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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Silicon Partitioning Between Iron-Rich Metal and Silicate Melt: New Constraints From Aerodynamic Laser Levitation Furnace Experiments

The partitioning of light elements (e.g., Si, C, H, etc.) between silicate melts and iron metal alloys as a function of pressure and temperature is a critical constraint in defining the compositional evolution of planetary interiors. While there are a significant number of experimental studies in the literature that examine the various influences of oxygen fugacity, temperature, pressure, and composition on the metal-melt partitioning of silicon, it is difficult to disentangle the effects of each variable due to the nominally independent parameters (e.g., pressure, temperature, composition) being collinear. To better test for the independent effects of pressure, temperature, and melt composition on the partitioning of silicon between iron alloy and silicate melt, new high temperature (1800°–2500°C), rapid quench (~700°C/s) aerodynamic levitation laser-heating experiments in the Fe-Si-Mg-O (En65-Fa5-Si3-Fe27) system were conducted. This high temperature, low pressure method is ideal for these experiments because it eliminates the metal container as a sink for elements of interest to partition into, and it has a rapid quench rate that minimizes potential exsolution of silicon from the metal phase during quench cooling. Given the short run times of the levitation experiments (30–60 seconds), a time series at a lower temperature (1700°C) in a vertical gas-mixing muffle tube furnace was also conducted to assess equilibrium times of the bulk composition. All successful runs were imaged using back-scatter electron imaging and analyzed for phase composition using a JEOL 8530F field emission microprobe. These new data were added to a comprehensive and internally consistent data set created from published experiments, and subsequently modeled using parameters designed to minimize collinearity (e.g., optical basicity is used as a proxy for melt composition). High collinearity is found in the data set however between temperature and oxygen fugacity, precluding any model that contains both as nominally independent variables. The resulting model demonstrates a statistically significant effect of pressure, temperature, and melt composition on the partitioning of silicon in Fe-rich metal, which has implications for the formation of planetary cores in rocky planets and provides important constraints on potential bulk core compositions.

Metal↗
DOE OSTI2020

Method for controlling heat flow within a silicon melt using a heat diffusion barrier assembly

An apparatus for controlling heat flow within a melt. The apparatus may include a crucible configured to contain the melt where the melt has an exposed surface. The apparatus may also include a heater disposed below a first side of the crucible and configured to supply heat through the melt to the exposed surface, and a heat diffusion barrier assembly comprising at least one heat diffusion barrier disposed within the crucible and defining an isolation region in the melt and an outer region in the melt.

42 ENGINEERING↗
DOE OSTI2025

Operando synchrotron X-ray analysis of melt pool dynamics in an Al-Sn immiscible alloy

The melt flow in an Al-50vol.% Sn immiscible alloy, produced by single-track laser melting of Al and Sn elemental powders, was studied in real time. High-speed synchrotron X-ray imaging was used to track Al and Sn liquids’ movements, and also to examine elemental distributions in the laser tracks, complimented by electron microscopy after solidification. Key aspects, including melt pool geometry, keyhole instability, and flow dynamics (flow pattern and velocity), were examined using digital image analysis. Relatively deeper melt pools formed at 400 W and 300 mm/s exhibited greater stability, with smooth surfaces, consistent outward flow, and minor vortices near the keyhole. In contrast, shallower pools produced at higher scanning speeds (>500 mm/s) demonstrated greater instability with increased surface waviness, and stronger velocity fluctuations, leading to numerous micro-vortices and increased Al-Sn heterogeneity. Velocity scale estimations, supported by experimental observations, examined the roles of vapour pressure, Marangoni effect, buoyancy, inertial, and surface tension forces in the flow. The results revealed that vapour pressure and mechanical waves dominated at high scanning speeds (shallow pools), while Marangoni forces were equally significant in deep pools at lower speeds (300 mm/s). Buoyancy was found to have minimal impact in both cases. Furthermore, the interaction between inertial and surface tension forces played a critical role in determining the degree of waviness of the pools’ surfaces. These findings offer valuable insights into melt pool dynamics during laser processing of immiscible alloys and other metallic systems using elemental powders, and provide guidance for developing high-fidelity computational fluid dynamics models.

