Robotic spray coating of self-sensing metakaolin geopolymer for concrete monitoring

Jack McAlorum, Marcus Perry, Christos Vlachakis, Lorena Biondi, Brenden Lavoie

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)
9 Downloads (Pure)


Sensors and new materials can support optimised concrete maintenance, and produce the data needed to justify new, low carbon structural designs. While these technologies are affordable, the process of manual installation in a construction context comes with acute and unfamiliar risks to productivity, personnel safety, and confidence in the quality of workmanship. The installation of smart materials using robotics could address some of these issues, but there are few proofs-of-concept at the time of writing. Here, we present a robotically controlled process for spray coating geopolymers — a class of self-sensing concrete repair materials. By tuning mix design, robotic toolpaths and spray dispenser parameters, we show reliable and automated spray coating of 250 mm2 patches in a laboratory setting. The cured geopolymer has a compressive strength of 20 MPa, and a bond strength to the concrete substrate of 0.5 MPa. Electrical interrogation of patches, via a set of four electrodes, produces strain and temperature measurements of the underlying concrete substrate with resolutions of 1 με and 0.2 ◦C, respectively. This demonstration multifunctional material deposition using robotics is a step towards remote, traceable, and low-risk technology deployment across civil engineering sectors. This could support more widespread adoption of novel concrete health monitoring and repair systems in future.
Original languageEnglish
Article number103415
Number of pages7
JournalAutomation in Construction
Early online date9 Oct 2020
Publication statusPublished - 31 Jan 2021


  • robotic sensing
  • multifunctional materials
  • skin sensors
  • alkali-activated materials
  • metakaolin
  • structural health monitoring


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