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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
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↗
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↗
DOE OSTI2020

Bathymetric Influences on Antarctic Ice-Shelf Melt Rates

Ocean bathymetry exerts a strong control on ice sheet-ocean interactions within Antarctic ice-shelf cavities, where it can limit the access of warm, dense water at depth to the underside of floating ice shelves. However, ocean bathymetry is challenging to measure within or close to ice-shelf cavities. It remains unclear how uncertainty in existing bathymetry datasets affect simulated sub-ice-shelf melt rates. In this work, we infer linear sensitivities of ice-shelf melt rates to bathymetric shape with grid-scale detail by means of the adjoint of an ocean general circulation model. Both idealized and realistic-geometry experiments of sub-ice-shelf cavities in West Antarctica reveal that bathymetry has a strong impact on melt in localized regions such as topographic obstacles to flow. Moreover, response of melt to bathymetric perturbation is found to be non-monotonic, with deepening leading to either increased or decreased melt depending on location. Our computational approach provides a comprehensive way of identifying regions, where refined knowledge of bathymetry is most impactful, and also where bathymetric errors have relatively little effect on modeled ice sheet-ocean interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Melting and density of MgSiO 3 determined by shock compression of bridgmanite to 1254GPa

The essential data for interior and thermal evolution models of the Earth and super-Earths are the density and melting of mantle silicate under extreme conditions. Here, we report an unprecedently high melting temperature of MgSiO 3 at 500 GPa by direct shockwave loading of pre-synthesized dense MgSiO3 (bridgmanite) using the Z Pulsed Power Facility. We also present the first high-precision density data of crystalline MgSiO 3 to 422 GPa and 7200 K and of silicate melt to 1254 GPa. The experimental density measurements support our density functional theory based molecular dynamics calculations, providing benchmarks for theoretical calculations under extreme conditions. The excellent agreement between experiment and theory provides a reliable reference density profile for super-Earth mantles. Furthermore, the observed upper bound of melting temperature, 9430 K at 500 GPa, provides a critical constraint on the accretion energy required to melt the mantle and the prospect of driving a dynamo in massive rocky planets.

58 GEOSCIENCES↗
DOE OSTI2023

Melting and defect transitions in FeO up to pressures of Earth’s core-mantle boundary

The high-pressure melting curve of FeO controls key aspects of Earth’s deep interior and the evolution of rocky planets more broadly. However, existing melting studies on wüstite were conducted across a limited pressure range and exhibit substantial disagreement. Here we use an in-situ dual-technique approach that combines a suite of >1000 x-ray diffraction and synchrotron Mössbauer measurements to report the melting curve for Fe 1-x O wüstite to pressures of Earth’s lowermost mantle. We further observe features in the data suggesting an order-disorder transition in the iron defect structure several hundred kelvin below melting. This solid-solid transition, suggested by decades of ambient pressure research, is detected across the full pressure range of the study (30 to 140 GPa). At 136 GPa, our results constrain a relatively high melting temperature of 4140 ± 110 K, which falls above recent temperature estimates for Earth’s present-day core-mantle boundary and supports the viability of solid FeO-rich structures at the roots of mantle plumes. The coincidence of the defect order-disorder transition with pressure-temperature conditions of Earth’s mantle base raises broad questions about its possible influence on key physical properties of the region, including rheology and conductivity.

58 GEOSCIENCES↗
DOE OSTI2021

A critical look at the prediction of the temperature field around a laser-induced melt pool on metallic substrates

The study of microstructure evolution in additive manufacturing of metals would be aided by knowing the thermal history. Since temperature measurements beneath the surface are difficult, estimates are obtained from computational thermo-mechanical models calibrated against traces left in the sample revealed after etching, such as the trace of the melt pool boundary. Here we examine the question of how reliable thermal histories computed from a model that reproduces the melt pool trace are. To this end, we perform experiments in which one of two different laser beams moves with constant velocity and power over a substrate of 17-4PH SS or Ti-6Al-4V, with low enough power to avoid generating a keyhole. We find that thermal histories appear to be reliably computed provided that (a) the power density distribution of the laser beam over the substrate is well characterized, and (b) convective heat transport effects are accounted for. Poor control of the laser beam leads to potentially multiple three-dimensional melt pool shapes compatible with the melt pool trace, and therefore to multiple potential thermal histories. Ignoring convective effects leads to results that are inconsistent with experiments, even for the mild melt pools here.

