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

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Time at Temperature Abstract and Intern Poster

Current NRC regulations for BWR operations dictate that any occurrence reaching the point of Departure from Nucleate Boiling (DNB) disqualifies the use of the fuel rod for further reactor operation. That criteria does not account for duration of rate of the power increase, the corresponding effects on material properties or rewetting that may occur. Previous Anticipated Operational Occurrences (AOOs) show short durations power increase that may require limited amounts of heat removal. Industrial experience has shown evidence that fuel can reach dryout yet continue to safely operate in regular reactor conditions. The gap in research into such occurrences is the motivation for a series of experiments, including this current work. Time-at-Temperature experiments aim to identify and characterize the microstructural changes in Zircaloy-2 under oxygen-free high temperatures. This work uses the FlashDSC instrument to rapidly ramp up and down the temperature of a focus ion beam (FIB) prepared large area lift-out (LALO) of Zircaloy-2 at a rate of 10,000 K/s to desired values. The focus is to characterize the microstructure evolution, if any, of Zircaloy-2 that may impact its performance under typical BWR conditions. This characterization includes analyzing grain structure and size, secondary phase particle (SPPs) size, shape, composition, and location using Transmission Electron Microscopy (TEM). Further data collection and analysis is in progress including diffraction pattern indexing and 4D STEM processing. While current results focus on the testing and characterizing unirradiated material, future plans include expansion to irradiated material to explore the effects of rapid transition rates seen in DNB and dryout conditions on irradiationg damage and defect annealing.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Precious metal oxygen-evolving anodes for electrolytic reduction of metal oxides in molten LiCl-Li 2 O electrolyte

Understanding the electrochemical stability of oxygen-evolving anode materials in molten salt electrolytes is essential to enable decarbonized electrolytic reduction of metal oxides (e.g., used nuclear oxide fuels). Here, this work investigated three precious metals (Ir, Ru, and Pt) as oxygen-evolving anodes in molten LiCl-Li 2 O (99.0-1.0 wt%) at 650 °C. For consistent measurements, this work employed a three-electrode cell comprised of a two-phase Li-Bi (65-35 at%) reference electrode and a NiO counter electrode. Anodic polarization behavior of each anode was investigated via cyclic voltammetry (CV) and chronoamperometry. The onset potential for oxygen evolution was observed at E > 2.9 V (vs. Li/Li + ) for the Ir and Ru anodes and anodic current density was as high as 1.0 A cm -2 at 3.23 V. The dimensional stability of each anode was evaluated from long-term electrolysis experiments (10.0-32.1 h) at 3.23 V. Rapid consumption of the Pt anode was observed after the application of 26,453 C cm -2 with a reduction in diameter of about 15.8% due to the formation of a non-protective Li 2 PtO 3 compound. The formation of this compound was also observed during CV measurements as additional anodic waves at potentials more negative than that of oxygen evolution. In contrast, both the Ir and Ru anodes exhibited excellent dimensional stability with a reduction in diameter or thickness of less than 1.5% even after applying greater charge density of ~41,100 C cm -2 , demonstrating superior stability during oxygen evolution in the LiCl-Li 2 O electrolyte.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Correlated fission fragment spin dynamics

Here, this study explores the role of nucleon exchange for the generation of the fission fragment angular momenta. For a number of typical fission cases, samples of 10 4 shape evolutions are generated by Langevin simulation and, subsequently, for each such evolution, the nucleon exchange transport theory previously developed for damped nuclear reactions is used to obtain the development of the fragment spin-spin distribution within the Fokker-Planck transport framework. The characteristic evolution of both parallel and perpendicular spin components is discussed. A common feature is that the rotational modes fall out of equilibrium before scission when the temperature rises rapidly while the concurrent shrinking of the neck suppresses further exchange. A number of fission observables are extracted from the event ensembles: the distribution of the magnitude of the fragment spin and its orientation relative to the fission axis, as well as the correlation between the two spins and the distribution of their opening angle. The dependence of these observables on the mass asymmetry is also examined.

fission↗
DOE OSTI2024

Photoluminescence probing of light absorption centers at silica laser damage

We use photoluminescence (PL) imaging to study damage growth precursors within laser damage sites on the surface of silica. Damage site evolution is induced by multiple shots of UV nanosecond pulsed laser at various energy densities and monitored throughout the early stages of growth. Wide-field PL imaging rapidly locates microscopic light absorption centers within the silica damage site. Our quantitative analysis shows that damage sites with strong local PL intensity show a higher probability of growth upon subsequent laser pulses. Scanning electron microscopy (SEM) paired with a study of PL spectrum shows that the strong PL intensity appears from the subsurface fractures with high defect density, which provides a local light absorption center leading to significant damage growth. We believe that this result offers an efficient optical damage mitigation strategy by providing a rapid and non-destructive optical inspection approach.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Building Nuclear-Specific Cybersecurity Expertise in Higher Education

