The MSE is very proud to welcome the following plenary speakers at MSE 2018:
Fatigue-life prediction for loading conditions with very small strain amplitudes, i.e., high-cycle fatigue regime (HCF), is mostly based on S/N diagrams in the range of the fatigue limit. This solely phenomenological approach is reasonable and valuable from the point of view of applicability to design purposes, however a sound mechanistic understanding of the physical reasons for the cyclic life behaviour in the HCF and in particular in the VHCF (very-high-cycle fatigue) range is still lacking. In general, it is assumed that crack initiation mechanisms and short fatigue crack propagation processes govern fatigue life in these regimes. Moreover, it is now becoming accepted that the conventional fatigue limit does not imply complete reversibility of plastic strain. Local slip irreversibility causes crack initiation far below the fatigue limit. However, interaction of the crack tip with microstructural barriers, such as grain boundaries or second phase particles or grains, leads to a decrease and eventually to a stop in the crack-propagation rate.
In the present contribution examples for propagating and non-propagating conditions of short fatigue cracks are given from numerous Ph.D. works carried out in the author`s laboratory on various structural alloys, such as beta and alpha+beta titanium alloys, duplex steels, metastable austenitic stainless steels, and different ferritic and martensitic steels. To classify the results within the scope of predicting the service life for HCF- and VHCF-loading conditions, a numerical model based on the boundary-element method has been developed, where crack propagation is described by means of partially irreversible dislocation glide on crystallographic slip planes in a polycrystalline model microstructure (Voronoi cells). It is demonstrated that this approach is capable to account for the strong scatter in fatigue life for very small strain amplitudes, to model the effect of hydrogen and to contribute to the concept of tailored microstructures for improved cyclic-loading behaviour.
Computer science has advanced rapidly in the internet era, primarily due to the availability of very large data sets coupled with deep learning algorithms. The results have been impressive: autonomous vehicles, targeted advertisements, and computers chess champions. However, although there are significant opportunities to apply machine intelligence (MI) to materials problems, materials science has not yet capitalized on these advances. In this presentation, we will discuss various roles for MI – from black boxes to full physics predictors – using case studies that involve computer science approaches such as computer vision, data science, and machine learning applied to materials science and engineering objectives in interface science, micromechanics, microstructural characterization, and additive manufacturing. Based on our experience, we will suggest strategies for developing an MI ecosystem that combines advanced computational methods with well-curated data sets in order to realize the potential of these powerful tools.
In the last decades, the bio-based, biodegradable and eco-sustainable materials have irrupted in the panoram of the available options for different commercial and potential applications and have captured the interest of the researchers not only for the capability of replacing fuel-based raw materials, but for the new functionalities and properties that can be exploited
Plant-based materials have received considerable attenttion; plant oils, carbohydrates and proteins have all been used as starting materials for the synthesis of polymer-based goods. Starch and plant oils have had and protagonic role, but also the almost unmodified plant biomass, such as vegetable fibers that have been widely used mainly in the construction and automobile industries.
The main component of plants is cellulose , a carbohydrate with very useful properties, among which, its high crystallinity explains its high specific mechanical properties. This particular characteristic and its low density were the reasons for using vegetable fibers (natural composites with varying concentration of cellulose, lignin, hemicellulose and other minor components) as reinforcement of plastic composites, in the first place. Besides, cellulose fibers can be the source of very interesting and useful nanomaterials: microfibrillar cellulose and cellulose nanocrystals. Any of them can be used as main phases or as reinforcing phases in different composites. The applications are extremely varied and uses in nanoreinforced composites, strong papers, hydrogels, coatings, etc. have been reported or proposed.
In this presentation, the role of cellulose nanocrystals (CNC) from vegetable sources will be discussed, in particular as reinforcing materials for polyurethanes and bio-based polymeric matrices. Additionally, the capability of suspensions of cellulose nanocrystals to behave as liquid crystals will also be addressed, since this feature offers potential for the preparation of optically active films.
