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At least 235 records · Page 13

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DOE OSTI2023

Mosaic Cu I −Cu II −In III 2D Perovskites: Pressure‐Dependence of the Intervalence Charge Transfer and a Mechanochemical Alloying Method

Abstract The perovskite (BA) 4 [Cu II (Cu I In III ) 0.5 ]Cl 8 ( 1 BA ; BA + =butylammonium) allows us to study the high‐pressure structural, optical, and transport properties of a mixed‐valence 2D perovskite. Compressing 1 BA reduces the onset energy of Cu I/II intervalence charge transfer from 1.2 eV at ambient pressure to 0.2 eV at 21 GPa. The electronic conductivity of 1 BA increases by 4 orders of magnitude upon compression to 20 GPa, when the activation energy for conduction decreases to 0.16 eV. In contrast, Cu II perovskites achieve similar conductivity at ≈50 GPa. The solution‐state synthesis of these perovskites is complicated, with more undesirable side products likely from the precursor mixtures containing three different metal ions. To circumvent this problem, we demonstrate an efficient mechanochemical synthesis to expand this family of halide perovskites with complex composition by simply pulverizing together powders of 2D Cu II single perovskites and Cu I In III double perovskites.

Li, Jiayi↗

DOE OSTI2021

Oxidation Behavior of Welded Fe-Based and Ni-Based Alloys in Supercritical CO 2

Next-generation supercritical CO 2 (sCO 2 ) power cycles will require different classes of alloy throughout the operational temperatures to optimize tradeoff of creep strength, oxidation performance and cost. This will necessitate joining methods such as welding, which might pose compatibility concerns at the joined interfaces. In this study, similar and dissimilar metal welds were generated from a variety of candidate alloys for sCO 2 systems including ferritic/martensitic steels, austenitic steels, and Ni-based superalloys. Samples were extracted from different regions of the welds and exposed to sCO 2 at 550 °C and 20 MPa for 2500 h, then characterized to understand their behavior in this environment. Unsurprisingly, the local oxidation behavior was largely dictated by the Cr content in the underlying metal. High-Cr austenitic steels and Ni alloys formed slow-growing Cr-rich oxide scales with minimal carburization of the underlying metal, while low-Cr ferritic/martensitic steels formed fast-growing Fe-rich oxide scales with significant carburization. Most welds did not show any unusual oxidation behavior at the interfaces, considering the local Cr content. The one exception was the 347H similar metal weld, where a larger grain size and complex grain structure in the fusion zone led to a significantly higher rate of Fe-rich oxide nodule formation compared to the base metal. This suggests that microstructural changes at joined interfaces can play an important role on the oxidation-limited lifetimes in future sCO 2 systems. The composition changes across the interfaces enabled study of the effect of Fe on the growth rate of Cr-rich oxides and of the origins of the sub-surface recrystallization zone that forms beneath them.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A Review of Medium-Mn, Low-Density Steels for Transportation Applications

Low-density steels constitute a broad and complex alloy space (Fe–Mn–Al–C) suitable for a variety of applications. In particular, there has been growing interest in duplex (ferrite + austenite) or multiphase (+ martensite, carbides) low-density steels as a lightweight, advanced high-strength steel (AHSS) for vehicle applications, spurred by extensive decarbonization efforts. Medium-Mn (med-Mn) (3 to 12 wt pct) steels with 3.5 to 10 wt pct Al additions have decreased densities, presenting an interesting opportunity for high-specific strength, intrusion-resistant, and energy-absorbing sheet components with reduced alloying contents compared to high-Mn grades like austenitic Fe–Mn–Al–C or twinning-induced plasticity steels. Compared to leaner med-Mn steels, the physical metallurgy of med-Mn, low-density steels (MMLS) is complex and distinguished by increased δ-ferrite fractions and austenite stacking fault energies, decreased martensite start temperatures, and modified phase transformation windows. Mechanical properties of MMLS are comparable to 3rd generation AHSS, attributable to the unique, multiphase microstructures, and the array of strengthening mechanisms that can be accessed. Despite this, challenges and unknowns remain with respect to their industrial implementation, and new processing routes may need to be developed. Here, this review aims to highlight the composition effects, processing methods, microstructural evolution, deformation behavior, and application properties geared toward manufacturing and performance, altogether assessing the potential of MMLS for transportation applications.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Mosaic Cu I –Cu II –In III 2D Perovskites: Pressure–Dependence of the Intervalence Charge Transfer and a Mechanochemical Alloying Method