immiscible alloys↗
DOE OSTI2022

The solubility of titanite in silicate melt determined from growth and dissolution experiments

The solubility of titanite (CaTiSiO 5 ) in Si-rich melts was measured experimentally through growth experiments at 800–1000 °C, 0.5–1.0 GPa, log fO 2 ~ CCO–0.8, t = 72–168 h, and H 2 O = 0 to 4 wt.%, and in dissolution experiments at 925–1300 °C, 0.8 GPa, t = 18–118 h, and H 2 O = 1–10 wt.% in a piston-cylinder apparatus. Run product glasses in growth experiments were homogeneous, and iron loss suppressed ilmenite crystallization. Saturation concentrations in dissolution experiments were estimated by fitting measured diffusion profiles. Titanite solubility increases with increasing temperature and melt composition parameter \(M = {\text{ molar }}\left( {{\text{Na }} + {\text{ K }} + {\text{ 2Ca}}} \right)/\left( {{\text{Al }} \times {\text{ Si}}} \right)\) . Multiple linear regression of glass composition data from growth and dissolution experiments ( n = 29) plus 39 experiments from the LEPR database (Hirschmann et al. 2008 ) yielded the titanite solubility equation (adj. r 2 = 0.95): \(\left( {TiO_{2} } \right)^{melt} \left( {wt.\% } \right) = 0.978 \times M + 0.0048 \times T\left( K \right){-}5.90\) . This model correctly predicted undersaturation in 95% of 2344 experiments from the LEPR database that did not have titanite or rutile. Application to natural rocks yields saturation temperatures that are similar to independent temperature estimates. Finally, this equation should be useful for constraining the temperatures of titanite-saturated melts, for determining whether titanite saturation in magmatic source regions is likely, and for determining when titanite can crystallize and begin to exert an influence on melt geochemistry.

58 GEOSCIENCES↗
DOE OSTI2024

Deep-learning based artificial intelligence tool for melt pools and defect segmentation

Accelerating fabrication of additively manufactured components with precise microstructures is important for quality and qualification of built parts, as well as for a fundamental understanding of process improvement. Accomplishing this requires fast and robust characterization of melt pool geometries and structural defects in images. This paper proposes a pragmatic approach based on implementation of deep learning models and self-consistent workflow that enable systematic segmentation of defects and melt pools in optical images. Deep learning is based on an image-to-image translation–conditional generative adversarial neural network architecture. An artificial intelligence (AI) tool based on this deep learning model enables fast and incrementally more accurate predictions of the prevalent geometric features, including melt pool boundaries and printing-induced structural defects. We present statistical analysis of geometric features that is enabled by the AI tool, showing strong spatial correlation of defects and the melt pool boundaries. The correlations of widths and heights of melt pools with dataset processing parameters show the highest sensitivity to thermal influences resulting from laser passes in adjacent and subsequent layer passes. The presented models and tools are demonstrated on the aluminum alloy and datasets produced with different sets of processing parameters. However, they have universal quality and could easily be adapted to different material compositions. The method can be easily generalized to microstructural characterizations other than optical microscopy.

additive manufacturing↗
DOE OSTI2025

Vector-level feedforward control of LPBF melt pool area using a physics-based thermal model

Laser powder bed fusion (LPBF) is an additive manufacturing technique that has gained popularity thanks to its ability to produce geometrically complex, fully dense metal parts. However, these parts are prone to internal defects and geometric inaccuracies, stemming in part from variations in the melt pool. Here, this paper proposes a novel vector-level feedforward control framework for regulating melt pool area in LPBF. By decoupling part-scale thermal behavior from small-scale melt pool physics, the controller provides a scale-agnostic prediction of melt pool area and efficient optimization over it. This is done by operating on two coupled lightweight models: a finite-difference thermal model that efficiently captures vector-level temperature fields and a reduced-order, analytical melt pool model. Each model is calibrated separately with minimal single-track and 2D experiments, and the framework is validated on a complex 3D geometry in both Inconel 718 and 316L stainless steel. Results showed that feedforward vector-level laser power scheduling reduced geometric inaccuracy in key dimensions by 62%, overall porosity by 16.5%, and photodiode root-mean-squared deviation by 38.5% on average. Overall, this modular, data-efficient approach demonstrates that proactively compensating for known thermal effects can significantly improve part quality while remaining computationally efficient and readily extensible to other materials and machines.

