Microstructure and mechanical properties of ultrafine-grained fcc/hcp cobalt processed by a bottom-up approach

Bulk Co samples having a mean grain size of ～300 nm were processed by hot isostatic pressing of a high purity Co nanopowder synthesized by chimie douce. The grain interior exhibited a highly faulted nanoscale lamellar microstructure comprising an intricate mixture of face-centered cubic, hexagonal close-packed phases and nanotwins. Room temperature compression tests carried out at a strain rate of ～2 × 10^?4 s^?1 revealed a yield stress of ～1 GPa, a strain to rupture of ～5%. During straining it was found that the hexagonal close-packed phase content increased from 55% to 65% suggesting a deformation mechanism based on stress-assisted face-centered cubic to hexagonal close-packed phase transformation. In addition, an apparent activation volume of ～3b³ was computed which indicates that the deformation mechanism was controlled by dislocation nucleation from the numerous boundaries. Nonetheless, in such an intricate microstructure, the overall mechanical properties are discussed in term of a complex interplay between lattice dislocation plasticity, transformation-induced plasticity and possibly twin-induced plasticity.     

Fabrication,microstructure and mechanical properties of novel bulk binderless (Ti0.8Zr0.2)C carbides prepared by mechanical alloying and spark plasma sintering

Nanocrystalline (Ti_0.8Zr_0.2)C powder consisting in grains of about 200 nm in diameter obtained by mechanical alloying was sintered by a spark plasma sintering (SPS) process without the addition of any binder phase. The microstructure, Vickers micro hardness and density in relation to the sintering time and temperature are carefully described. The most suitable sintering condition under pressure of 50 MPa is 1650 °C for 5 min. In this sintering condition, the hardness can reach 2760 Hv and the relative density can reach 98%.     

Key Resources and Internationalization Modes of Creative Knowledge‐Intensive Business Services: The Case of Design Consultancies

In the ‘knowledge economy’, knowledge‐intensive business services (KIBS) are a key driver for innovation and competitiveness. The internationalization of these businesses raises challenges given their specificities such as knowledge intensity, the importance of customer interaction and intimacy in service delivery. This paper focuses on design consultancies as a specific type of creative KIBS for which these characteristics are emphasized. The objective of this research is to analyse the resources leveraged by the firms to compete internationally. It is based on 11 case studies of design consultancies located in five different countries (France, Italy, Portugal, Spain and the UK) that were selected for their capacity to perform at the international level for several years. The paper advances three internationalization modes depending on contingent variables and focusing on specific resources that enable international competitiveness: star‐based, process‐based and glocality‐based. In star‐based creative KIBS, the individual designer has developed a reputation that attracts customers internationally, operating as a brand. In process‐based creative KIBS, the reputation of a collective creative process attracts clients from other countries. In glocality‐based creative KIBS, the geographical proximity obtained by opening international offices helps to develop a close understanding of the client through frequent interactions, and also to know the client's market well and to better understand local codes and signs. These modes complement those presented in the existing internationalization literature which takes the peculiarities of creative KIBS into consideration.     

Gelatin and amylopectin-based phase-separated hydrogels: An in-depth analysis of the swelling,mechanical, electrical and drug release properties

The current study delineates the development of gelatin–amylopectin-based phase-separated hydrogels for drug delivery applications. Gelatin and amylopectin were used as the representative protein and polysaccharide phases, respectively. The hydrogels were prepared by adding different proportions of amylopectin to gelatin solutions and subsequently cross-linking the mixture using glutaraldehyde. Microscopic analysis showed formation of phase-separated hydrogels. Secondary structure of gelatin was conserved within the hydrogels. The presence of amylopectin drastically reduced the rate of water absorption by the hydrogels. Viscoelastic analysis using stress relaxation study suggested an increase in the viscous component of the hydrogels with the increase in the amylopectin content. After incorporating amylopectin within the gelatin hydrogel, even though the bulk resistance remained unaltered, there was a corresponding variation in the capacitive elements of the equivalent electrical models. The release of the drug from the hydrogels was diffusion mediated. Suitable mathematical models were used for the analysis of the swelling (Peleg’s model), viscoelastic (Weichert model), electrical (RQQ model) and drug release (Korsmeyer–Peppas and Peppas–Sahlin models) properties. The drug retained its antimicrobial activity within the hydrogels. An analysis of the results suggested that the developed hydrogels may be explored as matrices for controlled drug delivery applications.     

