Multi-stimuli and AI-guided electrically-responsive self-healing nanocomposites for low-temperature structural applications

Self‑healing nanocomposites capable of operating under sub‑ambient aerospace conditions remain limited by slow reaction kinetics, single‑stimulus activation, and insufficient predictive control. In this work, we develop a multi‑stimuli and AI‑guided electrically‑responsive self‑healing nanocomposite based on urea‑formaldehyde nanocapsules (295 ± 58 nm; shell thickness 22 ± 4 nm) embedded in an aerospace‑grade epoxy matrix. The capsules incorporate conductive, magnetic, and photoactive domains, enabling activation by electric fields, magnetic fields, and optical stimuli. Mechanical testing (n = 5, ANOVA p < 0.05) shows that the system achieves rapid crack closure and healing efficiencies of 74% at - 10 °C and up to 92% at 0 °C under combined multi‑stimuli activation, significantly outperforming conventional thermally‑activated systems. Crack‑closure kinetics follow a first‑order model, with healing rate constants increasing from k ≈ 0 for pristine epoxy to k = 0.019-0.027 min⁻¹ for electrically and multi‑stimuli activated composites. High‑resolution SEM confirms capsule rupture and polymer bridging within the crack plane, while DSC verifies in‑situ polymerization of the released healing agent. Finite element simulations validate compatibility with aerospace electrical systems and confirm uniform field distribution around crack tips. A supervised machine‑learning framework (3,420 microscopy images; 1,150 FEA maps; F1 = 0.91) predicts crack initiation sites and optimizes activation parameters, reducing energy consumption to 0.27-0.42 J per healing event. A new Healing Availability Index 2.0, incorporating cyclic durability, multi‑cycle repairability, and energy demand, demonstrates a substantial improvement from 0.61 (pristine epoxy) to 0.93 (multi‑stimuli composite). These results establish a robust pathway toward intelligent, low‑temperature, and energy‑efficient self‑healing materials for next‑generation aerospace structures.

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Publication Details

Journal
Scientific Reports
Published
2026-04-25
DOI
https://doi.org/10.1038/s41598-026-50437-x
Primary Topic
Polymer composites and self-healing
Type
article
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article

Multi-stimuli and AI-guided electrically-responsive self-healing nanocomposites for low-temperature structural applications

Asgar Hosseinnezhad, Hadi Sabri
Scientific Reports
Polymer composites and self-healing
article

Multi-stimuli and AI-guided electrically-responsive self-healing nanocomposites for low-temperature structural applications

Asgar Hosseinnezhad, Hadi Sabri
article en

Abstract

Self‑healing nanocomposites capable of operating under sub‑ambient aerospace conditions remain limited by slow reaction kinetics, single‑stimulus activation, and insufficient predictive control. In this work, we develop a multi‑stimuli and AI‑guided electrically‑responsive self‑healing nanocomposite based on urea‑formaldehyde nanocapsules (295 ± 58 nm; shell thickness 22 ± 4 nm) embedded in an aerospace‑grade epoxy matrix. The capsules incorporate conductive, magnetic, and photoactive domains, enabling activation by electric fields, magnetic fields, and optical stimuli. Mechanical testing (n = 5, ANOVA p < 0.05) shows that the system achieves rapid crack closure and healing efficiencies of 74% at - 10 °C and up to 92% at 0 °C under combined multi‑stimuli activation, significantly outperforming conventional thermally‑activated systems. Crack‑closure kinetics follow a first‑order model, with healing rate constants increasing from k ≈ 0 for pristine epoxy to k = 0.019-0.027 min⁻¹ for electrically and multi‑stimuli activated composites. High‑resolution SEM confirms capsule rupture and polymer bridging within the crack plane, while DSC verifies in‑situ polymerization of the released healing agent. Finite element simulations validate compatibility with aerospace electrical systems and confirm uniform field distribution around crack tips. A supervised machine‑learning framework (3,420 microscopy images; 1,150 FEA maps; F1 = 0.91) predicts crack initiation sites and optimizes activation parameters, reducing energy consumption to 0.27-0.42 J per healing event. A new Healing Availability Index 2.0, incorporating cyclic durability, multi‑cycle repairability, and energy demand, demonstrates a substantial improvement from 0.61 (pristine epoxy) to 0.93 (multi‑stimuli composite). These results establish a robust pathway toward intelligent, low‑temperature, and energy‑efficient self‑healing materials for next‑generation aerospace structures.

Scientific Reports
University of Tabriz (IR)
Openalex Percentile: Top 9%
Polymer composites and self-healing
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