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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Model Parameter Development for Complex Materials: Species-Specific Diffusion Barriers in 316 Stainless Steel from Systematic DFT Calculations

Vacancy-mediated diffusion barriers in 316 stainless steel have been systematically calculated using density functional theory to provide essential parameters for mesoscale microstructure evolution models. A statistical sampling approach employing 210 nudged elastic band calculations across multiple special quasi-random structures captures the effects of local chemical environments in this concentrated alloy. The computational methodology addresses challenges specific to chemically disordered systems, including proper magnetic treatment throughout multi-step calculations and validation against experimental structural properties. The calculated activation barriers reveal clear species-dependent diffusion behavior with the hierarchy Ni >> Fe ˜ Cr >> Mo. Nickel exhibits the highest barriers (0.74–1.31 eV, mean 1.045 eV), confirming its role as the slowest-diffusing major component. Iron and chromium show similar moderate barriers averaging 0.587 eV and 0.522 eV, respectively. Remarkably, molybdenum demonstrates exceptionally low barriers (0.12–0.28 eV, mean 0.194 eV), suggesting much higher mobility than previously recognized and potentially significant implications for precipitation kinetics and microstructure evolution. The barrier ranges remain consistent across different 316 SS compositions, supporting parameter transferability for modeling applications. The overall mean barrier of 0.64 eV provides a practical approximation for phase field simulations, while species-specific values enable detailed treatments of diffusion-controlled processes. This systematic approach establishes a validated framework for generating diffusion parameters in other concentrated alloys where experimental data are limited, while providing the first systematic set of species-specific barriers for predictive modeling of 316 stainless steel microstructure evolution.

36 MATERIALS SCIENCE↗
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 OSTI2021

Neural network-based order parameter for phase transitions and its applications in high-entropy alloys

Phase transition is one of the most important phenomena in nature and plays a central role in materials design. All phase transitions are characterized by suitable order parameters, including the order–disorder phase transition. However, finding a representative order parameter for complex systems is non-trivial, such as for high-entropy alloys. Given the strength of dimensionality reduction of a variational autoencoder (VAE), we introduce a VAE-based order parameter. Here, we propose that the Manhattan distance in the VAE latent space can serve as a generic order parameter for order–disorder phase transitions. The physical properties of our order parameter are quantitatively interpreted and demonstrated by multiple refractory high-entropy alloys. Using this order parameter, a generally applicable alloy design concept is proposed by mimicking the natural mixing process of elements. Our physically interpretable VAE-based order parameter provides a computational technique for understanding chemical ordering in alloys, which can facilitate the development of rational alloy design strategies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Magnetic structure and properties of the compositionally complex perovskite (Y 0.2 La 0.2 Pr 0.2 Nd 0.2 Tb 0.2 )MnO 3

Large configurational disorder in compositionally complex ceramics can lead to unique functional properties that deviate from traditional rules of alloy mixing. In recent years, compositionally complex oxides (CCOs) have shown intriguing magnetic behavior including long-range order, enhanced magnetic exchange couplings, and mixed phase magnetic structures. This work focuses on how large local spin disorder affects magnetic ordering in a CCO. Specifically, we investigated the A-site alloyed perovskite, (Y 0.2 La 0.2 Pr 0.2 Nd 0.2 Tb 0.2 )MnO 3 , or (5A)MnO 3 , using a combination of bulk magnetometry, synchrotron X-ray diffraction, and temperature-dependent neutron diffraction. The five A-site ions have an average spin and ionic radius nearly equal to that of Nd 3+ ions, which minimizes structural distortions and allows for an understanding of the local spin disorder effects through a direct comparison with NdMnO 3 . Our magnetometry data show that (5A)MnO 3 exhibits two distinct phase transitions associated with the A-site and B-site sublattices, as seen in NdMnO 3 , as well as the presence of domain pinning and exchange bias at low temperature, suggesting a mixed phase magnetic ground state, as seen in other magnetic CCOs. Neutron powder diffraction shows clear long-range antiferromagnetic ordering below 67 K and refines to a Pn'ma' magnetic structure at low temperature, in excellent agreement with the well-studied behavior of NdMnO 3 . The two most notable differences in (5A)MnO 3 magnetism apparent from our data are a slight suppression of the B-site ordering temperature, which is explained by a smaller Mn–O–Mn bond angle in (5A)MnO 3 than NdMnO 3 , and the presence of a magnetic susceptibility transition above the B-site ordering, which could indicate the formation of a cluster glass but requires further study. Finally, this work demonstrates a general method of isolated investigation of size and spin disorder in CCOs and motivates future work using local structure probes to better understand the effects of nanoscale clustering and local spin disorder in magnetic CCOs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Structural and chemical disorder enhance point defect diffusion and atomic transport in Ni 3 Al-based γ' phase

