TY - JOUR A1 - Zare Pakzad, S. A1 - Nasr Esfahani, M. A1 - Tasdemir, Z. A1 - Wollschläger, Nicole A1 - Li, T. A1 - Li, X. A1 - Yilmaz, M. A1 - Leblebici, Y. A1 - Erdem Alaca, B. T1 - Nanomechanical Modeling of the Bending Response of Silicon Nanowires JF - Applied Nano Materials N2 - Understanding the mechanical behavior of silicon nanowires is essential for the implementation of advanced nanoscale devices. Although bending tests are predominantly used for this purpose, their findings should be properly interpreted through modeling. Various modeling approaches tend to ignore parts of the effective parameter set involved in the rather complex bending response. This oversimplification is the main reason behind the spread of the modulus of elasticity and strength data in the literature. Addressing this challenge, a surface-based nanomechanical model is introduced in this study. The proposed model considers two important factors that have so far remained neglected despite their significance: (i) intrinsic stresses composed of the initial residual stress and surface-induced residual stress and (ii) anisotropic implementation of surface stress and elasticity. The modeling study is consolidated with molecular dynamics-based study of the native oxide surface through reactive force fields and a series of nanoscale characterization work through in situ threepoint bending test and Raman spectroscopy. The treatment of the test data through a series of models with increasing complexity demonstrates a spread of 85 GPa for the modulus of elasticity and points to the origins of ambiguity regarding silicon nanowire properties, which are some of the most commonly employed nanoscale building blocks. A similar conclusion is reached for strength with variations of up to 3 GPa estimated by the aforementioned nanomechanical models. Precise consideration of the nanowire surface state is thus critical to comprehending the mechanical behavior of silicon nanowires accurately. Overall, this study highlights the need for a multiscale theoretical framework to fully understand the size-dependent mechanical behavior of silicon nanowires, with fortifying effects on the design and reliability assessment of future nanoelectromechanical systems. KW - Silicon nanowires KW - Native oxide KW - Surface stress KW - Surface elasticity KW - Mechanical behavior PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-581676 DO - https://doi.org/10.1021/acsanm.3c02077 SP - 1 EP - 14 PB - ACS Publications AN - OPUS4-58167 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Vogel, F. A1 - Ngai, S. A1 - Zhou, X. Y. A1 - Zaiser, E. A1 - Manzoni, Anna Maria A1 - Wu, Y. A1 - Zheng, W. W. A1 - Zhang, P. A1 - Thompson, G. B. T1 - Tracking maze-like hierarchical phase separation behavior in a Fe-Si-V alloy JF - Journal of Alloys and Compounds N2 - Optimizing the properties of next-generation high-temperature and corrosion-resistant alloys is rooted in balancing structure-property relationships and phase chemistry. Here, we implement a complementary approach based on transmission electron microscopy (TEM) and atom probe tomography (APT) to ascertain aspects of hierarchical phase separation behavior, by understanding the microstructural evolution and the three-dimensional (3D) nanochemistry of a single crystal Fe79.5Si15.5V5.0 (at%) alloy. A maze-like hierarchical microstructure forms, in which a complex network of metastable disordered α plates (A2 phase) emerges within ordered α1 precipitates (D03 phase). The supersaturation in α1 (D03) precipitates with Fe and V drives the formation of α (A2) plates. The morphology of α (A2) plates is discussed concerning crystal structure, lattice misfit, and elastic strain. Phase compositions and a ternary phase diagram aid the thermodynamic assessment of the hierarchical phase separation mechanism via the Gibbs energy of mixing. A perspective on the stabilization of hierarchical microstructures beyond Fe79.5Si15.5V5.0 is elaborated by comparing hierarchical alloys. We find that the ratio of elastic anisotropy (Zener ratio) serves as a predictor of the hierarchical particles’ morphology. We suggest that the