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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The complexity of { 11 2 ¯ 1 } twin interface structure and energetics in HCP materials

Here, the quest for a deeper understanding of the mechanical properties of HCP alloys has been an ongoing effort. Due to the lack of a sufficient number of slip systems, twin nucleation and migration originate as a substantial plastic deformation mechanism in HCP metals. The paper uncovers the energetics and atomistic mechanism of the {$11\overline{2}1$} < $11\overline{2}6$ > which is one of the most prominent twin modes in HCP materials that has not been fully understood. In view of corrugated {$11\overline{2}1$} interfaces, the positioning of lattice/motif atoms needs to be clarified. First, we establish the initial twin boundary (TB) structure unambiguously via the lattice offsets resulting in volume invariancy and correct relative positioning of the twin variants. Secondly, the TB migration mechanism is determined from a crystallographic (zero net shuffle, $Σ\vec{s}$ = 0) and energetic standpoints (minimum energy path). The Generalized Planar Fault Energy (GPFE) curves are calculated for Ti, Hf, Mg, and Zr. Such GPFE curves for this twin mode are calculated for the first time, and point to unusually high unstable energies (300-850 mJ/m 2 ), and low migration barriers (<60 mJ/m 2 ) for twinning accompanied with large shuffle magnitudes, |$\vec{s}$|, comparable to the Burger’s vector (|$\vec{s}$| ≅ $b_e$ > 0.44Å)

36 MATERIALS SCIENCE↗
DOE OSTI2025

An energetic link between order and strength in metals: A nanocrystalline strength limit in high-entropy alloys and intermetallic compounds

The metallurgy and materials communities have long understood and exploited fundamental links between chemical and structural ordering in metallic solids to tailor their mechanical properties. We extend these ideas to include prediction of the nanocrystalline strength limit in high-entropy alloys and intermetallic compounds, where a breakdown occurs in the classical Hall-Petch strengthening behavior. The highest reported strength achievable through alloying has rapidly climbed and given rise to new classifications of materials with extraordinary properties, with a notable case being nanocrystalline metals. High-entropy alloys (chemically disordered, concentrated solid solutions) and intermetallic compounds are two boundary cases of how tailored order can be used to manipulate mechanical behavior. Here, we show that the complex electronic-structure mechanisms governing the peak strength of alloys and pure metals can be reduced to a few physically meaningful parameters based on their atomic arrangements and used – with no fitting parameters – to predict the maximum strength of these materials. This includes a generalized energy-based accounting for the degree of structural and chemical ordering that allows for rapid and reasonably accurate prediction of peak strength (validated in the nanocrystalline limit) as a function of temperature. Predictions of maximum strength based on the activation energy (with all materials properties derived from DFT calculations or experiments) for a stress-driven transition to an amorphous state is shown to accurately describe the breakdown in Hall-Petch behavior at the smallest crystallite sizes for pure metals, intermetallic compounds, high-entropy alloys, and metallic glasses. Further, this activation energy is also shown to be directly proportional to interstitial electronic charge density, which is a good predictor of ductility, stiffness (moduli), and phase stability in high-entropy alloys and solid metals generally. The proposed framework suggests the possibility of coupling ordering and intrinsic strength to mechanisms like dislocation nucleation, hydrogen embrittlement, and transport properties, such as through correlations between the activation energies for amorphization with stacking-fault and grain boundary energies. It additionally opens the prospect for greatly accelerated structural materials design and development to address materials challenges limiting more sustainable and efficient use of energy.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Utah FORGE 5-2557: Trixial Shear and Wellbore Breakout Tests Report and Data

Included are a report and data from triaxial shear tests on simulated Sierra White fault gouge and a borehole stimulation experiment. This serves as a progress report for the Role of Fluid and Temperature in Fracture Mechanics and Coupled Thermo-Hydro-Mechanical-Chemical (THMC) Processes for Enhanced Geothermal Systems project by Purdue University (Utah FORGE R&D project 5-2557). Tests were done with Sierra White granite (SWG) to investigate slip mechanisms and to evaluate the fracture initiation and propagation from a geothermal borehole. Raw data is provided alongside a report on all experimental testing protocols, experimental design, and results.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Dislocation line tension model to improve understanding of the effects of hydrogen on the deformation of structural materials

