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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Understanding Phase and Interfacial Effects of Spall Fracture in Additively Manufactured Ti-5Al-5V-5Mo-3Cr

Additive manufactured Ti-5Al-5V-5Mo-3Cr (Ti-5553) is being considered as an AM repair material for engineering applications because of its superior strength properties compared to other titanium alloys. Here, we describe the failure mechanisms observed through computed tomography, electron backscatter diffraction (EBSD), and scanning electron microscopy (SEM) of spall damage as a result of tensile failure in as-built and annealed Ti-5553. We also investigate the phase stability in native powder, as-built and annealed Ti-5553 through diamond anvil cell (DAC) and ramp compression experiments. We then explore the effect of tensile loading on a sample containing an interface between a Ti-6Al-V4 (Ti-64) baseplate and additively manufactured Ti-5553 layer. Post-mortem materials characterization showed spallation occurred in regions of initial porosity and the interface provides a nucleation site for spall damage below the spall strength of Ti-5553. Preliminary peridynamics modeling of the dynamic experiments is described. Finally, we discuss further development of Stochastic Parallel PARticle Kinteic Simulator (SPPARKS) Monte Carlo (MC) capabilities to include the integration of alpha (α)-phase and microstructural simulations for this multiphase titanium alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Stress-controlled fatigue of HfNbTaTiZr high-entropy alloy and associated deformation and fracture mechanisms

The stress-controlled fatigue tests are carried out at a stress ratio of 0.1 and a frequency of 10 Hz, and span both low-cycle and high-cycle regimes by varying the applied stress amplitudes. The high-cycle fatigue regime gives a fatigue strength of 497 MPa and a fatigue ratio of 0.44. At equivalent conditions, the alloy's fatigue strength is greater than all other high-entropy alloys (HEAs) with reported high-cycle fatigue data, dilute body-centered cubic alloys, and many structural alloys such as steels, titanium alloys, and aluminum alloys. Through in-depth analyses of crack-propagation trajectories, fracture-surface morphologies and deformation plasticity by means of various microstructural analysis techniques and theoretical frameworks, the alloy's remarkable fatigue resistance is attributed to delayed crack initiation in the high-cycle regime, which is achieved by retarding the formation of localized persistent slip bands, and its good resistance to crack propagation in the low-cycle regime, which is accomplished by intrinsic toughening backed up by extrinsic toughening. Additionally, the stochastic nature of the fatigue data is neatly captured with a 2-parameter Weibull model.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Enhanced work hardening from oxygen-stabilized ω precipitates in an aged metastable β Ti-Nb alloy

High levels of oxygen in solid solution in Ti alloys are considered detrimental to mechanical properties because of embrittlement concerns. In metastable β titanium alloys, the formation of isothermal ω precipitates is also known to cause severe embrittlement and ductility reduction. However, oxygen has been shown to partition to the ω phase during ageing, and this partitioning behavior may potentially impact ω’s mechanical contribution. Using micropillar compression, we compared the deformation behavior of Ti-20Nb (at. %) with oxygen-stabilized ω precipitates to the behavior of oxygen-free specimens. The oxygen-stabilized microstructures showed increased compressive yield strength and enhanced work hardening behavior compared to oxygen-free specimens. In the absence of oxygen, the compressed pillars showed slip band formation and catastrophic failure, and transmission electron microscopy imaging revealed that ω precipitates were sheared within the continuous deformation channels resulting in slip localization. In contrast, oxygen-stabilized ω precipitates were harder to shear and the formation of continuous deformation channels was suppressed during compression, leading to improved work hardening behavior up to 15% strain. Furthermore, this counter-intuitive role of oxygen may offer design strategies to address the significant embrittlement and loss of ductility observed for ω-strengthened β Ti alloys without oxygen and avenues to expand the use of β Ti alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Extraction of mechanical properties of materials through deep learning from instrumented indentation

