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Contacts: Alessandro Cultrera, a.cultrera@inrim.it
Web-site: http://www.inrim.it/
Abstract
Abstract
Electrical Resistance Tomography was successfully applied for the first time for mapping the conductivity of metallic Nanowire Networks [1], which are emerging as efficient transparent conducting materials in several applications (touch screens, solar cells, and organic LED). For the task, the Electrical Resistance Tomography recently developed at INRIM [2], has been adapted to allow for non-invasive measurements of Nanowire Networks which are particularly sensitive to the applied voltage [3].
About
About
Graphical summary of the Electrical Resistance Tomography on Nanowire Networks.
Adapted from [1] and [3] (CC BY 4.0).
Metallic nanowire networks (NWN) combining high electrical conductivity, high transparency, high flexibility, and stretchability are considered emerging candidates as transparent conductive materials.
Within the framework of the EMPIR project 20FUN06 MemQuD, lead by INRIM, Electrical Resistance Tomography (ERT) is being exploited for the conductivity mapping of large area (cm2) NWN.
ERT is a non-invasive technique based on multiterminal resistance measurements which allows to recover the conductivity distribution of an object by only performing boundary measurements.
Usually ERT, which has been developed for clinical applications, is applied to 3D objects to get insight of their interior conductivity distribution (which is tipically related to their morphology – e.g. hart and lungs tissues have very different conductivity).
Moreover, ERT can also be implemented for «flat» objects, in order to map their conductivity (usually related to their uniformity). INRIM implemented ERT for the mapping of thin conductive films [4], graphene [2] and recently also for NWN [1].
References
References
[1] G Milano et al., ACS Applied Nano Materials 3 (12), 11987-11997, 2020.
[2] A Cultrera et al., Scientific reports 9 (1), 1-9, 2019.
[3] A Cultrera et al., Scientific reports 11 (1), 1-8, 2021.
[4] A Cultrera and L Callegaro, IEEE trans. Instrum. Meas. 65 (9), 2101-2107, 2016.
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