Effect of Sn on the Dehydrogenation Process of TiH2 in Al Foams

The study of the dehydrogenation process of TiH2 in aluminum foams produced by the powder metallurgy technique is essential to understanding its foaming behavior. Tin was added to the Al foam to modify the dehydrogenation process and stabilize the foam. A gradual decomposition and more retention of hydrogen gas can be achieved with Sn addition resulting in a gradual and larger expansion of the foam

Properties of heat treated aluminium foams

Aluminium foams based on the wrought alloy AA6061 were subjected to different heat treatments in order to evaluate possibilities to tailor their mechanical properties. Quenching after foaming was carried out either in air or in water. Solution heat treatment conditions were varied from 'no treatment' to treatments combined with different air and water quenching methods. This gave rise to different cooling rates that were measured in-situ. Full age-hardening cycles were compared to heat treatments in which a simplified programme was applied. In total, the effect of nine different heat treatments on micro-hardness and the compression properties of foams were investigated. Foams that were fully heat-treated performed best with an increase of strength by 60-75% over the untreated samples. However, age-hardening directly after foaming also caused significant improvements of strength, thus allowing to omit water quenching steps which carry the danger of damaging the foamed structure

Material-integrated cluster computing in self-adaptive robotic materials using mobile multi-agent systems

Recent trends like internet-of-things (IoT) and internet-of-everything (IoE) require new distributed computing and communication approaches as size of interconnected devices moves from a cm 3 - to the sub-mm 3 -scale. Technological advance behind size reduction will facilitate integration of networked computing on material rather than structural level, requiring algorithmic and architectural scaling towards distributed computing. Associated challenges are linked to use of low reliability, large scale computer networks operating on low to very low resources in robotic materials capable of performing cluster computing on micro-scale. Networks of this type need superior robustness to cope with harsh conditions of operation. These can be provided by self-organization and—adaptivity. On macro scale, robotic materials afford unified distributed data processing models to allow their connection to smart environments like IoT/IoE. The present study addresses these challenges by applying mobile Multi-agent systems (MAS) and an advanced JavaScript agent processing platform (JAM), realizing self-adaptivity as feature of both data processing and the mechanical system itself. The MAS’ task is to solve a distributed optimization problem using a mechanically adaptive robotic material in which stiffness is increased via minimization of elastic energy. A practical realization of this example necessitates environmental interaction and perception, demonstrated here via a reference architecture employing a decentralized approach to control local property change in service based on identification of the loading situation. In robotic materials, such capabilities can support actuation and/or lightweight design, and thus sustainability

Computing within materials: Self-adaptive materials and self-organizing agents

Materials Informatics addresses commonly the design of new materials using advanced algorithms and methods from computer science like Machine Learning and Data Mining. Ongoing miniaturization of computers down to the micro-scale-level enables the integration of computing in structures and materials that can be understand as Materials Informatics from another point of view. There are two major application classes: Smart Sensorial Materials and Smart Adaptive Materials. The latter class is considered in this work by combining self-organizing and adaptive Multi-agent Systems with materials posing changeable material properties like stiffness by actuators. It is assumed that the computational part of this micro-scale Cyber-Physical-System is entirely integrated in the material or structure as a distributed computer composed of a network of low-resource computers. Each node is connected to sensors and actuators. Actually only macroscopic systems can be realized. Therefore a multi-domain simulation combining computational and physical simulation is used to demonstrate the approach and to evaluate self-adaptive algorithms

Adaptation of aluminium foam properties by means of precipitation hardening

Aluminium foam samples based on four aluminium alloys were investigated with respect to their reaction to heat treatments, namely precipitation hardening treatments. Foam samples were produced according to the powder compact foaming or Fraunhofer process. 6000 and 7000 series alloys containing significant amounts of copper 6061, 7075 were compared to members of the same group with lower copper content 6082, 7020 as matrix alloys. Comparison was based on strength values and failure modes as reflected in the stress strain curves obtained in quasi static compression tests. Measurements were performed on samples without heat treatment and samples subjected to different precipitation hardening treatments. To evaluate the influence of quench sensitivity, the quench rate was varied for the alloys 6082 and 7020 by using air and water as quenchant

Kinetic analysis of foaming agent variants as a means towards optimised temperature cycles and foaming agent/matrix alloy combinations

Different titanium hydride variants have been produced by means of thermal treatment in air. Thermal analysis data on these materials has been used for kinetic analyses comparing different kinetic models for the description of the decomposition reaction. Models based on Prout-Tompkins kinetic equations have finally been selected. For these, parameter values of the so-called kinetic triplet have been determined, allowing prediction of the course of the decomposition for arbitrary temperature cycles. These predictions are compared to measured data and the models thus justified. For a range of low-melting matrix alloys of the Al-Si-Cu-Zn type containing different foaming agent variants, foam expansion experiments have been performed during which time and temperature as well as volume expansion were recorded. AlSi7 has been included in the study as a reference material. For each combination of matrix alloy and foaming agent the foaming temperature and thus the temperature cycle endured by the precursor has been varied as an additional parameter. The resulting expansion curves have been matched with the prediction of the decomposition reaction for the respective temperature cycles derived from the initial kinetic analyses of the foaming agent variants, showing good agreement up to medium levels of expansion. As criterion for foam collapse, a limiting gas release rate is proposed. Based on such criteria on the one hand and kinetic analysis results on the other, temperature cycles giving tailored shapes of the degree of reaction-vs.-time/temperature curve and promising improved foam expansion can be defined. Entnommen aus TEMA</a

Additive Manufacturing of Composites and Complex Materials

Advanced composite materials form an important class of high-performance industrial materials used in weight-sensitive applications such as aerospace structures, automotive structures and sports equipment. In many of these applications, parts are made in small production runs, are highly customized and involve long process development times. Developments in additive manufacturing (AM) methods have helped in overcoming many of these limitations. The special topic of Additive Manufacturing of Composites and Complex Materials captures the state of the art in this area by collecting nine papers that present much novel advancement in this field. The studies under this topic show advancement in the area of AM of carbon fiber and graphene-reinforced composites with high thermal and electrical conductivities, development of new hollow glass particle-filled syntactic foam filaments for printing lightweight structures and integration of sensors or actuators during AM of metallic parts. Some of the studies are focused on process optimization or modification to increase the manufacturing speed or tuning manufacturing techniques to enable AM of new materials