The ordered L1 2 γ' Ni 3 Al intermetallic inclusions are routinely used as strengthening constituents in Ni-based superalloys and recent high-entropy alloys. As there are different metallic elements relative to the alloy matrix, the composition of γ' phase inclusions usually suffers some variations. In this work, we studied the elemental partition and its influence on atomic transport properties in a model (NiCo) 3 Al γ' phase with chemical and structural disorder. Combining the Monte Carlo and molecular static techniques, we first determined the elemental distribution in such compositionally-complexed γ' phase. The results suggest that Co tends to segregate, which profoundly influences defect energetics and diffusion properties. By modeling thermally activated diffusion by molecular dynamics, we found that chemical disorder induced by Co can enhance vacancy diffusion while significantly suppress diffusion via interstitial atom migration, as compared to the stoichiometric γ' Ni 3 Al. We further reveal that these observations are closely related to the defect energetics in these systems. Furthermore, our results explain the effects of disorder, long- and short-range orders on the diffusion properties in multicomponent intermetallic alloys, which helps to understand the stability and, thus, γ'-phase-assisted strengthening at different conditions including annealing and irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Disordered hyperuniform solid state materials

Disordered hyperuniform (DHU) states are recently discovered exotic states of condensed matter. DHU systems are similar to liquids or glasses in that they are statistically isotropic and lack conventional long-range translational and orientational order. On the other hand, they completely suppress normalized infinite-wavelength density fluctuations like crystals and, in this sense, possess a hidden long-range correlation. Very recently, there have been several exciting discoveries of disordered hyperuniformity in solid-state materials, including amorphous carbon nanotubes, amorphous 2D silica, amorphous graphene, defected transition metal dichalcogenides, defected pentagonal 2D materials, and medium/high-entropy alloys. It has been found that the DHU states of these materials often possess a significantly lower energy than other disorder models and can lead to unique electronic and thermal transport properties, which results from mechanisms distinct from those identified for their crystalline counterparts. For example, DHU states can enhance electronic transport in 2D amorphous silica; DHU medium/high-entropy alloys realize the Vegard's law and possess enhanced electronic bandgaps and thermal transport at low temperatures. These unique properties open up many promising potential device applications in optoelectronics and thermoelectrics. Here, we provide a focused review on these important new developments of hyperuniformity in solid-state materials, taking an applied and “materials” perspective, which complements the existing reviews on hyperuniformity in physical systems and photonic materials. As a result, future directions and outlook are also provided, with a focus on the design and discovery of DHU quantum materials for quantum information science and engineering.

2D materials↗
DOE OSTI2020

Effects of Solidification Cooling Rates on Microstructures and Physical Properties of Fe-6.5%Si Alloys

Compared to the widely used Fe-3.2wt%Si steel, Fe-6.5wt%Si has superior electric and magnetic properties, including higher electrical resistivity, lower iron loss, higher permeability, and near zero magnetostriction. However, Fe-6.5wt%Si sheet is difficult to produce using traditional manufacturing processes as the high silicon content favors the formation of ordered phases that embrittle the material. Fortunately, these ordered phases can be suppressed if the alloy is cooled fast enough from a high temperature kinetically trapping the disordered solid solution or amorphous state. Planar flow casting is known for its rapid solidification rate. In order to consider it as a viable method to manufacture ductile Fe-6.5wt%Si sheets, the effect of cooling rate on physical properties of Fe-6.5wt%Si alloy are systematically investigated. In this work, various cooling rates are achieved by changing melt-spin wheel speeds, which significantly affect the solidification temperature profile and have profound effects on ordering, microstructures, textures, hardness, and magnetic properties. High cooling rates result in refined grains, reduced ordering, enhanced <100> out of the plane texture, decreased hardness, and increased coercivity. This study demonstrates a critical cooling rate at ~1.7 × 10 5 K/s, corresponding to a tangential wheel speed of 5-7 m/s, below which the hardness significantly increases in agreement with the sudden increase of the ordered phases that causes the material embrittlement.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Complex concentrated alloys and chemical short-range ordering

