skip to main content


Title: Plasticity Enhancement by Fe-Addition on NiAl Alloy: A Synchrotron X-ray Diffraction Mapping and Molecular Dynamics Simulation Study
Unalloyed nickel aluminide has important applications but lacks ductility at room temperature. In this study, iron-added nickel aluminide alloys exhibit plasticity enhancement. The nickel aluminide alloys are prepared with different iron contents (0, 0.25, and 1 at%) to study their plasticity. The indentation-induced deformed areas are mapped by the synchrotron X-ray diffraction to compare their plastic zones. A complimentary tight binding calculation and generalized embedded atom method demonstrate how the Fe-addition enhances the plasticity of the iron-added nickel aluminide alloys.  more » « less
Award ID(s):
1809640
NSF-PAR ID:
10179057
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ;
Date Published:
Journal Name:
Quantum Beam Science
Volume:
2
Issue:
3
ISSN:
2412-382X
Page Range / eLocation ID:
18
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. In this paper we develop a material index for selecting alloys resistant to frictional ignition in high pressure oxygen environments. A previous ignition-resistance metric proposed by NASA WSTF varies strongly and unpredictably with test conditions, thus limiting its usefulness. The material index developed here incorporates key material properties that strongly influence ignition behaviors, including friction coefficient, ignition temperature, and thermal effusivity. Finite element simulations were used to compute ignition temperatures for 15 alloys based on published frictional ignition data from NASA White Sands Testing Facility (WSTF). These values were used with the material index to construct property diagrams for ranking the materials based on their intrinsic frictional ignition resistance. The results demonstrate that nickel-based superalloys with low iron content are less likely to ignite under frictional heating than ferrous alloys and nickel-based superalloys with high content iron. The material index is then used to predict material performance outside of the test conditions, highlighting the effect of ambient temperature on nominal ignition resistance. We conclude by developing an empirical relation between ignition temperature and enthalpy of oxidation which can guide design of new ignition-resistant alloys. 
    more » « less
  2. null (Ed.)
    Abstract Metallic nanofoams, cellular structures consisting of interlinked thin nanowires and empty pores, create low density, high surface area materials. These structures can suffer from macroscopically brittle behavior. In this work, we present a multiscale approach to study and explain the mechanical behavior of metallic nanofoams obtained by an electrospinning method. In this multiscale approach, atomistic simulations were first used to obtain the yield surfaces of different metallic nanofoam cell structures. Then, a continuum plasticity model using finite elements was used to predict the alloy nanofoam's overall strength in compression. The manufactured metallic nanofoams were produced by electrospinning a polymeric non-woven fabric containing metal precursors for alloys of copper–nickel and then thermally processing the fabric to create alloy metallic nanofoams. The nanofoams were tested with nanoindentation. The experimental results suggest that the addition of nickel increases the hardening of the nanofoams. The multiscale simulation modeling results agreed qualitatively with the experiments by suggesting that the addition of the alloying can be beneficial to the hardening behavior of the metallic nanofoams and helps to isolate the effects of alloying from morphological changes in the foam. This behavior was related to the addition of solute atoms that prevent the free dislocation movement and increase the strength of the structure. 
    more » « less
  3. It is believed that the core formation processes sequestered a large majority of Earth’s carbon into its metallic core. Incorporation of carbon to liquid iron may significantly influence its properties under physicochemical conditions pertinent to the deep magma ocean and thus the chemical evolution of terrestrial planets and moons. Compared to available experimental data on the physical properties of crystalline iron alloys under pressure, there is a remarkable lack of data on the properties of liquid iron‐rich alloys, due to experimental challenges. Here we review experimental and computational results on the structure and properties of iron or iron‐nickel liquids alloyed with carbon upon compression. These laboratory data provide an important foundation on which the interpretation of ultrahigh pressure laboratory data and the verification of theoretical data will have to be based. The low‐pressure data can be used to validate results from theoretical calculations at the same conditions, and high‐pressure calculations can be used to estimate and predict liquid properties under core conditions. Availability of the liquid properties of Fe‐C liquids will provide essential data for stringent tests of carbon‐rich core composition models for the outer core. 
    more » « less
  4. Abstract

    Earth’s inner core exhibits strong seismic anisotropy, often attributed to the alignment of hexagonal close‐packed iron (hcp‐Fe) alloy crystallites with the Earth’s poles. How this alignment developed depends on material properties of the alloy and is important to our understanding of the core’s crystallization history and active geodynamical forcing. Previous studies suggested that hcp‐Fe is weak under deep Earth conditions but did not investigate the effects of the lighter elements known to be part of the inner core alloy. Here, we present results from radial X‐ray diffraction experiments in a diamond anvil cell that constrain the strength and deformation properties of iron‐nickel‐silicon (Fe–Ni–Si) alloys up to 60 GPa. We also show the results of laser heating to 1650 K to evaluate the effect of temperature. Observed alloy textures suggest different relative activities of the various hcp deformation mechanisms compared to pure Fe, but these textures could still account for the theorized polar alignment. Fe–Ni–Si alloys are mechanically stronger than Fe and Fe–Ni; extrapolated to inner core conditions, Si‐bearing alloys may be more than an order of magnitude stronger. This enhanced strength proportionally reduces the effectivity of dislocation creep as a deformation mechanism, which may suggest that texture developed during crystallization rather than as the result of postsolidification plastic flow.

     
    more » « less
  5. Thermal conductivity (TC) is greatly influenced by the working temperature, microstructures, thermal processing (heat treatment) history and the composition of alloys. Due to computational costs and lengthy experimental procedures, obtaining the thermal conductivity for novel alloys, particularly parts made with additive manufacturing, is difficult and it is almost impossible to optimize the compositional space for an absolute targeted value of thermal conductivity. To address these difficulties, a machine learning method is explored to predict the TC of additive manufactured alloys. To accomplish this, an extensive thermal conductivity dataset for additively manufactured alloys was generated for several AM alloy families (nickel, copper, iron, cobalt-based) over various temperatures (300–1273 K). This unique dataset was used in training and validating machine learning models. Among the five different regression machine learning models trained with the dataset, extreme gradient boosting performs the best as compared with other models with an R2 score of 0.99. Furthermore, the accuracy of this model was tested using Inconel 718 and GRCop-42 fabricated with laser powder bed fusion-based additive manufacture, which have never been observed by the extreme gradient boosting model, and a good match between the experimental results and machine learning prediction was observed. The average mean error in predicting the thermal conductivity of Inconel 718 and GRCop-42 at different temperatures was 3.9% and 2.08%, respectively. This paper demonstrates that the thermal conductivity of novel AM alloys could be predicted quickly based on the dataset and the ML model.

     
    more » « less