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High‐temperature KCl‐induced corrosion of high Cr and Ni alloys investigated by in‐situ diffraction
(2024)
High‐temperature KCl‐induced corrosion in laboratory air was observed in situ utilizing X‐ray diffraction. High Cr‐containing model alloys (Fe‐13Cr, Fe‐18Cr‐12Ni, and Fe‐25Cr‐20Ni) were coated with KCl and exposed to dry air at 560°C. KCl‐free alloys were studied in the equivalent atmosphere as a reference. After exposure to KCl‐free environments, all alloys showed the formation of very thin oxide layers, indicating good corrosion resistance. In contrast, KCl‐bearing alloys showed distinct damage after exposure.
In this work we instigated the fragmentation of Au microparticles supported on a thin amorphous carbon film by irradiating them with a gradually convergent electron beam inside the Transmission Electron Microscope. This phenomenon has been generically labeled as ‘‘electron beam-induced fragmentation’’ or EBIF and its physical origin remains contested. On the one hand, EBIF has been primarily characterized as a consequence of beam-induced heating. On the other, EBIF has been attributed to beam-induced charging eventually leading to Coulomb explosion. To test the feasibility of the charging framework for EBIF, we instigated the fragmentation of Au particles under two different experimental conditions. First, with the magnetic objective lens of the microscope operating at full capacity, i.e. background magnetic field 𝐵 = 2 T, and with the magnetic objective lens switched off (Lorenz mode), i.e. 𝐵 = 0 T. We observe that the presence or absence of the magnetic field noticeably affects the critical current density at which EBIF occurs. This strongly suggests that magnetic field effects play a crucial role in instigating EBIF on the microparticles. The dependence of the value of the critical current density on the absence or presence of an ambient magnetic field cannot be accounted for by the beam-induced heating model. Consequently, this work presents robust experimental evidence suggesting that Coulomb explosion driven by electrostatic charging is the root cause of EBIF.
This study investigates the room‐ and high‐temperature (650 °C) tensile and low‐cycle‐fatigue behavior of Inconel 718 produced by laser powder bed fusion (PBF‐LB/M) with a four‐step heat treatment and compares the results to the conventional wrought material. The microstructure after heat treatment is characterized on different length scales. Compared to the wrought variant, the elastic and yield properties are comparable at both test temperatures while tensile strength, ductility, and strain hardening capacity are lower. The fatigue life of the PBF‐LB/M variant at room temperature is slightly lower than that of the wrought material, while at 650 °C, it is vice versa. The cyclic stress response for both material variants is characterized by cyclic softening, which is more pronounced at the higher test temperature. High strain amplitudes (≥0.7%) at room temperature and especially a high testing temperature result in the formation of multiple secondary cracks at the transitions of regions comprising predominantly elongated grain morphology and columns of stacked grains with ripple patterns in the PBF‐LB/M material. This observation and pronounced crack branching and deflection indicate that the cracks are controlled by sharp micromechanical gradients and local crystallite clusters.
Extended X-ray absorption fine structure (EXAFS) conducted on an equiatomic MoNbTaW bcc medium-entropy alloy that was annealed at 2273 K reveals unexpectedly small 1st and 2nd shell element-specific lattice distortions. An experimental size-mismatch parameter, δexp, is determined to be ca. 50% lower than the corresponding calculated value. Around W, short-range order (SRO) preferring 4d elements in the 1st and 2nd shells persists. A Nb-W ordering is found, which is reminiscent of ordering emerging at lower temperatures in the B2(Mo,W;Ta,Nb)- and B32(Nb,W)-phases. With high-temperature ordering preferences in fcc also foreshadowing low-temperature phase, these findings suggest a general feature of high-temperature SRO.
The unusual behavior observed in the coefficient of thermal expansion and specific heat capacity of CrFeNi, CoCrNi, and CoCrFeNi medium/high-entropy alloys is commonly referred to as the K-state effect. It is shown to be independent of the Curie temperature, as demonstrated by temperature-dependent magnetic moment measurements. CoCrFeNi alloy is chosen for detailed characterization; potential reasons for the K-state effect such as texture, recrystallization, and second-phase precipitation are ruled out. An examination of the electronic structure indicates the formation of a pseudo-gap in the Density of States, which suggests a specific chemical interaction between Ni and Cr atoms upon alloying. Hybrid Monte Carlo/Molecular Dynamic (MC/MD) simulations indicate the presence of non-negligible chemical short-range order (CSRO). Local lattice distortions are shown to be negligible, although deviations around Cr and Ni elements from those expected in a fully disordered structure are experimentally observed by X-ray absorption spectroscopy. The determined bonding distances are in good agreement with MC/MD calculations. A mechanism is proposed to explain the anomalies and calorimetric experiments and their results are used to validate the mechanism.
