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Here, we will present recently peer-reviewed results to showcase the advanced multimodal imaging capabilities developed to study irradiated materials at the Pacific Northwest National Laboratory. Irradiated cladding samples selected to support the tritium science and technology program will be used as an example to demonstrate the multimodal imaging capabilities.
Increasing peak cylinder pressures and operating temperatures of turbo-charged internal combustion engines (ICEs) engines present new challenges for existing materials employed in engine exhaust valves. Oxidation induced degradation of current Ni based alloys for these components will be a life-limiting mechanism while strict cost margins in the automotive transportation industry further limit the choice of suitable candidate materials. Metallic diffusion aluminide coatings can provide a cost-effective way to improve the oxidation resistance of underlying materials. In this study, the high temperature oxidation behavior of diffusion nickel aluminide coatings on two Ni based alloys (commercially available alloy 31V and a developmental alloy) during cyclic oxidation behavior in air+10% H 2 O at 900 °C was investigated. A complete depletion of the beneficial Al-rich β-(NiFe)Al phase was observed in the coating on alloy 31V while a significant fraction of this phase was retained in the coating on the second alloy. A coupled thermodynamic-kinetic model showed that the disappearance of the Al-rich phase in the coating on 31V was mainly due to the combined effect of steeper chemical potential gradients of Al and Ti between the coating and the substrate and their faster diffusivities compared to the coated developmental alloy. Finally, a higher content of Fe was shown to support the retention of β-(NiFe)Al phase in the coating on the developmental alloy while the presence of Ti in the alloy was shown to be detrimental for long-term coating performance.
Surface coatings of steels used in extreme conditions and corrosive environments generally aim to provide protection and increased durability. In the case of tritium-producing burnable absorber rods (TPBARs) used in nuclear reactors, a 316 stainless steel has been coated with Al. Scanning transmission electron microscopy (STEM) characterization of the coating found three Al-rich (>60 atom % Al) iron aluminide alloys identified as hexagonal FeNiAl 5 , monoclinic Fe 4 Al 13 , and orthorhombic Fe 2 Al 5 . Density functional theory simulations using nudged elastic band have been performed to investigate the diffusion of interstitial tritium in each Al-rich iron aluminide phase. While FeNiAl 5 and Fe 4 Al 13 can be viewed as the stacking of two layers, the structural peculiarity of Fe 2 Al 5 is that channels of variable Al vacancy content are present along the c-axis. Therefore, three stoichiometries for Fe 2 Al x phase, namely, Fe 2 Al 4 , Fe 2 Al 5 , and Fe 2 Al 6 , have been considered to evaluate the impact of Al vacancy concentration on tritium diffusion behavior. Altogether, we found that at 600 K, tritium diffusion decreases from a faster rate in the channels of Fe 2 Al x phases (D T ≤ 10 –11 m 2 ·s –1 ) to Fe 4 Al 13 (D T ≈ 10–12 m2·s–1), and finally in FeNiAl5 (D T ≈ 10 –13 m 2 ·s –1 ). Here, we also find that interstitial tritium generally diffuses faster in Fe–Al coating phases than in the tritium breeding material γ-LiAlO 2 (D T ≈ 10 –14 m 2 ·s –1 ) but slightly slower than in 316 stainless steel (D T ≈ 10 –10 m 2 ·s –1 ).
Density functional theory simulations have been carried out to investigate the potential for tritium trapping by metal vacancies in five different Fe-Al aluminide coating phases. It was found that tritiation of Fe and Ni vacancies is generally less favorable than the tritiation of Al vacancies. However, for the first tritiation, a trend in the defect formation energy can be obtained such that metal defects in the Fe 2 Al x family of materials (i.e., Fe 2 Al 4 , Fe 2 Al 5 , and Fe 2 Al 6 ) trap tritium species more favorably than metal vacancies in Fe 4 Al 13 and FeNiAl 5 . Further investigations using ab initio thermodynamics calculations confirmed that trend for a range of tritium partial pressure at a temperature of 700 K. Especially, it was shown that the energy difference between tritiated and non-tritiated metal vacancies is smaller and more favorable for the Fe 2 Al x family, followed by Fe 4 Al 13 , and FeNiAl 5 . While this study shows that tritium interacts differently in the various Fe-Al aluminide phases, it also suggests that tritium trapping and retention could be more efficient if metal defects are present in some Fe-Al phases.
