed suitable for material physics. The active learning scheme begins with fully randomized atomic configurations. Then, many Molecular Dynamics (MD) trajectories are simulated using current ML potentials, where each MD trajectory is initialized to a random disordered configuration. The temperature is varied in order to diversify the sampled configuration during these simulations. The variance of predictions for eight neural networks within an ensemble is analyzed to determine whether the model is operating as expected. This helps in determining whether collecting more data would be helpful to the model by checking the ensemble variance is greater than the threshold. In this case, the MD trajectory is terminated and the final atomic configuration is placed on a queue (SQL database) for DFT calculations and added to training dataset. Periodically, ML model is retrained to the updated training model. This Active Learning loop is iterated until the cost of MD simulations becomes prohibitively expensive. The MD simulations will hopefully be sufficiently robust to support nucleation after many active learning iterations. In this sense, active learning scheme must automatically discover the important low energy and nonequilibrium physics.

Nebgen, Benjamin↗
DOE OSTI2024

Engineering phonon transport through cation disorder in dimensionally constricted high entropy MXene

Designing materials with low thermal conductivity is a crucial objective for applications in thermal insulation and thermoelectrics. Traditional methods such as doping, mechanical strain and introducing defects in perfect crystals have been widely explored to impede the flow of heat. Here, this work introduces dimensional constriction and cationic disorder as novel avenues to manipulate lattice thermal conductivity (LTC). High entropy materials characterized by random distribution of multiple elements, creates a suitable environment for thermal insulation due to its configurational disorder and local lattice distortions. On the other hand, MXenes, derived from MAX-phase, have garnered considerable attention due to their unique structural attributes, leading to potential applications in catalysis and energy storage. Ti 2 AlC MAX-phase is examined to understand the impact of dimensional constriction on phonon transport of Ti 2 C with cationic disorder, i.e., (Ti 0.25 Nb 0.25 Cr 0.25 Ta 0.25 ) 2 C. The exponential reduction in LTC of HE-MXene is attributed to disorder scattering that significantly limits phonon mean free path (MFP) and relaxation time. The spread of mode-resolved LTC with MFP highlights the influence of disorder on phonon scattering. This work provides a systematic approach to engineer LTC through dimensional constriction and cationic disorder, laying the foundation for tailored materials with desired thermal properties.

2D materials↗
DOE OSTI2024

Disorder Enhanced Thermalization in Interacting Many-Particle System

We introduce an extension of the non-equilibrium dynamical mean field theory to incorporate the effects of static random disorder in the dynamics of a many-particle system by integrating out different disorder configurations resulting in an effective time-dependent density-density interaction. We use this method to study the non-equilibrium transient dynamics of a system described by the Fermi Anderson-Hubbard model following an interaction and disorder quench. The method recovers the solution of the disorder-free case for which the system exhibits qualitatively distinct dynamical behaviors in the weak-coupling (prethermalization) and strong-coupling regimes (collapse-and-revival oscillations). However, we find that weak random disorder promotes thermalization. In the weak coupling regime, the jump in the quasiparticle weight in the prethermal regime is suppressed by random disorder while in the strong-coupling regime, random disorder reduces the amplitude of the quasiparticle weight oscillations. These results highlight the importance of disorder in the dynamics of realistic many-particle systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

The search for high-entropy fuel-cell catalysts using disorder descriptors

The transition to a hydrogen economy depends on efficient, affordable catalysts for fuel cells. Platinum—the industry standard for fuel-cell electrodes—is costly and scarce, highlighting the need for practical alternatives. High-entropy alloys offer vast compositional diversity and tunable properties that can mitigate these issues, yet their chemical complexity and configurational disorder have hindered rational discovery. Here, we introduce a data-driven framework that couples machine learning with first-principles disorder descriptors—including the entropy forming ability, disordered enthalpy-entropy descriptor, and electronic-structure similarity metrics to platinum—to predict alloy synthesizability and catalytic performance. These descriptors are applied for the first time in the context of fuel-cell catalyst discovery. The workflow rapidly screens more than 20 000 compositions and identifies several platinum-free candidates that are economically viable, readily scalable, and exhibit promising predicted activity. These results demonstrate that disorder descriptors are reliably predicted by machine learning models and can be effectively integrated into materials-discovery pipelines, accelerating innovation across complex compositional spaces.

fuel-cell catalysts↗
DOE OSTI2026

Long-range magnetic order and relaxor ferroelectricity in a hexagonal high-entropy ferrite