strengthening effect of hierarchical microstructures can be harnessed by improving the temporal and thermal stability of hierarchical particles. This can be achieved through phase-targeted alloying aiming at the hierarchical particles phase by considering the constituents partitioning behavior. Beyond Fe79.5Si15.5V5.0, our results demonstrate a potential pathway for improving the properties of high-temperature structural materials. KW - Atom probe tomography KW - Transmission electron microscopy KW - Hierarchical microstructure KW - Phase separation PY - 2023 DO - https://doi.org/10.1016/j.jallcom.2023.172157 SN - 0925-8388 VL - 968 SP - 1 EP - 17 PB - Elsevier B.V. AN - OPUS4-58343 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ulbricht, Alexander A1 - Avila Calderon, Luis A1 - Sommer, Konstantin A1 - Mohr, Gunther A1 - Evans, Alexander A1 - Skrotzki, Birgit A1 - Bruno, Giovanni T1 - Evolution of Creep Damage of 316L Produced by Laser Powder Bed Fusion JF - Advanced Engineering Materials N2 - The damage mechanisms of metallic components produced by process laser powder bed fusion differ significantly from those typically observed in conventionally manufactured variants of the same alloy. This is due to the unique microstructures of additively manufactured materials. Herein, the focus is on the study of the evolution of creep damage in stainless steel 316L specimens produced by laser powder bed fusion. X-ray computed tomography is used to unravel the influence of the process-specific microstructure from the influence of the initial void distribution on creep damage mechanisms. The void distribution of two specimens tested at 600 °C and 650 °C is analyzed before a creep test, after an interruption, and after fracture. The results indicate that the formation of damage is not connected to the initial void distribution. Instead, damage accumulation at grain boundaries resulting from intergranular cracking is observed. KW - Creep KW - Computed Tomography KW - PBF-LB/M/316L KW - Laser Powder Bed Fusion KW - Microstructure KW - AISI 316L KW - Additive Manufacturing PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-574127 DO - https://doi.org/10.1002/adem.202201581 SP - 1 EP - 9 PB - Wiley-VCH GmbH CY - Weinheim AN - OPUS4-57412 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Swaminathan, Srinivasan A1 - Sun, K. A1 - Was, G. S. T1 - Decoupling the roles of grain boundary oxidation and stress in IASCC of neutron-irradiated 304L stainless steel JF - Journal of Nuclear Materials N2 - Irradiation assisted stress corrosion cracking (IASCC) is known to be a combination of applied stress, and a corrosive environment in irradiated materials, but an appropriate understanding of how each of these components affects cracking is not yet clear. In this work, we isolate the role of grain boundary (GB) oxidation in IASCC. For this purpose, solution-annealed 304L stainless steel irradiated in reactor to 5.4 or 69 dpa was studied using a miniaturized four-point bend technique. Two modes of bend tests were conducted; straining in simulated pressurized water reactor primary water (PW) at 320 ◦C in an incremental manner, and pre-oxidation in PW at 320 ◦C without application of stress followed by dynamic straining in purified Ar at the same temperature until crack initiation. Exposure of the 5.4 dpa sample for 210 h in high temperature water initiated cracks in Ar at 60% of the yield stress (0.6YS), whereas the companion sample of the same dose exposed for 1010 h cracked in Ar at 0.5YS. The long-term exposure in water led to GB oxidation that ultimately lowered the crack initiation stress. Dynamic straining in water resulted in larger crack lengths and greater crack depths indicating stress accelerated oxidation and cracking. Dislocation pile-ups at dislocation channel-grain boundary sites provide an amplification of the applied stress to a level consistent with the fracture stress of the grain boundary oxide, providing an explanation for IASCC that occurs at applied stresses well below the irradiated yield stress of the alloy. There was no evidence of cracking upon straining of an unoxidized 69 dpa