The perovskite (BA) 4 [Cu II (Cu I In III ) 0.5 ]Cl 8 (1 BA ; BA + =butylammonium) allows us to study the high-pressure structural, optical, and transport properties of a mixed-valence 2D perovskite. Compressing 1 BA reduces the onset energy of Cu I/II intervalence charge transfer from 1.2 eV at ambient pressure to 0.2 eV at 21 GPa. The electronic conductivity of 1 BA increases by 4 orders of magnitude upon compression to 20 GPa, when the activation energy for conduction decreases to 0.16 eV. In contrast, Cu II perovskites achieve similar conductivity at ≈50 GPa. The solution-state synthesis of these perovskites is complicated, with more undesirable side products likely from the precursor mixtures containing three different metal ions. Finally, to circumvent this problem, we demonstrate an efficient mechanochemical synthesis to expand this family of halide perovskites with complex composition by simply pulverizing together powders of 2D Cu II single perovskites and Cu I In III double perovskites.

2D perovskite↗

DOE OSTI2022

Mapping structural heterogeneity at the nanoscale with scanning nano-structure electron microscopy (SNEM)

Here, in this work, we explore the use of scanning electron diffraction (also known as 4D-STEM) coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order (structure and chemistry) as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr 65 Cu 17.5 Ni 10 Al 7.5 bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modeled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don’t require energy filters on the instrument. We spatially map different quantities of interest (QoI’s), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI’s. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Aging heat treatment design for Haynes 282 made by wire-feed additive manufacturing using high-throughput experiments and interpretable machine learning

Wire-feed additive manufacturing (WFAM) produces superalloys with complex thermal cycles and unique microstructures, often requiring optimized heat treatments. To address this challenge, we present a hybrid approach that combines high-throughput experiments, precipitation simulation, and machine learning to design effective aging conditions for the WFAM Haynes 282 superalloy. Our results demonstrate that the γ’ radius is the critical microstructural feature for strengthening Haynes 282 during post-heat treatment compared with the matrix composition and γ’ volume fraction. New aging conditions at 770°C for 50 hours and 730°C for 200 hours were discovered based on the machine learning model and were applied to enhance yield strength, bringing it on par with the wrought counterpart. This approach has significant implications for future AM alloy production, enabling more efficient and effective heat treatment design to achieve desired properties.

CALPHAD↗

DOE OSTI2025

Overcoming time and complexity limitations in molecular dynamics investigations of equilibrium melting

Abstract A hybrid Monte-Carlo molecular-dynamics method for determining solidus and liquidus compositions in multicomponent systems is presented that overcomes both the time limitations in conventional molecular dynamics that prevent the evolution of distinct solid and liquid compositions via diffusion and the complexity challenge that prevents use of thermodynamic assessment in systems of many components. This hybrid method is validated in the Cu–Ni system against an independent assessment of solidus and liquidus compositions based on the regular solution model. Strategies for efficient mapping of different phase diagrams, based on the thermodynamic parameter T 0 , the temperature at which two phases of the composition X 0 have equal free energies, are presented and then demonstrated for the copper-nickel fully miscible system and the gold–silicon eutectic system. A calculation of the solidus and liquidus sampled during the equilibrium melting of equiatomic CrMnFeCoNi is performed, indicating that this method has potential to be extended to the study of many component alloys.

