Driving forces for localized corrosion‐to‐fatigue crack transition in Al–Zn–Mg–Cu

Research on fatigue crack formation from a corroded 7075‐T651 surface provides insight into the governing mechanical driving forces at microstructure‐scale lengths that are intermediate between safe life and damage tolerant feature sizes. Crack surface marker‐bands accurately quantify cycles (N_i) to form a 10–20 μm fatigue crack emanating from both an isolated pit perimeter and EXCO corroded surface. The N_i decreases with increasing‐applied stress. Fatigue crack formation involves a complex interaction of elastic stress concentration due to three‐dimensional pit macro‐topography coupled with local micro‐topographic plastic strain concentration, further enhanced by microstructure (particularly sub‐surface constituents). These driving force interactions lead to high variability in cycles to form a fatigue crack, but from an engineering perspective, a broadly corroded surface should contain an extreme group of features that are likely to drive the portion of life to form a crack to near 0. At low‐applied stresses, crack formation can constitute a significant portion of life, which is predicted by coupling macro‐pit and micro‐feature elastic–plastic stress/strain concentrations from finite element analysis with empirical low‐cycle fatigue life models. The presented experimental results provide a foundation to validate next‐generation crack formation models and prognosis methods.     

Micrometer‐sized DNA–Single‐Fluorophore–DNA Supramolecule: Synthesis and Single‐Molecule Characterization

The synthesis of single‐fluorophore‐bis(micrometer‐sized DNA) triblock supramolecules and the optical and structural characterization of the construct at the single‐molecule level is reported. A fluorophore‐bis(oligodeoxynucleotide) triblock is synthesized via the amide‐coupling reaction. Subsequent protocols of DNA hybridization/ligation are developed to form the supramolecular triblock structure with λ‐DNA fragments on the micrometer length scale. The successful synthesis of the micrometer‐sized DNA–single‐fluorophore–DNA supramolecule is confirmed by agarose gel electrophoresis with fluorescence imaging under UV excitation. Single triblock structures are directly imaged by combined scanning force microscopy and single‐molecule fluorescence microscopy, and provide unambiguous confirmation of the existence of the single fluorophore inserted in the middle of the long DNA. This type of triblock structure is a step closer to providing a scaffold for single‐molecule electronic devices after metallization of the DNAs.     

Seed‐Induced Growth of Flower‐Like Au–Ni–ZnO Metal–Semiconductor Hybrid Nanocrystals for Photocatalytic Applications

The combination of metal and semiconductor components in nanoscale to form a hybrid nanocrystal provides an important approach for achieving advanced functional materials with special optical, magnetic and photocatalytic functionalities. Here, a facile solution method is reported for the synthesis of Au–Ni–ZnO metal–semiconductor hybrid nanocrystals with a flower‐like morphology and multifunctional properties. This synthetic strategy uses noble and magnetic metal Au@Ni nanocrystal seeds formed in situ to induce the heteroepitaxial growth of semiconducting ZnO nanopyramids onto the surface of metal cores. Evidence of epitaxial growth of ZnO{0001} facets on Ni {111} facets is observed on the heterojunction, even though there is a large lattice mismatch between the semiconducting and magnetic components. Adjustment of the amount of Au and Ni precursors can control the size and composition of the metal core, and consequently modify the surface plasmon resonance (SPR) and magnetic properties. Room‐temperature superparamagnetic properties can be achieved by tuning the size of Ni core. The as‐prepared Au–Ni–ZnO nanocrystals are strongly photocatalytic and can be separated and re‐cycled by virtue of their magnetic properties. The simultaneous combination of plasmonic, semiconducting and magnetic components within a single hybrid nanocrystal furnishes it multifunctionalities that may find wide potential applications.     