sample in Ar to well above yield, confirming that the irradiated state is not inherently susceptible to intergranular (IG) cracking and that oxidized GBs are responsible for initiation of IG cracking. KW - Stress corrosion cracking KW - Grain boundary oxidation KW - Stainless steel KW - Crack initiation KW - IASCC PY - 2023 DO - https://doi.org/10.1016/j.jnucmat.2023.154604 SN - 0022-3115 VL - 585 SP - 1 EP - 15 PB - Elsevier B.V. AN - OPUS4-58233 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Suárez Ocaño, Patricia A1 - Manzoni, Anna Maria A1 - Lopez-Galilea, I. A1 - Ruttert, B. A1 - Laplanche, G. A1 - Agudo Jácome, Leonardo T1 - Influence of cooling rate on the microstructure and room temperature mechanical properties in the refractory AlMo0.5NbTa0.5TiZr superalloy JF - Journal of Alloys and Compounds N2 - Refractory chemically complex alloys with bcc-based microstructures show great potential for high-temperature applications but most of them exhibit limited room-temperature ductility, which remains a challenge. One such example is the AlMo0.5NbTa0.5TiZr alloy, mainly consisting of a nano-scaled structure with an ordered B2 matrix and a high-volume fraction of aligned cuboidal and coherently embedded A2 precipitates. This work aims to investigate how the cooling rate after hot isostatic pressing of the AlMo0.5NbTa0.5TiZr alloy affects its microstructure and its resulting hardness and fracture toughness at room temperature. A slow cooling rate of 5 °C/min leads to a coarse microstructure consisting of aligned slabs (mean A2 precipitate ≈ 25 nm) with a nanohardness of about 8 GPa. In contrast, after the fastest cooling rate (30 °C/min), the A2 precipitates become more cubic with an edge length of ≈ 16 nm, resulting in an increase in nanohardness by 10 %. The fracture toughness is roughly independent of the cooling rate and its mean value (≈ 4.2 MPa∙m1/2) resembles that of some B2 intermetallics and other A2/B2 alloys. As the lattice misfit between the A2 and B2 phases is known to play a key role in microstructure formation and evolution, its temperature dependence between 20 and 900 °C was investigated. These findings offer insights into the evolution of the microstructure and room-temperature mechanical properties of the AlMo0.5NbTa0.5TiZr alloy, which could help the development of advanced chemically complex alloys. KW - High entropy alloy KW - Lattice misfit KW - Scanning electron microscopy KW - Transmission electron microscopy KW - X-ray diffraction KW - Refractory alloy PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-572809 DO - https://doi.org/10.1016/j.jallcom.2023.169871 SN - 0925-8388 VL - 949 SP - 169871 PB - Elsevier B.V. AN - OPUS4-57280 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Suárez Ocano, Patricia A1 - Agudo Jácome, Leonardo A1 - Lopez-Galilea, I. A1 - Darvishi Kamachali, Reza A1 - Fries, S. G. T1 - Data regarding the experimental findings compared with CALPHAD calculations of the AlMo0.5NbTa0.5TiZr refractory high entropy superalloy JF - Data in brief N2 - This contribution contains the raw data used to compare experimental results with thermodynamic calculations using the CALPHAD method, which is related to the research article “The AlMo0.5NbTa0.5TiZr refractory high entropy superalloy: experimental findings and comparison with calculations using the CALPHAD method” [1] , and therefore this article can be used as a basis for interpreting the data contained therein. The AlMo0.5NbTa0.5TiZr refractory superalloy was characterized in the cast and annealed condition (1400 °C for 24 h) in order to measure grain size and to identify and measure the size and area fraction of the phases present. The raw data of this article include X-ray diffraction (XRD) measurements, microstructural characterization by scanning and transmission electron microscopy (SEM and TEM), and elemental analysis by energy dispersive X-ray spectroscopy (EDX). XRD includes the determination of phases and the lattice parameters (A2, B2, and hexagonal structure). Microstructural analysis by scanning and transmission electron microscopy includes (1) identification of composition, size, and