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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Comparison of the Thermal Stability in Equal‐Channel‐Angular‐Pressed and High‐Pressure‐Torsion‐Processed Fe–21Cr–5Al Alloy

Nanostructured steels are expected to have enhanced irradiation tolerance and improved strength. However, they suffer from poor microstructural stability at elevated temperatures. In this study, Fe–21Cr–5Al–0.026C (wt%) Kanthal D (KD) alloy belonging to a class of (FeCrAl) alloys considered for accident‐tolerant fuel cladding in light‐water reactors is nanostructured using two severe plastic deformation techniques of equal‐channel angular pressing (ECAP) and high‐pressure torsion (HPT), and their thermal stability between 500–700 °C is studied and compared. ECAP KD is found to be thermally stable up to 500 °C, whereas HPT KD is unstable at 500 °C. Microstructural characterization reveals that ECAP KD undergoes recovery at 550 °C and recrystallization above 600 °C, while HPT KD shows continuous grain growth after annealing above 500 °C. Enhanced thermal stability of ECAP KD is from significant fraction (>50%) of low‐angle grain boundaries (GBs) (misorientation angle 2–15°) stabilizing the microstructure due to their low mobility. Small grain sizes, a high fraction (>80%) of high‐angle GBs (misorientation angle >15°) and accordingly a large amount of stored GB energy, serve as the driving force for HPT KD to undergo grain growth instead of recrystallization driven by excess stored strain energy.

Arivu, Maalavan↗
DOE OSTI2021

Formation of dislocations via misfit strain across interfaces in epitaxial BaTiO 3 and SrIrO 3 heterostructures

Abstract Dislocations often occur in thin films with large misfit strain as a result of strain energy accumulation and can drastically change the film properties. Here the structure and dislocations in oxide heterostructures with large misfit strain are investigated on atomic scale. When grown on SrTiO 3 (001), the dislocations in both the monolithic BaTiO 3 thin film and its superlattices with SrIrO 3 appear above a critical thickness around 6 nm. The edge component of the dislocations is seen in both cases with the Burgers vector of a ⟨100⟩. However, compared to monolithic BaTiO 3 , the dislocation density is slightly lower in BaTiO 3 /SrIrO 3 superlattices. In the superlattice, when considering the SrTiO 3 lattice constant as the reference, BaTiO 3 has a larger misfit strain comparing with SrIrO 3 . It is found that in both cases, the formation of dislocation is only affected by the critical thickness of the film with larger lattice misfit (BaTiO 3 ), regardless of the existence of a strong octahedral tilt/rotation mismatch at BaTiO 3 /SrIrO 3 interface. Our findings suggest that it is possible to control the position of dislocations, an important step toward defect engineering.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Machine learning for deep elastic strain engineering of semiconductor electronic band structure and effective mass

Abstract The controlled introduction of elastic strains is an appealing strategy for modulating the physical properties of semiconductor materials. With the recent discovery of large elastic deformation in nanoscale specimens as diverse as silicon and diamond, employing this strategy to improve device performance necessitates first-principles computations of the fundamental electronic band structure and target figures-of-merit, through the design of an optimal straining pathway. Such simulations, however, call for approaches that combine deep learning algorithms and physics of deformation with band structure calculations to custom-design electronic and optical properties. Motivated by this challenge, we present here details of a machine learning framework involving convolutional neural networks to represent the topology and curvature of band structures in k -space. These calculations enable us to identify ways in which the physical properties can be altered through “deep” elastic strain engineering up to a large fraction of the ideal strain. Algorithms capable of active learning and informed by the underlying physics were presented here for predicting the bandgap and the band structure. By training a surrogate model with ab initio computational data, our method can identify the most efficient strain energy pathway to realize physical property changes. The power of this method is further demonstrated with results from the prediction of strain states that influence the effective electron mass. We illustrate the applications of the method with specific results for diamonds, although the general deep learning technique presented here is potentially useful for optimizing the physical properties of a wide variety of semiconductor materials.