42 ENGINEERING↗
DOE OSTI2024

Atomistic origin of the entropy of melting from inelastic neutron scattering and machine learned molecular dynamics

The latent heat, L, is central to melting, but its atomic origin remains elusive. It is proportional to the entropy of fusion, ΔS fus = L/T m (T m is the melting temperature), which depends on changes of atom configurations, atom vibrations, and thermal electron excitations. Here, we combine inelastic neutron scattering and machine-learned molecular dynamics to separate ΔS fus into these components for Ge, Si, Bi, Sn, Pb, and Li. When the vibrational entropy of melting, ΔS vib , is zero, ΔS fus ≃ 1.2 kB per atom. This result provides a baseline for ΔSconfig and nearly coincides with “Richard’s Rule” of melting. The ΔSfus deviates from this value for most elements, however, and we show that this deviation originates with extra ΔS vib and extra ΔS config . These two components are correlated for positive and negative deviations from Richard’s rule – the extra ΔS config is consistently ~ 80% of ΔS vib . Our results, interpreted with potential energy landscape theory, imply a correlation between the change in the number of basins and the change in the inverse of their curvature for the melting of pure elements.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The influence of laser power modulation on melt pool dynamics in laser powder bed fusion

While the majority of laser powder bed fusion (LPBF) metal additive manufacturing uses a continuous wave (CW) laser heat source, some commercial applications of LPBF additive manufacturing instead involve the modulation of the laser power on tens-of-microsecond timescales as an adjustable process variable. This article reports the use of in situ, high speed x-ray and optical imaging to probe melt pool fluid flow, defect formation, and nearby powder motion during LPBF with both modulated and CW laser heat sources. We observe melt pool dynamics unique to modulated laser melting even at very high duty cycles that are related to fluctuations in vapor depression depth, complex pore formation mechanisms, and changes to denudation physics when compared to CW melting. These behaviors are present in Ti–6Al–4V, 316L stainless steel, and AL1100 alloys but vary slightly as a function of material, indicating a substantial dependence on the viscosity and surface tension of the liquid metal. While high duty cycles produce weld tracks of comparable quality to CW melting, lower duty cycles introduce substantial defect concentrations. At intermediate duty cycles, careful control of modulation parameters can repeatably and precisely yield one pore per laser pulse, suggesting a method for intentionally inserting engineered porosity at specific sites during an LPBF build.

3D printing↗
DOE OSTI2024

Peculiarities of CsPbBr3 perovskites melting in quasi-equilibrium conditions

The melting behavior of CsPbBr3 perovskite was studied by differential thermal analysis (DTA). It was found that melting of CsPbBr3 occurs non-isothermally in the temperature range of 561-570 °C. From the temperature dependence of the solid-phase melting rate, it was established that at 567±1 °C the change in the mechanism of the solid-phase melting goes from fragmentation to dissolution at the surface. The obtained values of the activation energy of the melting of the solid phase in CsPbBr3 show that the activation energy of the dissolution of the solid-phase fragments is 4 times greater than the energy of the fragmentation of the solid phase.

Kopach, O.↗
DOE OSTI2021

In situ characterization of laser-generated melt pools using synchronized ultrasound and high-speed X-ray imaging

Metal additive manufacturing is a fabrication method that forms a part by fusing layers of powder to one another. An energy source, such as a laser, is commonly used to heat the metal powder sufficiently to cause a molten pool to form, which is known as the melt pool. The melt pool can exist in the conduction or the keyhole mode where the material begins to rapidly evaporate. The interaction between the laser and the material is physically complex and difficult to predict or measure. Here, high-speed X-ray imaging was combined with immersion ultrasound to obtain synchronized measurements of stationary laser-generated melt pools. Furthermore, two-dimensional and three-dimensional finite-element simulations were conducted to help explain the ultrasonic response in the experiments. In particular, the time-of-flight and amplitude in pulse-echo configuration were observed to have a linear relationship to the depth of the melt pool. These results are promising for the use of ultrasound to characterize the melt pool behavior and for finite-element simulations to aid in interpretation.

42 ENGINEERING↗
DOE OSTI2023

Real-time (nanoseconds) determination of liquid phase growth during shock-induced melting

Melting of solids is a fundamental natural phenomenon whose pressure dependence has been of interest for nearly a century. However, the temporal evolution of the molten phase under pressure has eluded measurements because of experimental challenges. By using the shock front as a fiducial, we investigated the time-dependent growth of the molten phase in shock-compressed germanium. In situ x-ray diffraction measurements at different times (1 to 6 nanoseconds) behind the shock front quantified the real-time growth of the liquid phase at several peak stresses. These results show that the characteristic time for melting in shock-compressed germanium decreases from ~7.2 nanoseconds at 35 gigapascals to less than 1 nanosecond at 42 gigapascals. Our melting kinetics results suggest the need to consider heterogeneous nucleation as a mechanism for shock-induced melting and provide an approach to measuring melting kinetics in shock-compressed solids.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Survival of Snow in the Melting Layer: Relative Humidity Influence