Internal interfaces, stacking faults and dislocations determine many mechanical, functional, and kinetic properties of alloys. These defects can be chemically manipulated by solute decoration, confined elemental partitioning and even by low-dimensional transformation phenomena, altering their energy, mobility, structure, and cohesion. Some of these phenomena are long known: Examples are Cottrell atmospheres at dislocations, Suzuki partitioning to stacking faults and grain boundary segregation according to the adsorption isotherm.
The lecture presents and discusses three aspects in that context. First, recent atomic-scale experiments show that the interplay between defect structure and chemistry can lead to a much larger variety of compositional – structural states than commonly assumed. Second, some of these states can be described by established thermodynamic and kinetic models. Third, embracing the full complexity of these defect decoration states via alloying and thermomechanical treatments establishes an approach referred to as 'segregation engineering'. In this concept defect decoration and transformation are not regarded as undesired phenomena but instead utilized to manipulate specific interface and dislocation structures, compositions and properties for advanced microstructure design.
Magnetic materials are key components in energy technologies, robotics, sensors and information technology. Magnets are inseparable from our everyday life. “Green” energy technologies such as wind turbines, electro-mobility and solid state cooling, rely on high performance magnetic materials which have to be available in bulk quantities, at low-cost and with tailored magnetic hysteresis.
The realisation of renewable energy technologies is generally linked to the sustainable availability of strategic metals such as the group of rare earth elements (REE) namely Nd, Gd, Tb, Dy, transition metals such as Co, Ga, Ge, In, and the platinum group metals. Resource criticality is understood here as a concept to assess potentials and risks in using raw materials and their functionality in emerging technologies. Specifically, the demand, sustainability and the reality of alternatives of rare earth elements will be discussed.
There is an ever-growing demand for the benchmark high performance Nd-Fe-B magnets. The increase in e-mobility and wind energy and other smart magnet usages in the future has yet to have its impact on the rare earth market. No substitute is at hand for the massive amounts of high-energy density magnets needed; yet various concept of heavy rare earth free, free rare earth and rare earth free magnets are being explored.
Gas-vapour compression technology for refrigeration, heating, ventilation, and air-conditioning has remained unchallenged for more than 150 years. There is a huge demand for a smarter, more flexible and more efficient cooling technology. Magnetic refrigeration could be that alternative working without gas-based refrigerants. Energy spent for domestic cooling is expected to outreach that for heating worldwide over the course of the twenty-first century.
I will address these different global trends and will attempt to scale bridge these challenges by discussing the modelling, synthesis, characterization, and property evaluation of novel magnetic materials considering their micromagnetic length scales, phase transition characteristics and hysteretic properties.
This Plenary Talk covers elements of physical metallurgy to explore new phases and guide unique nanostructure formation in alloys applied as thin films. Different thermodynamical driving forces are included in the free energy calculations for possible phase transformations from metastable solid solutions. Atom migration on the film surface and in the bulk are considered during film growth or post-deposition annealing for primary and secondary phase transformation, respectively. Microstructure and lattice defect formation is followed using XRD, HREM, and APT. The concept of age hardening in transition metal nitride alloys is demonstrated for isotructural model systems. Spinodal decomposition is thus reviewed for TiAlN by the formation of cubic-phase nm-size domains in a checker-board-pattern of TiN and AlN at temperatures corresponding to cutting tool operation.
2-D-nanolabyrinthine structuring in ZrAlN is obtained from intergrowth of non-isostructural phases of cubicZrN and wurtziteAlN. Superhardening occurs in TiN/Si3N4 nanocomposites due to thermodynamically-driven Si segregation forming monolayer-thick SiNx tissue phase, which may be a vacancy-stabilized cubic-SiNx phase. Curved-lattice growth is demonstrated in InAlN nanospirals by employing directional deposition flux and substrate rotation. Finally, overstoichiometric TiN provides a nanolaboratory to study precipitation of nitrogen gas bubbles. Here, the Gibbs Thomson effect leads to overpressurizing and eventual solidification of the nitrogen with crystallographic faceting to the TiN matrix.