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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Toward the design of ultrahigh-entropy alloys via mining six million texts

Abstract It has long been a norm that researchers extract knowledge from literature to design materials. However, the avalanche of publications makes the norm challenging to follow. Text mining (TM) is efficient in extracting information from corpora. Still, it cannot discover materials not present in the corpora, hindering its broader applications in exploring novel materials, such as high-entropy alloys (HEAs). Here we introduce a concept of “context similarity" for selecting chemical elements for HEAs, based on TM models that analyze the abstracts of 6.4 million papers. The method captures the similarity of chemical elements in the context used by scientists. It overcomes the limitations of TM and identifies the Cantor and Senkov HEAs. We demonstrate its screening capability for six- and seven-component lightweight HEAs by finding nearly 500 promising alloys out of 2.6 million candidates. The method thus brings an approach to the development of ultrahigh-entropy alloys and multicomponent materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Rejuvenation as the origin of planar defects in the CrCoNi medium entropy alloy

Abstract High or medium- entropy alloys (HEAs/MEAs) are multi-principal element alloys with equal atomic elemental composition, some of which have shown record-breaking mechanical performance. However, the link between short-range order (SRO) and the exceptional mechanical properties of these alloys has remained elusive. The local destruction of SRO by dislocation glide has been predicted to lead to a rejuvenated state with increased entropy and free energy, creating softer zones within the matrix and planar fault boundaries that enhance the ductility, but this has not been verified. Here, we integrate in situ nanomechanical testing with energy-filtered four-dimensional scanning transmission electron microscopy (4D-STEM) and directly observe the rejuvenation during cyclic mechanical loading in single crystal CrCoNi at room temperature. Surprisingly, stacking faults (SFs) and twin boundaries (TBs) are reversible in initial cycles but become irreversible after a thousand cycles, indicating SF energy reduction and rejuvenation. Molecular dynamics (MD) simulation further reveals that the local breakdown of SRO in the MEA triggers these SF reversibility changes. As a result, the deformation features in HEAs/MEAs remain planar and highly localized to the rejuvenated planes, leading to the superior damage tolerance characteristic in this class of alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High-entropy electrolytes for practical lithium metal batteries

Electrolyte engineering is crucial for improving battery performance, particularly for lithium metal batteries. Recent advances in electrolytes have greatly improved cyclability by enhancing electrochemical stability at the electrode interfaces, but concurrently achieving high ionic conductivity has remained challenging. Here we report an electrolyte design strategy for enhanced lithium metal batteries by increasing the molecular diversity in electrolytes, which essentially leads to high entropy electrolytes (HEEs). We find that in weakly solvating electrolytes, the entropy effect reduces ion clustering while preserving the characteristic anion-rich solvation structures, which is characterized by synchrotron-based X-ray scattering and molecular dynamics simulations. Electrolytes with smaller- sized clusters exhibit a 2-fold improvement in ionic conductivity compared to conventional weakly- solvating electrolytes, enabling stable cycling at high current densities up to 2C (6.2 mA cm -2 ) in anode- free LiNi 0.6 Mn 0.2 Co 0.2 (NMC622)||Cu pouch cells. In conclusion, the efficacy of the design strategy is verified by performance improvements in three disparate weakly solvating electrolyte systems.

25 ENERGY STORAGE↗
DOE OSTI2021

Bifunctional nanoprecipitates strengthen and ductilize a medium-entropy alloy

Single-phase high- and medium-entropy alloys with face-centred cubic (fcc) structure can exhibit high tensile ductility and excellent toughness, but their room-temperature strengths are low. Dislocation obstacles such as grain boundaries, twin boundaries, solute atoms and precipitates can increase strength. However, with few exceptions, such obstacles tend to decrease ductility. Interestingly, precipitates can also hinder phase transformations. Here, using a model, precipitate-strengthened, Fe–Ni–Al–Ti medium-entropy alloy, we demonstrate a strategy that combines these dual functions in a single alloy. The nanoprecipitates in our alloy, in addition to providing conventional strengthening of the matrix, also modulate its transformation from fcc-austenite to body-centred cubic (bcc) martensite, constraining it to remain as metastable fcc after quenching through the transformation temperature. During subsequent tensile testing, the matrix progressively transforms to bcc-martensite, enabling substantial increases in strength, work hardening and ductility. This use of nanoprecipitates exploits synergies between precipitation strengthening and transformation-induced plasticity, resulting in simultaneous enhancement of tensile strength and uniform elongation. Further, our findings demonstrate how synergistic deformation mechanisms can be deliberately activated, exactly when needed, by altering precipitate characteristics (such as size, spacing, and so on), along with the chemical driving force for phase transformation, to optimize strength and ductility.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Functional composites by programming entropy-driven nanosheet growth