Irradiation assisted stress corrosion cracking (IASCC) is a form of intergranular stress corrosion cracking that occurs in irradiated austenitic alloys. It requires an irradiated microstructure along with high temperature water and stress. The process is ubiquitous in that it occurs in a wide range of austenitic alloys and water chemistries, but only when the alloy is irradiated. Despite evidence of this degradation mode that dates back to the 1960s, the mechanism by which it occurs has remained elusive. Here, using high resolution electron backscattering detection to analyze local stress-strain states, high resolution transmission electron microscopy to identify grain boundary phases at crack tips, and decoupling the roles of stress and grain boundary oxidation, we are able to unfold the complexities of the phenomenon to reveal the mechanism by which IASCC occurs. The significance of the findings impacts the mechanical integrity of core components of both current and advanced nuclear reactor designs worldwide.
Using the method of directional solidification, single crystals of experimental nickel-based superalloys with negative, zero, and positive γ/γ' misfits are obtained. The γ' solvus, solidus, and liquidus temperatures of the alloys are determined, and the microstructures of the alloys after directional solidification, heat treatment, and creep tests are investigated. Creep tests are performed at temperatures of 800 and 1000°C. It is found that single crystals of the alloy with a negative γ/γ' misfit have the highest creep resistance and lifetime (the crystal lattice period of the γ' phase is smaller than that of the γ matrix).
A systematic study on a face‐centered cubic‐based compositionally complex alloy system Al–Co–Cr–Cu–Fe–Ni in its single‐phase state is carried out, where a mother senary compound Al₈Co₁₇Cr₁₇Cu₈Fe₁₇Ni₃₃ and five of its suballoys, obtained by removing one element at a time, are investigated and exhaustively analyzed determining the contribution of each alloying element in the solid solution. The senary and the quinaries are compared using experimental techniques including X‐ray absorption spectroscopy, X‐ray diffraction, transmission electron microscopy, and first principles hybrid Monte Carlo/molecular dynamics simulations. Chemical short‐range order and bond length distances have been determined both at the experimental and computational level. Electronic structure and local atomic distortions up to 5.2 Å have been correlated to the microhardness values. A linear regression model connecting hardness with local lattice distortions is presented.
Interpreting high-temperature corrosion induced by mixed-gas atmospheres is challenging due to the different contributions of oxidizing gases. Here, a comprehensive study on the combined oxidation/sulfidation using label molecules is presented. Fe-Cr model alloys with 2 wt% and 9 wt% Cr were isothermally exposed using a volumetric mixture of 0.5%S16O2/27%H218O and 0.5%S16O2/7%H218O at 650 ◦C for 5 h and then characterized by secondary ion mass spectroscopy (SIMS). Additionally, the reactions were followed in-situ utilizing energy dispersive X-ray diffraction. The study showed that both S16O2 and H218O contribute to the oxidation of the alloys but to different extents depending on the Cr-content.
Fractography plays a critical role in failure analysis of engineering components and has a considerable importance for safety investigations. Usually, the interpretation of fracture surfaces is done by experts with the help of literature and experimental data, that requires a lot of experience. The use of deep learning (DL) with neural networks in failure analysis becomes more and more relevant with the rapidly developing possibilities. Especially, the modern network architectures can assist fractographers in determining various fracture features on SEM images of the fracture surfaces. The basis for the best possible evaluation is the understanding of the influence of the input data used for training deep neural networks (DNN). Therefore, this study discusses the influence of the selection of the input data used for the prediction quality of these networks in order to take this into account for future data acquisition. Specimens of various metallic materials were subjected to fatigue cracking experiment under laboratory conditions. The fractured surfaces were then imaged using various modes or detectors (such as SE, BSE and topography) in SEM, and those captured images were used to create a training data set. The relevance of the individual data for the quality of the prediction is determined by a specific combination of the different detector data. For the training, the well-established architecture of a UNet-ResNet34 with a fixed set of hyperparameters is used. It has been found in this present study that the combination of all input data significantly increases the prediction accuracy, whereby even the combination of SE and BSE data provides considerable advantages over the exclusive use of SE images.