Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 27 tok/s
Gemini 2.5 Pro 46 tok/s Pro
GPT-5 Medium 23 tok/s Pro
GPT-5 High 29 tok/s Pro
GPT-4o 70 tok/s Pro
Kimi K2 117 tok/s Pro
GPT OSS 120B 459 tok/s Pro
Claude Sonnet 4 34 tok/s Pro
2000 character limit reached

Boundary curvature guided shape-programming kirigami sheets (2103.11076v1)

Published 20 Mar 2021 in physics.app-ph

Abstract: Kirigami, an ancient paper cutting art, offers a promising strategy for 2D-to-3D shape morphing through cut-guided deformation. Existing kirigami designs for target 3D curved shapes rely on intricate cut patterns in thin sheets, making the inverse design challenging. Motivated by the Gauss-Bonnet theorem that correlates the geodesic curvature along the boundary with the topological Gaussian curvature, here, we exploit programming the curvature of cut boundaries rather than complex cut patterns in kirigami sheets for target 3D curved topologies through both forward and inverse designs. Such a new strategy largely simplifies the inverse design. We demonstrate the achievement of varieties of dynamic 3D shape shifting under both mechanical stretching and remote magnetic actuation, and its potential application as an untethered predator-like kirigami soft robot. This study opens a new avenue to encode boundary curvatures for shape-programing materials with potential applications in shape-morphing structures, soft robots, and multifunctional devices.

Citations (68)

Summary

We haven't generated a summary for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-Up Questions

We haven't generated follow-up questions for this paper yet.