Here, nanomaterials must be systematically designed to be technologically viable. Driven by optimizing intermolecular interactions, current designs are too rigid to plug in new chemical functionalities and cannot mitigate condition differences during integration. Despite extensive optimization of building blocks and treatments, accessing nanostructures with the required feature sizes and chemistries is difficult. Programming their growth across the nano-to-macro hierarchy also remains challenging, if not impossible. To address these limitations, we should shift to entropy-driven assemblies to gain design flexibility, as seen in high-entropy alloys, and program nanomaterial growth to kinetically match target feature sizes to the mobility of the system during processing. In tis report, following a micro-then-nano growth sequence in ternary composite blends composed of block-copolymer-based supramolecules, small molecules and nanoparticles, we successfully fabricate high-performance barrier materials composed of more than 200 stacked nanosheets (125 nm sheet thickness) with a defect density less than 0.056 µm -2 and about 98% efficiency in controlling the defect type. Contrary to common perception, polymer-chain entanglements are advantageous to realize long-range order, accelerate the fabrication process (<30 min) and satisfy specific requirements to advance multilayered film technology. This study showcases the feasibility, necessity and unlimited opportunities to transform laboratory nanoscience into nanotechnology through systems engineering of self-assembly.

42 ENGINEERING↗
DOE OSTI2025

Superheating gold beyond the predicted entropy catastrophe threshold

In their landmark study, Fecht and Johnson unveiled a phenomenon that they termed the ‘entropy catastrophe’, a critical point where the entropy of superheated crystals equates to that of their liquid counterparts. This point marks the uppermost stability boundary for solids at temperatures typically around three times their melting point. Despite the theoretical prediction of this ultimate stability threshold, its practical exploration has been prevented by numerous intermediate destabilizing events, colloquially known as a hierarchy of catastrophes, which occur at far lower temperatures. Here we experimentally test this limit under ultrafast heating conditions, directly tracking the lattice temperature by using high-resolution inelastic X-ray scattering. Our gold samples are heated to temperatures over 14 times their melting point while retaining their crystalline structure, far surpassing the predicted threshold and suggesting a substantially higher or potentially no limit for superheating. We point to the inability of our samples to expand on these very short timescales as an important difference from previous estimates. These observations provide insights into the dynamics of melting under extreme conditions.

Laser-produced plasmas↗
DOE OSTI2025

Isothermal solidification for high-entropy alloy synthesis

Kinetically trapping the high-temperature states through rapid cooling solidification is widely used for the synthesis of high-entropy alloys (HEAs), especially those with intrinsically immiscible elemental combinations. However, strategies need to be developed to overcome the fundamental limitations of rapid cooling solidification in controlling the crystallinity, structure and morphology of HEAs. Here, in this study, we introduce an isothermal solidification strategy for the synthesis of HEAs by rapidly altering the metal alloy composition through liquid–liquid interface reactions at low temperatures, for example, from 25 °C to 80 °C. We use gallium (Ga)-based metal as the sacrificial reagent and mixing medium. By directing the reactions to the interfaces between the Ga-based liquid metal and an aqueous metal ion solution, the foreign metal ions can be reduced at the interfaces and incorporated into the liquid metal quickly. HEAs with various crystallinity (single crystal, mesocrystal, polycrystal and amorphous), morphology (zero, two and three dimensions) and compositions can be achieved through the isothermal solidification. Ga can be completely consumed, resulting in Ga-free HEAs. If desired, Ga can be one of the metal elements in the final products. In situ liquid phase transmission electron microscopy (TEM) studies and theoretical analysis show the isothermal solidification mechanisms. Our direct observations show the enhanced mixing of liquid metal elements and the solidification process with fluctuating nucleation dynamics. The isothermal solidification marks a powerful strategy for HEA synthesis through an unexplored pathway of kinetically trapping the high-entropy states.