volume fraction of the present phases and (2) determination of grain size. Based on these experimental data, it is possible to identify similarities and discrepancies with the data calculated using the CALPHAD method for the alloy under study in Ref. [1] , which provides the basis for better and more efficient development of reliable databases. KW - Transmission electron microscopy KW - Scanning electron microscopy KW - Microstructural characterization KW - Refractory high entropy alloys PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-568009 DO - https://doi.org/10.1016/j.dib.2022.108858 SN - 2352-3409 VL - 46 SP - 1 EP - 19 PB - Elsevier CY - Amsterdam AN - OPUS4-56800 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schröder, Jakob A1 - Heldmann, A. A1 - Hofmann, M. A1 - Evans, Alexander A1 - Petry, W. A1 - Bruno, Giovanni T1 - Determination of diffraction and single-crystal elastic constants of laser powder bed fused Inconel 718 JF - Materials Letters N2 - High energy X-ray synchrotron diffraction is used to investigate the elastic anisotropy of the nickel-based superalloy IN718 produced by laser powder bed fusion (PBF-LB). This material is characterized by a columnar grain morphology with some crystallographic texture. The material is subjected to elastic loading to determine the diffraction elastic constants (DECs). Furthermore, the single-crystal elastic constants (SCEC) are refined from these experiments using different micromechanical models. The results show that each micromechanical model predicts a specific set of SCEC that well describes the elastic anisotropy of PBF-LB/IN718. KW - Mechanical Engineering KW - Mechanics of Materials KW - Condensed Matter Physics KW - General Materials Science PY - 2023 DO - https://doi.org/10.1016/j.matlet.2023.135305 SN - 0167-577X VL - 353 SP - 1 EP - 5 PB - Elsevier B.V. AN - OPUS4-58477 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schröder, Jakob A1 - Evans, Alexander A1 - Luzin, V. A1 - Abreu Faria, G. A1 - Degener, Sebastian A1 - Polatidis, E. A1 - Čapek, J. A1 - Kromm, Arne A1 - Dovzhenko, G. A1 - Bruno, Giovanni T1 - Texture-based residual stress analysis of laser powder bed fused Inconel 718 parts JF - Journal of Applied Crystallography N2 - Although layer-based additive manufacturing methods such as laser powder bed fusion (PBF-LB) offer an immense geometrical freedom in design, they are typically subject to a build-up of internal stress (i.e. thermal stress) during manufacturing. As a consequence, significant residual stress (RS) is retained in the final part as a footprint of these internal stresses. Furthermore, localized melting and solidification inherently induce columnar-type grain growth accompanied by crystallographic texture. Although diffraction-based methods are commonly used to determine the RS distribution in PBF-LB parts, such features pose metrological challenges in their application. In theory, preferred grain orientation invalidates the hypothesis of isotropic material behavior underlying the common methods to determine RS. In this work, more refined methods are employed to determine RS in PBF-LB/M/IN718 prisms, based on crystallographic texture data. In fact, the employment of direction-dependent elastic constants (i.e. stress factors) for the calculation of RS results in insignificant differences from conventional approaches based on the hypothesis of isotropic mechanical properties. It can be concluded that this result is directly linked to the fact that the {311} lattice planes typically used for RS analysis in nickel-based alloys have high multiplicity and less strong texture intensities compared with other lattice planes. It is also found that the length of the laser scan vectors determines the surface RS distribution in prisms prior to their removal from the baseplate. On removal from the baseplate the surface RS considerably relaxes and/or redistributes; a combination of the geometry and the scanning strategy dictates the sub-surface RS distribution. KW - Additive manufacturing KW - Electron backscattered diffraction KW - Principal stress KW - Residual stress PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-578331 DO - https://doi.org/10.1107/S1600576723004855 SN - 1600-5767 VL - 56 IS - Pt 4 SP - 1076 EP - 1090 AN - OPUS4-57833 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schmies, Lennart A1 - Hemmleb, Matthias A1 - Bettge, Dirk T1 - Relevant input data for crack feature segmentation with deep learning on SEM imagery and topography data JF - Engineering Failure Analysis N2 - 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. KW - Fractography KW - Machine Learning KW - Deep Learning KW - KI PY - 2023 DO - https://doi.org/10.1016/j.engfailanal.2023.107814 VL - 156 SP - 1 EP - 8 PB - Elsevier AN - OPUS4-58918 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schmies, Lennart A1 - Botsch, B. A1 - Le, Q.-H. A1 - Yarysh, A. A1 - Sonntag, U. A1 - Hemmleb, M. A1 - Bettge, Dirk T1 - Classification of fracture characteristics and fracture mechanisms using deep learning and topography data T1 - Klassifikation von Bruchmerkmalen und Bruchmechanismen mittels Deep Learning und unter Verwendung von Topographiedaten JF - Practical Metallography N2 - In failure analysis, micro-fractographic analysis of fracture surfaces is usually performed based on practical knowledge which is gained from available studies, own comparative tests, from the literature, as well as online databases. Based on comparisons with already existing images, fracture mechanisms are determined qualitatively. These images are mostly two-dimensional and obtained by light optical and scanning electron imaging techniques. So far, quantitative assessments have been limited to macrocopically determined percentages of fracture types or to the manual measurement of fatigue striations, for example. Recently, more and more approaches relying on computer algorithms have been taken, with algorithms capable of finding and classifying differently structured fracture characteristics. For the Industrial Collective Research (Industrielle Gemeinschaftsforschung, IGF) project “iFrakto” presented in this paper, electron-optical images are obtained, from which topographic information is calculated. This topographic information is analyzed together with the conventional 2D images. Analytical algorithms and deep learning are used to analyze and evaluate fracture characteristics and are linked to information from a fractography database. The most important aim is to provide software aiding in the application of fractography for failure analysis. This paper will present some first results of the project. N2 - Die mikrofraktographische Analyse von Bruchflächen wird in der Schadensanalyse meist auf der Basis von Erfahrungswissen vorgenommen, welches aus vorliegenden Untersuchungen, eigenen Vergleichsversuchen und aus der Literatur und online Datenbanken stammt. Durch Vergleiche mit bereits vorliegenden Bildern werden qualitativ Bruchmechanismen ermittelt. Grundlage dafür sind zumeist zweidimensionale Aufnahmen aus licht- und elektronenoptischen Verfahren. Quantitative Aussagen beschränken sich bislang beispielsweise auf makroskopische Anteile von Bruchmechanismen oder die manuelle Ausmessung von Schwingstreifen. In jüngerer Zeit gibt es vermehrt Ansätze, Computer-Algorithmen einzusetzen, die in der Lage sind, unterschiedlich strukturierte Bruchmerkmale zu finden und zu klassifizieren. Im hier vorgestellten IGF-Vorhaben „iFrakto“ werden elektronenoptische Aufnahmen erzeugt und daraus Topographie-Informationen berechnet. Diese gewonnenen Topographie-Informationen werden zusammen mit den klassischen 2D-Bildern ausgewertet. Analytische Algorithmen und Deep Learning werden eingesetzt, um Bruchmerkmale zu analysieren, zu bewerten und mit Informationen aus einer fraktographischen Datenbank zu verknüpfen. Wichtigstes Ziel ist die Bereitstellung von Software zur Unterstützung der Fraktographie in der Schadensanalyse. In diesem Beitrag werden erste Ergebnisse des Vorhabens vorgestellt. KW - Fractography KW - Deep Learning KW - Classification PY - 2023 DO - https://doi.org/10.1515/pm-2022-1008 SN - 0032-678X VL - 60 IS - 2 SP - 76 EP - 92 PB - De Gruyter AN - OPUS4-56962 LA - mul AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -