Project Details
Description
This project seeks to validate an artificial intelligence (AI)-assisted design strategy for the development of carbon nanotube (CNT)-reinforced polyimide (PI) nanocomposites with electromagnetic shielding (SE) levels comparable to commercial solutions, but with lower weight, greater flexibility, and less environmental impact.
The shielding effectiveness of these materials does not depend exclusively on the intrinsic properties of their components, but also on the three-dimensional distribution of the CNTs, which is difficult to predict and control using conventional methods. To overcome this limitation, three key components are integrated: (i) controlled manufacturing using electrical stimulation to modify the distribution of CNTs during curing; (ii) advanced characterization using Second Harmonic Electrostatic Force Microscopy (EFM-2ω), which allows the observation of conductive networks with subsurface sensitivity; and (iii) modeling with interpretable AI, using techniques such as Nonlinear Oblique Subspace Projections (NObSP), capable of extracting and correlating morphological descriptors with manufacturing parameters and functional levels of SE.
The shielding effectiveness of these materials does not depend exclusively on the intrinsic properties of their components, but also on the three-dimensional distribution of the CNTs, which is difficult to predict and control using conventional methods. To overcome this limitation, three key components are integrated: (i) controlled manufacturing using electrical stimulation to modify the distribution of CNTs during curing; (ii) advanced characterization using Second Harmonic Electrostatic Force Microscopy (EFM-2ω), which allows the observation of conductive networks with subsurface sensitivity; and (iii) modeling with interpretable AI, using techniques such as Nonlinear Oblique Subspace Projections (NObSP), capable of extracting and correlating morphological descriptors with manufacturing parameters and functional levels of SE.
Keywords
Electromagnetic Shielding, Materials Engineering, Materials Informatics, Polymer Nanocomposites, Atomic Force Microscopy, Artificial Intelligence, Image Processing
| Status | Active |
|---|---|
| Effective start/end date | 9/30/25 → 9/30/27 |
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
Main Funding Source
- URosario-UAndes-Javeriana
Location
- Bogotá D.C.
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