Instrumented indentation has been developed and widely utilized as one of the most versatile and practical means of extracting mechanical properties of materials. This method is particularly desirable for those applications where it is difficult to experimentally determine the mechanical properties using stress–strain data obtained from coupon specimens. Such applications include material processing and manufacturing of small and large engineering components and structures involving the following: three-dimensional (3D) printing, thin-film and multilayered structures, and integrated manufacturing of materials for coupled mechanical and functional properties. Here, we utilize the latest developments in neural networks, including a multifidelity approach whereby deep-learning algorithms are trained to extract elastoplastic properties of metals and alloys from instrumented indentation results using multiple datasets for desired levels of improved accuracy. We have established algorithms for solving inverse problems by recourse to single, dual, and multiple indentation and demonstrate that these algorithms significantly outperform traditional brute force computations and function-fitting methods. Moreover, we present several multifidelity approaches specifically for solving the inverse indentation problem which 1) significantly reduce the number of high-fidelity datasets required to achieve a given level of accuracy, 2) utilize known physical and scaling laws to improve training efficiency and accuracy, and 3) integrate simulation and experimental data for training disparate datasets to learn and minimize systematic errors. The predictive capabilities and advantages of these multifidelity methods have been assessed by direct comparisons with experimental results for indentation for different commercial alloys, including two wrought aluminum alloys and several 3D printed titanium alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Extraction of mechanical properties of materials through deep learning from instrumented indentation

Instrumented indentation has been developed and widely utilized as one of the most versatile and practical means of extracting mechanical properties of materials. This method is particularly desirable for those applications where it is difficult to experimentally determine the mechanical properties using stress–strain data obtained from coupon specimens. Such applications include material processing and manufacturing of small and large engineering components and structures involving the following: three dimensional (3D) printing, thin-film and multilayered structures, and integrated manufacturing of materials for coupled mechanical and functional properties. Here, we utilize the latest developments in neural networks, including a multifidelity approach whereby deep-learning algorithms are trained to extract elastoplastic properties of metals an d alloys from instrumented indentation results using multiple datasets for desired levels of improved accuracy. We have established algorithms for solving inverse problems by recourse to single, dual, and multiple indentation and demonstrate that these algorithms significantly outperform traditional brute force computations and function-fitting methods. Moreover, we present several multifidelity approaches specifically for solving the inverse indentation problem which 1) significantly reduce the number of high-fidelity datasets required to achieve a given level of accuracy, 2) utilize known physical and scaling laws to improve training efficiency and accuracy, and 3) integrate simulation and experimental data for training disparate datasets to learn and minimize systematic errors. The predictive capabilities and advantages of these multifidelity methods have been assessed by direct comparisons with experimental results for indentation for different commercial alloys, including two wrought aluminum alloys and several 3D printed titanium alloys.

3D printed materials, stress-strain behavior, mult↗
DOE OSTI2021

Elimination of oxygen sensitivity in α-titanium by substitutional alloying with Al

Individually, increasing the concentration of either oxygen or aluminum has a deleterious effect on the ductility of titanium alloys. For example, extremely small amounts of interstitial oxygen can severely deteriorate the tensile ductility of titanium, particularly at cryogenic temperatures. Likewise, substitutional aluminum will decrease the ductility of titanium at low-oxygen concentrations. Here, we demonstrate that, counter-intuitively, significant additions of both Al and O substantially improves both strength and ductility, with a 6-fold increase in ductility for a Ti-6Al-0.3 O alloy as compared to a Ti-0.3 O alloy. The Al and O solutes act together to increase and sustain a high strain-hardening rate by modifying the planar slip that predominates into a delocalized, three-dimensional dislocation pattern. Furthermore, the mechanism can be attributed to decreasing stacking fault energy by Al, modification of the “shuffle” mechanism of oxygen-dislocation interaction by the repulsive Al-O interaction in Ti, and micro-segregation of Al and O by the same cause.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hydrogen in disordered titania: connecting local chemistry, structure, and stoichiometry through accelerated exploration

Hydrogen incorporation in native surface oxides of metal alloys often controls the onset of metal hydriding, with implications for materials corrosion and hydrogen storage. A key representative example is titania, which forms as a passivating layer on a variety of titanium alloys for structural and functional applications. These oxides tend to be structurally diverse, featuring polymorphic phases, grain boundaries, and amorphous regions that generate a disparate set of unique local environments for hydrogen. Here, we introduce a workflow that can efficiently and accurately navigate this complexity. First, a machine learning force field, trained on ab initio molecular dynamics simulations, was used to generate amorphous configurations. Density functional theory calculations were then performed on these structures to identify local oxygen environments, which were compared against experimental observations. Second, to classify subtle differences across the disordered configuration space, we employ a graph-based sampling procedure. Finally, local hydrogen binding energies and hopping kinetics are computed using exhaustive density functional theory calculations on representative configurations. Here, we leverage this methodology to show that hydrogen binding energetics are described by local oxygen coordination, which in turn is affected by stoichiometry, and form the basis of hopping kinetics and diffusion. Together these results imply that hydrogen incorporation and transport in TiO x can be tailored through compositional engineering, with implications for improving the performance and durability of titanium-derived alloys in hydrogen environments.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Developing ductile and isotropic Ti alloy with tailored composition for laser powder bed fusion