Decarbonization efforts highlight hydrogen as an attractive alternative to fossil fuels, but its tendency to embrittle structural metals demands careful consideration when designing hydrogen infrastructure. Moreover, the mechanisms by which hydrogen degrades these materials are still being elucidated. The current work develops new computational tools to quantify the different contributions of hydrogen to the energy barrier of cross-slip, a key deformation mechanism. Novel features are implemented to a line tension model, which include the use of non-singular dislocation interactions, character-dependent dislocation energies and simulations of the constriction configurations. A new molecular dynamics technique is developed to calculate the interaction energy between the partials of a dissociated dislocation via fixing the centers of mass of the regions below and above the Shockley partials and performing time-averaged calculations. Hydrogen is found to impact the stacking fault width of dislocations in different ways depending on their characters: it decreases for dislocations with a character θ > 30°, remains unchanged for θ = 30° and increases for θ < 30°. The latter regime is a newly identified mechanism by which hydrogen inhibits cross-slip. Moreover, formation of nano-hydrides is predicted to occur around screw dislocations for high hydrogen concentrations, a phenomenon previously identified only in dislocations with an edge component. If nano-hydrides develop, their influence extending the equilibrium stacking fault width and increasing both the constriction and cross-slip energy barriers dominate over all other hydrogen contributions. The theory and tools developed will pave the way towards a comprehensive understanding of hydrogen-dislocation interactions in structural metals.

08 HYDROGEN↗
DOE OSTI2025

Developing reliable machine learning interatomic potential for Fe–Cr–Ni austenitic alloys

Gaining atomistic understanding of mechanical behavior of heat-resistant structural materials such as Fe–Cr–Ni-based alloys requires an approach with an accuracy close to density functional theory (DFT) that considers the intrinsic properties of the bulk lattice and important defects such as stacking faults, grain boundaries, and surfaces. This work aims to develop reliable machine learning interatomic potential (MLIAP) at cross-scale for Fe–Cr–Ni ternary alloys with a focus on the face-centered-cubic (fcc) solid solution structure. Leveraging the advantages of moment tensor potentials, which typically necessitate a relatively small training dataset and enable rapid calculations using the large-scale atomic/molecular massively parallel simulator package, we ensure the stability and accuracy of the trained potentials. Important defects such as stacking faults, grain boundaries, and surfaces for wide-range compositions are investigated. Structural, thermal, elastic, and defect properties are determined from molecular dynamics simulations comprising several thousand atoms, generated via canonical Monte Carlo simulations guided by the trained potential. The trained potential allows efficient atomic simulations of structural, thermal, and mechanical properties of fcc Fe–Cr–Ni solid solution alloys as a function of composition and temperature. Therefore, the MLIAP approach represents a major advancement from DFT calculations that are limited to small simulation sizes and traditional molecular dynamics simulations using relatively low accuracy potentials. Furthermore, this work outlines a practical foundation for further investigating the structural evolution and mechanical behavior of austenitic stainless steel and nickel-based alloys in a wide array of applications in extreme environments.

Crystal structure↗
DOE OSTI2020

Short-range order and its impact on the CrCoNi medium-entropy alloy

Traditional metallic alloys are mixtures of elements in which the atoms of minority species tend to be distributed randomly if they are below their solubility limit, or to form secondary phases if they are above it. The concept of multiple-principal-element alloys has recently expanded this view, as these materials are single-phase solid solutions of generally equiatomic mixtures of metallic elements. This group of materials has received much interest owing to their enhanced mechanical properties 1,2,3,4,5 . They are usually called medium-entropy alloys in ternary systems and high-entropy alloys in quaternary or quinary systems, alluding to their high degree of configurational entropy. However, the question has remained as to how random these solid solutions actually are, with the influence of short-range order being suggested in computational simulations but not seen experimentally 6,7 . In this paper we report the observation, using energy-filtered transmission electron microscopy, of structural features attributable to short-range order in the CrCoNi medium-entropy alloy. Increasing amounts of such order give rise to both higher stacking-fault energy and hardness. These findings suggest that the degree of local ordering at the nanometre scale can be tailored through thermomechanical processing, providing a new avenue for tuning the mechanical properties of medium- and high-entropy alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Deformation mechanisms in single crystal Ni-based concentrated solid solution alloys by nanoindentation