Au-Si↗

DOE OSTI2021

Data Science Techniques, Assumptions, and Challenges in Alloy Clustering and Property Prediction

Data analytics methods have been increasingly applied to understanding materials chemistry, processing due to the manufacturing approach, and uni-axial and cyclic property relationships in the highly complex space of alloy design. There are several benefits to applying data analytics to this space, including the ability to manage non-linearities in the responses of the alloy attributes and the resulting mechanical properties. However, key difficulties in applying and understanding the results of data analytics include the often lack of reported assumptions and data processing steps necessary to improve interpretation and reproducibility in derived results. In this work, the methods used to generate clustering and correlation analyses for experimental 9% Cr ferritic-martensitic steel data were investigated and the resulting implications for mechanical property predictions were assessed. This work uses principal component analysis, partitioning around medoids, t-SNE, and k-means clustering to investigate trends in composition, processing and microstructure information with creep and tensile properties, building on work done previously using a smaller version of the same dataset. The initial assumptions, preprocessing steps and methods are investigated and outlined in order to depict the fine level of detail required to convey the steps taken to process data and produce analytical results. Here, the variations in the resulting analyses are explored due to the influence of new and more varied data.

36 MATERIALS SCIENCE↗

DOE OSTI2026

RidgeAlloy: A high pressure die casting alloy that captures the approaching wave of automotive body sheet scrap

Oak Ridge National Laboratory (ORNL) has recently launched an effort to economically expand the North American aluminum supply chain by designing and developing a new family of Al-Mg-Si-Fe-Mn structural die cast aluminum alloys that can be made from up to 100% mixed 5xxx and 6xxx series automotive post-consumer sheet scrap and do not require heat treatment. The goal is to develop an alloy capable of capturing the approaching scrap wave of aluminum sheet intensive vehicles (in the 2030’s) into integrated structural high pressure die castings, rather than down-cycling these high-grade sheet alloys into non-structural castings. ORNL discovered a significant gap in the commercial thermodynamic databases that were unable to predict the trends of a key primary intermetallic phase as a function of composition. Experiments were performed to correct this gap and to create a unique, corrected quaternary database for Al-Mg-Si-Fe. High throughput computational methods, including solidification simulations, were used to identify a composition volume capable of avoiding this embrittling primary intermetallic phase, even at higher Fe + Si contents. Laboratory scale castings validated the thermodynamic and solidification predictions and resulted in lab-cast alloys with little primary intermetallic, and which met or exceeded structural casting properties requirements for yield strength and ductility. An accelerated demonstration of an HPDC automotive part was conducted in collaboration with two U.S. small businesses. Ingots made from 100% recycled 5xxx and 6xxx series scrap (plus Fe) were used to die cast one variant of this new family of Al-Mg-Si-Fe-Mn alloys (with high Si + Fe content) into a mid-sized HPDC structural-type automotive component. The HPDC alloy demonstration part showed good properties (especially ductility) and good castability for a complex component.

Plotkowski, Alex [ORNL] (ORCID:0000000154718681)↗

DOE OSTI2021

Visualizing temperature-dependent phase stability in high entropy alloys

High entropy alloys (HEAs) contain near equimolar amounts of five or more elements and are a compelling space for materials design. In the design of HEAs, great emphasis is placed on identifying thermodynamic conditions for single-phase and multi-phase stability regions, but this process is hindered by the difficulty of navigating stability relationships in high-component spaces. Traditional phase diagrams use barycentric coordinates to represent composition axes, which require ( N – 1) spatial dimensions to represent an N -component system, meaning that HEA systems with N > 4 components cannot be readily visualized. Here, we propose forgoing barycentric composition axes in favor of two energy axes: a formation-energy axis and a ‘reaction energy’ axis. These Inverse Hull Webs offer an information-dense 2D representation that successfully captures complex phase stability relationships in N ≥ 5 component systems. We use our proposed diagrams to visualize the transition of HEA solid-solutions from high-temperature stability to metastability upon quenching, and identify important thermodynamic features that are correlated with the persistence or decomposition of metastable HEAs.

