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Published on: March 9, 2017
Mechanochemical and machine-intelligent design of programmable materials: From molecular interactions to macroscale
Mitra Najafloo1,2, Leila Naji1, Christoph Eberl2
1Department of Chemistry, AmirKabir University of Technology (Polytechnic), Tehran, Iran.
Materials Today. Bio
|May 25, 2026
Summary
This review explores programmable materials that combine chemical and mechanical responses. Integrating these properties enables intelligent, adaptive systems with controllable behavior across scales.
Area of Science:
- Materials Science
- Polymer Science
- Chemical Engineering
- Artificial Intelligence
Background:
- Programmable materials dynamically alter properties in response to stimuli.
- Previous research often separated chemical and mechanical responsiveness.
- Integrating these domains offers new possibilities for adaptive systems.
Purpose of the Study:
- To review the integration of chemical reactivity and mechanical deformation in programmable materials.
- To explore the use of mechanochemical design for intelligent, adaptive systems.
- To highlight the role of AI in accelerating the discovery and optimization of these materials.
Main Methods:
- Harnessing force-activated molecular units (mechanophores).
- Utilizing stress-guided chemical patterning.
- Investigating materials with load-dependent structure-function relationships.
- Applying machine intelligence for inverse design and property prediction.
Main Results:
- Demonstrates the creation of materials with controllable behavior across multiple scales.
- Highlights chemomechanical feedback loops enhanced by computational tools.
- Showcases applications in soft robotics, shape-memory systems, and self-healing materials.
Conclusions:
- The integration of chemomechanical principles and AI enables the design of responsive, predictive, and self-evolving materials.
- Future directions include developing biologically inspired, resilient material systems.
- Challenges remain in scalability, reversibility, and durability.