Density functional theory (DFT) simulations have been carried out to evaluate the potential for tritium trapping by metal vacancies in four phases (i.e., (Fe, Cr, Ni), AlFe 3 , NiAl, and AlFe) identified near the interface between the Al coating and 316 stainless steel (316 SS) cladding. In addition, an ab initio thermodynamics approach has been employed to predict the temperature and T 2 -partial pressure dependence on the thermodynamics of tritiated defects. Key results in this work suggest that metal vacancies in the four phases have the potential to favorably trap tritium species. This thermodynamic trend can be correlated to the high energy cost of having an interstitial tritium in the lattice, which has been calculated to be at least 0.48 eV. By combining the results of this study with previous theoretical works investigating tritium behavior in other Fe-Al phases identified in the aluminide coating, suggest that metal vacancies are generally able to trap tritium in various Fe-Al aluminide phases. Especially, it was found that Al vacancies are the most efficient to trap tritium, followed by Fe vacancies, then Ni and Cr vacancies. Strong interactions between tritium and the metal vacancies are occurring by the formation of Fe—T bonds. The formation of Cr—T, Ni—T, or Al—T bonds are found less energetically favorable than Fe—T bonds.
Superconductivity is reported in an endohedral aluminide compound, RuAl6, with Tc = 1.21 K. The normalized heat capacity jump at Tc, ΔC/γTc = 1.58, confirms bulk superconductivity. The Ginzburg-Landau parameter of κ = 9.5 shows that RuAl6 is a type-II superconductor. Electronic structure calculations for RuAl6 are explored in comparison to its structural analogue ReAl6 (Tc = 0.74 K). The stability of the phases is discussed in terms of the crystal orbital Hamilton population (-COHP) analysis. The difference in Tc in the two materials is caused by the significantly stronger electron-phonon coupling found in RuAl6, which is a result of significantly stronger antibonding interactions. The presence of superconductivity in yet another compound made of aluminum clusters possibly expands the correlation of critical temperature and the structure shown for Ga-built clusters.
This project funded under DOE-FOA-0001816 was performed with the intent of evaluating the potential of utilizing a low density, high specific strength Titanium Aluminide (TiAl) alloy in a large annulus last stage gas turbine blade with the intent of improving combined cycle gas turbine efficiency toward a goal of reaching 65% efficiency. The project consisted of identifying a potentially suitable TiAl material for manufacture of such a large blade by investment casting. This included estimation of design properties for the selected alloy, trade studies using a baseline design created for a nickel based alloy cast in the TiAl alloy to evaluate potential design changes required for the use of this material and optimization of a prototype design for the same baseline application using the selected TiAl alloy. Several rounds of optimization were completed with the intent of meeting the baseline design targets with a resulting design that showed at least equivalent performance in terms of creep, LCF/TMF, HCF and aerodynamic damping potential. While it was found that significant reductions in blade loading on the disk were possible, the design resulting from the optimization met most lifing targets at the baseline size, but showed a reduction in margins in some areas in comparison to the Ni-based baseline design. Additionally, it was found that the low strain tolerance of the TiAl alloy for temperatures at and below the operational temperature of the attachment resulted in marginal, although still acceptable, creep rupture performance of the design. Due to results indicating the reduced potential for increasing turbine annulus compared to expectations a Phase II award was not proposed and it is not recommended to pursue additional design optimization efforts until further material advances with TiAl materials are achieved.
The theoretical investigations of interstitial tritium diffusion pathways in various Al-rich (>60% at. Al) iron aluminide coating phases found that in FeNiAl 5 tritium prefers to diffuse in between layers, while in Fe 4 Al 13 , tritium prefers to diffuse across layers. In the case of Fe 2 Al x phases, the simulations show that the variable Al content in the channels affects the diffusion behavior of tritium in the channels. For 100% of vacancy, tritium prefers to diffuse at the center of the channel, while for 0% Al vacancy, tritium prefers to diffuse along the channel’s wall. In the case where 50% Al vacancy are present in the channels, tritium can diffuse in a mixed way, with positions oscillating between the channel’s center and wall. However, the large energy barrier involved in this case suggests that tritium diffusion could be correlated with Al diffusion in the channels. While we found that at 600 K interstitial tritium diffuses faster in Fe 2 Al x phases (D Τ ≤10 -11 m 2 .s -1 ), then in Fe 4 Al 13 (D Τ ≈10 -12 m 2 .s -1 ), and finally in FeNiAl 5 (D Τ ≈10 -13 m 2 .s -1 ), we also find that interstitial tritium generally diffuses faster in Fe-Al coating phases than in γ-LiAlO 2 pellets (D Τ ≈10 -14 m 2 .s -1 ).