Laser powder bed fusion (LPBF) is an advanced technology to create metallic components with complex geometry. Ti-6Al-4V (Ti64) is one of the most frequently used materials for LPBF. The intrinsic high cooling rates and ultra-high directional thermal gradient of melt, however, lead to a hierarchical structure composed of fine martensitic alpha' within columnar prior-beta grains in LPBF Ti64. This microstructure results in poor ductility and strong mechanical anisotropy in as-built Ti64 components, which largely limit their applications. Here, we report that the above shortcomings can be overcome by tailoring the alloy composition. Specifically, by reducing the aluminum content from 6 wt% to 4 wt%, the resultant LPBF Ti-4Al-4V (Ti44) alloy exhibits substantially improved ductility and mechanical isotropy. These improvements are attributed to grain refinement during solidification and the activation of multiple slip modes and twinning in the as-built material during deformation. This work offers a simple strategy to design new titanium alloys for LPBF with significantly improved ductility and isotropy.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Predictive binder jet additive manufacturing enabled by clean burn-off binder design

Binder jet additive manufacturing (BJAM) presents an avenue for advanced manufacturing of various high-value materials due to high deposition rates, scalability, and geometric flexibility. However, conventional organic binders in BJAM introduce residual carbon upon pyrolysis, often leading to imprecise alloy composition in the final sintered part. The undesirable residual carbon from binder burn-off limits the application of BJAM for high-performance alloys due to their high sensitivity to carbon addition. In this study, we have designed poly(vinylpyrrolidone-co-vinyl acetate) (PVP-VAc) as a clean burn-off binder for BJAM, where excess oxygen groups in VAc enable cleaner burn-off and reduce residual carbon retention. Compared to a widely used commercial binder, the optimized PVP-VAc binder reduced residual carbon retention by over 90% in H13 tool steel. The significant reduction in residual carbon enables predictable printing and subsequent sintering of complex H13 tool steel geometries, an alloy known to have substantial challenges around distortion due to the sintering window shifting from carbon addition. The design of a clean burnout binder provides a major path forward for BJAM by enabling new AM designs and applications for composition-sensitive high-performance alloys, such as nickel-based superalloys, titanium alloys, and high alloyed steels.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Incorporating dynamic recrystallization into a crystal plasticity model for high-temperature deformation of Ti-6Al-4V

During hot deformation of (α + β) titanium alloys, the simultaneous action of strain and temperature in the (α + β) regime facilitates dynamic recovery, dynamic recrystallization (DRX), and phase transformations via non-equilibrium paths. DRX is manifested in the form of fine recrystallized α or β grains. Here, in the present study, a two-phase crystal plasticity finite element framework (CP-DRX) has been developed which incorporates DRX kinetics into the crystal plasticity (CP) model to predict the flow characteristics of Ti-6Al-4V alloys during thermo-mechanical processing. The CP slip system parameters, as well as elastic properties from both α and β phases of Ti, are calibrated for different strain rate conditions. An EBSD-informed two-phase microstructure representation has been utilized in the CP-DRX framework to explore the time-dependent evolution of DRX microstructure and crystal orientation for different strain rate conditions. The proposed CP-DRX can capture the evolution of crystal orientation and plastic flow stress–strain response of polycrystalline Ti-6Al-4V during the deformation process. Furthermore, the proposed model is able to capture the softening behavior, observed in average stress–strain response from experiments performed using a Gleeble thermomechanical simulator and predict the recrystallization texture.

(α+ β)-Titanium (Ti) Alloys↗
DOE OSTI2022

Thermal modeling of directed energy deposition additive manufacturing using graph theory

