5 Werkstofftechnik
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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.
Gypsum (CaSO4∙2H2O), bassanite (CaSO4∙0.5H2O), and anhydrite (CaSO4) are essential evaporite minerals for the evolution of hyper-arid surface environments on Earth and Mars (Voigt et al. 2019; Vaniman et al. 2018). The formation mechanism of especially anhydrite has been a matter of scientific debate for more than a century (van’t Hoff et al. 1903). To date, there exists no model that can reliably predict anhydrite formation at earth’s surface conditions. While thermodynamics favor its formation, it is hardly achieved on laboratory time scales at conditions fitting either the Atacama Desert on Earth, or the surface of Mars (Wehmann et al. 2023). In light of most recent developments (e.g. Stawski et al. 2016), that advocate for a complex, non-classical nucleation mechanism for all calcium sulphates, we present an analysis of natural samples from the Atacama Desert to identify key features that promote the nucleation and growth of anhydrite under planetary surface conditions. Our analyses reveal at least three distinct anhydrite facies, with differing mineralogy and micro- to nano-structures. The facies are (1) aeolian deposits with sub-μm grain sizes, (2) (sub-)surface nodules that formed from aeolian deposits and (3) selenites with secondary anhydrite rims. Possible mechanisms of their formation will be discussed.
Several studies have shown that the electron beam (e-beam) can be used to create nanomaterials from microparticles in situ in a TEM. However, attempts to produce gold nanoparticles (NPs) on silicon oxide substrate remained to be accomplished. Here, we show that the production of gold NPs is possible by using the e-beam in a SEM, under a set of parameters. To understand the physical mechanisms leading to the gold NPs, the mechanisms of e-beam induced charging as well as e-beam induced heating of the MPs were discussed. Several hints point to heating as the driving mechanism.
Several studies have shown that the electron beam (e-beam) can be used to create nanomaterials from microparticles in situ in a TEM. However, attempts to produce gold nanoparticles (NPs) on silicon oxide substrate remained to be accomplished. Here, we show that the production of gold NPs is possible by using the e-beam in a SEM, under a set of parameters. The NPs produced present a size gradient along the radial direction. A parameter study shows that the microparticles may: 1) flicker away without producing NPs, 2) fragment to form NPs and/or 3) react with the silicon oxide substrate, depending on the applied current. A hypothesis regarding the driving physical phenomena that lead the microparticles to fragment into NPs is discussed. Fabrication of gold NPs in the SEM provides a more cost-effective option as compared to the established method in the TEM.
Gypsum (CaSO4∙2H2O) and anhydrite (CaSO4) are among the dominant evaporite minerals in the Atacama Desert [1]. They are distributed ubiquitously, and play a key role in local landscape evolution.
The formation mechanism of especially anhydrite has been a matter of scientific debate for more than a century [2]. To date, there exists no model that can reliably predict anhydrite formation at earth’s surface conditions. While thermodynamics favor its formation [3], it is hardly achieved on laboratory time scales at conditions fitting the Atacama Desert. Long induction times for nucleation have recently been modeled by Ossorio et al. [4]. However, anhydrite can be readily found in the Atacama Desert. Recently, the mineral was synthesized in flow-through reactors as a byproduct of K-jarosite dissolution at high water activity (aw=0.98) and room temperature [5], even-though the thermodynamic stability field begins only under a value of ~0.8. Additionally, recent studies investigated the nano-structure of various calcium-sulfates, which advocate for highly non-classical crystallization behavior [6]. The specific roles of particulates, ionic or organic reagents working as catalysts for the non-classical crystallization pathway remain to be determined.
Here, we present recent results from flow-through experiments as well as analyses of anhydrite samples from the Atacama Desert. Flow-through experiments were performed to systematically explore the domains of flow rate, composition, ionic-strengths and starting materials. Neither primary, nor secondary anhydrite was produced in any of these experiments. Analyses on Atacama samples reveal the existence of at least three distinct anhydrite facies, with differing mineralogy and micro- to nano-structures. The facies are (1) aeolian deposits with sub-µm grain sizes, (2) (sub-)surface nodules that formed from aeolian deposits and (3) selenites with secondary anhydrite rims. Possible mechanisms of their formation will be discussed.
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.
While a lage amount of research on high entropy alloys is oriented towards mechanical properties and the microstructural improvement it is also necessary to keep an eye on the environment that potential application materials will be submitted to. The Co-Cr-Fe-Ni based high entropy family has shown great potential over the years of high entropy research and some candidate alloys are chosen for an insight into their corrosion behaviour. Several atmospheres are studied, i.e. O2, H2O, SO2 and a mix thereof in argon as well as synthetic air. Just as for classic alloys, the chromium is the most important element in terms of protection agains further corrosion. The addition of manganese, as in case of the “Cantor alloy” CrMnFeCoNi, overpasses Cr when it comes to oxygen affinity and thus counteracts the layer formation of Cr2O3. Even without Mn, a temperature chosen too high will also affect the formation of the chromium oxide layer and spall it off, annulling its protective potential. We can also observe how trace elements influence the layer formation. These effects and their mechanisms will be discussed for the alloys CrFeNi, CoCrNi, CrMnFeCoNi and variations of Al10Co25Cr8Fe15Ni36Ti6 using a combination of electron microscopy, thermodynamic calculations and x-ray diffraction.
The multi-phase approach has proven to widen the application properties of high entropy alloys. After a decade of testing different alloys in the Al-Co-Cr-Cu-Fe-Ni-Ti family the Al10Co25Cr8Fe15Ni36Ti6 was found to be a solid base for more fine-tuned microstructural optimization. Following the example of superalloys, the Al10Co25Cr8Fe15Ni36Ti6 alloy aims for a γ/γ' microstructures in order to guarantee a good microstructural stability at high temperatures. The shape and volume fraction of the γ' particles is known to influence the mechanical properties of superalloys, and they do so in the high entropy family as well [1]. Shape, misfit and creep properties of several modified versions of the Al10Co25Cr8Fe15Ni36Ti6 alloy are compared and discussed in this talk.
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.
A round-robin study has been carried out to estimate the impact of the human element in small-angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions and two from powders. Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5% and half of the population width entries within 40%. Due to the added complexity of the structure factor, far fewer people submitted answers on the powder datasets. For those that did, half of the entries for the means and widths were within 44 and 86%, respectively. This round-robin experiment highlights several causes for the discrepancies, for which solutions are proposed.