Multiferroics that combine ferroelectricity and magnetic order are attractive for electronic and spintronic technologies, yet chemical disorder that promotes relaxor ferroelectricity usually suppresses long-range magnetic order. Here, we report entropy-stabilized relaxor multiferroicity in epitaxial hexagonal (Tb0.2Dy0.2Ho0.2Lu0.2Yb0.2)FeO3 thin films. Structural, magnetic, dielectric, and synchrotron spectroscopic measurements show the coexistence of relaxor ferroelectricity and long-range ferromagnetic order. We find that improper ferroelectricity remains robust against A-site configurational disorder, while the Fe sublattice preserves magnetic exchange. This separation of the microscopic origins of the polar and magnetic responses enables chemically disordered multiferroicity. Our results establish entropy engineering in hexagonal ferrites as a route toward multifunctional oxide thin films and provide a general design strategy for high-entropy multiferroics.

Miertschin, Duncan [Baylor University]↗
DOE OSTI2021

Multisublattice cluster expansion study of short-range ordering in iron-substituted strontium titanate

Owing to the challenges in obtaining realistic atomic configurations in large chemical phase spaces, it is not straightforward to describe structure–property relations in materials exhibiting configurational disorder. One example is iron-substituted strontium titanate (SrTi 1–x Fe x O 3–d , STF), a promising perovskite-derivative cathode material in solid oxide fuel cells that exhibits full solid solubility 0 ≤ x ≤ 1 and a tendency to exhibit short-range order. Here we demonstrate a multisublattice cluster expansion (CE) framework and apply it to STF across the full composition range. The CE approach is distinct from more traditional CE formulations in that clusters are defined explicitly by the chemical species distributed among multiple sublattices, rather than via cluster functions of occupation variables with decoration. The modified CE approach makes it easy to distinguish meaningful chemical interactions that are harder to extract from conventional CE, since for the latter chemical identity in a cluster is expressed as a product of site occupations. The least absolute shrinkage and selection operator (LASSO) is implemented as a regression analysis tool to select key clusters and avoid overfitting. We demonstrate this formulation on STF, and show that it can accurately predict configurational energies in comparison to conventional CE. From the key clusters, we identify that short-range ordering between substitutional Fe and oxygen vacancies (V O ) results in the formation of Fe–VO strings. In addition, we consider the stability of STF through CE-based Monte Carlo (MC) simulations and confirm the presence of superstructures that were previously observed in transmission electron microscopy. In this work, analysis of atomic configurations from MC samples reveals variations in the oxidation state of Fe atoms, which can be explained by the ordering tendency of Fe and V O . The cluster description and selection formalism described here may be applied to other disordered multisublattice systems for accurate and efficient material modeling.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Significance of the structural configuration of B2 disorder in Co and Ti based Heusler alloys

We investigate here structural (at local and global levels) and transport properties for 𝑋 2 ⁢MnAl (𝑋= Co and Ti). Additionally, the magnetic properties were also studied for Ti 2 ⁢MnAl. Our x-ray diffraction results show that both the compounds stabilize in B2 disordered phase with cubic structure of 𝑃⁢𝑚⁢$\overline{3}$⁢𝑚 space group. Further, the structural configuration of the above disordered phase for both the compounds was identified using combined studies of x-ray absorption spectroscopy and multiple scattering calculations at the transition metal 𝐾 edges. Upon such identification, in the case of Co 2 ⁢Mn 1−𝑦⁢ Cr 𝑦 ⁢Al (𝑦= 0, 0.05, 0.1, 0.2) with change in 𝑦, we are able to establish a better connection quantitatively between the inverse of Mn-Co bonds and peak in the temperature-dependent resistivity. This highlights the crucial importance of a detailed understanding of the nature of B2 disorder. In the case of 𝑦=0, in the temperature range of study, the resistivity is driven by the functional form associated with (a) three-dimensional enhanced electron-electron Coulomb interaction scattering mechanism and (b) an unconventional one-magnon process. For Ti 2 ⁢MnAl, the transport shows metallic glasslike behavior at high temperature, while at low temperature it follows both the Cote-Meisel's model and quantum correction model. In this compound, the magnetic studies suggest the formation of superparamagnetic clusters in the paramagnetic matrix at low temperatures. Our density functional theory results are in line with the transport and magnetic properties. In literature, the spin polarization percentage (𝑃) for 𝑋= Co in B2 disordered phase is 76%. However, the present results emphasize the fact that in B2 disordered phase, the value of 𝑃 can range from 90% to 71% depending on the structural configuration introduced by swapping of the atomic positions of Mn and Al. For the compound under study, the value of percentage spin polarization obtained ranges between 82% to 85%. In addition, we also identify the origin of the difference in the shape of the Mn 3⁢𝑑 density of states for both the alloys. In conclusion, our results for 𝑋= Co alloy highlights the importance of identifying the specific structural configuration associated with a particular disorder category especially in the estimation of 𝑇 𝑐 and 𝑃 and for 𝑋= Ti, the physical properties can be tuned by varying the position of 𝐸 𝐹 and thereby its utilization in device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Structural and Optical Properties of High Entropy (La,Lu,Y,Gd,Ce)AlO 3 Perovskite Thin Films

