AI-enabled “smart cement” with CNTs: 3D printing, self-healing, and integrated damage sensing

A team led by Vikrant S. Vairagade (Priyadarshini College of Engineering, Nagpur) presents a cement-based composite that combines mechanical strength, electrical conductivity, self-healing, and condition monitoring in a single system. The aim is to address typical weaknesses of conventional building materials—cracking, lack of intrinsic monitoring, and complex external sensor networks—and thereby facilitate use in resilient, digitally monitored infrastructure.

Technically, the study uses chemically functionalized carbon nanotubes (CNTs) modified with a 70:30 volume ratio of nitric and sulfuric acid. According to the authors, functionalization improves dispersion and interfacial adhesion in the cement matrix, increasing compressive strength by around 30% to 65 MPa and boosting electrical conductivity by a factor of ten. For self-healing, silica microcapsules with an epoxy-containing polymer (5% relative to cement mass) are incorporated. This closes cracks up to 0.5 mm with over 85% efficiency; cracks of 0.3 mm healed within 36 hours in testing. Electrical sensitivity is leveraged via the percolating CNT structure: antenna structures formed by the conductive matrix detect cracks from 0.05 mm at radio ranges up to 50 m, with a detection rate of 95%.

For 3D printing, the work highlights targeted pore control and the integration of embedded sensing. In additively manufactured geometries, structural integrity increased by roughly 20%, while the material response remained at 85% of the initial strength after 300 freeze–thaw cycles. The specific resistivity is reported at about 100 Ω·m, enabling the combination of data acquisition and load bearing. In addition, the researchers trained SVM, ANN, and gradient-boosting models, which achieved 95–98% accuracy in crack-progression prediction and reduced maintenance effort by about 30% in scenario analyses.

Compared with alternative CNT incorporation methods (plasma treatment, superplasticizers), the study reports advantages in compressive strength, healing rate, and electrical sensitivity. For practical use, this yields a construction material that can be produced in geometrically complex forms via 3D printing, while simultaneously delivering measurement data for structural health monitoring and supporting proactive maintenance strategies through AI models.