Embodying Multifunctional Mechano-Intelligence in and Through Phononic Metastructures Harnessing Physical Reservoir...

Area of Science:

• Materials Science
• Mechanical Engineering
• Computer Science

Background:

• Autonomous systems require adaptive structures with built-in mechanical intelligence (MI).
• Prior MI approaches lacked systematic methods for integrating intelligent functions.
• Conventional systems rely on external computers, increasing power and complexity.

Purpose of the Study:

• To develop a systematic approach for creating multifunctional mechano-intelligence (MI) in adaptive structures.
• To integrate computing power and intelligent functions directly within the mechanical domain.
• To advance adaptive structures beyond conventional reliance on add-on electronics.

Main Methods:

• Utilized physical reservoir computing (PRC) to embody computing and intelligence in mechanical systems.
• Developed a mechanically intelligent phononic metastructure as an exemplar platform.
• Harnessed the nonlinear dynamics of the metastructure for PRC capabilities.

Main Results:

• Demonstrated multifunctional MI, including self-tuning wave controls and wave-based logic gates.
• Successfully integrated perception, decision-making, and commanding within the mechanical structure.
• Validated the PRC approach through analyses and experimental results.

Conclusions:

• This research establishes a foundation for next-generation smart structures and materials.
• The PRC approach offers lower power consumption, direct interaction, and enhanced survivability.
• Enables new functionalities and autonomy in systems without overloading onboard computers.