Tsymbalov, Evgenii↗
DOE OSTI2023

A prediction of the thermodynamic, thermophysical, and mechanical properties of CrTaO 4 from first principles

It is reported that the self-forming CrTaO 4 oxide scale can protect refractory high-entropy alloys from oxidation, superior to Cr 2 O 3 . In this paper, the phase stability, mechanical, and thermal properties of three polymorphous phases of CrTaO 4 are systematically investigated from first-principles density functional theory calculations. The mechanical properties predicted using the strain–energy methods indicated that all three phases are mechanically stable. The temperature dependence of elastic constants and polycrystalline moduli of three phases demonstrated the thermal softening as temperature increase. The Helmholtz-free energies as a function of volume and temperature are derived from phonon dispersions within the quasi-harmonic approximation at six strained volumes. The calculated apparent bulk coefficients of thermal expansion of these three phases are evaluated, the highest value approximately 13.4× 10 –6 K –1 within a temperature range of 500–2000 K for the rutile I4 1 md phase. The lattice thermal conductivity calculated by the Debye–Callaway model suggested that the rutile type I4 1 md phase has the lowest value of approximately 2.1 W/m/K at 1800 K. The other two phases, C2/m and P2/c, exhibit higher values due to relatively lower Grüneisen parameters and larger phonon velocities. The melting point of CrTaO 4 is predicted to be between 1975 and 2449 K using ab initio molecular dynamics simulations. Finally, this work provides a comprehensive theoretical understanding of the thermodynamic, mechanical, and thermal properties for the new material CrTaO 4 and serves as an example of a viable computational design strategy for improved oxidation resistance of refractory alloys at high temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Physics augmented machine learning discovery of composition-dependent constitutive laws for 3D printed digital materials

Multi-material 3D printing, particularly through polymer jetting, enables the fabrication of digital materials by mixing distinct photopolymers at the micron scale within a single build to create a composite with tunable mechanical properties. Here, this work presents an integrated experimental and computational investigation into the composition-dependent mechanical behavior of 3D printed digital materials. We experimentally characterize five formulations, combining soft and rigid UV-cured polymers under uniaxial tension and torsion across three strain and twist rates. The results reveal nonlinear and rate-dependent responses that strongly depend on composition. To model this behavior, we develop a physics-augmented neural network (PANN) that combines a partially input convex neural network (pICNN) for learning the composition-dependent hyperelastic strain energy function with a quasi-linear viscoelastic (QLV) formulation for time-dependent response. The pICNN ensures convexity with respect to strain invariants while allowing non-convex dependence on composition. To enhance interpretability, we apply $L_0$ sparsification. For the time-dependent response, we introduce a multilayer perceptron (MLP) to predict viscoelastic relaxation parameters from composition. The proposed model accurately captures the nonlinear, rate-dependent behavior of 3D printed digital materials in both uniaxial tension and torsion, achieving high predictive accuracy for interpolated material compositions. This approach provides a scalable framework for automated, composition-aware constitutive model discovery for multi-material 3D printing.

Constitutive modeling↗
DOE OSTI2020

Modeling of the thermo-mechanical response and texture evolution of WE43 Mg alloy in the dynamic recrystallization regime using a viscoplastic self-consistent formulation

This paper presents a microstructure sensitive model for predicting mechanical response and texture evolution of metals in the dynamic recrystallization regime. A recently proposed viscoplastic self-consistent (VPSC) formulation for the prediction of recrystallization driven by strain energy and intragranular misorientation is extended to hexagonal close-packed (hcp) metals. The model is applied to the dynamic recrystallization of magnesium alloy WE43 at different temperatures and strain rates. Model predictions in terms of stress-strain response and texture evolution are compared to the experimental measurements and acceptable agreement is achieved. According to the model predictions, superplastic behavior of nuclei was found to be the dominant softening mechanism at high temperatures and low strain rates. High concentration of precipitates at the grain boundaries and presence of alloying elements are the likely causes of low boundary mobility, resulting in nucleation dominated dynamic recrystallization. Relatively strong basal compression textures indicate dominant activity of basal slip, which can be achieved only through large difference in slip resistance between soft basal and hard prismatic and pyramidal modes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Role of tilt grain boundaries on the structural integrity of WSe 2 monolayers

