The unique electric properties of carbon nanotubes (CNT)1, have opened new scientific and technological fields2 based on the investigation and optimization of CNT filled polymers3. CNTs, when added to polymer matrices (such as epoxy, bitumen, concrete) make them conductive once they overcome a specific (so-called percolative) concentration4. When this percolative threshold is reached, a CNT electric circuit is formed and the composite materials become conductors. Based on such peculiar behavior, smart materials able to monitor their own conditions could be realized and employed for several applications ranging from automotive and aeronautics to civil engineering infrastructures. The main goal of this work is to understand, through a theoretical-computational approach, the electric behavior of CNT based composites5 and help in improving their performances. In particular, the Joule effect, i.e. the heat dissipation of the conductive CNTs is simulated. The CNTs Joule effect can be employed to build smart materials able to have specific properties (i.e. self-deicing under certain temperatures) or to repair their own cracks (self-healing). The piezoresistivity, i.e. the change in the electric resistance of the CNTs due to an applied strain or stress, is also investigated. This feature allows these composites to be sensitive to an external stress or damage (self-sensing), in this way an immediate and efficient repair can be performed. A computational protocol to understand the behavior, the sensitivity and the limits of such materials at the nanoscale is proposed. This will improve the materials performances and efficiency on larger scales. For the first time, a computational modeling strategy along with preliminary results is built and presented to simulate at the nanoscale the Joule effect and the piezoresistivity of CNTs filled polymers. Obtaining a widely applicable strategy to model electric properties of CNTs and characteristic behavior trends of such materials is the final goal of this project. [1] Iijima, Nature, 1991, 354, 56-58. [2] W. Nan, Y. Shen, J. Ma, Annu.Rev.Mater.Res., 2010, 40, 131-151. [3] M. Ajayan, O. Stephan, C. Colliex, D. Trauth, Science, 1994, 265, 1212-1214. [4] M. Mutiso, K. I. Winey, Prog. Polym. Sci., 2015, 40, 63.84. [5] Zhao, M. Byshkin, Y. Cong, T. Kawakatsu, L. Guadagno, A. De Nicola, N. Yu, G. Milano, B. Dong, Nanoscale, 2016, 8, 15538-15552.
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