Additive manufacturing↗
DOE OSTI2022

Revealing melt flow instabilities in laser powder bed fusion additive manufacturing of aluminum alloy via in-situ high-speed X-ray imaging

Laser metal additive manufacturing technologies enable the fabrication of geometrically and compositionally complex parts unachievable by conventional manufacturing methods. However, the certification and qualification of additively manufactured parts are greatly hindered by the stochastic melt flow instabilities intrinsic to the process, which has not been explicitly revealed by direct observation. Here, we report the mechanisms of the melt flow instabilities in laser powder bed fusion additive manufacturing process revealed by in-situ high-speed high-resolution synchrotron X-ray imaging. Here we identified powder/droplet impact, significant keyhole oscillation, and melting-mode switching as three major mechanisms for causing melt flow instabilities. We demonstrated the detrimental consequences of these instabilities brought to the process, and presented new understanding on the melt flow evolution and keyhole oscillation. This work provides critical insights into process instabilities during laser metal additive manufacturing, which may guide the development of instability mitigation approaches. The results reported here are also important for the development and validation of high-fidelity computational models.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Glass production rate in an electric melter: Melting rate correlation and primary foam stability

Waste loading and melting rate are major factors determining the lifecycle of nuclear waste disposal by vitrification in electric melters in which the heat to the cold cap is delivered from the melt pool. One of the crucial parameters that affect the rate of melting is the temperature at which the primary foam collapses at the cold cap bottom. Further, apart from the transient glass-forming melt viscosity, primary foam stability is affected by the shear stress imposed by the flow in the melt pool and the presence of residual solid particles.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Eutectic melting of alloy microparticles upon low velocity impact

Although impact melting has been quantified in a number of pure metals, alloyed microparticles have access to low melting-point eutectics that can promote earlier melting. Through real-time monitoring of single particle impacts resolved at the nanosecond- and micron-scales, we explore the impact melting of AA7075 from high velocities, where it is abundant and clear, to velocities as low as ∼269 m/s. Here, by using a hard substrate to isolate the deformation largely to the particle, we show that the adiabatic heat produced by the plasticity of the impact can explain the onset of melting at low velocity.

Additive manufacturing↗
DOE OSTI2020

Effect of the Ionic Liquid Structure on the Melt Processability of Polyacrylonitrile Fibers

The production of high-strength carbon fibers is an energy-intensive process, where a significant cost involves the wet or dry-spinning of polyacrylonitrile (PAN) fiber precursors. Melt-spinning PAN fibers would allow for significant reduction in the production cost and production hazards. Ionic liquids (ILs) are an attractive fiber-processing medium because of their negligible vapor pressure and low toxicity. In addition, they are carbon-forming precursors; upon carbonization, residual ILs can enhance the carbon yield, although primarily useful for plasticized melt-spinning of PAN precursor fibers. Here, we investigated the influence of the molecular structure of ILs and the control of plasticizing interactions with PAN during melt-spinning. The structural, thermal, and mechanical properties of the melt-spun PAN fibers were obtained by a combination of various characterization methods, such as differential scanning calorimetry, thermogravimetric analysis, Fourier transform infrared spectroscopy, scanning electron microscopy, X-ray diffraction, and mechanical testing. These results demonstrated that the IL structure and counteranions influence the PAN fiber formation. More specifically, ILs containing bromide counteranions produced PAN precursor fibers with increased mechanical properties compared to ILs containing chloride anions. Our research can provide a foundation to understand the influence of ILs on melt-spinning of PAN fibers and provides us the guidelines for a higher cost-/energy-efficient production of PAN-based carbon fibers.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Effects of PLA/PHB Blend Ratio and Wood Flour Loading on the Melt Rheology and Thermomechanical Properties of Biobased Polymer Composites