Nanoindentation is a critical technique to probe mechanical properties at the micrometer and sub-micrometer scales, accompanied by challenges from indentation size effect, pile-up/sink-in effect, and strain rate sensitivity. In this work, different nanoindentation techniques have been employed to explore Ni-based concentrated solid solution alloys (CSAs) with the addition of 3d transition metal elements including Co, Cr, Mn, and Fe, including unique single-crystal Ni, NiCo, NiFe, Ni 80 Cr 20 , and NiCoFeCr samples with (100) surfaces. A procedure of nanoindentation tests and data analysis/correction have been developed, and a data set of hardness, elastic modulus, strain rate sensitivity, and activation volume for Ni-based CSAs are provided, including the less explored binary alloys such as Ni 80 Cr 20 and Ni 80 Mn 20 . The results show that the type of alloying elements is more critical than the number of elements in strengthening: Co does not provide strengthening in NiCo, while Cr, Mn, and Fe are effective strengthening elements. Cr is the most effective among all the 3d transition metal elements. Furthermore, atomic-level lattice distortion is responsible for the strengthening and the role of stacking fault energy is insignificant in Ni-based CSAs at room temperature. In summary, nanoindentation shows increasing promise as a reliable and fast tool to provide comprehensive mechanical information for new alloy design and development.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Off-policy deep reinforcement learning with automatic entropy adjustment for adaptive online grid emergency control

Electric overloading conditions and contingencies put modern power systems at risk of voltage collapse and blackouts. Load shedding is crucial to maintain voltage stability for grid emergency control. However, the rule- or model-based schemes rely on accurate dynamic system models and face considerable challenges in adapting to various operating conditions and uncertain event occurrences. Here, to address these issues, this paper proposes a novel deep reinforcement learning (DRL)-based voltage stability control algorithm with automatic entropy adjustment (AEA) for grid emergency control. Various dynamic network components for complex system operations are modeled to construct the DRL environment. An off-policy soft actor-critic architecture is developed to maximize the expected reward and policy entropy simultaneously. The AEA mechanism is proposed to facilitate the policy maximum entropy procedure, and the proposed method can automatically provide effective discrete and continuous actions against various fault scenarios. Our approach accomplishes high sampling efficiency, scalability, and auto-adaptivity of the control policies under high uncertainties. Comparative studies with the existing DRL-based control methods in IEEE benchmarks indicate salient performance improvement of the proposed method for dynamic system emergency control.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Structural and magnetic properties of hard magnetic system Ce(Co 1 -Fe ) 4.4 Cu 0.6 (0 ≤ x ≤ 0.19)

The Ce(Co 1 -Fe ) 4.4 Cu 0.6 (0 ≤ x ≤ 0.19) is a composite, hard magnetic system that is based on the CaCu 5 -type structure (1:5). It shows both, unique magnetic and microstructural features that are essential for permanent magnets, e.g., exceptional squareness of the 2nd. quadrant of the magnetization loops and microstructural features typically needed for pinning. Samples solidified in alumina crucibles are coarse-grained and often clearly faceted and readily align in a magnetic field. X-ray, SEM, and TEM analyses show a 1:5-type single-phase material when quenched from high temperature, which, after heat treatment, transforms into a laminar coherent nanostructure through the formation of a dense array of extended intercalated regions. Furthermore, these extended intercalated regions are comprised of segments of the Ce 2 Ni 7 –type structure (2:7) which segregate into various closely related precipitates forming a nanostructure similar to the SmCo 5 - Sm 2 Co 17 composites seen in Sm-Co permanent magnets. Based on TEM and Lorentz microscopy of well-aligned single grain particles, the magnetic domains’ reversal mechanism is regulated by anisotropy fluctuations occurring along the easy direction of magnetization and strong exchange interactions between the matrix and defects (e.g.: stacking faults). Lorentz microscopy suggests the domain wall is not physically pinned by the defect, but rather is offset/deflected when it interacts with the defect. The Lorentz and magnetization data suggest that defects cause a bending of the moment away from the c axis inside the grains.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Stacking faults and alternate crystal structures for the shape-memory alloy NiTi

Here, we use ab initio calculations to study the role of stacking faults in connecting the high-temperature B2 and the theoretically predicted low-temperature B33 NiTi phases. In contrast with prior work, we describe the B 2 → B 33 phase transformation in terms of alternate bilayer shifts by 1 2 [100] on the ( 011 ) B 2 plane, obtaining a viable pathway; the same mechanism could also work with the B19 parent phase. We then examine B33-like structures built from alternate stacking sequences of B19 bilayers, constructed to have monoclinic tilt angles close to the experimentally reported NiTi B19' martensite, and find four low-energy stacking-fault variants with energies 5.8–8.5 meV/atom above the calculated B19' martensite structure, suggesting that such structures might appear as a part of the NiTi martensite phase at low temperatures. Investigating further the occurrence of specific coordinated planar shifts in NiTi systems, we report a dynamically stable NiTi B27 phase and find that it is only 1.2 meV/atom above the calculated B33 ground-state structure, thus having a potential to also play a role in NiTi martensitic phase transformation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An Online Search Method for Representative Risky Fault Chains Based on Reinforcement Learning and Knowledge Transfer