Density functional theory simulations have been carried out to investigate the potential for tritium trapping by metal vacancies in intermetallic Al 12 (TM) 2.35 phase (TM = Fe, Cr, and Ni) as function of temperature and tritium partial pressure. It was found that tritium could be favorably trapped by Fe and Ni vacancies and not favorably trapped by Al and Cr vacancies. However, due to the presence of partially occupied Al sites in bulk Al 12 (TM) 2.35 , leading to the approximate number of ~255 Al atoms in the unit cell, 86 sites were found energetically favorable to the creation of an Al vacancy. While adding a tritium atom in an Al vacancy is not energetically favorable, the tritiated defect still has a negative Gibbs free energy because the energy gain for creating an Al vacancy overcome the energy cost of adding the tritium species. Based on the calculated Gibbs free energy, the first tritiation of a metal vacancy, at conditions relevant to in-reactor operations, should be more favorable for Al, followed Fe, Ni, and Cr vacancies. By comparing the behavior of tritium in Al 12 (TM) 2.35 with previously studied Fe-Al coating phases (i.e., FeNiAl 5 , Fe 4 Al 13 , and Fe 2 Al 5.6 ), we found that there is a correlation between interstitial tritium solubility and the potential for vacancy trapping. The current trend suggests that if the insertion of an interstitial tritium cost more than 0.3 eV, then trapping by metal vacancies should be preferred. By combining the simulations results obtained to date, we noticed different trapping mechanisms of tritium in the Al coating. Tritium is mostly trapped by Fe and Ni vacancies in the outer Fe-Al coating phase Al 12 (TM) 2.35 while tritium should be preferentially trapped by Al and Fe vacancies for the inner Fe-Al coating phases (FeNiAl 5 , Fe 4 Al 13 , Fe 2 Al 5.6 ). Altogether, these studies show that tritium interacts differently with the various Fe-Al aluminide phases, they also suggest that tritium trapping and retention could be more efficient if metal defects are present and if the solubility of interstitial tritium in the different phases is low.
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Density functional theory simulations have been carried out to investigate the diffusion of interstitial tritium in Al 12 (TM) 2.34 and Al 2 O bulk phases. In Al 12 (TM) 2.34 the transition metal (TM) sites are occupied on average by 58.93 at.% Fe, 18.52 at.% Cr, and 22.54 at.% Ni. While the insertion of interstitial tritium in Al 2 O lead to a strong disordering of the structure, we only investigated interstitial tritium in Al 12 (TM) 2.34 and its iron end-member (i.e., Al 12 Fe 2.34 ). Nine diffusion pathways have been investigated along the a-, b-, and c -axis of Al 12 (TM) 2.34 . The direction of fastest diffusion for interstitial tritium is found to be along the b-axis, with a calculated diffusion coefficient of ≈10 -10 m 2 .s -1 at 600 K, which is at least one order of magnitude faster than those previously calculated for interstitial tritium in other Al-rich phases such as Fe2Alx, Fe4Al13, and FeNiAl5 for which D T =10 -11 m 2 .s -1 , ≈10 -12 m 2 .s -1 , and D T ≈10 -13 m 2 .s -1 respectively. The comparison of the energy landscape between Al 12 (TM) 2.34 and Al 12 Fe 2.34 for the fastest diffusion pathways in each axis direction, found that some pathways are not sensitive to transition metal mixing, while other are more affected, leading to higher energy barrier in Al 12 Fe 2.34 in part due to a more energetically favorable formation of Fe—T bond compared to Ni—T. However, we found that both materials have similar diffusion coefficients as the fastest diffusion pathways occurs along pathways that are not very sensitive to transition metal mixing.
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Parabolic rate constants, k p , were collected from published reports and calculated from corrosion product data (sample mass gain or corrosion product thickness) and tabulated for 75 alloys exposed to temperatures between ~800 and 2000 K (~500–1700 °C; 900–3000°F). Data were collected for environments including lab air, ambient and supercritical carbon dioxide, supercritical water, and steam. Materials studied include low- and high-Cr ferritic and austenitic steels, nickel superalloys, and aluminide materials. A combination of Arrhenius analysis, simple linear regression, supervised and unsupervised machine learning methods were used to investigate the relations between composition and oxidation kinetics. The supervised machine learning techniques produced the lowest mean standard errors. The most significant elements controlling oxidation kinetics were Ni, Cr, Al, and Fe, with Mo and Co composition also found to be significant features. The activation energies produced from the machine learning analysis were in the correct distributions for the diffusion constants for the oxide scales expected to dominate in each class.