Mixtures of Ce-doped rare-earth aluminum perovskites are drawing a significant amount of attention as potential scintillating devices. However, the synthesis of complex perovskite systems leads to many challenges. Designing the A-site cations with an equiatomic ratio allows for the stabilization of a single-crystal phase driven by an entropic regime. This work describes the synthesis of a highly epitaxial thin film of configurationally disordered rare-earth aluminum perovskite oxide (La 0.2 Lu 0.2 Y 0.2 Gd 0.2 Ce 0.2 )AlO 3 and characterizes the structural and optical properties. The thin films exhibit three equivalent epitaxial domains having an orthorhombic structure resulting from monoclinic distortion of the perovskite cubic cell. An excitation of 286.5 nm from Gd 3+ and energy transfer to Ce 3+ with 405 nm emission are observed, which represents the potential for high-energy conversion. These experimental results also offer the pathway to tunable optical properties of high-entropy rare-earth epitaxial perovskite films for a range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

How arsenic makes amorphous GeSe a robust chalcogenide glass for advanced memory integration

The 3D integration technology in semiconductor fabrication requires a key component, the ovonic threshold switching (OTS) selector, to suppress the current leakage. The As doped amorphous (a-) GeSe glass is a commercialized OTS material in 3D phase-change memory, but the understanding of such a doping mechanism is still inadequate. Here we systematically explore the effect of As doping on the structural, bonding, and dynamics properties of a-GeAsSe using ab initio molecular dynamics simulations. The results reveal that As atoms form strong bonds with both Ge and Se atoms. The distorted octahedral structures and the 5-fold rings linked by atoms are increased. All of these structural features lead to a more disordered configuration. Moreover, as atoms have notably slowed down the atomic mobility, rendering a-GeAsSe a high stability. Overall, our studies offer insightful understanding of As-doping in OTS materials, paving the way for the design and application of advanced selector devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Quasi-Ordered Mn-Rich Cathode with Highly Reversible Oxygen Anion Redox Chemistry

Anionic oxygen redox chemistry in Li-rich Mn-based layer oxide cathodes represents a transformative approach for boosting the energy density of next-generation lithium-ion batteries. However, conventional oxygen redox reactions often induce oxygen dimerization at high voltages, leading to irreversible lattice oxygen loss and a rapid voltage fade. Herein, we achieve highly reversible oxygen redox chemistry through a new quasi-ordered structural design that incorporates both intra- and interlayer cation disorder configurations. This unique structure significantly enhances lattice oxygen stability, effectively stabilizes oxidized oxygen, and inhibits the formation of peroxo- or superoxol-like species, thereby enabling anionic redox reactions to proceed reversibly even at deep delithiation states. The quasi-ordered design mitigates irreversible phase transitions and preserves the structural integrity throughout extended cycling. Consequently, the proposed cathode demonstrates exceptional cyclability with negligible capacity and voltage fade, retaining 99% capacity and 98% average voltage after long-term cycling. Finally this work provides fresh insights into addressing issues related to lattice oxygen instabilities and reforming strategies for developing long-life, high-energy-density anionic redox cathode materials for advanced batteries.

chemical structure↗
DOE OSTI2025

Entropy-Driven Structural Evolution in Ceramic Oxides

High-entropy ceramics, with five or more elements randomly occupying the same cation crystallographic sites, offer vast compositional diversity and unique properties for material design and applications. However, for many dissimilar elements, entropic stabilization cannot overcome the enthalpic barrier to cation substitution. As a result, most high-entropy ceramics incorporate only a few similar elements, limiting the in-depth exploration of the effect of entropy on ceramic properties. Here, we first use density functional theory to model fluorite crystal structures composed of 1-10 elements and then experimentally present practical fluorite oxide nanostructures containing 1, 3, 8, and 15 metals, as well as a record-breaking 25-element high-entropy ceramic incorporating a diverse palette of rare-earth, transition, alkaline, p-block, and noble metals. As entropy increases, structural and configurational disorder in the solid solution rises, altering structural features such as lattice distortion, crystallinity, homogeneity, defect density, and thermal stability. This research provides new insights and understanding of the role of entropy in stabilizing compositionally complex ceramics.

Liu, Shuo↗