Chemistry↗

DOE OSTI2023

Influence of atomic ordering and cerium doping on magnetostrictive Fe-Al alloys

Magnetostrictive iron-aluminum alloys can be a low-cost, mechanically stable alternative to iron-gallium and rare earth-iron alloys. The magnetostrictive performance of polycrystalline Fe-Al (alfenol) with 13–24 at. % Al was investigated, studying the role of compositional variation and thermal history. It was found that rapid cooling enhances the magnetostrictive response, and peak magnetostriction was found in Fe 78 Al 22 by high temperature annealing followed by quenching. Synchrotron diffraction enabled a direct correlation of magnetostrictive behavior and the transition from short-range order to long-range ordered cluster domains in the material which can be suppressed by rapid cooling. Following recent success of doping Fe-Ga with rare earth elements, we investigated the influence of Ce doping on improving magnetostriction and found that Fe-Al shows negligible solubility for cerium, inhibiting potential magnetostriction enhancement. In conclusion, our results illustrate the complex interplay between phase stability, ordering, and optimized magnetostrictive response.

36 MATERIALS SCIENCE↗

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↗

DOE OSTI2024

Lightweight single-phase Al-based complex concentrated alloy with high specific strength

Developing light yet strong aluminum (Al)-based alloys has been attracting unremitting efforts due to the soaring demand for energy-efficient structural materials. However, this endeavor is impeded by the limited solubility of other lighter components in Al. Here, we propose to surmount this challenge by converting multiple brittle phases into a ductile solid solution in Al-based complex concentrated alloys (CCA) by applying high pressure and temperature. We successfully develop a face-centered cubic single-phase Al-based CCA, Al 55 Mg 35 Li 5 Zn 5 , with a low density of 2.40 g/cm 3 and a high specific yield strength of 344×10 3 N·m/kg (typically ~ 200×10 3 N·m/kg in conventional Al-based alloys). Our analysis reveals that formation of the single-phase CCA can be attributed to the decreased difference in atomic size and electronegativity between the solute elements and Al under high pressure, as well as the synergistic high entropy effect caused by high temperature and high pressure. The increase in strength originates mainly from high solid solution and nanoscale chemical fluctuations. Our findings could offer a viable route to explore lightweight single-phase CCAs in a vast composition-temperature-pressure space with enhanced mechanical properties.

42 ENGINEERING↗

DOE OSTI2023

Pulsed Light Synthesis of High Entropy Nanocatalysts with Enhanced Catalytic Activity and Prolonged Stability for Oxygen Evolution Reaction

The ability to synthesize compositionally complex nanostructures rapidly is a key to high-throughput functional materials discovery. In addition to being time-consuming, a majority of conventional materials synthesis processes closely follow thermodynamics equilibria, which limit the discovery of new classes of metastable phases such as high entropy oxides (HEO). Herein, a photonic flash synthesis of HEO nanoparticles at timescales of milliseconds is demonstrated. By leveraging the abrupt heating and cooling cycles induced by a high-power-density xenon pulsed light, mixed transition metal salt precursors undergo rapid chemical transformations. Hence, nanoparticles form within milliseconds with a strong affinity to bind to the carbon substrate. Oxygen evolution reaction (OER) activity measurements of the synthesized nanoparticles demonstrate two orders of magnitude prolonged stability at high current densities, without noticeable decay in performance, compared to commercial IrO 2 catalyst. This superior catalytic activity originates from the synergistic effect of different alloying elements mixed at a high entropic state. It is found that Cr addition influences surface activity the most by promoting higher oxidation states, favoring optimal interaction with OER intermediates. The proposed high-throughput method opens new pathways toward developing next-generation functional materials for various electronics, sensing, and environmental applications, in addition to renewable energy conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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 OSTI2021