The rapid digitalization of nuclear power plants (NPPs) and the deployment of advanced and small modular reactors (A/SMRs) have expanded the cybersecurity attack surface within the nuclear sector. This evolution introduces unique challenges beyond those faced in general information technology (IT), operational technology (OT) and industrial control system (ICS) security, due to nuclear power’s regulatory rigor, safety-critical nature, and operational needs. A pressing workforce gap persists; cybersecurity graduates typically lack nuclear-specific context and retraining them for industry readiness requires 12–18 months, creating a significant burden. This paper addresses this gap by defining the domains of knowledge that nuclear cybersecurity specialists must master, spanning cybersecurity, nuclear engineering, OT/ICS security, and regulatory governance. We propose a curricular framework integrating technical, regulatory, and applied learning components to accelerate workforce readiness. Our approach builds on existing findings that current curricula inadequately integrate nuclear engineering and cybersecurity, shifting the discourse from why specialization is needed to what knowledge must be taught. The recommendations have implications for workforce development and long-term resilience of the nuclear energy sector.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

From atomistic models to machine learning: Predictive design of nanocarbons under extreme conditions

The formation of technologically valuable nanocarbon structures under extreme conditions, such as those produced during high-explosive detonations, remains poorly understood but holds significant potential for the development of controlled synthesis pathways. While detonation shockwaves provide the high-pressure, high-temperature environment required for nanodiamond formation, subsequent cooling and decompression dictate whether the diamond phase is preserved or transformed into other nanocarbon structures. Here, in this study, we employ GPU-accelerated reactive molecular dynamics (ReaxFF) simulations to investigate the graphitization and structural remodeling of detonation nanodiamond under nonlinear quench and pressure-release trajectories. We further investigate how the initial nanodiamond morphology; cuboctahedral, octahedral, or hexagonal prism influences the resulting transformation products. Evolution of nanostructure, allotrope (via simulated x-ray diffraction), carbon hybridization, and ring statistics are tracked during a two-stage quench from 5000 K to 60 GPa. Rapid cooling combined with slow decompression optimizes cubic diamond retention, whereas slow cooling with rapid pressure release promotes surface-to-core graphitization, producing concentric sp 2 -hybridized layers and hollowed inner shells. Octahedral nanodiamonds evolve into carbon nano-onions, initially forming bucky diamonds that progressively transform into fully sp 2 -hybridized structures, while hexagonal prisms preferentially form parallel-stacked graphite layers resembling carbon dots. Transient hexagonal diamond (lonsdaleite) emerges as an interfacial phase, suggesting potential reversibility in the shock-induced graphite-to-diamond transformation pathway transformation route. To extend predictive capabilities, we trained machine learning (ML) regressors on over 10 5 node-hours of molecular dynamics (MD) trajectories. A multilayer perceptron (MLP) model reliably predicts the number of graphitized layers from temperature–pressure trajectories with a coefficient of determination (R 2 ) exceeding 0.90. This high predictive fidelity enables efficient, high-throughput mapping of the synthesis parameter space for optimized graphitization outcomes. Collectively, morphological control combined with optimized quench–decompression conditions promote the selective synthesis of nanocarbon allotropes. This work establishes a data-driven framework for the rational, a priori design of carbon nanomaterials for applications in energy storage, sensing, and biomedicine.

Detonation nanodiamond remodeling↗
DOE OSTI2024

Uncertainty-informed selection of CMIP6 Earth System Model subsets for use in multisectoral and impact models

