Flexible, self-healing and portable supramolecular visualization smart sensors for monitoring and quantifying structural damage
Visually monitoring micro-crack initiation and corrosion failure evolution is crucial for early diagnosis of structural health and ensuring safe operation of infrastructures. However, existing damage detecting approaches are subject to the limited-detection of heterogeneous structures, intolerance of harsh environments, and challenge of quantitative analysis, impeding applications in structural health monitoring (SHM). Herein, we present a stretchable, semi-quantitative, instrument-free, supramolecular SHM sensor by integrating a polyurea elastomer with sensitive corrosion-probes, enabling localized corrosion monitoring and quantification of failure dynamics. Initially, a correlation between visual monitoring signals and structural health status is proposed, and sensor-based image processing software that accurately quantifies structural failure indicators (crack scale, corrosion reactivity and deterioration status) is proposed. Moreover, this sensor can be fabricated as multiple derivatives: a coating or patch covered on metallic substrates and an ionic-responsive test strip, ensuring real-time detection of the initiation of pitting, degradation events of metallic components and convenient monitoring of ion concentrations in corrosive media. Furthermore, the inherent geometric plasticity and dynamic hydrogen-bonded network validates the reliability for heterogeneous components and stability under extreme environments of sensors. This portable, smart SHM strategy established the channel-transformation model from corrosion dynamics to visual signals, exhibiting prospects for structural monitoring in offshore energy-harvesting equipment.
Authors
- Cheng‐Bao Liu (ORCID: https://orcid.org/0000-0002-7784-9833)
- Shuo‐Qi Li (ORCID: https://orcid.org/0000-0001-7138-3713)
- Cheng‐Hui Li (ORCID: https://orcid.org/0000-0001-8982-5938)
- Dezhi Jiao (ORCID: https://orcid.org/0009-0006-2687-6176)
- Sihan Gu
Institutions
- Qingdao University of Science and Technology (CN)
- Shandong University of Science and Technology (CN)
Publication Details
- Journal
- Materials Horizons
- Published
- 2024-10-11
- DOI
- https://doi.org/10.1039/d4mh01233j
- Citations
- 9
- Primary Topic
- Analytical Chemistry and Sensors
- Type
- article
- Field-Weighted Citation Impact
- 2.60
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Shandong Province
- Natural Science Foundation of Qingdao