Abstract Complex concentrated alloys (CCAs) are materials comprising three or more elements in similar proportions and possessing structural but no chemical long-range order. Fascination with CCAs has grown over the last 20 years and to date, CCAs have opened a new materials design paradigm and horizon for discovery of materials to meet the demands of applications in aggressive environments. Understanding the fundamental mechanisms controlling their response, however, is challenging due to the chemical and structural variations that wildly fluctuate over fine atomic and nanoscales. This issue focuses on the experimental, computational, and theoretical investigations that aim to uncover phenomena and processes determining the structure, kinetics, mechanics, or deformation mechanisms in CCAs at the atomic scale. At the atomic scale at which they operate, chemical short-range ordering can be influential. This issue further addresses the capabilities, as well as the debatable need, to characterize, predict, and relate short-range ordering to material performance. Collectively, the articles in this issue highlight the insights, understanding, and experimental and computational tools that attempt to create property-tunable CCAs “from the atom up” by treating short-range ordering and engineering atomic-scale mechanisms. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2020

Effect of synthesis temperature on the phase formation of NiTiAlFeCr compositionally complex alloy thin films

Here, the synthesis temperature dependent phase formation of Ni 10 Ti 10 Al 25 Fe 35 Cr 20 thin films is compared to a bulk processed sample of identical composition. The as-cast alloy exhibits a dual-phase microstructure which is composed of a disordered BCC phase and AlNiTi-based B2- and/or L2 1 -ordered phase(s). Formation of the BCC phase as well as an ordered AlNi-based B2 phase is observed for a thin film synthesised at 500 °C (ratio of synthesis temperature of thin film to melting temperature of bulk alloy: T/T m = 0.49), which is attributed to both surface and bulk diffusion mediated growth. Post deposition annealing at 900 °C (T/T m = 0.75) of a thin film deposited without intentional heating results in the formation of NiAlTi-based B2 and/or L2 1 -phase(s) similar to the bulk sample, which is attributed to bulk diffusion. Depositions conducted at room temperature without intentional substrate heating (T/T m = 0.20) resulted in the formation of an X-ray amorphous phase, while a substrate temperature increase to 175 °C (T/T m = 0.28) causes the formation of a BCC phase. Atom probe tomography of the thin films deposited without intentional substrate heating and at 175 °C indicates the formation of ~5 nm and ~10 nm FeAl-rich domains, respectively. This can be rationalized based on the activation energy for surface diffusion, as Ti and Ni exhibt 2.5 to 4 times larger activation energy barriers than Al, Fe and Cr. It is evident from the homologous temperature that the phase formation observed at 500 °C (T/T m = 0.49) is a result of both surface and bulk diffusion. As the temperature is reduced, the formation of FeAl-rich domains can be understood based on the differences in activation energy for surface diffusion and is consistent with kinetically limited thin film growth.

36 MATERIALS SCIENCE↗
DOE OSTI2021

High-throughput design of high-performance lightweight high-entropy alloys

Developing affordable and light high-temperature materials alternative to Ni-base superalloys has significantly increased the efforts in designing advanced ferritic superalloys. However, currently developed ferritic superalloys still exhibit low high-temperature strengths, which limits their usage. Here we use a CALPHAD-based high-throughput computational method to design light, strong, and low-cost high-entropy alloys for elevated-temperature applications. Through the high-throughput screening, precipitation-strengthened lightweight high-entropy alloys are discovered from thousands of initial compositions, which exhibit enhanced strengths compared to other counterparts at room and elevated temperatures. The experimental and theoretical understanding of both successful and failed cases in their strengthening mechanisms and order-disorder transitions further improves the accuracy of the thermodynamic database of the discovered alloy system. This study shows that integrating high-throughput screening, multiscale modeling, and experimental validation proves to be efficient and useful in accelerating the discovery of advanced precipitation-strengthened structural materials tuned by the high-entropy alloy concept.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Larger than uncorrelated vacancy diffusion contributions in chemically disordered crystalline materials