Earth system models (ESMs) and general circulation models (GCMs) are heavily used to provide inputs to sectoral impact and multisector dynamic models, which include representations of energy, water, land, economics, and their interactions. Therefore, representing the full range of model uncertainty, scenario uncertainty, and interannual variability that ensembles of these models capture is critical to the exploration of the future co-evolution of the integrated human–Earth system. The pre-eminent source of these ensembles has been the Coupled Model Intercomparison Project (CMIP). With more modeling centers participating in each new CMIP phase, the size of the model archive is rapidly increasing, which can be intractable for impact modelers to effectively utilize due to computational constraints and the challenges of analyzing large datasets. In this work, we present a method to select a subset of the latest phase, CMIP6, featuring models for use as inputs to a sectoral impact or multisector dynamics models, while prioritizing preservation of the range of model uncertainty, scenario uncertainty, and interannual variability in the full CMIP6 ensemble results. This method is intended to help impact modelers select climate information from the CMIP archive efficiently for use in downstream models that require global coverage of climate information. This is particularly critical for large-ensemble experiments of multisector dynamic models that may be varying additional features beyond climate inputs in a factorial design, thus putting constraints on the number of climate simulations that can be used. We focus on temperature and precipitation outputs of CMIP6 models, as these are two of the most used variables among impact models, and many other key input variables for impacts are at least correlated with one or both of temperature and precipitation (e.g., relative humidity). Besides preserving the multi-model ensemble variance characteristics, we prioritize selecting CMIP6 models in the subset that preserve the very likely distribution of equilibrium climate sensitivity values as assessed by the latest Intergovernmental Panel on Climate Change (IPCC) report. This approach could be applied to other output variables of climate models and, possibly when combined with emulators, offers a flexible framework for designing more efficient experiments on human-relevant climate impacts. It can also provide greater insight into the properties of existing CMIP6 models.

Snyder, Abigail C.↗
DOE OSTI2026

Kinetic Monte Carlo Framework for Coupled Degradation and Dehydration of Anion Exchange Membranes

Kinetic Monte Carlo (kMC) simulations, augmented with temporal-acceleration schemes, can efficiently handle stiff reaction-transport networks when fast processes rapidly relax to quasi-equilibrium on a fixed lattice. However, in glassy anion-exchange membranes (AEM), rare and irreversible chemical degradation events continuously reshape the nanoscale morphology, and the associated hydration and transport degrees of freedom remain far from a well-defined local equilibrium. This combination of evolving state space and nonequilibrated fast dynamics lies outside the scope of existing kMC acceleration frameworks. Here, to address this challenge, we introduce an auxiliary-particle kinetic Monte Carlo (AP-kMC) scheme. In AP-kMC, short-lived mobile particles spawned at degradation sites execute hop, water-elimination, and decay moves, enforcing rapid local relaxation of the hydration structure while preserving the stochastic rules of kMC. Parameterized with molecular-dynamics morphologies and experimental solution degradation kinetics, AP-kMC reproduces the evolution of ion-exchange capacity, water uptake, and conductivity, and reveals a feedback loop in which poorly hydrated sites degrade first and each degradation event induces further local dehydration. The resulting thinning and fragmentation of water channels cause loss of hydrophilic percolation and abrupt conductivity collapse well before complete charge loss. AP-kMC thus reframes AEM durability as a coupled degradation–drying–percolation problem and provides a transferable strategy to simulate reactive, out-of-equilibrium polymer electrolytes where local solvation controls reactivity.

organic↗
DOE OSTI2025

Probing the Surface Chemistry of Lithium Nitridation

Chemical synthesis of Li 3 N through lithium nitridation has potential to advance rechargeable battery and nitrogen fixation technology. However, studies of the conditions for forming Li 3 N on the lithium surface via nitrogen gas exposure report contradictory findings, such as the spontaneous reaction of Li with pure N 2 , the impossibility of forming Li 3 N through pure Li and N 2 interaction, the requirement of trace H 2 O to catalyze the reaction, and evidence to the contrary. In this study, ambient pressure X-ray photoelectron spectroscopy (APXPS) was applied to evaluate the in situ chemical evolution of the lithium metal surface under nitrogen gas up to 800 mTorr. At pressures ≤10 mTorr, no Li 3 N was detected. At higher pressures, surface Li 3 N rapidly reacts with trace CO 2 . Additionally, because metallic lithium is readily oxidized by trace gases, the atomic nitrogen concentration of the lithium surface remains below 2%. When nitridation follows oxidation by O 2 gas, CO 2 gas, or H 2 O vapor, surface Li 3 N formation is inhibited. These results suggest that nitrogen gas can diffuse through the oxidized lithium metal surface to react with subsurface metallic lithium.

Binding energy↗
DOE OSTI2025

Molecular dynamics study of grain boundaries as defect sinks under irradiation in LiAlO 2 and LiAl 5 O 8

Lithium aluminate ceramics, LiAlO 2 and LiAl 5 O 8 , show promise in nuclear environments due to their excellent radiation tolerance. Molecular dynamics simulations investigate grain boundaries (GB) and their role in defect evolution. Results reveal that GBs act as efficient defect sinks, with Li and Al atoms exhibiting distinct behaviors during displacement cascades. Tritium migration in LiAlO 2 is also studied, showing rapid diffusion and stable configurations with oxygen, corroborated by ab initio simulations from the literature. The calculated tritium diffusion coefficient of 1.33 × 10 - ¹⁴ m²/s aligns with the literature, validating the model. LiAl 5 O 8 demonstrates superior defect healing compared to LiAlO 2 , attributed to enhanced atomic transfer between grains and GBs. These findings reveal key insights into defect dynamics, providing essential insights for their application in tritium-producing burnable absorber rods (TPBARs).