Efficient Vacuum‐Processed Light‐Emitting Diodes Based on Carbene–Metal–Amides

Efficient vacuum‐processed organic light‐emitting diodes are fabricated using a carbene–metal–amide material, CMA1. An electroluminescence (EL) external quantum efficiency of 23% is achieved in a host‐free emissive layer comprising pure CMA1. Furthermore external quantum efficiencies of up to 26.9% are achieved in host–guest emissive layers. EL spectra are found to depend on both the emissive‐layer doping concentration and the choice of host material, enabling tuning of emission color from mid‐green (Commission Internationale de l'Éclairage co‐ordinates [0.24, 0.46]) to sky blue ([0.22 0.35]) without changing dopant. This tuning is achieved without compromising luminescence efficiency (>80%) while maintaining a short radiative lifetime of triplets (<1 μs).     

Umformtechnologie: Prozesse – Werkstoff‐ charakterisierung – Simulation – Verifikation

Sheet forming technology – processes, materials, simulation and verification Hydroforming and Deep Drawing represent leading technologies for forming sheet metal components. The Materials Branch of the University of Duisburg‐Essen works since more than 10 years in the field of Hydroforming and showed that Hydroforming increases the strength and that the weldings of hydroformed tubes normally exhibit a same (fatigue) strength as the base material. For an improvement of the economics of hydroforming spliced tubes were considered and standard hollow nodes for tubes nodes structures were developed and a proposal was made to produce these tubes in variable tools with segments or lamellas. A significant increase in economics of Hydroforming and of Deep Drawing of components is achieved by an introduction of the principles of an integral (cooperative) development of products. At the University of Duisburg‐Essen the following stages are run through: CAD (the Material Branch uses PRO/ENGINEER®), forming simulation – for that PAM‐STAMP® (ESI) and PATRAN MARC MENTAT® (MSC) are used – FEM strength calculation and EVICD for a consideration of variable service loading. Forming simulation needs as basic material data the yield curve, the parameters of anisotropy and the Forming Limit Curve (FLC). For a determination of the FLC in Deep Drawing Tests suitable Nakazima specimens were developed by applying the principles of cooperative product development. The specimens could then successfully be validated in Deep Drawing Tests, which were instrumented by the advanced 3D‐forming‐analysis‐system AUTOGRID inProcess (VIALUX). Various other forming simulations were also performed and some general rules for the performance of forming simulations were formulated. Finally, reverse engineering is briefly discussed.     

Gold‐Catalyzed Vapor–Liquid–Solid Germanium‐Nanowire Nucleation on Porous Silicon

Nanoporous Si(111) substrates are used to study the effects of Au catalyst coarsening on the nucleation of vapor–liquid–solid‐synthesized epitaxial Ge nanowires (NWs) at temperatures less than 400 °C. Porous Si substrates, with greater effective interparticle separations for Au surface diffusion than nonporous Si, inhibit catalyst coarsening and agglomeration prior to NW nucleation. This greatly reduces the variation in wire diameter and length and increases the yield compared to nucleation on identically prepared nonporous Si substrates.     

Modelling the dependency of the Smith–Watson–Topper parameter on the cycles‐to‐failure using serial hybrid neural networks

Calculating the fatigue damage with a strain‐based approach requires an ?–N durability curve that links the strain amplitude to the corresponding number of cycles‐to‐failure. This ?–N curve is usually modelled by the Coffin–Manson relationship. If a loading mean‐level also needs to be considered, the original Coffin–Manson relationship is modified using a Smith–Watson–Topper parameter. In this article a methodology for modelling the dependence of the Smith–Watson–Topper parameter on the number of cycles‐to‐failure is presented. The core of the presented methodology represents a multilayer perceptron neural network combined with the Smith–Watson–Topper analytical model. The article presents the theoretical background of the methodology, which is applied for the case of the experimental fatigue data. The results show that it is possible to model ?–N curves for different influential parameters, such as the specimen's diameter and the testing temperature. The results further show that it is possible to predict ?–N curves even for those combinations of the influential parameters for which no experimental data about the material endurance is available. This fact makes the presented model very suitable for the application in an R&D process when a durability of a product should be estimated on the basis of a very limited set of experimental data about the material endurance characteristics.