Spatial structural sensing by carbon nanotube-based skins

Kenneth J. Loh, Tsung Chin Hou, Jerome P. Lynch, Nicholas A. Kotov

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)


The integrity and safety of metallic structures can be jeopardized by structural damage (e.g., yielding, cracking, impact, corrosion) that can occur during operation or service. While a variety of sensors have been proposed and validated for structural health monitoring, most sensors only provide data regarding a discrete point on the structure, thereby requiring densely-distributed sensors; however, such an approach may be infeasible for many structures due to geometrical and economic constraints. In this study, a nanoengineered carbon nanotube-polyelectrolyte sensing skin is proposed for monitoring strain, impact, and corrosion of metallic structures. Experimental validation studies have verified that these conformable films exhibit highly sensitive electromechanical and electrochemical responses to applied strain and corrosion processes, respectively. Here, the proposed nanocomposite is coupled with an electrical impedance tomographic (EIT) conductivity imaging technique. Unlike traditional point-based sensing transducers, EIT reconstructs two-dimensional skin conductivity distributions for damage identification of large structural components. Since EIT relies solely on boundary electrical measurements, one does not need to physically probe each structural location for data acquisition. Instead, any structural damage that affects the nanocomposite coating will produce localized changes in film conductivity detectable via EIT and boundary electrical measurements.

Original languageEnglish
Article number693207
JournalProceedings of SPIE - The International Society for Optical Engineering
Publication statusPublished - 2008
EventSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2008 - San Diego, CA, United States
Duration: 2008 Mar 102008 Mar 13

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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