In the analysis of cascading outages and blackouts in power systems, risky cascading fault chains should be accurately identified in order to do further block or alleviate blackouts. However, the huge computational burden makes online analysis difficult. In this paper, an online search method for representative risky fault chains based on reinforcement learning and knowledge transfer is proposed. This method aims at promoting efficiency by exploiting similarities of adjacent power flow snapshots in operations. After the “representative risky fault chain” is defined, a framework of tree search based on Markov Decision Process and Q-learning is constructed. The knowledge in past runs is accumulated offline and then applied online, with a mechanism of knowledge transition and extension. The proposed learning based approach is verified on an illustrative 39-bus system with different loading levels, and simulations are carried out on a realworld 1000-bus power grid in China to show the effectiveness and efficiency of the proposed approach.

Blackout↗
DOE OSTI2021

In-situ TEM observation of shear induced microstructure evolution in Cu-Nb alloy

Phase boundaries in multiphase alloys govern defect interaction and chemical intermixing across different phases during plastic deformation. Dynamic interaction of defects with phase boundaries in multiphase alloys, especially for immiscible alloys, has been topic of significant research interest in recent years. In this work, we describe a novel approach for carrying out in-situ TEM shear deformation to directly observe interfacial microstructural evolution of a Cu-Nb alloy. A unique double shear specimen geometry is microfabricated by a focused ion beam technique to apply shear deformation upon push loading inside the TEM. From the real-time observation, we discover that the phase boundary with a zigzag morphology effectively blocks stacking faults nucleated in a Cu grain from slipping into a Nb grain. Meanwhile, the Cu phase bears the most plastic deformation through slip or twinning mechanisms. This work sheds light on understanding the shear deformation and the behavior of phase boundaries in multiphase alloys during shear deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

High Energy Arcing Fault (HEAF): Sandia National Laboratories 2023 Report

High Energy Arcing Faults (HEAFs) are hazardous events in which an electrical arc leads to the rapid release of energy in the form of heat, vaporized metal, and mechanical force. In Nuclear Power Plants (NPPs), these events are often accompanied by loss of essential power and complicated shutdowns. To confirm the probabilistic risk analysis (PRA) methodology in NUREG/CR-6850, which was formulated based on limited observational data, the NRC led an international experimental campaign from 2014 to 2016. The results of these experiments uncovered an unexpected hazard posed by aluminum components in or near electrical equipment and the potential for unanalyzed equipment failures. Sandia National Laboratories (SNL), in support of the NRC work, collaborated with NIST, BSI, KEMA, and NRC to support the full-scale HEAF test campaign in 2023. SNL provided high speed and real time from visible and infrared video/data of tests that collected data from copper and aluminum busses from switchgears and bus-ducts. Part of SNL work was to place cameras with high-speed data collection capability at different vantage points that provide the NRC a more complete and granular view of the test events.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

High Energy Arcing Fault (HEAF) Photometrics 2022 Test Report

High Energy Arcing Faults (HEAFs) are hazardous events in which an electrical arc leads to the rapid release of energy in the form of heat, vaporized metal, and mechanical force. In Nuclear Power Plants, these events are often accompanied by loss of essential power and complicated shutdowns. To confirm the probabilistic risk analysis (PRA) methodology in NUREG/CR-6850, which was formulated based on limited observational data, the NRC led an international experimental campaign from 2014 to 2016. The results of these experiments uncovered an unexpected hazard posed by aluminum components in or near electrical equipment and the potential for unanalyzed equipment failures. Sandia National Laboratories (SNL), in support of the NRC work, collaborated with NIST, BSI, KEMA, and NRC to support the full-scale HEAF test campaign in 2022. SNL provided high speed visible and infrared video/data of ten tests that collected data from HEAFs originated on copper and aluminum buses inside switchgears and bus ducts. Part of the SNL scope was to place cameras with high-speed data collection at different vantage points within the test facility to provide NRC a more complete and granular view of the test events.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Deciphering the multiple deformation mechanisms responsible for sustained work hardening in a FeCrCoNi medium entropy alloy

Two important and desirable properties of materials for most structural applications are high tensile strength and ductility, which typically require high work hardening to delay necking. Here, in this work, we designed and tensile tested a face-centered cubic (fcc) Fe-Cr-Co-Ni medium-entropy alloy in which multiple deformation mechanisms are triggered during tensile loading at different temperatures to induce sustained work hardening. Our strategy involved control of the relative stabilities of the fcc, hcp (hexagonal close-packed), and bcc (body-centered cubic) phases in this quaternary system via high-throughput thermodynamic calculations. This alloy not only exhibits extensive deformation-induced nanotwinning at room temperature, but also displays a two-step sequential phase transformation [γ (fcc) → ε (hcp) martensite → α’ (bcc) martensite] at 77 K, which contrasts with the single-step phase transformation [γ → ε martensite] observed in many other fcc high/medium entropy alloys with a low stacking fault energy. The sequence of phase transformation at 77K was supported by first-principles density functional theory calculations. This work provides new templates for the design of alloys capable of multiple deformation mechanisms for sustained work hardening.