The development of sustainable, biobased polymer composites is crucial for reducing supply chain dependence on fossil fuels. A major challenge lies in understanding and predicting the processability of these sustainable material alternatives, which directly impacts large-scale manufacturing. Here, this study systematically investigates the effect of poly(lactic acid) (PLA)/polyhydroxybutyrate (PHB) blend ratios and wood flour (WF) loadings on the thermal, rheological, and mechanical properties of the composites. Composites were prepared via melt compounding and characterized by using differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), oscillatory shear melt rheology, tensile testing, and scanning electron microscopy. Results showed that increasing the PHB content lowered the glass transition temperature, while higher PHB and WF loadings decreased thermal stability. Complex viscosity decreased with increasing PHB in 0 and 10% WF, whereas it increased in 20% and 30% WF for PHB-rich blends (80/20 and 70/30 PLA/PHB) due to stronger filler interactions with flexible PHB chains. At 30% WF, PHB-containing composites also showed elastic dominance with G′ higher than G″. This behavior was confirmed by van Gurp–Palmen plots, where the phase angle decreased with increasing PHB and WF loadings. WF addition also shifted Cole–Cole plots away from semicircular terminal relaxation, while time–temperature superposition validity was maintained, confirming that polymer chain dynamics continue to dominate melt behavior. Young’s modulus increased with WF loading, while tensile strength and toughness decreased due to weaker interfacial adhesion between the matrix and the filler. Interestingly, 10% WF systems containing PHB exhibited the highest toughness among all of the filled systems, indicating synergistic reinforcement from WF fillers and PHB-induced ductility. Overall, melt rheology effectively captured the internal structure and stiffness of the composites as the formulation changed, reinforcing the concept that the PLA/PHB ratio and WF content can be tuned to adjust melt elasticity and balance mechanical property trade-offs for targeted applications.

melt rheology↗
DOE OSTI2024

Melting anisotropy in crystalline solids

Despite the long and extensive history of melting studies, experiments to determine the dependence of melting on crystal orientation are lacking. Using longitudinal sound speed measurements in aluminum single crystals shock compressed along < 100 > and < 110 > to 168 GPa, we address this need and show that the melting transition (both onset and completion) is strongly anisotropic. Furthermore, the present findings demonstrate the need to consider the role of deformation induced lattice defects on the melting transition and provide a general approach to examine melting anisotropy in crystalline solids.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Combining synchrotron X-ray diffraction, mechanistic modeling and machine learning for in situ subsurface temperature quantification during laser melting

Laser melting, such as that encountered during additive manufacturing, produces extreme gradients of temperature in both space and time, which in turn influence microstructural development in the material. Qualification and model validation of the process itself and the resulting material necessitate the ability to characterize these temperature fields. However, well established means to directly probe the material temperature below the surface of an alloy while it is being processed are limited. To address this gap in characterization capabilities, a novel means is presented to extract subsurface temperature-distribution metrics, with uncertainty, from in situ synchrotron X-ray diffraction measurements to provide quantitative temperature evolution data during laser melting. Temperature-distribution metrics are determined using Gaussian process regression supervised machine-learning surrogate models trained with a combination of mechanistic modeling (heat transfer and fluid flow) and X-ray diffraction simulation. The trained surrogate model uncertainties are found to range from 5 to 15% depending on the metric and current temperature. The surrogate models are then applied to experimental data to extract temperature metrics from an Inconel 625 nickel superalloy wall specimen during laser melting. The maximum temperatures of the solid phase in the diffraction volume through melting and cooling are found to reach the solidus temperature as expected, with the mean and minimum temperatures found to be several hundred degrees less. The extracted temperature metrics near melting are determined to be more accurate because of the lower relative levels of mechanical elastic strains. However, uncertainties for temperature metrics during cooling are increased due to the effects of thermomechanical stress.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Melt-Spun PAN Precursor for Cost-Effective Carbon Fibers in High Pressure Compressed Gas Tankage

