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Pengrong Lyu1,2, Samuël A M Weima1,2, Jaeryang Baek3

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Researchers developed a trainable liquid crystal oligomer network (LCON) that stores digital information in its molecular structure. This material exhibits learning behavior, enabling binary classification and actuation based on stored photonic stimuli.

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Area of Science:

  • Materials Science
  • Soft Robotics
  • Molecular Engineering

Background:

  • Soft materials offer potential as sensors and actuators, but incorporating learning capabilities remains a challenge.
  • Artificial intelligence inspires methods for training physical responsiveness in materials through data.
  • Digital information storage and processing in soft matter are key research areas.

Purpose of the Study:

  • To develop a soft material capable of storing digital information and exhibiting learning behavior.
  • To engineer a material that integrates logic and memory for data processing and actuation.
  • To demonstrate a novel approach for training soft materials using photonic stimuli.

Main Methods:

  • Development of a trainable liquid crystal oligomer network (LCON) storing information in its molecular configuration.
  • Functionalization of the LCON with photo-switchable azobenzene to create a binary-state system (trainable self-propelled gate, T-SPG).
  • Training the T-SPG using photonic stimuli controlled by a digital controller.

Main Results:

  • The T-SPG successfully stored digital information within its molecular structure.
  • The material demonstrated trainability through photonic stimuli, enabling memory tuning.
  • Hierarchical tasks, including binary classification and motion triggering, were successfully performed using the stored memory.

Conclusions:

  • A novel trainable soft material (T-SPG) integrating logic and memory has been successfully developed.
  • The T-SPG can be trained using external stimuli, showcasing a pathway for learning in soft matter.
  • This work opens possibilities for advanced soft sensors, actuators, and bio-inspired computing systems.