36 MATERIALS SCIENCE↗
DOE OSTI2023

3-D Simulations of earthquakes rupture jumps: 1. Homogeneous pre-stress conditions

SUMMARY Observational and modelling studies indicate that earthquake ruptures can jump between fault sections as large as ∼3 and ∼5 km for compressional and extensional offsets, respectively. Here, we compare characteristics of the rupture jump process on parallel but offset fault sections from traditional 3-D dynamic rupture simulations governed by slip weakening friction using the finite element code, FaultMod, to those from quasi-dynamic simulations governed by rate- and state-dependent friction (rate-state friction) using the code RSQSim. These simulations use spatially uniform initial stresses. For a variety of measures the rupture renucleation position on the offset fault, the rate-state friction and slip weakening friction models produce very similar results. The principal difference is the additional occurrence of delayed rupture jumps that arise from the time- and stress-dependent nucleation that is characteristic of rate-state friction. For immediate rupture jumps, models with slip weakening friction span greater offsets than those with rate-state friction. However the jump distances are nearly identical when delayed rupture jumps are included in the comparisons. We propose that delayed rupture jumps are the likely mechanism for adjacent large-earthquake pairs and clusters. Based on the similarity of renucleation positions with both dynamic and quasi-dynamic models, we conclude that the renucleation positions for rupture initiation on the receiver fault (separated by less than ∼3 km from the source fault) are primarily controlled by static stress changes induced by slip on the initiating fault. However, in light of the slightly greater maximum jump distances (>3 km) seen with the dynamic slip weakening friction model, dynamic stress changes from seismic waves play an increasingly important role as offset distances increase.

, RSQSim↗
DOE OSTI2023

LAVA 1.0: A general-purpose python toolkit for calculation of material properties with LAMMPS and VASP

Here, we introduce LAVA, a general-purpose python toolkit to provide user-friendly and high throughput calculations for material properties using both LAMMPS and VASP. It contains a set of classes as well as pre-processing and post-processing functions to prepare, execute and extract information from LAMMPS/VASP simulations. An overview of the program structure is provided. The current version contains modules to calculate elastic and mechanical properties such as lattice constant, cohesive energy, cold curve, elastic constants, bulk and shear modulus, volume conserving/non-conserving deformation path, vacancy/interstitial formation energy, surface energy, stacking fault energy, melting point, radial distribution function, and thermal expansion. These functionalities are demonstrated for different interatomic potentials and DFT calculations in Al.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Innovations in underground hydrogen storage with multiphysics simulations, optimization, and monitoring: A review

Underground Hydrogen Storage (UHS) is a promising solution for large-scale energy storage and a critical component in advancing low-carbon energy system. Ensuring the safety and efficiency of UHS necessitates a comprehensive understanding of multiphysical interactions driven by cyclic pore fluid pressure fluctuations and coupled physicochemical processes. Here, this review examines the key geomechanical responses in UHS, including rock property variations under cyclic loading, fracture evolution and propagation, reservoir stress sensitivity, and fault stability. It also explores the impact of geochemical and microbial reactions on geomechanical characteristics. We provide an in-depth analysis of Thermal-Hydraulic-Mechanical-Chemical (THMC) coupled numerical simulations, highlighting their potential for future multi-scale modeling. Limitations of current machine learning (ML) approaches in addressing UHS challenges are highlighted, emphasizing the need for innovative ML-based methodologies. Operational strategies for hydrogen injection and production are reviewed, focusing on safety, efficiency, and economic viability. The necessity for multi-objective optimization (MOO) to balance storage efficiency, risk mitigation, and cost-effectiveness is also discussed. Current monitoring technologies are evaluated to ensure safe and efficient UHS operations. Finally, this review identifies critical knowledge gaps and underscores the importance of advancing geomechanical understanding under multiphysics-coupling. We highlight the need for ML-driven multiphysics theories, enhanced modeling techniques, and robust optimization strategies to improve UHS performance. This study serves as a comprehensive reference for future research and the large-scale implementation of UHS systems.

25 ENERGY STORAGE↗