Transition metal dichalcogenides (TMDCs) are potential materials for future optoelectronic devices. Grain boundaries (GBs) can significantly influence the optoelectronic properties of TMDC materials. Here, we have investigated the mechanical characteristics of tungsten diselenide (WSe 2 ) monolayers and failure process with symmetric tilt GBs using ReaxFF molecular dynamics simulations. In particular, the effects of topological defects, loading rates, and temperatures are investigated. We considered nine different grain boundary structures of monolayer WSe 2 , of which six are armchair (AC) tilt structures, and the remaining three are zigzag (ZZ) tilt structures. Our results indicate that both tensile strength and fracture strain of WSe 2 with symmetric tilt GBs decrease as the temperature increases. We revealed an interfacial phase transition for high-angle GBs reduces the elastic strain energy within the interface at finite temperatures. Furthermore, brittle cracking is the dominant failure mode in the WSe 2 monolayer with tilted GBs. WSe 2 GB structures showed more strain rate sensitivity at high temperatures than at low temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Anomalous softening of 3D printed elastomeric foam irradiated under compressive strain

Elastomeric foam is an essential component in many industrial and technological settings, primarily as thermal insulators and as positional/mechanical support cushions. In particular, silicone foam is utilized in harsh environments due to exceptional thermal and chemical stability. Under service conditions within certain applications such material gets exposed to a high dosage of gamma radiation, which can permanently alter the material’s structural and mechanical response properties. Most studies on gamma-exposure under inert or oxidative atmosphere indicate hardening of silicone foam, which is attributed to radiation-induced enhancement in chemical cross-linking. Here we report two contrasting effects depending on whether (non-oxidative) radiation exposure is carried out with the foam under zero or finite compressive strain. While in the former case we observe radiation-hardening consistent with previous studies, in the latter case (50% porous foam under 30% uniaxial compression) we see a monotonic decrease in Young’s modulus with increasing dosage, although solvent swelling experiments on the constituent rubber indicate a net increase in cross-link density independent of the state of strain. We quantitatively model all dose-dependent data using the Ogden Hyperfoam strain-energy function within the framework of Tobolsky two-network scheme and attribute the above anomaly to a combined effect of radiation-induced thickness change (compression set) and inherent nonlinearity in the foam’s stress-strain response.

Coarse-grained models↗
DOE OSTI2020

Phase Inversion in a Two-phase, BCC+B2, Refractory High Entropy Alloy

A phenomenon of "phase inversion", presumably the first ever experimental evidence in metallic alloys, is shown in a refractory high entropy alloy (RHEA), Al0.5NbTa0.8Ti1.5V0.2Zr. Phase inversion in crystalline solid systems is driven by the differences in elastic modulus of the two phases. Quenching from a high-temperature single phase field, the RHEA exhibits a co-continuous mixture of a disordered BCC and an ordered B2 phase, that upon isothermal annealing at 600°C develops via spinodal decomposition into a continuous B2 matrix with discrete cuboidal BCC precipitates aligned along the <001> directions. Longer term annealing at 600°C results in the development of necking constrictions along the B2 channels, eventually pinching-off these channels and making the BCC phase continuous with discrete B2 precipitates. This inversion the process can be related to the simultaneous operation of two processes:(i) spheroidization of the initially discrete cuboidal BCC precipitates driven by a reduction in the total interface energy and (ii) an increase in the stiffness of the B2 phase, relative to the BCC phase, due to chemical composition changes during annealing, forcing the B2 regions to become discrete driven by the reduction in the total elastic strain energy.

Soni, Vishal↗
DOE OSTI2020

The rupture mechanism of rubredoxin is more complex than previously thought

The surprisingly low rupture force and remarkable mechanical anisotropy of rubredoxin have been known for several years. Exploiting the first combination of steered molecular dynamics and the quantum chemical Judgement of Energy DIstribution (JEDI) analysis, the common belief that hydrogen bonds between neighboring amino acid backbones and the sulfur atoms of the central FeS 4 unit in rubredoxin determine the low mechanical resistance of the protein is invalidated. The distribution of strain energy in the central part of rubredoxin is elucidated in real-time with unprecedented detail, giving important insights into the mechanical unfolding pathway of rubredoxin. While structural anisotropy as well as the contribution of angle bendings in the FeS 4 unit have a significant influence on the mechanical properties of rubredoxin, these factors are insufficient to explain the experimentally observed low rupture force. Instead, the rupture mechanism of rubredoxin is far more complex than previously thought and requires more than just a hydrogen bond network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Learning constitutive relations using symmetric positive definite neural networks

