Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Cell-matrix's Response to Mechanical Forces

Cell-matrix's Response to Mechanical Forces

In animal cells, the extracellular matrix allows cells within tissues to withstand external stresses and transmits signals from the outside of the cell to the inside. The extracellular matrix is extensive, and its composition varies between different types of tissues. For example, the reticular fibers and ground substance make up the ECM in loose connective tissue, while collagen and bone minerals make up the ECM of bone tissue.
Anchoring junctions mechanically attach a cell to the...

Mechanisms of Membrane-bending

Mechanisms of Membrane-bending

The living membranes are flexible due to their fluid mosaic nature; however, their bending into different shapes is an active process regulated by specific lipids and proteins. The membrane bending can be transient as seen in vesicles or stable for a long time as in microvilli. Cells regulate the size, location, and duration of the membrane curvature.
Membrane bending can happen due to intrinsic changes in lipid composition or extrinsic association with different proteins. The proteins involved...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

A Worm-Inspired Origami Robot with Multimodal Locomotion for Adaptive Mobility in Complex Pipeline Environments.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026

Same author

A comprehensive IMU dataset for evaluating sensor layouts in human activity and intensity recognition.

Scientific data·2026

Same author

CPG-based neural control of peristaltic planar locomotion in an earthworm-like robot: evaluation of nonlinear oscillators.

Bioinspiration & biomimetics·2025

Same author

Evaluating dynamic models for rigid-foldable origami: unveiling intricate bistable dynamics of stacked-Miura-origami structures as a case study.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2024

Same author

Origami-Enhanced Mechanical Properties for Worm-Like Robot.

Soft robotics·2024

Same author

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

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2023

Search research articles

Related Experiment Video

Updated: Jul 12, 2025

Origami Inspired Self-assembly of Patterned and Reconfigurable Particles

Origami Inspired Self-assembly of Patterned and Reconfigurable Particles

Published on: February 4, 2013

Cellular Automata Inspired Multistable Origami Metamaterials for Mechanical Learning.

Zuolin Liu^1,2, Hongbin Fang¹, Jian Xu¹

¹Institute of AI and Robotics, State Key Laboratory of Medical Neurobiology, MOE Engineering Research Center of AI & Robotics, Fudan University, Shanghai, 200433, China.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)

|October 23, 2023

Summary

Intelligent materials can now perform complex computations using multistable origami metamaterials and reservoir computing. This novel framework eliminates the need for traditional logic gates, enabling advanced material-based computation for tasks like handwriting recognition.

Keywords:

image recognition mechanical intelligence mechanical memory mechanical metamaterials physical computing

More Related Videos

Folding and Characterization of a Bio-responsive Robot from DNA Origami

Folding and Characterization of a Bio-responsive Robot from DNA Origami

Published on: December 3, 2015

Directed Cellular Self-Assembly to Fabricate Cell-Derived Tissue Rings for Biomechanical Analysis and Tissue Engineering

Directed Cellular Self-Assembly to Fabricate Cell-Derived Tissue Rings for Biomechanical Analysis and Tissue Engineering

Published on: November 25, 2011

Related Experiment Videos

Last Updated: Jul 12, 2025

Origami Inspired Self-assembly of Patterned and Reconfigurable Particles

Origami Inspired Self-assembly of Patterned and Reconfigurable Particles

Published on: February 4, 2013

Folding and Characterization of a Bio-responsive Robot from DNA Origami

Folding and Characterization of a Bio-responsive Robot from DNA Origami

Published on: December 3, 2015

Directed Cellular Self-Assembly to Fabricate Cell-Derived Tissue Rings for Biomechanical Analysis and Tissue Engineering

Directed Cellular Self-Assembly to Fabricate Cell-Derived Tissue Rings for Biomechanical Analysis and Tissue Engineering

Published on: November 25, 2011

Area of Science:

Materials Science
Computational Science
Mechanical Engineering

Background:

Multistable metamaterials exhibit a connection between structural changes and Boolean logic operations.
Current computational frameworks for intelligent materials require complex networks of logic gates, posing fabrication and signal propagation challenges.
Cellular automata principles offer inspiration for novel computational approaches in materials.

Purpose of the Study:

To propose a new computational framework for multistable origami metamaterials using reservoir computing.
To overcome the limitations of traditional logic gate networks in material-based computation.
To demonstrate the feasibility of high-level computation using a single-actuator system.

Main Methods:

Developed a computational framework integrating reservoir computing with multistable origami metamaterials.
Utilized a multistable stacked Miura-origami metamaterial as a platform for experimental validation.
Implemented digit recognition, handwriting recognition, and 5-bit memory tasks.

Main Results:

Successfully demonstrated high-level computation without requiring a logic gate network.
Digit recognition was achieved using a single actuator on the origami metamaterial.
Feasibility of complex tasks like handwriting recognition and memory functions was experimentally validated.

Conclusions:

The proposed framework enables advanced computational capabilities in intelligent materials.
This approach significantly reduces fabrication complexity and signal propagation issues associated with large-scale material networks.
Represents a significant advancement towards material mechano-intelligence and transformative applications in computation.