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DOE OSTI2026

Binder-jetted AISI M2 tool steel during hot isostatic pressing: Densification and carbide transformation

Binder jetting (BJ) enables fabrication of complex components from high-alloy steels such as AISI M2; however, residual porosity after sintering limits mechanical performance. This study investigates the coupled effects of binder chemistry, sintering conditions, cooling rate, and subsequent hot isostatic pressing (HIP) on densification, microstructure, and mechanical response in binder-jetted M2 tool steel. HIP increased relative density from ∼93 to 95% to >99% and improved compressive strength by ∼40-70%. Densification was governed by initial pore morphology, where closed porosity was effectively eliminated, while interconnected porosity limited full consolidation. Microstructural analysis (XRD, EBSD, SEM) shows that HIP promotes dissolution of metastable carbides and redistribution of alloying elements (W, Mo, V), transforming heterogeneous carbide networks into finer and more uniformly distributed M 2 C, MC, and M 6 C phases through diffusion-assisted homogenization. Among the investigated conditions, the FluidFuse binder combined with sintering at 1270 °C for 60 min and furnace cooling produced the most balanced response, achieving ∼99.7% density, ∼855 HV hardness, ∼4130 MPa compressive strength, and ∼24% strain. In contrast, higher sintering temperatures promoted carbide coarsening, reducing ductility despite high density. HIP reduces microstructural heterogeneity and drives the system toward a near-equilibrium state with reduced sensitivity to prior processing history. A comparative assessment with conventional and additive manufacturing routes (LPBF, DED, EBM, FFF) shows that the BJ-HIP approach achieves competitive densification and mechanical performance. These findings provide a mechanistic basis for controlling densification and microstructure in high-alloy steels processed via BJAM.

AISI M2 tool steel↗

DOE OSTI2025

Strong, ductile, and hierarchical hetero-lamellar-structured alloys through microstructural inheritance and refinement

The strength−ductility trade-off exists ubiquitously, especially in brittle intermetallic-containing multiple principal element alloys (MPEAs), where the intermetallic phases often induce premature failure leading to severe ductility reduction. Hierarchical heterogeneities represent a promising microstructural solution to achieve simultaneous strength−ductility enhancement. However, it remains fundamentally challenging to tailor hierarchical heterostructures using conventional methods, which often rely on costly and time-consuming processing. Here, we report a multiscale microstructural inheritance and refinement strategy to process “structural hierarchy precursors” in as-cast heterogeneous Al 0.7 CoCrFeNi MPEAs, which lead directly to a hierarchical hetero-lamellar structure (HLS) after simple rolling and annealing. Interestingly, it takes only 10 min of annealing time, two orders of magnitude less than that required to render the state-of-the-art properties during conventional processing of Al 0.7 CoCrFeNi, for us to achieve record-high strength−ductility combinations via the hierarchical HLS design that sequentially stimulates multiple unusual deformation and reinforcement mechanisms. In particular, the HLS-enabled high hetero-deformation-induced (HDI) internal stress triggers profuse <111>-type dislocations on over five independent slip systems in the supposedly brittle intermetallic phase and activates extensive stacking faults (SFs) and nanotwinning in the adjoining soft phase with a rather high SF energy. These unexpected, dynamically reinforcing hetero-deformation mechanisms across multiple length scales facilitate high sustained HDI strain hardening, along with a salient microcrack-mediated extrinsic ductilization effect, suggesting that the proposed microstructural inheritance and refinement strategy provides an efficient, fast, and low-cost approach to overcome the strength−ductility trade-off in a broad range of structural materials.

Science & Technology - Other Topics↗

DOE OSTI2024

Image-Based Failure Assessment of Li-Ion Batteries

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. In this work, a digital twin is created to investigate the performance of a heterogeneous Li-ion battery cathode and simulate degradation accumulation. Pixel-based model construction is used to represent the complex material geometries from microstructural images supplied by the National Renewable Energy Laboratory (NREL). Because of the expected large deformation and crack opening, the reproducing kernel particle method (RKPM), a meshfree method with discretization at the image pixels, is used to approximate the field variables: electrostatic potential, concentration, and displacement. An interface modified reproducing kernel (IM-RK) is constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. IM-RK is additionally used to inform how crack evolution in turn affects the coupled electro-chemo-mechanical behavior of the Li-ion battery cathode.

image-based modeling↗

DOE OSTI2025

Characterization of Build Parameters and Microstructure in Low Heat Input WAAM of Ni-Based Superalloy Haynes 282