The objective of this program was to synthesize melt-spinnable polyacrylonitrile (PAN) precursor that will lead to carbon fiber 25% less expensive than carbon fiber produced from conventional PAN precursor when produced in large volumes. The carbon fiber produced from this precursor needs to achieve ≥ 700 ksi tensile strength with this cost reduction to replace the incumbent fiber. In this program, the technology for producing precursor and then converted carbon fiber (CF) capable of meeting the 700 ksi target was to be demonstrated at a small scale in tows, containing ≥ 100 filaments. If this program moved on to a “Phase 2”, the processes would be scaled up to produce and test Type IV compressed gas storage tanks capable of meeting the 700-bar ultimate targeted FOA performance level. Precursor fiber production typically contributes a large fraction (~50%) to finished CF manufactured cost. Presently, all high strength CFs are manufactured from solution spun PAN precursor, accomplished at low temperatures using large amounts of environmentally unfriendly solvents that impart major impact to line speed and costs involved with handling and reclaiming the solvents and associated “waste streams” required in spinning and extracting those solvents. PAN melt spinning was demonstrated by the company BASF in CF precursor production and used in production of some other acrylic fibers, but significant production challenges remain for meeting the established CF metrics. Melt spinning requires use of plasticizers to suppress the melt temperature of the predominantly PAN formulation to a point sufficiently below the temperature of significant cross-linking. Fortunately, BASF and this team’s earlier work had demonstrated acrylic formulations melt spun with combinations of plasticizing solvents at much lower solvent levels. This project team made significant progress in understanding technical issues and identifying formulation pathways in earlier work in this area where >250ksi strength was achieved. The goal of this program was to pursue a more comprehensive approach with a larger, more diverse team having greater equipment design and overall production capabilities to push rapidly beyond the science to resolve remaining “engineering” issues associated with establishing stable, continuous processes for precursor fiber leading to enhanced, cost-effective CF and composite tank production.

36 MATERIALS SCIENCE↗
NASA NTRS2021

Melt Infiltration Studies of 2D Tyranno SA3(R) Ceramic Matrix Composite Preforms with CrSi2 Intermetallic Alloy

The present paper reports the results of melt infiltrating 2D Tyranno SA3@ fiber woven preforms with molten CrSi2 between 1768 and 1896 K under a vacuum of 1.3 x 10-4 Pa (10-6 torr). The infiltration times varied between 1800 and 7200 s, which did not have any significant effect on the volume fraction of voids filled with the metal. Optical and scanning electron microscopy, back scattered electron imaging, energy dispersion spectroscopy and Raman spectroscopy were used to characterize the infiltrated preforms. A plot of the volume fraction of open voids infiltrated against the absolute melt infiltration temperature showed a sharp peak at 1773 K with almost complete infiltration of the voids at this temperature. The extent of silicide infiltration of the preforms dropped steeply above 1773 K with increasing melt infiltration temperature irrespective of the amount of infiltration time. Above 1805 K, the volume fraction of voids infiltrated with the melt was nearly 0%. It is demonstrated that CrSi2 did not show evidence of a reaction with the SiC fibers. The possibility that a resisting force due to contact angle hysteresis (CAH) may have influenced the diminishing amount of voids filled with increasing temperature above 1773 K was examined. The resistance force was estimated to be extremely small to be consequential. Another possibility that the CrSi2 may have decomposed into Cr(g) and Si(g) in the vacuum melt infiltration furnace appeared to be more plausible based on thermodynamic analyses. An empirical equation is proposed to calculate the amount of remaining charge left to infiltrate the preforms at the infiltration temperature. It is shown that an initial charge of 10 g would rationalize the present observations. While the decomposition of the CrSi2 appeared to mostly explain the present results, some discrepancies were observed, which were inconsistent with the decomposition model.