In this work, we present a new neural-network architecture, called the Cholesky-factored symmetric positive definite neural network (SPD-NN), for modeling constitutive relations in computational mechanics. Instead of directly predicting the stress of the material, the SPD-NN trains a neural network to predict the Cholesky factor of the tangent stiffness matrix, based on which the stress is calculated in incremental form. As a result of this special structure, SPD-NN weakly imposes convexity on the strain energy function, satisfies the second order work criterion (Hill's criterion) and time consistency for path-dependent materials, and therefore improves numerical stability, especially when the SPD-NN is used in finite element simulations. Depending on the types of available data, we propose two training methods, namely direct training for strain and stress pairs and indirect training for loads and displacement pairs. We demonstrate the effectiveness of SPD-NN on hyperelastic, elasto-plastic, and multiscale fiber-reinforced plate problems from solid mechanics. The generality and robustness of SPD-NN make it a promising tool for a wide range of constitutive modeling applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Activating dislocation mediated plasticity in boron carbide through Al-doping

Dislocation slip, deformation twinning, phase transformations, and fast fracture are energy dissipation mechanisms that accommodate mechanical loading in materials. The energetically unfavorable formation of dislocation attributes to the ease of cracking and the low damage tolerance observed in superhard ceramics, notably boron carbide. Here, this work demonstrates that room temperature dislocation slip can be enabled in boron carbide by altering its chemistry through Al doping. The activation of dislocation slip is mechanistically explained by quantum mechanics simulations and electron microscopy, which indicate that strain energy is released through basal icosahedral slip facilitated by icosahedral rotation and chain bond breaking and reconfiguring. The new insight gained through this work suggests that atomic doping could be an effective strategy to tune deformation mechanisms in boron carbide, which provides a significant potential for limiting amorphization and catastrophic failure, and opens a new strategy to enhance damage tolerance in brittle ceramics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Automated Design-for-Reliability of a Power Electronics Module

The design of a power electronics module is a multiphysics problem and involves electrical, thermal, and reliability targets and constraints. Although the electrical and thermal design consider multiple aspects such as materials, geometry, and energy losses, reliability design is often limited to the selection of the attachment materials and electrical interconnect types. In this paper, we incorporate reliability metrics in the design phase by investigating the impact of package geometry on the thermomechanical behavior of the die-attachment material. To this end, we conducted thermal and power cycling simulations of a commercial six-pack power module with silicon carbide devices to compute junction temperature and strain energy density per cycle, respectively. We performed multiple simulations with different geometric dimensions and established a correlation between input features and output variables using subspace-based dimension reduction. The machine learning-based dimension reduction method serves as a surrogate model, which can be employed to identify the optimal module design from a thermal and reliability standpoint.

design-for-reliability↗
DOE OSTI2020

Optimizing Piezoelectric Material Location and Size for Multiple-Mode Vibration Reduction of Turbomachinery Blades

Modern turbomachinery blades have extremely low inherent damping, which can lead to high transient vibrations and failure through high-cycle fatigue. Smart materials enable vibration reduction while meeting strict blade requirements such as weight and aerodynamic efficiency. In particular, piezoelectric-based vibration reduction offers the potential to reduce vibration semi-actively while simultaneously harvesting sufficient energy to power the implementation. The placement and the size of the piezoelectric material is critical to the vibration reduction capabilities of the system. Furthermore, the implementation should target multiple vibration modes. In this study, we develop a procedure to optimize electromechanical coupling across multiple vibration modes for a representative turbomachinery blade with surface-mounted piezoelectric patches. Experimental validation demonstrates good coupling across three targeted modes with a single piezoelectric patch. Placing the piezoelectric material in regions of high signed strain energy for all targeted modes enables vibration reduction across all of the targeted modes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Influence of Pore Surface Structure and Contents on Shock-Induced Collapse and Energy Localization