Arising from a variational approach to compute diffusion coefficients, we introduce “superkinetic kinosons”, which are contributions to the diffusion flux of mobile defects and atomic species by single jump mechanisms that can exceed their uncorrelated values. In vacancy-mediated diffusion in crystalline random and high entropy materials, these contributions primarily arise from intermittent jumps of slow moving atoms that remove the vacancy out of correlation traps and enable a quantification of such effects on the diffusion coefficients. They can be significant contributors to diffusion, even when faster moving atoms have infinite percolation networks. Furthermore, their existence and importance provide fundamental insights about underlying aspects of vacancy diffusion such as formation of localized correlation traps and deviation of vacancy diffusion from percolation behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nonmonotonic crossover in electronic phase separated manganite superlattices driven by the superlattice period

Studying manganite superlattices [(LCMO) 2n / (PCMO) n ] t made of La 0.625 Ca 0.375 MnO 3 (LCMO) and Pr 0.625 Ca 0.375 MnO 3 (PCMO), we found an unexpected behavior varying the period n. At small n, the ensemble is a three-dimensional ferromagnetic metal due to interfacial charge transfer. At large n , the LCMO layers dominate transport. However, rather than a smooth interpolation between these limits a sharp transport and magnetic anomaly is found at an intermediate critical PCMO thickness n*. Magnetic force microscopy reveals that the phase-separation length scale also maximizes at n* where, unexpectedly, it becomes comparable to that of the (La 1-y Pr y ) 0.625 Ca 0.375 MnO 3 (LPCMO) alloy. Finally, we conjecture the phenomenon originates in a disorder-related length scale: Large charge-ordered clusters as in LPCMO can only nucleate when Pr-rich regions reach a critical size related to n*.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Defect control in the Heisenberg-Kitaev candidate material NaRuO 2

The combination of geometric frustration, extended hopping, spin-orbit coupling, and a disordered magnetic ground state make NaRuO 2 an attractive Heisenberg-Kitaev candidate material. Historically, NaRuO 2 has been a challenging material to produce, even in polycrystalline form. Here we present synthetic efforts that identify a propensity for Na Ru defects to form in NaRuO 2 , revealing a full solid-solution between NaRuO 2 and disordered Na 2 RuO 3 . We report the synthesis of alloys along the Na 3+x Ru 3–x O 6 solid solution and characterize changes in the bulk magnetization and electron transport as a function of Na loading. Furthermore, our results highlight the importance of stoichiometry control in NaRuO 2 when investigating and interpreting this material’s physical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Perfect short-range ordered alloy with line-compound-like properties in the ZnSnN 2 :ZnO system

We present a new solid-state material phase which is a disordered solid solution but offers many ordered line-compound features. The emergent physical phenomena are rooted in the perfect short-range order which conserves the local octet rule. We model the dual-sublattice-mixed semiconductor alloy (ZnSnN 2 ) 1-x (ZnO) 2x using first-principles calculations, Monte-Carlo simulations with a model Hamiltonian, and an extension of the regular solution model by incorporating short-range order. We demonstrate that this unique solid solution, occurring at a “magic” composition, can provide an electronically pristine character without disorder-induced charge localization and, therefore, a superior carrier transport similar to ordered phases. Interestingly, this phase shows singularities that are absent in the conventional solid-solution models, such as the regular solution and band-gap bowing model. Thermodynamically, this alloy phase has a sharply reduced enthalpy at its composition (like a line compound), but it still requires the entropy from long-range disorder to be stabilized at experimentally accessible temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Utilizing Site Disorder in the Development of New Energy-Relevant Semiconductors