Ni-based superalloy Haynes® 282® is being targeted for various applications in advanced power generation systems for its superior fabricability, weldability, and excellent high temperature creep and corrosion performance. This process optimization study aims to use a low heat-input, high deposition rate, controlled Gas Metal Arc Welding (GMAW) process, Cold Metal Transfer (CMT) by Fronius, attempting to achieve fully dense fabrication and possibly avoid the need for HIP. Twenty-one multilayer blocks (~25x100x40 mm3) were deposited to explore a large set of build parameters variations that focused on varying the travel speed from 14 to 42 inches per minute (ipm) and wire feed speed from 150 to 450 ipm. A strong correlation has been observed between arc energy – controlled primarily by travel and wire feed speed. Initial visual inspection, internal microstructural examination, and computed tomography (CT) have been used to determine the effects of built parameters on evolution of internal porosity and defects. Scanning electron microscopy techniques enabled structural and compositional imaging of heterogeneity and changes in microstructural properties.

additive manufacturing↗

DOE OSTI2025

Characterization of Build Parameters and Microstructure in Low Heat Input WAAM of Ni-Based Superalloy Haynes 282

additive manufacturing↗

DOE OSTI2023

Towards inverse microstructure-centered materials design using generative phase-field modeling and deep variational autoencoders

The field of Integrated Computational Materials Engineering (ICME) combines a broad range of methods to study materials’ responses over a spectrum of length scales. A relatively unexplored aspect of microstructure-sensitive materials design is uncertainty propagation and quantification (UP/UQ) of materials’ microstructure, as well as establishing process-structure–property (PSP) relationships for inverse material design. In this study, an efficient UP technique built on the idea of changing probability measures and a deep generative unsupervised representative machine learning method for microstructure-based design of thermal conductivity of materials is proposed. Probability measures are used to represent microstructure space, and Wasserstein metrics are used to test the efficiency of the UP method. By using deep Variational AutoEncoder (VAE), we identify the correlations between the material/process parameters and the thermal conductivity of heterogeneous dual-phase microstructures. Through high-throughput screening, UP, and the deep-generative VAE method, PSP relationships that are too complex can be revealed by exploiting the materials’ design space with an emphasis on microstructures. As a last point, we demonstrate generative machine learning serves as a useful tool for inverse microstructure-centered materials design, and we demonstrate this by examining the inverse design of thermal conductivity in nano-structured materials. Here, the results reveal the effects of morphology, volume fraction, characteristic length scale, and the individual thermal diffusivity of phases on the thermal conductivity of dual-phase alloys. Our findings emphasize the advantages of high-throughput phase-field modeling and generative deep learning for linking PSP and inverse microstructure-centered materials design.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Uncertainty quantification and propagation in lithium-ion battery electrodes using bayesian convolutional neural networks

The complex nature of manufacturing processes stipulates electrodes to possess high variability with increased heterogeneity during production. X-ray computed tomography imaging has proved to be critical in visualizing the complicated stochastic particle distribution of as-manufactured electrodes in lithium-ion batteries. However, accurate prediction of their electrochemical performance necessitates precise evaluation of kinetic and transport properties from real electrodes. Image segmentation that characterizes voxels to particle/pore phase is often meticulous and fraught with subjectivity owing to a myriad of unconstrained choices and filter algorithms. Here we utilize a Bayesian convolutional neural network to tackle segmentation subjectivity and quantify its pertinent uncertainties. Otsu inter-variance and Blind/Referenceless Imaging Spatial Quality Evaluator are used to assess the relative image quality of grayscale tomograms, thus evaluating the uncertainty in the derived microstructural attributes. We analyze how image uncertainty is correlated with the uncertainties and magnitude of kinetic and transport properties of an electrode, further identifying pathways of uncertainty propagation within microstructural attributes. The coupled effect of spatial heterogeneity and microstructural anisotropy on the uncertainty quantification of transport parameters is also understood. This work demonstrates a novel methodology to extract microstructural descriptors from real electrode images through quantification of associated uncertainties and discerning the relative strength of their propagation, thus facilitating feedback to manufacturing processes from accurate image based electrochemical simulations.

