Recrystallization kinetic behavior of copper-bearing strip cast steel

In the present study, copper-bearing low carbon steels were produced by direct strip casting (DSC) method on a pilot scale. The effects of copper on mechanical, microstructural, and recrystallization behavior were investigated. As-cast microstructure mainly consists of polygonal ferrite and Widmanstatten ferrite. The increase in Cu increases the amount of Widmanstatten ferrite and induces the formation of bainite in the as-cast condition. It was found that copper increases strength and hardness by solid solution strengthening, grain refinement, and precipitation hardening and the increment is significant above 1% Cu in as-cast condition. Six different compositions were selected for recrystallization study. All the samples were cold rolled to 70% reduction and annealed at three different temperatures, 600, 650, and 700°C for various times. Recrystallization responses were strongly dependent on initial microstructure and Cu content and the effect is dramatic between 1 and 2% Cu. Recrystallization time and temperature were found to be increased with increase in copper content.

Solidification behaviour and microstructural development of ironbased alloys under conditions pertinent to strip casting - 200 series stainless steels

The castability and microstructures produced from strip casting simulations of three compositions in the 200 series stainless steels have been examined. The nucleation density was similar for all three compositions.The as-cast microstructure showed very fine austenite grains of 10–20 μm in width. Retained delta ferrite was observed in the inter-dendritic regions, and was likely to be stabilised by the segregation of Cr into these regions. An analysis of the crystallography expected of different solidification sequences is presented, but a strict adherence to the Kurdjumov-Sachs orientation relationship was not found in these samples.

In hot pursuit : fluctuating mating system and sexual selection in sand lizards

A changing climate is expected to have profound effects on many aspects of ectotherm biology. We report on a decade-long study of free-ranging sand lizards (Lacerta agilis), exposed to an increasing mean mating season temperature and with known operational sex ratios. We assessed year-to-year variation in sexual selection on body size and postcopulatory sperm competition and cryptic female choice. Higher temperature was not linked to strength of sexual selection on body mass, but operational sex ratio (more males) did increase the strength of sexual selection on body size. Elevated temperature increased mating rate and number of sires per clutch with positive effects on offspring fitness. In years when the “quality” of a female's partners was more variable (in standard errors of a male sexual ornament), clutches showed less multiple paternity. This agrees with prior laboratory trials in which females exercised stronger cryptic female choice when male quality varied more. An increased number of sires contributing to within-clutch paternity decreased the risk of having malformed offspring. Ultimately, such variation may contribute to highly dynamic and shifting selection mosaics in the wild, with potential implications for the evolutionary ecology of mating systems and population responses to rapidly changing environmental conditions.

Deformation behaviour of a commercial pure titanium alloy during hot compression testing

The flow curve behaviour and microstructure evolution of commercially pure titanium (CP-Ti) through uniaxial hot compression was investigated at 850 °C and a strain rate of 0.1/s. Electron back scattered diffraction (EBSD) was employed to characterize the microstructure and crystallographic texture development for different thermomechanical conditions. The stress-strain curves of CP-Ti alloy under hot compression displayed a typical flow behaviour of metals undergoing dynamic recrystallization (DRX), which resulted in grain refinement. The critical strain for the onset of DRX was 0.13 using the double differentiation analysis technique. It was also revealed that the texture was markably altered during hot deformation. © (2014) Trans Tech Publications, Switzerland.

Novel ultrathin nanoflake assembled porous MnO2/carbon strip microspheres for superior pseudocapacitors

A novel hierarchical MnO2/carbon strip (MnO2/C) microsphere is synthesized via galvanostatic charge-discharge of a MnO@C matrix precursor where the carbon is from a low-cost citric acid. This hierarchical structure is composed of manganese oxides nanoflakes and inlaid carbon strips. The ultrathin nanoflakes assemble to form porous microspheres with a rippled surface superstructure. Due to its improved conductivity and remarkable increased phase contact area, this novel structure exhibits an excellent electrochemical performance with a specific capacitance of 485.6 F g -1 at a current density of 0.5 A g-1 and an area capacitance as high as 4.23 F cm-2 at a mass loading of 8.7 mg cm-2. It also shows an excellent cycling stability with 88.9% capacity retention after 1000 cycles. It is speculated that the present low-cost novel hierarchical porous microspheres can serve as a promising electrode material for pseudocapacitors. © 2014 American Chemical Society.

The development of ultrafine-grained hot rolling products using advanced thermomechanical processing

The aim of the work is development of industry guidance concerning production of ultrafine-grained (UFG) High Strength Low Alloy (HSLA) steels using strain-induced dynamic phase transformations during advanced thermomechanical processing. In the first part of the work, the effect of processing parameters on the grain refinement was studied. Based on the obtained results, a multiscale computer model was developed in the second part of the work that was subsequently used to predict the mechanical response of studied structures. As an overall outcome, a process window was established for the production of UFG steels that can be adopted in existing hot rolling mills. © 2014 Elsevier B.V.

Artificial neural network modeling of flow stress in hot rolling

In this study, an artificial neural network model is proposed to predict the flow stress variations during the hot rolling process. Optimization of the proposed neural network with respect to number of neurons within the hidden layer, different training methods and transfer functions of the neural network is performed. The results of the optimal network were compared with those of the conventional analytic method and it is shown that using an optimal neural network the mean calculated error is drastically reduced.