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nonconservation of Lepton Numbers in the Neutrino Sector Could Change the Prospects for Core Collapse Supernova Explosions

We show that interactions violating the conservation of lepton numbers in the neutrino sector could significantly alter the standard low entropy picture for the presupernova collapsing core of a massive star. A rapid neutrino-antineutrino equilibration leads to entropy generation and enhanced electron capture and, hence, a lower electron fraction than in the standard model. This would affect the downstream core evolution, the prospects for a supernova explosion, and the emergent neutrino signal. If realized by lepton-number-violating neutrino self-interactions (LNV 𝜈⁢SI), the relevant mediator mass and coupling ranges can be probed by future accelerator-based experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Quark flavor equilibration of the quark-gluon plasma

The early stage of a heavy-ion collision is marked by rapid entropy production and the transition from a gluon saturated initial condition to a plasma of quarks and gluons that evolves hydrodynamically. However, during the early times of the hydrodynamic evolution, the chemical composition of the QCD medium is still largely unknown. We present a study of quark chemical equilibration in the (Q)GP using a novel model of viscous hydrodynamic evolution in partial chemical equilibrium. Motivated by the success of gluon saturated initial condition models, we initialize the QCD medium as a completely gluon dominated state. Local quark production during the hydrodynamic phase is then simulated through the evolution of time-dependent fugacities for each independent quark flavor, with the timescales set as free parameters to compare different rates of equilibration. We present the results of complete heavy-ion collision simulations using this partial chemical equilibrium model, and show the effects on hadronic and electromagnetic observables. In particular, we show that the development of flow is sensitive to the equilibration timescale, providing an empirical way to probe the chemical equilibration of the QCD medium.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Probing Operando Electrochemical Strain Generation in α-NaFeO 2 Composite Cathodes during Cycling of Na-Ion Batteries

The transition metal oxide (TMO) cathodes in Na-ion batteries suffer from low-capacity retention. Chemo-mechanical instabilities lead to the deterioration of the electrochemical performance of TMO cathodes in Li-ion batteries. However, there is not much known about the chemo-mechanical instabilities in the TMO cathodes for Na-ion batteries. Understanding the governing forces behind the interplay between the electrochemical performance and mechanical stability in TMO cathodes is critical for the development of Na-ion batteries. Here, we synchronize the digital image correlation (DIC) technique with electrochemical analysis to capture the real-time deformation behavior of the α-NaFeO 2 cathodes during cycling. When the charge cutoff voltage is 3.6 V, the cathode experiences reversible deformations (except for the first cycle). There is negative strain (shrinkage) generation during Na extraction and positive strain (expansion) generation during the subsequent Na insertion. A detailed analysis of the potential-dependent strain rate evolution points out complicated phase transformations and nonequilibrium conditions in the α-NaFeO 2 cathodes during cycling. When the charge cutoff voltage was increased to 4.2 V, there was a rapid capacity loss and large plastic deformations in the α-NaFeO 2 cathodes. We provide an in-depth discussion about the possible mechanisms behind the chemo-mechanical instabilities in the α-NaFeO 2 . In conclusion, the correlation is critical to develop material-based strategies to mitigate instability mechanisms in TMO cathodes for Na-ion batteries.

Wable, Minal [University of Maryland Baltimore Cou↗
DOE OSTI2025

Automated Nanocrystal Synthesis: Lessons from 25 Years of Robots, Microfluidics, and Machine Learning

Here, this perspective highlights the evolution of techniques for automating the synthesis of colloidal nanocrystals. Over the past 25 years, microfluidic reactors and robotic workflows have been developed to enhance the reproducibility of nanocrystal synthesis, facilitate rapid screening of reaction conditions, optimize material properties, and perform multistep syntheses of high-quality nanoparticles with complex heterostructures. Modern automated systems are now valued for their ability to generate robust data sets for validating physical models, supporting chemical mechanisms, training machine learning models, and for directing autonomous experimentation. We discuss the early challenges and limitations of these technologies and present key lessons for effectively utilizing automated and ML-guided tools to accelerate nanocrystal discovery for the next 25 years.