The majority of computational efforts in the shockwave driven collapse of porosity focus on idealized pore geometries and structures. These give significant insight into the physical mechanisms in play, but omit some potentially important effects of real energetic materials. Here, to address this, we simulate pore collapse in 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) for four types of pore surfaces and fillings: an idealized cylindrical pore, a pore surface coated with polymer, a melted/amorphous pore surface, and a pore filled with gas molecules. We find that these perturbations to the pore structure result in only minor changes to the highly complex collapse mechanisms. However, significant differences in hotspot temperature are observed, with peak temperatures ranging over several hundred Kelvin. The polymer-coated system has the most effect, lowering the hotspot temperature by 300 K, and also limiting the manifestation of intramolecular strain energy that is known to induce mechanochemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

How earthquakes organize stress

Stress is not uniform in the Earth. Therefore, we must use natural experiments to measure the distribution of stresses and related quantities, rather than single values. For instance, dynamic triggering shows that faults are uniformly distributed over their loading cycles in Southern California. The probability that a fault ruptures across a barrier measures the in situ energy distribution. Fault roughness reflects the distribution of strength. These natural experiments produce observable distributions that are surprisingly consistent and suggest some degree of self-organization in the Earth’s crust. Once established, the functional form of the distributions can be used to track changes in response to earthquakes as well as to distinguish fundamentally different fault systems. Transient fault locking before stress release in laboratory experiments can be interpreted as a consequence of self-organization of fault stress. The robust self-organization of multiple variables in earthquake systems suggests that the most consequential mechanical outcome of earthquakes may be the redistribution of stress and the strain energy associated with it. The low friction on a fault during seismic slip as inferred by temperature measurements of the Tohoku earthquake is consistent with dissipation playing a secondary role to this redistribution process. Through stress redistribution and interaction, subduction zone faults tend to synchronize, perhaps due to their geometric simplicity, while the continental system of Southern California cannot synchronize, perhaps due to the complexity of the fault network. Earthquakes organize stress in the crust and produce a suite of well-defined, consistent distributions.

earthquakes↗
DOE OSTI2020

Microstructure and Mechanical Properties of Intercritically Treated Grade 91 Steel

Premature creep failures at the intercritical heat affected zone (ICHAZ) of creep-resistant steel weldments have been frequently reported. However, the creep degradation mechanism of different microstructure constituents in ICHAZ is complicated and needs further clarification. In this work, Grade 91 steel was intercritically heat-treated at a temperature (860 °C) between the critical temperatures AC1 and AC3, and a correlation between microstructure and mechanical properties of the heat-treated specimen was built. The effects of austenitization and tempering resulting from the intercritical treatment (IT) differentiated the local strain energies between the two microstructure constituents: newly transformed martensite (NTM) and over-tempered martensite (OTM). The formation of NTM grains led to a hardness increase from 247 HV0.5 in the base metal to 332 HV0.5 in the IT specimen. The ultimate tensile strength (UTS) increased from 739 MPa in the base metal to 1054 MPa in the IT specimen. Extensive growth of the OTM grains and rapid recovery of NTM grains took place simultaneously in the IT specimen during a typical tempering at 760 °C. These microstructure degradations led to a lowered hardness of 178 HV0.5, a reduced UTS of 596 MPa, and a poor creep resistance with a minimum creep strain rate of 0.49 %/h at 650 °C in an IT + tempering (ITT) specimen.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Effect of Impurities on the Redox Properties of Goethite

Iron oxide minerals regulate the flux of electrons in the environment and are important hosts for trace and minor, yet critical, elements. Here, we present the first evidence of a direct link between the local coordination environments of Ni and Zn and the redox properties of their host phase goethite (α-FeOOH), the most abundant Fe(III) (oxyhydr)oxide at Earth’s surface. Here, we used aqueous redox measurements to show that the redox potential E H 0 , and hence the mineral’s stability, follows the order: pure goethite ≥ Zn-goethite > Ni-goethite. Parallel X-ray absorption and scattering measurements demonstrate, using quantum-informed analysis, that the local coordination environment of the smaller impurity, Ni, causes more bulk strain energy than Zn, which nearly accounts for the difference in E H 0 between Ni- and Zn-goethite. Our theory-informed, experimental study reveals how two common impurities affect the stability of goethite with implications for the biogeochemical reactivity of Fe(III) (oxyhydr)oxide in mediating elemental and electron fluxes in the environment.

42 ENGINEERING↗