25 ENERGY STORAGE↗

DOE OSTI2022

Data-driven analysis of neutron diffraction line profiles: application to plastically deformed Ta

Abstract Non-destructive evaluation of plastically deformed metals, particularly diffraction line profile analysis (DLPA), is valuable both to estimate dislocation densities and arrangements and to validate microstructure-aware constitutive models. To date, the interpretation of whole line diffraction profiles relies on the use of semi-analytical models such as the extended convolutional multiple whole profile (eCMWP) method. This study introduces and validates two data-driven DLPA models to extract dislocation densities from experimentally gathered whole line diffraction profiles. Using two distinct virtual diffraction models accounting for both strain and instrument induced broadening, a database of virtual diffraction whole line profiles of Ta single crystals is generated using discrete dislocation dynamics. The databases are mined to create Gaussian process regression-based surrogate models, allowing dislocation densities to be extracted from experimental profiles. The method is validated against 11 experimentally gathered whole line diffraction profiles from plastically deformed Ta polycrystals. The newly proposed model predicts dislocation densities consistent with estimates from eCMWP. Advantageously, this data driven LPA model can distinguish broadening originating from the instrument and from the dislocation content even at low dislocation densities. Finally, the data-driven model is used to explore the effect of heterogeneous dislocation densities in microstructures containing grains, which may lead to more accurate data-driven predictions of dislocation density in plastically deformed polycrystals.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Assessment of binary eutectic Ni alloys for high-temperature applications via laser remelting

It has been recently demonstrated that eutectic alloys processed by additive manufacturing have excellent high-temperature mechanical properties. We suggest that nickel-base eutectic alloys may enable new combinations of structural and functional properties. To this end, we investigate the processability, microstructure, and thermal stability of five, binary near-eutectic Ni-X (X = B, Ce, La, Y, and Zr) alloys processed via surface laser-remelting. The microstructure of all alloys contain a two-phase lamellar eutectic microstructure consisting of γ-Ni and intermetallic phases; this microstructure is significantly finer (100–200 nm lamellar spacing) in the laser-remelted alloys than in the cast substrate (0.5–1.0 µm lamellar spacing). The microhardness of the laser-remelted alloys (550–770 HV) is 35–50% higher than that of the cast alloys (370–570 HV) due to this finer eutectic spacing. An anomalous eutectic microstructure appears at the meltpool boundaries, containing globular and lamellar γ-Ni phases. The alloys contain a high volume fraction (>50 vol%) of intermetallic phase which forms a continuous network, causing brittleness. Following laser-remelting trials, the alloys showed a high density of solid-state cracks, except for the Ni-Zr alloy which processed well. During thermal exposure at 700 and 900°C for up to 500 h, the eutectic microstructure coarsens. Coarsening occurs heterogeneously and initiates at the meltpool boundaries. This process occurs more slowly in the Ni-Zr and Ni-Y alloys, and more rapidly in the remaining alloys, resulting in greater microhardness retention in the Ni-Zr and Ni-Y alloys following thermal exposure at 700°C. Thus, among the five alloys, the Ni-Zr system exhibits a good combination of high-temperature mechanical properties and processability. Here, we conclude with recommendations for future work on designing additively manufactured alloys based on these eutectic Ni systems.

Additive manufacturing↗

DOE OSTI2021

New Opportunity for Carbon-Supported Ni-based Electrocatalysts: Gas-Phase CO 2 Methanation

The cost-effectiveness and excellent performance of conductive-carbon-supported Ni-based electrocatalysts make them attractive materials for hydrogen oxidation and evolution reactions. However, they were previously unused in gas-phase hydrogenation reactions. In this work, we have expanded the applicability of commercially available advanced Ni/C, NiMo/C and NiRe/C materials from electrocatalysis to heterogeneous catalysis of CO 2 methanation. Our catalytic testing efforts indicate that the monometallic Ni/C material demonstrates the best CO 2 methanation properties, achieving an excellent CO 2 conversion of 83 % at 400 °C with nearly complete selectivity to CH 4 of 99.7 %, plus exhibiting intact performance during 90 h of time-on-stream testing. Such catalytic properties are among the highest reported to date among carbon-supported Ni-based methanation catalysts. Finally, excellent performance of Ni/C stems from the good dispersion of the Ni nanoparticles over N-containing carbon support material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Simulation of dynamic crystal plasticity with a Lagrangian discontinuous Galerkin hydrodynamic method

Here we present a new Lagrangian modal discontinuous Galerkin (DG) hydrodynamic method that supports a dynamic dislocation based crystal plasticity model for simulating the mechanical behavior of crystallographic materials, both single crystal and polycrystalline, under dynamic conditions. A modal DG approach is used to evolve fields relevant to conservation laws. These fields are approximated by Taylor series polynomials of varying degree. These polynomials describe macro-scale hydrodynamic behavior while their evolution is determined by evaluating the dynamic crystal plasticity model at material points within the element. The dynamic crystal plasticity model is sensitive to the time increment size, with too large of time increments leading to instability in the model. To mitigate this, the temporal evolution of the dynamic crystal plasticity model is achieved with the combination of a sub-incrementing scheme with Heun’s third-order time integration scheme, which is also used to temporally evolve the governing equations. The implementation of the dynamic crystal plasticity model within the DG framework is tested using a 2D approximation of the Taylor impact test with a single crystal material, using quadratic elements that have faces that can bend. In addition to the standard continuous material modeling, we propose a new simulation method that would represent the heterogeneous behavior of polycrystalline microstructures within an element by varying the position and material properties of the material points within the element. This method is demonstrated using random orientation distributions on materials points that are arranged in both structured and random configurations.