Zhang, Qiubo [Lawrence Berkeley National Laborator↗
DOE OSTI2019

Influence of ordered L1 2 precipitation on strain-rate dependent mechanical behavior in a eutectic high entropy alloy

Recent studies indicate that eutectic high-entropy alloys can simultaneously possess high strength and high ductility, which have potential industrial applications. The present study focuses on Al 0.7 CoCrFeNi, a lamellar dual-phase ( fcc + B2) precipitation-strengthenable eutectic high entropy alloy. This alloy exhibits an fcc + B2 (B2 with bcc nano-precipitates) microstructure resulting in a combination of the soft and ductile fcc phase together with hard B2 phase. Low temperature annealing leads to the precipitation of ordered L1 2 intermetallic precipitates within the fcc resulting in enhanced strength. The strengthening contribution due to fine scale L1 2 is modeled using Orowan dislocation bowing and by-pass mechanism. The alloy was tested under quasi-static (strain-rate = 10 –3 s –1 ) tensile loading and dynamic (strain-rate = 10 3 s –1 ) compressive loading. Due to the fine lamellar microstructure with a large number of fcc - bcc interfaces, the alloy show relatively high flow-stresses, ~1400 MPa under quasi-static loading and in excess of 1800 MPa under dynamic loading. Interestingly, the coherent nano-scale L1 2 precipitate caused a significant rise in the yield strength, without affecting the strain rate sensitivity (SRS) significantly. These lamellar structures had higher work hardening due to their capability for easily storing higher dislocation densities. The back-stresses from the coherent L1 2 precipitate were insufficient to cause improvement in twin nucleation, owing to elevated twinning stress under quasi-static testing. However, under dynamic testing high density of twins were observed.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Element Effects on High-Entropy Alloy Vacancy and Heterogeneous Lattice Distortion Subjected to Quasi-equilibrium Heating

We applied Simmons–Balluffi methods, positron measurements, and neutron diffraction to estimate the vacancy of CoCrFeNi and CoCrFeMnNi high-entropy alloys (HEAs) using Cu as a benchmark. The corresponding formation enthalpies and associated entropies of the HEAs and Cu were calculated. The vacancy-dependent effective free volumes in both CoCrFeNi and CoCrFeMnNi alloys are greater than those in Cu, implying the easier formation of vacancies by lattice structure relaxation of HEAs at elevated temperatures. Spatially resolved synchrotron X-ray measurements revealed different characteristics of CoCrFeNi and CoCrFeMnNi HEAs subjected to quasi-equilibrium conditions at high temperatures. Element-dependent behavior revealed by X-ray fluorescence (XRF) mapping indicates the effect of Mn on the Cantor Alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Atomistic origin of the entropy of melting from inelastic neutron scattering and machine learned molecular dynamics

The latent heat, L, is central to melting, but its atomic origin remains elusive. It is proportional to the entropy of fusion, ΔS fus = L/T m (T m is the melting temperature), which depends on changes of atom configurations, atom vibrations, and thermal electron excitations. Here, we combine inelastic neutron scattering and machine-learned molecular dynamics to separate ΔS fus into these components for Ge, Si, Bi, Sn, Pb, and Li. When the vibrational entropy of melting, ΔS vib , is zero, ΔS fus ≃ 1.2 kB per atom. This result provides a baseline for ΔSconfig and nearly coincides with “Richard’s Rule” of melting. The ΔSfus deviates from this value for most elements, however, and we show that this deviation originates with extra ΔS vib and extra ΔS config . These two components are correlated for positive and negative deviations from Richard’s rule – the extra ΔS config is consistently ~ 80% of ΔS vib . Our results, interpreted with potential energy landscape theory, imply a correlation between the change in the number of basins and the change in the inverse of their curvature for the melting of pure elements.