This study quantifies how far snow can fall into the melting layer (ML) before all snow has melted by examining a combination of in-situ observations from aircraft measurements in Lagrangian spiral descents from above through the ML and descents and ascents into the ML, as well as an extensive database of NOAA surface observer reports during the past 50 years. The airborne data contain information on the particle phase (solid, mixed, or liquid), population size distributions and shapes, along with temperature, relative humidity, and vertical velocity. A wide range of temperatures and ambient relative humidities are used for both the airborne and ground-based data. It is shown that an ice bulb temperature of 0°C, together with the air temperature and pressure (altitude), are good first order predictors of the highest temperature snowflakes can survive in the melting layer before completely melting. Particle size is also important, as is whether the particles are graupel or hail. If the relative humidity is too low, the particles will sublimate completely as they fall into the melting layer. Snow as warm as +7°C is observed from aircraft measurements and surface observations. Snow pellets survive to even warmer temperatures. Relationships are developed to represent the primary findings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Improved melt model for power flow

Accelerators that drive z-pinch experiments transport current densities in excess of 1 MA/cm 2 in order to melt or ionize the target and implode it on axis. These high current densities stress the transmission lines upstream from the target, where rapid electrode heating causes plasma formation, melt, and possibly vaporization. These plasmas negatively impact accelerator efficiency by diverting some portion of the current away from the target, referred to as “current loss”. Simulations that are able to reproduce this behavior may be applied to improving the efficiency of existing accelerators and to designing systems operating at ever higher current densities. The relativistic particle-in-cell code CHICAGO ® is the primary code for modeling power flow on Sandia National Laboratories’ Z accelerator. We report here on new algorithms that incorporate vaporization and melt into the standard power-flow simulation framework. Taking a hybrid approach, the CHICAGO® kinetic/multi-fluid treatment has been expanded to include vaporization while the quasi-neutral equation-of-motion has been updated for melt at high current-densities. For vaporization, a new one-dimensional substrate model provides a more accurate calculation of electrode thermal, mass, and magnetic field diffusion as well as a means of emitting absorbed contaminants and vaporized metal ions. A quasi-fluid model has been implemented expressly to mimic the motion of imploding liners for accurate inductance histories. For melt, a multi-ion Hall-MHD option has been implemented and benchmarked against Alegra MHD. This new model is described with sufficient detail to reproduce these algorithms in any hybrid kinetic code. Physics results from the new code are also presented. A CHICAGO ® Hall-MHD simulation of a radial transmission line demonstrates that Hall physics, not included in Alegra, has no significant impact on the diffusion of electrode material. When surface contaminant desorption is mocked in as a hydrogen surface plasma, both the surface and bulk-material plasmas largely compress under the influence of the j × B force. Similar results are seen in Alegra, which also shows magnetic and material diffusion scaling with peak current. Test vaporization simulations using MagLIF and a power-flow experimental geometry show Fe + ions diffuse only a few hundred µm from the electrodes, so present models of Z power flow remain valid.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Multi phenomena melt pool sensor data fusion for enhanced process monitoring of laser powder bed fusion additive manufacturing

Finding actionable trends in laser-based metal additive manufacturing process monitoring data is challenging owing to the diversity and complexity of the underlying physical interactions. A single monitoring solution that captures a particular process phenomenon, such as a photodiode that tracks melt pool intensity, is not alone capable of evaluating process stability or detecting flaw formation with sufficient precision for routine application in industry. In this work, to improve flaw detection performance, we adopted a data fusion approach that captures multiple process phenomena. To demonstrate this, we acquired data from laser powder bed fusion (LPBF) builds of cylindrical specimens produced with different laser spot sizes, emulating defocusing due to process faults such as thermal lensing. The resulting specimens had porosity of varying types and severity, quantified by post-build non-destructive X-ray computed tomography, Archimedes density measurements, and destructive metallographic characterization. During the build, the melt pool state was monitored with two coaxial high-speed video cameras and a temperature field imaging system. Physically intuitive low-level melt pool signatures, such as melt pool temperature, shape and size, and spatter intensity were extracted from this high-dimensional, image-based sensor data. These process signatures were subsequently used as input features in relatively simple machine learning models, such as a support vector machine, which were trained to detect laser defocusing, and in addition, predict porosity type and severity. The results show that the data fusion approach significantly enhanced system performance by reducing the overall false positive rate from ~ 0.1 to ~ 0.001 without sacrificing the true positive rate (~0.90). These results were at par with a black-box, deep machine learning approach (convolutional neural network).

36 MATERIALS SCIENCE↗