Mesoporous Silica-Based Materials for Electronics-Oriented Applications

International audienceElectronics, and nanoelectronics in particular, represent one of the most promising branches of technology. The search for novel and more efficient materials seems to be natural here. Thus far, silicon-based devices have been monopolizing this domain. Indeed, it is justified since it allows for significant miniaturization of electronic elements by their densification in integrated circuits. Nevertheless, silicon has some restrictions. Since this material is applied in the bulk form, the miniaturization limit seems to be already reached. Moreover, smaller silicon-based elements (mainly processors) need much more energy and generate significantly more heat than their larger counterparts. In our opinion, the future belongs to nanostructured materials where a proper structure is obtained by means of bottom-up nanotechnology. A great example of a material utilizing nanostructuring is mesoporous silica, which, due to its outstanding properties, can find numerous applications in electronic devices. This focused review is devoted to the application of porous silica-based materials in electronics. We guide the reader through the development and most crucial findings of porous silica from its first synthesis in 1992 to the present. The article describes constant struggle of researchers to find better solutions to supercapacitors, lower the k value or redox-active hybrids while maintaining robust mechanical properties. Finally, the last section refers to ultra-modern applications of silica such as molecular artificial neural networks or super-dense magnetic memory storage

Evolutionary Algorithms in Engineering Design Optimization

Evolutionary algorithms (EAs) are population-based global optimizers, which, due to their characteristics, have allowed us to solve, in a straightforward way, many real world optimization problems in the last three decades, particularly in engineering fields. Their main advantages are the following: they do not require any requisite to the objective/fitness evaluation function (continuity, derivability, convexity, etc.); they are not limited by the appearance of discrete and/or mixed variables or by the requirement of uncertainty quantification in the search. Moreover, they can deal with more than one objective function simultaneously through the use of evolutionary multi-objective optimization algorithms. This set of advantages, and the continuously increased computing capability of modern computers, has enhanced their application in research and industry. From the application point of view, in this Special Issue, all engineering fields are welcomed, such as aerospace and aeronautical, biomedical, civil, chemical and materials science, electronic and telecommunications, energy and electrical, manufacturing, logistics and transportation, mechanical, naval architecture, reliability, robotics, structural, etc. Within the EA field, the integration of innovative and improvement aspects in the algorithms for solving real world engineering design problems, in the abovementioned application fields, are welcomed and encouraged, such as the following: parallel EAs, surrogate modelling, hybridization with other optimization techniques, multi-objective and many-objective optimization, etc