Purpose: The purpose of this paper is to develop, apply and validate a mesh-free graph theory–based approach for rapid thermal modeling of the directed energy deposition (DED) additive manufacturing (AM) process. Design/methodology/approach: Here, the authors develop a novel mesh-free graph theory–based approach to predict the thermal history of the DED process. Subsequently, the authors validated the graph theory predicted temperature trends using experimental temperature data for DED of titanium alloy parts (Ti-6Al-4V). Temperature trends were tracked by embedding thermocouples in the substrate. The DED process was simulated using the graph theory approach, and the thermal history predictions were validated based on the data from the thermocouples. Findings: The temperature trends predicted by the graph theory approach have mean absolute percentage error of approximately 11% and root mean square error of 23°C when compared to the experimental data. Moreover, the graph theory simulation was obtained within 4 min using desktop computing resources, which is less than the build time of 25 min. By comparison, a finite element–based model required 136 min to converge to similar level of error. Research limitations/implications: This study uses data from fixed thermocouples when printing thin-wall DED parts. In the future, the authors will incorporate infrared thermal camera data from large parts. Practical implications: The DED process is particularly valuable for near-net shape manufacturing, repair and remanufacturing applications. However, DED parts are often afflicted with flaws, such as cracking and distortion. In DED, flaw formation is largely governed by the intensity and spatial distribution of heat in the part during the process, often referred to as the thermal history. Accordingly, fast and accurate thermal models to predict the thermal history are necessary to understand and preclude flaw formation. Originality/value: This paper presents a new mesh-free computational thermal modeling approach based on graph theory (network science) and applies it to DED. The approach eschews the tedious and computationally demanding meshing aspect of finite element modeling and allows rapid simulation of the thermal history in additive manufacturing. Although the graph theory has been applied to thermal modeling of laser powder bed fusion (LPBF), there are distinct phenomenological differences between DED and LPBF that necessitate substantial modifications to the graph theory approach.

42 ENGINEERING↗
DOE OSTI2022

Crystallographic ordering of Al and Sn in α-Ti

Increasing attention is being paid to α (2) Ti 3 (Al,Sn) precipitation from the α phase of titanium alloys owing to its effect on slip band formation, localisation and the implications for fatigue performance in jet engine titanium. However, the early stages of α 2 precipitation have historically been difficult to observe by electron microscopy, neutron diffraction or atom probe analysis. Here, small angle X-ray scattering is used to reexamine the phase boundary in binary Ti-Al and Ti-Sn alloys with around 500 ppmw O. It is found that the phase boundaries in the literature are approximately correct, at 6.2 wt.% Al and 16.9 wt.% Sn, and that this favours the use of Al as a solid solution strengthener over Sn for ambient temperature applications. However, once O content and phase partitioning in α + β alloys are taken into account, this implies that Al eq limits for future alloy design of critical rotating parts should be lowered substantially.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Model form and sensitivity analysis of CALPHAD-based nucleation models in b-stabilized Ti alloys

Accurate prediction of α-phase nucleation and growth in β-stabilized titanium alloys is crucial for designing heat treatments to optimize mechanical properties in additively manufactured lightweight components. Ideally, predictions of nucleation and growth would incorporate both top-down observations of past experimental heat treatments and bottom-up modeling of phase transformations; however, the appropriate method of combining these information sources is not self-evident. Combining top-down and bottom-up information requires a unified form of model that can connect between spatiotemporal scales, as well as sets of fitting parameters that can be identified by each data source. The selection of which parameters to fit to which data source can be made based on expert opinion, or by performing a sensitivity analysis. In solid-solid nucleation, direct observation of the nucleation and growth process is challenging. Most data on the heat treatment-controlled phase transformations are not in-situ. To predict the process and outcome of the nucleation, growth and coarsening of precipitates, theoretical models of the nucleation pathway are used to bridge the gap. Many sources of uncertainty affect the modeling of this nucleation process. It can be influenced by small variations in the thermomechanical processing history, chemical composition, and initial microstructure. If molecular dynamics (MD) simulations are used to determine thermodynamic quantities and inform CALPHAD modeling, additional uncertainty can be introduced and accounted for using Bayesian methods. Top-down uncertainties require additional steps to quantify. The influence of nucleation model form on the sensitivity of predictions to input parameters and physical conditions is the focus of this study. Classical nucleation theory (CNT) allows modeling to formulate the nucleation as homogeneous or, more commonly, heterogeneous. Non-classical nucleation models are also increasingly explored as a means of reconciling top-down and bottom-up data. In this study, the sensitivity of the intragranular nucleation of α in a β-annealed, slow-cooled aging (BASCA) heat treatment of β-stabilized Ti5553 alloy is explored using CNT and both heterogeneous and homogeneous assumptions. The Kampmann-Wagner Numerical model of precipitate nucleation and growth is employed. Using open-source tools (pyCalphad and thermodynamic modeling of TiMo as a surrogate system, a sensitivity analysis is performed to measure variations in key parameters, including chemical driving force, interfacial energy, and diffusivity, as they relate to predictions of precipitate number density. The inclusion of top-down and bottom-up data in selection of nucleation model form is discussed.

