University of Córdoba (Spain)

About: University of Córdoba (Spain) is a education organization based out in Cordova, Spain. It is known for research contribution in the topics: Population & Catalysis. The organization has 12006 authors who have published 22998 publications receiving 537842 citations. The organization is also known as: University of Córdoba (Spain) & Universidad de Córdoba.

Micromechanics modeling of the electrical conductivity of carbon nanotube cement-matrix composites

Abstract: The incorporation of Carbon Nanotubes (CNTs) as nanoinclusions for the development of electrically conductive cement-based composites opens a vast range of possibilities for monitoring of concrete structures. A key issue for the design and optimization of these composites is the development of theoretical models capable of providing a quantitative prediction of their overall electrical conductivity. Experimental results have evidenced the strong influence of the waviness and dispersion of the nanotubes on the overall conductivity of these materials, what makes the consideration of these two phenomena essential for the development of realistic theoretical models. Nevertheless, both waviness and agglomeration have been often neglected in the literature or, when considered, have been reproduced with very simple modeling approaches not suitable to catch the complexity of the problem at hand. This paper presents an improved micromechanics model of the effective electrical conductivity of CNT cement-based nanocomposites based on enhanced approaches for reproducing waviness and non-uniform spatial distributions of the nanoinclusions. The two mechanisms that govern the electrical conductivity of these composites, electron hopping and conductive networks, are incorporated in the mixed micromechanics model. On the basis of scanning electron microscopy inspections, a helical waviness model and a two-parameter agglomeration approach are proposed. In order to assess the accuracy of the proposed analytical model, cement-based specimens have been manufactured and tested for providing data to use as the basis of comparison. In particular, specimens of cement pastes, mortars and concretes with different concentrations of Multi-Walled Carbon Nanotubes (MWCNTs) have been prepared. It is shown that the consideration of straight uniformly distributed nanotubes, as typically done in the literature, leads to an overestimation of the overall conductivity. On the contrary, it is highlighted that the wavy state of the fibers as well as their agglomeration in bundles play a crucial role in the conductivity of cement-based nanocomposites, which is demonstrated by achieving a good fit to the experimental data when using the proposed models for waviness and agglomeration. Overall, the paper highlights the physical mechanisms governing the overall electrical conductivity of cement-based composites with MWCNTs and provides a powerful analytical tool for their design.

Frequent itemset mining: A 25 years review

Abstract: Frequent itemset mining (FIM) is an essential task within data analysis since it is responsible for extracting frequently occurring events, patterns, or items in data. Insights from such pattern analysis offer important benefits in decision‐making processes. However, algorithmic solutions for mining such kind of patterns are not straightforward since the computational complexity exponentially increases with the number of items in data. This issue, together with the significant memory consumption that is present in the mining process, makes it necessary to propose extremely efficient solutions. Since the FIM problem was first described in the early 1990s, multiple solutions have been proposed by considering centralized systems as well as parallel (shared or nonshared memory) architectures. Solutions can also be divided into exhaustive search and nonexhaustive search models. Many of such approaches are extensions of other solutions and it is therefore necessary to analyze how this task has been considered during the last decades.