High-Entropy Ceramic Coatings: Transformative New Materials for Environmentally-Compatible Thin-Film Insulators against High-T Molten Salts

An emerging new class of promising materials, High-Entropy Ceramics (HECs) or Compositionally-Complex Ceramics (CCCs), have been successfully fabricated in the last three years. This project evaluates HECs/CCCs in the concentrated solar power (CSP) context. In this project, we have identified a couple of simple, and key descriptors governing thermal conductivity in HECs. Size disorder among the cations was found to have a strong influence on the thermal conductivity across multiple systems and throughout a vast compositional space. Since identifying this, we have optimized previous compositions to achieve low thermal conductivities of $k$~$1-1.4Wm{-1}K{-1}$. We have further reduced our selection of promising compositions based on project guidelines and applied a theory that can potentially predict reactivity with molten salts to identify a small set of HECs that are suitable for further molten salt heat transfer media (HTM) stability testing. Many compositions reveal poor resistance to molten chloride salt after being exposed for 24 h compared to the reference structural alloy, Haynes 230. However, after 100 h, a few HECs/CCCs show strong parabolic rate constant effects and provide greater resistance to chloride salt compared to Haynes 230 alloy, which shows more linear kinetics. Postmortem characterization of the microstructure reveals the parabolic rate constant originates from a dense reaction layer form at the interface. This feature is absent in Haynes 230, which only shows grain boundary infiltration. The HECs/CCCs were also put in contact with the metal alloy under Ar for 800 h at 800°C and show negligible interaction. Lastly, parabolic rate constant HECs/CCCs also have low thermal conductivity $(<2 Wm^{-1} K^{-1})$ at 800°C. These specimens satisfy all project requirements and demonstrate their promising application in next-generation CSP.

14 SOLAR ENERGY↗

DOE OSTI2021

Designing order–disorder transformation in high-entropy ferritic steels

Order–disorder transformations hold an essential place in chemically complex high-entropy ferritic steels (HEFSs) due to their critical technological application. The chemical inhomogeneity arising from mixing of multi-principal elements of varying chemistry can drive property altering changes at the atomic scale, in particular short-range order. Using density-functional theory-based linear-response theory, we predict the effect of compositional tuning on the order–disorder transformation in ferritic steels—focusing on Cr–Ni–Al–Ti–Fe HEFSs. We show that Ti content in Cr–Ni–Al–Ti–Fe solid solutions can be tuned to modify short-range order that changes the order–disorder path from BCC-B2 (Ti atomic-fraction = 0) to BCC-B2-L2 1 (Ti atomic-fraction > 0) consistent with existing experiments. Our study suggests that tuning degree of SRO through compositional variation can be used as an effective means to optimize phase selection in technologically useful alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Control of ternary alloy composition during remote epitaxy on graphene

Understanding the sticking coefficient σ, i.e., the probability of an adatom sticking to a surface, is essential for controlling the stoichiometry during epitaxial film growth. However, σ on monolayer graphene-covered surfaces and its impact on remote epitaxy are not understood. Here, using molecular-beam epitaxial growth of the magnetic shape memory alloy Ni 2 MnGa, we show that the sticking coefficients for metals on graphene-covered MgO (001) are less than one and are temperature and element dependent, as revealed by ion backscattering spectrometry and energy-dispersive x-ray spectroscopy. This lies in stark contrast with most transition metals sticking on semiconductor and oxide substrates, for which σ is near unity at typical growth temperatures (T < 800°C). By initiating growth below 400°C, where the sticking coefficients are closer to unity and wetting on the graphene surface is improved, we demonstrate the epitaxy of Ni 2 MnGa films with controlled stoichiometry that can be exfoliated to produce freestanding membranes. Straining these membranes tunes the magnetic coercive field. Finally, our results provide a route to synthesize membranes with complex stoichiometries whose properties can be manipulated via strain.

36 MATERIALS SCIENCE↗