Density functional theory (DFT) simulations have been carried out to evaluate the potential for tritium trapping by metal vacancies in four phases Cr-containing phases (i.e., Cr3Si, Al0.3Cr0.7, Al8Cr5-HT, and Al8Cr5) identified near the interface between the Al coating and 316 stainless steel (316 SS) cladding. In addition, an ab initio thermodynamics approach has been employed to predict the temperature and T2-partial pressure dependence on the thermodynamics of singly tritiated defects. Key results in this work suggest that metal vacancies in the four phases have the potential to favorably trap tritium species, especially Si vacancies in Cr3Si phase. This overall thermodynamic trend can be correlated to the energy cost of having an interstitial tritium in the lattice, which has been calculated to range from 0.17 eV in Al8Cr5-HT to 0.89 eV in Cr3Si. A comparison of the results from this study with previous theoretical works investigating tritium behavior in other Fe-Al phases identified in the aluminide coating, suggests that metal vacancies are generally able to trap tritium in various Fe-Al aluminide phases. Especially, it was found that Si and Al vacancies would be the most efficient to trap for tritium, followed by Cr vacancies, then Fe and Ni vacancies. In the four Cr-based material phases investigated in this work, it is interesting to note that, in the absences of Fe or Ni species, strong interactions between tritium and the metal vacancies are always occurring by the formation of preferential Cr—T bonds (i.e., no Si—T or Al—T bonds were formed).
The chief objective of manufacturing process improvement efforts is to significantly minimize process resources such as time, cost, waste, and consumed energy while improving product quality and process productivity. This paper presents a novel physics-informed optimization approach based on artificial intelligence (AI) to generate digital process twins (DPTs). The utility of the DPT approach is demonstrated in the case of finish machining of aerospace components made from gamma titanium aluminide alloy (γ-TiAl). This particular component has been plagued with persistent quality defects, including surface and sub-surface cracks, which adversely affect resource efficiency. Previous process improvement efforts have been restricted to anecdotal post-mortem investigation and empirical modeling, which fail to address the fundamental issue of how and when cracks occur during cutting. In this work, the integration of in-situ process characterization with modular physics-based models is presented, and machine learning algorithms are used to create a DPT capable of reducing environmental and energy impacts while significantly increasing yield and profitability. Based on the preliminary results presented here, we report an improvement in the overall embodied energy efficiency of over 84%, 93% in process queuing time, 2% in scrap cost, and 93% in queuing cost has been realized for γ-TiAl machining using our novel approach.
Gamma titanium aluminide (γ-TiAl) is considered a high-performance, low-density replacement for nickel-based superalloys in the aerospace industry due to its high specific strength, which is retained at temperatures above 800 °C. However, low damage tolerance, i.e., brittle material behavior with a propensity to rapid crack propagation, has limited the application of γ-TiAl. Any cracks introduced during manufacturing would dramatically lower the useful (fatigue) life of γ-TiAl components, making the workpiece surface’s quality from finish machining a critical component to product quality and performance. To address this issue and enable more widespread use of γ-TiAl, this research aims to develop a real-time non-destructive evaluation (NDE) quality monitoring technique based on acoustic emission (AE) signals, wavelet transform, and deep neural networks (DNN). Previous efforts have opted for traditional approaches to AE signal analysis, using statistical feature extraction and classification, which face challenges such as the extraction of good/relevant features and low classification accuracy. Hence, this work proposes a novel AI-enabled method that uses a convolutional neural network (CNN) to extract rich and relevant features from a two-dimensional image representation of 1D time-domain AE signals (known as scalograms), subsequently classifying the AE signature based on pedigreed experimental data and finally predicting the process-induced surface quality. The results of the present work show good classification accuracy of 80.83% using scalogram images, in-situ experimental data, and a VGG-19 pre-trained neural network, establishing the significant potential for real-time quality monitoring in manufacturing processes.
The relative stability of the different tri-aluminide (Al 3 M) phases in three binary systems (M = Zr, Nb and V) was assessed for their potential to form fine cubic L1 2 precipitates in additively manufactured alloys. Supersaturated thin films of Al-(8–30) at% M were sputtered and heat treated during in-situ x-ray diffraction (XRD) measurements to observe the temperature ranges of stability for each phase. As-sputtered films were then processed with laser tracks simulating additive manufacturing solidification conditions, and the formation of phases in the laser tracks was correlated with density functional theory (DFT) and nucleation rate calculations. We found that the metastable L1 2 structure is highly competitive with the stable DO 23 structure in the Al-Zr system, but much less stable than the DO 22 structure in the Al-Nb system, and both the DO 22 and Al 8 V 5 structure in the Al-V system. Furthermore, these experimental results were found to be in good agreement with the DFT and kinetic calculations, as we determined that the metastable L1 2 in Al-Zr only requires a small amount of undercooling to favor its nucleation over the stable DO 23 , suggesting additive manufacturing can be a viable pathway to develop Al-Zr alloys strengthened by a high volume fraction of L1 2 Al 3 Zr phase.