42 ENGINEERING↗

DOE OSTI2026

High hardness and oxidation-resistant Cr-containing medium entropy ZrTaW diboride

This study reports the successful synthesis of a Cr-containing (Zr 0.30 Ta 0.34 Cr 0.06 W 0.30 )B 2 medium-entropy boride (MEB) via an in-situ reactive borothermal reduction route from oxide precursors. High-energy ball milling was employed to homogenize the precursor mixture prior to reactive densification. X-ray diffraction confirmed the formation of a predominantly AlB₂-type hexagonal diboride structure together with a secondary (W X , M 1-X )B monoboride phase. Microstructural characterization revealed compositional heterogeneity and localized W-rich regions associated with the secondary phase. The synthesized medium-entropy boride exhibited enhanced mechanical properties, which are attributed to lattice distortion and solid-solution strengthening effects. Thermogravimetric analysis revealed complex multistage oxidation behavior, and the oxidation resistance was compared with conventional ultra-high-temperature diborides. The results demonstrate the strong relationship between oxide-derived processing, compositional complexity, phase evolution, and oxidation behavior, highlighting the potential of medium-entropy borides for high-temperature structural applications

36 MATERIALS SCIENCE↗

DOE OSTI2019

A space-time adaptive finite element method with exponential time integrator for the phase field model of pitting corrosion

In this paper we propose a space-time adaptive finite element method for the phase field model of pitting corrosion, which is a parabolic partial differential equation system consisting of a phase variable and a concentration variable. A major challenge in solving this phase field model is that the problem is very stiff, which makes the time step size extremely small for standard temporal discretizations. Another difficulty is that a high spatial resolution is required to capture the steep gradients within the diffused interface, which results in very large number of degrees of freedom for uniform meshes. To overcome the stiffness of this model, we combine the Rosenbrock–Euler exponential integrator with Crank–Nicolson scheme for the temporal discretization. Moreover, by exploiting the fact that the speed of the corroding interface decreases with time, we derive an adaptive time stepping formula. For the spatial approximation, we propose a simple and efficient strategy to generate adaptive meshes that reduces the computational cost significantly. Thus, the proposed method utilizes local adaptivity and mesh refinement for efficient simulation of the corrosive dissolution over long times in heterogeneous media with complex microstructures. We also present an extensive set of numerical experiments in both two and three dimensional spaces to demonstrate efficiency and robustness of the proposed method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Synergistic Effects of Molten Salt Corrosion and Proton Irradiation on Grain Boundary Strength in Ni-20Cr

Nickel-based alloys are leading contenders for use as structural materials in molten salt reactors. While there have been extensive studies on the impact of fluoride/chloride-based molten salt corrosion on the microstructural evolution of various nickel-based alloys, the effects of simultaneous molten salt corrosion and radiation on the mechanical integrity of grain boundaries (GBs) remain underexplored. In this study, we use a Ni-20Cr model alloy to investigate this issue, subjecting it to simultaneous molten fluoride salt corrosion and proton irradiation. We performed cross-sectional and chemically-sensitive electron microscopy characterization of the microstructures of these materials, identifying the characteristic corrosion-induced microstructure and local chemical heterogeneity near GBs. After developing a sample preparation method for reliable characterization of GB strength, we assess the mechanical degradation of GBs using in situ push-to-pull micro tensile tests. Our findings reveal that voids induced by corrosion are the primary influence on the failure mode of GBs, regardless of whether proton irradiation is present. For materials that exhibit ductile fracture, those subjected to simultaneous corrosion and radiation exhibit lower yield strengths than those exposed to corrosion alone, which may be linked to the previously observed phenomenon of proton irradiation-decelerated intergranular corrosion in molten salt.