Global sensitivity analysis and multi-objective optimisation of loading path in tube hydroforming process based on metamodelling techniques

Tube hydroforming process is widely used in various industrial applications which consists of combining internal pressure and axial displacement to manufacture tubular parts. Inappropriate choice as small changes in such variables may affect the process stability and, in some cases, lead to failure. Consequently, loading path should be optimised to better control the process and to guarantee hydroformed parts with desired specifications. However, optimisation procedure requires several evaluations of the real models which induces a huge computational time. To cope with this limitation, we propose to compare two metamodelling techniques to solve the problem efficiently: the response surface method and the least squares support vector regression. To enhance the metamodels precision, optimal latin hypercube design is used to generate sampled points. It is obtained through iterative optimisation procedure based on a modified version of the simulated annealing algorithm by minimising simultaneously two optimality criterions. Then, multi-objective optimisation problem is formulated to search for the Pareto optimal solutions. Fuzzy classification is then applied to rank the non-dominated solutions which helps designers in the decision-making phase. Before optimising the process, a global sensitivity analysis is carried out using the variance-based method by coupling metamodels and Monte Carlo simulations in order to identify the relative importance of the design variables in terms of internal pressure and axial displacement on the variance of the responses of interest defined to control the process.     

Polyether-based polyrotaxane synthesis with controlled β-cyclodextrin threading ratio

An effective one-pot polyrotaxane synthesis with control of the threading ratio is realized. 2,5-Bis(chloromethyl)-4-methoxy-1-octoxybenzene (PMOC) is condensed with a starting rotaxane consisting of a bisphenol A salt threaded into β-cyclodextrin (βCD), to lead to a βCD-threaded polyether. We demonstrate that the threading ratio of βCD on the polyether chain (ratio between the polymer repeat units and the βCD in polyrotaxane) can be varied from zero to unity depending on two parameters: the reactant concentration and the bulkiness of the counter-ion stopper in the starting rotaxane.     

Energetic reasoning revisited: application to parallel machine scheduling

We consider the problem of minimizing makespan on identical parallel machines subject to release dates and delivery times. We present several new feasibility tests and adjustment techniques that consistently improve the classical energetic reasoning approach. Computational results carried out on a set of hard instances provide strong evidence that the performance of a state-of-the-art exact branch-and-bound algorithm is substantially improved through embedding the proposed enhanced energetic reasoning.     

Rolling Line Contact Problems in Elastohydrodynamic Lubrication: Modeling and Validation

A computer package has been developed and applied to solve line contact problems of elastohydrodynamic lubrication. The solutions computed by the package are maintained and are indexed by two dimensionless parameters, α and λ, within a database. Power law surfaces are fitted to the minimum film thickness and maximum pressure for each solution and are compared to interpolated surfaces of the same data, to film thickness measurements and to equations published previously in the literature.     

3D brain tumor segmentation in MRI images based on a modified PSO technique

Three-dimensional (3D) brain tumor segmentation is a clinical requirement for brain tumor diagnosis and radiotherapy planning. This is a challenging task due to variation in type, size, location, and shape of tumors. Several methods such as particle swarm optimization (PSO) algorithm formed a topological relationship for the slices that converts 2D images into 3D magnetic resonance imaging (MRI) images which does not provide accurate results and they depend on the number of input sections, positions, and the shape of the MRI images. In this article, we propose an efficient 3D brain tumor segmentation technique called modified particle swarm optimization. Also, segmentation results are compared with Darwinian particle swarm optimization (DPSO) and fractional-order Darwinian particle swarm optimization (FODPSO) approaches. The experimental results show that our method succeeded 3D segmentation with 97.6% of accuracy rate more efficient if compared with the DPSO and FODPSO methods with 78.1% and 70.21% for the case of T1-C modality.