CrSi2, chromium silicide, ceramic matrix composite↗
DOE OSTI2022

Quantifying Equiaxed vs Epitaxial Solidification in Laser Melting of CMSX-4 Single Crystal Superalloy

The competition between epitaxial vs. equiaxed solidification has been investigated in CMSX-4 single crystal superalloy during laser melting as practiced in additive manufacturing. Single-track laser scans were performed on a powder-free surface of directionally solidified CMSX-4 alloy with several combinations of laser power and scanning velocity. Electron backscattered diffraction (EBSD) mapping facilitated identification of new orientations, i.e., “stray grains” that nucleated within the fusion zone along with their area fraction and spatial distribution. Using high-fidelity computational fluid dynamics simulations, both the temperature and fluid velocity fields within the melt pool were estimated. This information was combined with a nucleation model to determine locations where nucleation has the highest probability to occur in melt pools. In conformance with general experience in metals additive manufacturing, the as-solidified microstructure of the laser-melted tracks is dominated by epitaxial grain growth; nevertheless, stray grains were evident in elongated melt pools. It was found that, though a higher laser scanning velocity and lower power are generally helpful in the reduction of stray grains, the combination of a stable keyhole and minimal fluid velocity further mitigates stray grains in laser single tracks.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Impact of melt viscosity on filler dispersion in elastomeric nanocomposites

Compounding of commercial nanocomposites usually involves the addition of viscosity enhancers such as binder resins in ink jet inks, and paints. Contrary to this, plasticizers such as process oils are added to reduce the melt viscosity and ease processability of reinforced elastomers. Nanofillers such as silica and carbon black are typically added to reinforce rubber and enhance performance of automotive tire treads. Filler dispersion has traditionally been qualitatively (indirectly) assessed by measuring the properties of reinforced elastomers. While dispersion can be quantified by examining filler agglomeration through surface roughness measurements and microscopy, the size-scale dependence for these hierarchical fillers has usually been ignored. Here, we have recently devised a method to quantify nano-scale dispersion of fillers using Ultra small-angle X-ray scattering (USAXS) techniques. This method is advantageous since it directly links the controllable processing/compounding parameters such as the mixing speed, mixer geometry, residence time (or mixing duration), melt density, flow gap distance, and melt viscosity to nano-scale dispersion. While our previous studies have explored the impact of different processing parameters, this study specifically investigates the impact of melt viscosity on nano-scale filler dispersion in elastomer compounds. Commercially available polybutadienes with different Mooney viscosities were used in conjunction with different grades and amounts of process oils to modify the melt viscosity.

Carbon black↗
DOE OSTI2021

Formation and surface melting of nanoparticle superlattices in a solution

The wisdom in the saying of “There are no two snowflakes alike” lies in the importance of history or kinetic pathways in the phase transitions of solids. Likewise, “artificial solids,” namely superlattices consisting of functional nanoparticles, have lattice size, surface morphology, crystallinity, symmetry, and structural reconfiguration (for example, transition into a disordered state) highly dependent on the kinetic pathways as the nanoparticles interact with each other in solution [1]. Great progresses have been made in understanding the formation pathways of superlattices using liquid-phase transmission electron microscopy (TEM) [2-4]. For example, by tracking single nanoparticle’s trajectories, especially aided by U-net neural network-based machine learning, previous studies mapped the fundamental nanoparticle interactions at nanometer resolution [5]. Nonclassical, two-step nucleation pathway has also been elucidated in the system of nanoprisms, by optimizing protocols such as loading nanoparticle suspensions over the supersaturation threshold and minimizing particle‒substrate interaction [2]. Surface morphologies or exposed facets of superlattices have been shown to follow the principles of Wulff construction rule, where the facet-dependent surface energy can be measured based on the capillary wave theory [4]. However, the reverse process of crystallization of superlattices, the conversion from crystalline to disordered state, has been much less explored. On one hand, the melting of nanoparticle superlattices can provide a preferred pathway to induce structural reorganization or shuffling of building blocks for them to transform into different types of crystal structures. On the other hand, understanding nanoscale superlattice melting and comparing such behaviors with the prevailing surface melting theories developed for atomic/molecular solids can provide a potent way to engineer phase transitions of supra- and hierarchical structures constructed from nanoscale entities (e.g., DNA-coated nanoparticles, proteins), for their applications in reprogrammable and switchable materials with multifunctional properties [6, 7]. The experimental challenges to observe melting of superlattices are twofold. Practically it is difficult to load the initial superlattice form, in an intact manner, into the highly confined liquid-phase TEM chamber for in-situ observation. Here, the triggering of melting also needs meticulous manipulation of nanoparticle concentration, interparticle interaction, and solution environment.

Kim, Ahyoung↗