Rodriguez Negron, A. M.↗
DOE OSTI2020

Passivation and alloying element retention in gas atomized powders

A method for gas atomization of a titanium alloy, nickel alloy, or other alumina (Al2O3)-forming alloy wherein the atomized particles are exposed as they solidify and cool in a very short time to multiple gaseous reactive agents for the in-situ formation of a passivation reaction film on the atomized particles wherein the reaction film retains a precursor halogen alloying element that is subsequently introduced into a microstructure formed by subsequent thermally processing of the atomized particles to improve oxidation resistance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Passivation and alloying element retention in gas atomized powders

A method for gas atomization of a titanium alloy, nickel alloy, or other alumina (Al 2 O 3 )-forming alloy wherein the atomized particles are exposed as they solidify and cool in a very short time to multiple gaseous reactive agents for the in-situ formation of a passivation reaction film on the atomized particles wherein the reaction film retains a precursor halogen alloying element that is subsequently introduced into a microstructure formed by subsequent thermally processing of the atomized particles to improve oxidation resistance.

Heidloff, Andrew J.↗
DOE OSTI2024

High Strength Aluminum Additive Manufacturing

High-strength aluminum alloys for elevated temperature applications are desirable to replace heavier and more expensive titanium alloys. However, most aluminum alloys lose a large fraction of their strength at temperatures above approximately 200°C. ORNL has designed DuAlumin-3D, an alloy with nominal composition Al-9Ce-4Ni-0.5Mn-1Zr (wt.%), which utilizes the high cooling rates in additive manufacturing (AM) to achieve a refined microstructure, and thermally stable mechanical properties. DuAlumin-3D was fabricated by laser powder bed fusion and tested for its tensile mechanical properties across a range of temperature, and for its room temperature high-cycle fatigue resistance. The alloy was tested in both the as-printed and heat treated conditions, and both parallel and perpendicular to the AM build direction. The alloy was found to have anisotropic mechanical behavior in the as-printed state, but the anisotropy significantly decreased (both for tensile and fatigue properties) following heat treatment. The tensile properties significantly out-performed benchmark wrought 2219-T61 across a wide temperature range. The room temperature fatigue performance was approximately similar to 2219-T61.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Notch-tensile behavior of Al0.1CrFeCoNi high entropy alloy

Notch-tensile behavior of an Al0.1CrFeCoNi high entropy alloy (Al0.1-HEA) was studied using V-notch geometry and with local strain mapping using digital image correlation (DIC). A notch-strength ratio of 1.51 indicated notch strengthening. Further analysis of stress-strain response supplemented with microstructural analysis revealed that, while the presence of notch results in strengthening due to work hardening by twinning induced plasticity, the notch also contributes strongly to geometrical softening in the non-uniform ductility regime, and accounts for the onset of failure. The strain localization behavior of Al0.1-HEA due to the presence of V-notch was compared with three conventional alloys: Inconel 625 nickel-based superalloy, 304 stainless steel and Ti–6Al–4V titanium alloy. The study revealed that the nature of notch widening with increasing strain was dependent on material characteristics. The extent of notch widening impacted the local strain field and stress distribution, thereby influencing the propensity for crack initiation and growth. The experimental results were verified by finite element analysis.

Sinha, Subhasis↗
DOE OSTI2020

Temperature Measurement of Laser-Irradiated Metals Using Hyperspectral Imaging

Accurate noncontact surface-temperature measurements during laser-based materials processing remain challenging due to the difficulty of establishing reliable emissivity values as a function of temperature and wavelength. Direct measurement of emissivity is difficult, as the emissivity may be changing constantly in the laser-material interaction region, where the temperature gradients are extreme and surface displacement can complicate the measurement. Here, we present a hyperspectral imaging method using a multiwavelength camera to capture the spectral radiance in eight different bands and fit the wavelength-dependent radiance to Planck’s law. Time-resolved temperature measurements during microsecond pulsed-laser irradiation of a metal plate made of the titanium alloy Ti -6 Al -4 V provide temperature information about the irradiated surface with an estimated accuracy of ± 10 % . The extracted wavelength-dependent emissivity slope compares well with reported results for macroscale titanium melts obtained using IR spectroscopy, which measure temperature without any built-in assumptions about the emissivity. The results are directly applicable to temperature monitoring during welding, additive manufacturing, and semiconductor growth.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