We report controlling site disorder in ternary and multinary compounds enables tuning optical and electronic properties at fixed lattice constants and stoichiometries, moving beyond many of the challenges facing binary alloy systems. Here, we consider possible enhancements to energy-related applications through the integration of disorder-tunable materials in devices such as light-emitting diodes, photonics, photovoltaics, photocatalytic materials, batteries, and thermoelectrics. However, challenges remain in controlling and characterizing disorder. Focusing primarily on II–IV–V 2 materials, we identify three metrics for experimentally characterizing cation site disorder. Complementary to these experiments, we discuss simulation methods to understand disordered materials. Nonidealities, such as off-stoichiometry and oxygen incorporation, can occur while synthesizing metastable disordered materials. While nonidealities may seem undesirable, we describe how if harnessed they could provide another knob for tuning disorder and subsequently properties. To illustrate the effects of disorder on device-relevant properties, we provide case examples of disordered materials and their potential in device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tuning the spin dynamics and magnetic phase transitions of the Cantor alloy via composition and sample processing protocols: A muon spin relaxation study

CrMnFeCoNi, also called the Cantor alloy, is a well-known high-entropy alloy whose magnetic properties have recently become a focus of attention. Here, we present a detailed muon spin relaxation study of the influence of chemical composition and sample processing protocols on the magnetic phase transitions and spin dynamics of several different Cantor alloy samples. Specific samples studied include a pristine equiatomic sample, samples with deficient and excess Mn content, and equiatomic samples magnetized in a field of 9 T or plastically deformed in pressures up to 0.5 GPa. The results confirm the sensitive dependence of the transition temperature on composition and demonstrate that post-synthesis pressure treatments cause the transition to become significantly less homogeneous throughout the sample volume. In addition, we observe critical spin dynamics in the vicinity of the transition in all samples, reminiscent of canonical spin glasses and magnetic materials with ideal continuous phase transitions. Application of an external magnetic field suppresses the critical dynamics in the Mn-deficient sample, while the equiatomic and Mn-rich samples show more robust critical dynamics. The spin-flip thermal activation energy in the paramagnetic phase increases with Mn content, ranging from 3.1⁢(3) × 10 -21 J for 0% Mn to 1.2⁢(2) × 10 -20 J for 30% Mn content. These results shed light on critical magnetic behavior in environments of extreme chemical disorder and demonstrate the tunability of spin dynamics in the Cantor alloy via chemical composition and sample processing.

36 MATERIALS SCIENCE↗
NASA NTRS1989

The effect of composition and cooling rate on the structure of rapidly solidified (Fe, Ni)3Al-C alloy

The quench rate-metastable structure dependence in the Fe-20Ni-8Al-2C wt pct alloy has been experimentally studied. The nonequilibrium gamma-prime and gamma phases were noted in foils 65-100 microns thick, while at higher quench rates (thinner samples) the matrix was found to be in a disordered fcc gamma phase with kappa carbide precipitates. With the addition of silicon to the alloys, the nonequilibrium gamma-prime and gamma structures are observed at higher cooling rates.

Myers, S. A.↗
DOE OSTI2025

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials

Atomic disorder can strongly influence material properties such as charge transport, optical response, and catalytic activity. However, efficiently modeling these disorder effects remains challenging for first-principles methods due to the cost of sampling large configurational spaces and computing complex physical quantities. Recent advances of machine learning techniques, particularly graph neural networks (GNNs), has enabled the efficient and accurate predictions of complex material properties, offering promising tools for studying disordered systems. In this work, we present a general machine-learning-assisted computational framework that integrates equivariant GNNs with Monte Carlo simulations to compute the thermodynamic and ensemble-averaged functional properties of disordered materials. Using the surface-termination-disordered MXene monolayer Ti 3 C 2 T 2–x as a representative system, we find that electrical conductivity exhibits an emergent peak near the order–disorder phase transition temperature due to the interplay between electron scattering and doping. In contrast, optical conductivity remains largely insensitive to local atomic disorder and reflects the global surface chemical composition. These results highlight the role of atomic disorder in affecting material properties and demonstrate the potential of our approach for statistically modeling disorder effects in a wide range of materials such as high-entropy alloys and spin liquids.

MXene↗