36 MATERIALS SCIENCE↗
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 OSTI2020

Chemical short-range order in derivative Cr–Ta–Ti–V–W high entropy alloys from the first-principles thermodynamic study

The development of high-entropy alloys (HEAs) focuses on exploring compositional regions in multi-component systems with all alloy elements in equal or near-equal atomic concentrations. Initially it was based on the main idea that high mixing configurational entropy contributions to the alloy free energy could promote the formation of a single solid solution phase. By using the ab-initio based Cluster Expansion (CE) Hamiltonian model constructed for the quinary bcc Cr–Ta–Ti–V–W system in combination with Monte Carlo (MC) simulations, we show that the phase stability and chemical short-range order (SRO) of the equiatomic quinary and five sub-quaternary systems, as well as their derivative alloys, can dramatically change the order–disorder transition temperatures (ODTT) as a function of alloy compositions. In particular, it has been found, that the equiatomic quaternary Ta–Ti–V–W and Cr–Ta–Ti–W alloys had the lowest order–disorder transition temperature (500 K) among all the analysed equiatomic compositions. In all investigated alloy systems, the strongest chemical ordering has been observed between Cr and V, which led to the conclusion that decreasing the concentration of either Cr or V might be beneficial in terms of decreasing the ODTT. It also predicts that increasing concentration of Ti significantly decreases the ODTT. Our analysis of chemical SRO as a function of alloy composition allows to understand the microstructure evolution of HEAs as a function of temperature in excellent agreement with available experimental observations. Importantly, our free energy of mixing and SRO calculations predict that the origin of precipitates formed by Cr- and V-rich in the sub-quaternary Cr–Ta–V–W system is driven by the thermodynamics. The modelling results are in an excellent agreement with experimental observation of Cr and V segregation in the W 0.38 Ta 0.36 Cr 0.15 V 0.11 alloy which in turns shows an exceptional radiation resistance.

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

Variational approach to quantum state tomography based on maximal entropy formalism

Quantum state tomography is an integral part of quantum computation and offers the starting point for the validation of various quantum devices. One of the central tasks in the field of state tomography is to reconstruct, with high fidelity, the quantum states of a quantum system. From an experiment on a real quantum device, one can obtain the mean measurement values of different operators. With such data as input, in this report we employ the maximal entropy formalism to construct the least biased mixed quantum state that is consistent with the given set of expectation values. Even though, in principle, the reported formalism is quite general and should work for an arbitrary set of observables, in practice we shall demonstrate the efficacy of the algorithm on an informationally complete (IC) set of Hermitian operators. Such a set possesses the advantage of uniquely specifying a single quantum state from which the experimental measurements have been sampled and hence renders the rare opportunity not only to construct a least-biased quantum state but even replicate the exact state prepared experimentally within a preset tolerance. Here, the primary workhorse of the algorithm is reconstructing an energy function which we designate as the effective Hamiltonian of the system, and parameterizing it with Lagrange multipliers, according to the formalism of maximal entropy. These parameters are thereafter optimized variationally so that the reconstructed quantum state of the system converges to the true quantum state within an error threshold. To this end, we employ a parameterized quantum circuit and a hybrid quantum-classical variational algorithm to obtain such a target state, making our recipe easily implementable on a near-term quantum device.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Towards Pareto optimal high entropy hydrides via data-driven materials discovery

The ability to rapidly screen material performance in the vast space of high entropy alloys is of critical importance to efficiently identify optimal hydride candidates for various use cases. Given the prohibitive complexity of first principles simulations and large-scale sampling required to rigorously predict hydrogen equilibrium in these systems, we turn to compositional machine learning models as the most feasible approach to screen on the order of tens of thousands of candidate equimolar high entropy alloys (HEAs). Critically, we show that machine learning models can predict hydride thermodynamics and capacities with reasonable accuracy (e.g. a mean absolute error in desorption enthalpy prediction of ~5 kJ mol H 2 –1 ) and that explainability analyses capture the competing trade-offs that arise from feature interdependence. We can therefore elucidate the multi-dimensional Pareto optimal set of materials, i.e., where two or more competing objective properties can't be simultaneously improved by another material. This provides rapid and efficient down-selection of the highest priority candidates for more time-consuming density functional theory investigations and experimental validation. Various targets were selected from the predicted Pareto front (with saturation capacities approaching two hydrogen per metal and desorption enthalpy less than 60 kJ mol H 2 –1 ) and were experimentally synthesized, characterized, and tested amongst an international collaboration group to validate the proposed novel hydrides. Finally, additional top-predicted candidates are suggested to the community for future synthesis efforts, and we conclude with an outlook on improving the current approach for the next generation of computational HEA hydride discovery efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Computational insights into hydrogen adsorption energies on medium-entropy oxides