Nanocrystals↗
DOE OSTI2026

Node Distortions as a Means of Defect Engineering in Zr-Based MOFs

Defect engineering in Zr-based metal–organic frameworks (Zr-MOFs) has focused primarily on missing-linker defects. However, recent studies suggest that node dehydroxylation–which creates distortions and coordinatively unsaturated Zr sites (Zr cus )–may have a more significant impact on properties. The present work uses pair distribution function (PDF) and thermogravimetric analysis coupled with systematic defect manipulation to study the effect of node dehydroxylation and missing-linker defects in UiO-66. By employing rapid heat treatment (RHT) under humid flow, we tracked the transition from high-symmetry [Zr 6 O 4 (OH) 4 ] 12+ to distorted [Zr 6 O 6 ] 12+ nodes. This structural evolution significantly improves As(V) uptake, whereas increasing the number of missing linkers–via chemical treatment or RHT of mixed-ligand frameworks–fails to enhance performance. Crucially, our detection of distorted nodes in as-synthesized UiO-66 also raises the possibility that these defects were silently present in many earlier studies that span various applications, where their role in governing performance may have been inadvertently overlooked. The present study challenges the prevailing “missing-linker” paradigm and establishes cluster dehydroxylation as a defect-engineering strategy to enhance Lewis-acidic performance in Zr-MOFs.

Adsorption↗
DOE OSTI2024

Promoting the regulatory acceptance of combined ion and neutron irradiation for material degradation in nuclear reactors

The Advanced Materials and Manufacturing Technologies (AMMT) program within the Department of Energy (DOE) Office of Nuclear Energy has developed its current recommendation for promoting the use of combined ion irradiation and neutron irradiation for the accelerated qualification of materials to be deployed in nuclear reactors. This plan is intended to provide a collaborative path forward that can be adopted by academia, national laboratories, and industry, and has been developed with input from the regulatory research arm of the U.S. Nuclear Regulatory Commission (NRC). To deploy new materials or materials manufactured with new technologies, such as additive manufacturing, materials must be evaluated for reactor-induced degradation from the combination of harsh temperatures, corrosive environments, and radiation fields. However, rapid deployment of materials necessitates accelerated testing methods rather than relying on years of neutron irradiation in a material test reactor. Ion irradiation has demonstrated success in reproducing material microstructure and select property evolution resulting from neutron irradiation with three to four orders of magnitude reduction in time and cost, making it an ideal candidate for accelerated irradiation testing. This presentation provides context governing both the scientific and regulatory aspects of the proposed goal. The discussion is aimed at a broad audience including researchers from industry, national laboratories, and academia. The recommended path forward is presented as a conceptual framework of specific steps. In brief, the strategy entails developing an integrated ion and neutron irradiation test plan for the material property of interest based on the fundamental tenet of the linkage of microstructure and properties in materials. Physics-based modeling interprets ion irradiation data and predicts neutron irradiation microstructure and properties with uncertainty bounds. The first round of testing is sufficient for an initial licensing application using a risk-informed approach, while a minimum required neutron irradiation test plan reduces cost and time requirements. A surveillance program with witness specimens in-reactor provides additional data over time to improve model predictions to higher damage levels and further reduce uncertainty bounds, which can be used for license extensions or longer lifetimes in new license applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Systematic discovery of new nano-scale metastable intermetallic eutectic phases in laser rapid solidified Aluminum-Germanium alloy

Laser surface remelting of as-cast Al-Ge eutectic alloy is shown to produce ultrafine lamellar eutectic morphology with interlamellar spacing refined up to ∼60 nm and composed of FCC Al solid solution and unusual Al x Ge y intermetallic phases that do not form during near-equilibrium solidification. The microstructures are characterized and analyzed using a combination of selected area electron diffraction, high-resolution scanning transmission electron microscopy, energy dispersive X-ray spectroscopy to obtain high-resolution elemental maps, and atomistic modeling using density functional theory followed by atomic-scale image simulation. Depending on the local solidification conditions, the crystallography of the Al x Ge y intermetallic phases in the eutectic microstructure is either monoclinic (C 2/c) or monoclinic (P 2 1 ), with high densities of defects in both cases. This is in sharp contrast to the as-cast alloys that showed nominally pure Al and Ge phases with significant solute partitioning and equilibrium FCC and diamond cubic crystal structures, respectively. Corresponding kinetic phase diagrams are proposed to interpret the evolution of nano-lamellar eutectic morphologies with equilibrium Al and metastable Al x Ge y phases, and to explain increased solid solubility in the Al phases manifested by precipitation of ultrafine clusters of Ge. Furthermore, the reasons for the formation of these metastable eutectics under laser rapid solidification are discussed from the perspective of the competitive growth criterion.

Al-Ge eutectic↗