36 - MATERIALS SCIENCE↗

DOE OSTI2025

Pore Resolved Simulations of Joule Heating in Fibrous Media using an Embedded Boundary Method

Joule heating has been regarded as an energy-efficient and sustainable method for heating materials and gases at large scales. The modeling of local temperature effects at pore-resolved scales for such systems, however, has been difficult to achieve due to challenges in coupling thermo-chemical processes in complex porous media and in large representative volume elements (RVEs). To this end, we developed an electro-thermal model at the pore scale to study Joule heating effects in large heterogeneous systems with different microstructures. This was achieved using the level set method to implicitly delineate distinct regions within the domain, and an embedded boundary method to facilitate heat exchange across the fluid-solid interface. Moreover, we applied this method to investigate unsteady non-linear electro-thermal effects in non-woven fibrous graphite conductors for RVEs with characteristic lengths of 2 mm, with different fiber orientations, porosity (80% – 90%) and fiber diameters (10 – 20µm). The coupled equations were solved numerically and they produced peak temperatures greater than 2000 K resulting in heating rates as high as 80,000 K/s. Moreover, the results depended strongly on the microstructure of the fiber skeleton and current density. Geometries with large fibers (∼ 20µm) had the highest average and peak temperatures with the mean temperature increasing by 3.9 % while the peak temperature increased by 9.9 %. Anisotropic domains on the other hand had the lowest mean and peak temperatures with peak and mean temperatures of 2293 K and 1437.7K respectively representing a corresponding 12.1% and 5.1% drop in the temperatures. An increase in porosity from 80% to 90%, however, led to an increase in the peak temperature by 5.1%.

Joule heating↗

DOE OSTI2024

Impact of Asymmetric Microstructure on Ion Transport in Ti 3 C 2 T x Membranes

Consolidation or densification of low-dimensional MXene materials into membranes can result in the formation of asymmetric membrane structures. Nanostructural (short-range) and microstructural (long-range) heterogeneity can influence mass transport and separation mechanisms. Short-range structural dynamics include the presence of water confined between the 2D layers, while long-range structural properties include the formation of defects, micropores, and mesopores. Herein, it is demonstrated that structural heterogeneity in Ti 3 C 2 T x membranes fabricated via vacuum-assisted filtration significantly affects ion transport. Higher ion permeabilities are achieved when the dense “bottom” side of the membrane, rather than the porous “top” side, faces the feed solution. Characterization of the membrane reveals distinct differences in flake alignment, surface roughness, and porosity across the membrane. In conclusion, the directional dependence on permeability suggests that one region of the membrane experiences stronger internal concentration polarization, potentially suppressing permeability through the porous side of the membrane.

MXene↗

DOE OSTI2021

Structural and chemical evolution in layered oxide cathodes of lithium-ion batteries revealed by synchrotron techniques

Abstract Rechargeable battery technologies have revolutionized electronics, transportation and grid energy storage. Many materials are being researched for battery applications, with layered transition metal oxides (LTMO) the dominating cathode candidate with remarkable electrochemical performance. Yet, daunting challenges persist in the quest for further battery developments targeting lower cost, longer lifespan, improved energy density and enhanced safety. This is, in part, because of the intrinsic complexity of real-world batteries, featuring sophisticated interplay among microstructural, compositional and chemical heterogeneities, which has motivated tremendous research efforts using state-of-the-art analytical techniques. In this research field, synchrotron techniques have been identified as a suite of effective methods for advanced battery characterization in a non-destructive manner with sensitivities to the lattice, electronic and morphological structures. This article provides a holistic overview of cutting-edge developments in synchrotron-based research on LTMO battery cathode materials. We discuss the complexity and evolution of LTMO’s material properties upon battery operation and review recent synchrotron-based research works that address the frontier challenges and provide novel insights in this field. Finally, we formulate a perspective on future directions of synchrotron-based battery research, involving next-generation X-ray facilities and advanced computational developments.

25 ENERGY STORAGE↗

DOE OSTI2023

Investigation of Deformation Behavior of Additively Manufactured AISI 316L Stainless Steel with In Situ Micro-Compression Testing

Additive manufacturing techniques are being used more and more to perform the precise fabrication of engineering components with complex geometries. The heterogeneity of additively manufactured microstructures deteriorates the mechanical integrity of products. In this paper, we printed AISI 316L stainless steel using the additive manufacturing technique of laser metal deposition. Both single-phase and dual-phase substructures were formed in the grain interiors. Electron backscatter diffraction and energy-dispersive X-ray spectroscopy indicate that Si, Mo, S, Cr were enriched, while Fe was depleted along the substructure boundaries. In situ micro-compression testing was performed at room temperature along the [001] orientation. The dual-phase substructures exhibited lower yield strength and higher Young’s modulus compared with single-phase substructures. Our research provides a fundamental understanding of the relationship between the microstructure and mechanical properties of additively manufactured metallic materials. The results suggest that the uneven heat treatment in the printing process could have negative impacts on the mechanical properties due to elemental segregation.

36 MATERIALS SCIENCE↗