High entropy oxides (HEOs) have emerged as promising catalysts for several important chemical transformations including alkane activation. Hydrogen adsorption energy (HAE) has been used as a key descriptor for many reactions including methane C–H activation and hydrogen evolution reactions. Hence, understanding the relationship between HAEs and the surface chemistry of HEO surfaces could lay the foundation for meaningful correlations among methane C–H activation, HAE, and the complex, local environment of HEO surfaces. Here, we used a medium-entropy oxide as a prototypical system – Mg 0.25 Ni 0.25 Cu 0.25 Zn 0.25 O with a rock-salt structure – to interrogate these relationships. We sampled 2000 different surfaces of its (100) plane and calculated the HAEs at randomly chosen surface O sites using density functional theory (DFT). Our analysis of the 2000 data points reveals that the HAEs at the surface O sites are significantly influenced by the local environment around the adsorption sites, particularly the nature of the metal atom directly below the surface O site where H adsorbs. After comparing several popular graph-neural-network-based machine learning models, we found that the DimeNet++ model performed best achieving satisfactory accuracy in predicting HAEs for both Mg 0.25 Ni 0.25 Cu 0.25 Zn 0.25 O and slightly varied compositions. Our work underscores the promise of such models and the need for further refinement to address the complexity of HEOs.

Song, Haohong [Vanderbilt Univ., Nashville, TN (Un↗
DOE OSTI2025

Beyond the four core effects: revisiting thermoelectrics with a high-entropy design

Low-exergy waste heat, which constitutes the majority of industrial-scale thermal losses, remains largely unrecoverable with conventional technologies. Thermoelectrics offer a solid-state solution for converting this hard-to-access energy into electricity, making them attractive for decentralized power generation and sensor applications. High-entropy materials (HEMs) have gained traction as a strategy for better-performing thermoelectrics, but the mechanisms driving their benefits require further exploration. This article highlights key insights for heat and electronic transport in HEMs. For heat transport, we argue that reduced, and often ultralow, lattice thermal conductivity in HEMs—with respect to ordered counterparts—can be taken for granted, emerging naturally as a fifth core effect of high-entropy systems. While band convergence is often considered beneficial for electronic transport, its impact depends strongly on the electronic structure. We summarize the scenarios where it can be detrimental to thermoelectric performance. These insights motivate strategies that align seamlessly with advancements in artificial intelligence and data-driven approaches, helping accelerate the discovery of next-generation thermoelectric materials.

Oses, Corey [Johns Hopkins Univ., Baltimore, MD (U↗
DOE OSTI2020

The emergent field of high entropy oxides: Design, prospects, challenges, and opportunities for tailoring material properties

A new class of ceramics, called entropy stabilized oxides, High Entropy Oxides (HEOs), multicomponent oxides, compositionally complex oxides, or polycation oxides, has generated considerable research interest since the first report in 2015. This multicomponent approach has created new opportunities for materials design and discovery. This Perspective will highlight some current research developments and possible applications while also providing an overview of the many successfully synthesized HEO systems to date. The polycation approach to composition development will be discussed along with a few case studies, challenges, and future possibilities afforded by this novel class of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

An investigation of high entropy alloy conductivity using first-principles calculations

The Kubo–Greenwood equation, in combination with the first-principles Korringa–Kohn–Rostoker coherent potential approximation (KKR-CPA) can be used to calculate the DC residual resistivity of random alloys at T = 0 K. We implemented this method in a multiple scattering theory based ab initio package, MuST, and applied it to the ab initio study of the residual resistivity of the high entropy alloy Al x CoCrFeNi as a function of x. The calculated resistivities are compared with experimental data. We also predict the residual resistivity of refractory high entropy alloy MoNbTaV x W. Furthermore, the calculated resistivity trends are also explained using theoretical arguments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