arXiv subjects

Sehui Jeong

Publications and source records attributed to Sehui Jeong.

5 recordsLinked to original sources

arXiv2025

Entanglement-driven responses through multiscale 3D-printed knits

For their resilience and toughness, filamentous entanglements are ubiquitous in both natural and engineered systems across length scales, from polymer-chain- to collagen-networks and from cable-net structures to forest canopies. Textiles are an everyday manifestation of filamentous entanglement: the remarkable resilience and toughness in knitted fabrics arise predominately from the topology of interlooped yarns. Yet most architected materials do not exploit entanglement as a design primitive, and industrial knitting fixes a narrow set of patterns for manufacturability. Additive manufacturing has recently enabled interlocking structures such as chainmail, knot and woven assemblies, hinting at broader possibilities for entangled architectures. The general challenge is to treat knitting itself as a three-dimensional architected material with predictable and tunable mechanics across scales. Here, we show that knitted architectures fabricated additively can be recast as periodic entangled solids whose responses are both fabric-like and programmable. We reproduce the characteristic behavior of conventional planar knits and extend knitting into the third dimension by interlooping along three orthogonal directions, yielding volumetric knits whose stiffness and dissipation are tuned by prescribed pre-strain. We propose a simple scaling that unifies the responses across stitch geometries and constituent materials. Further, we realize the same topology from centimeter to micrometer scales, culminating in the fabrication of what is, to our knowledge, the smallest knitted structure ever made. By demonstrating 3D-printed knits can be interpreted both as a traditional fabric, as well as a novel architected material with defined periodicity, this work establishes the dual nature of entangled filaments and paves the way towards a new form of material architectures with high degrees of entanglement.

physics.app-ph↗

arXiv2025

Design and Fabrication of Origami-Inspired Knitted Fabrics for Soft Robotics

Soft robots employing compliant materials and deformable structures offer great potential for wearable devices that are comfortable and safe for human interaction. However, achieving both structural integrity and compliance for comfort remains a significant challenge. In this study, we present a novel fabrication and design method that combines the advantages of origami structures with the material programmability and wearability of knitted fabrics. We introduce a general design method that translates origami patterns into knit designs by programming both stitch and material patterns. The method creates folds in preferred directions while suppressing unintended buckling and bending by selectively incorporating heat fusible yarn to create rigid panels around compliant creases. We experimentally quantify folding moments and show that stitch patterning enhances folding directionality while the heat fusible yarn (1) keeps geometry consistent by reducing edge curl and (2) prevents out-of-plane deformations by stiffening panels. We demonstrate the framework through the successful reproduction of complex origami tessellations, including Miura-ori, Yoshimura, and Kresling patterns, and present a wearable knitted Kaleidocycle robot capable of locomotion. The combination of structural reconfigurability, material programmability, and potential for manufacturing scalability highlights knitted origami as a promising platform for next-generation wearable robotics.

cs.RO↗

arXiv2025

Multi-level mechanical modeling and computational design framework for weft knitted fabrics

This work presents a multi-level modeling and design framework for weft knitted fabrics, beginning with a volumetric finite element analysis capturing their mechanical behavior from fundamental principles. Incorporating yarn-level data, it accurately predicts stress-strain responses, reducing the need for extensive physical testing. A simplified strain energy approach homogenizes the results into three key variables, enabling rapid, accurate predictions in minutes. After validation against experiments, our framework can simulate new knit fabrics without additional tests. In real-world scenarios, fabrics often feature variations in yarn materials or patterns. The framework extends to heterogeneous fabrics, showing that transitions between distinct regions can be captured using simple mechanical analogies: springs in series and parallel. This allows heterogeneous textiles to be treated as idealized patchworks of homogeneous pieces, preserving predictive accuracy. The method is demonstrated by designing and producing a compression sleeve with uniform pressure, illustrating how the framework supports development of knits tailored to specific assistance levels and anatomical features. By combining volumetric finite element analysis, simplified model through homogenization, and controlled material transitions, this approach provides a scalable, high-fidelity path toward next-generation weft knitted fabric design.

cond-mat.soft↗

arXiv2024

Printing Mosaics of Magnetically Programmed Liquid Crystal Directors for Reversibly Morphing Soft Matter

Liquid crystal elastomer (LCE) has been intensively utilized in 4D printing techniques to fabricate smart structures with reversible actuation on the basis of appropriate alignment of liquid crystal (LC) molecules. As a non-contact alignment strategy with a controllability of orientation, magnetic-field alignment has been rarely adapted in 4D printing of LCE because of its poor printing efficiency and demand on large field strength. Here, we report a digital light projection (DLP) system integrated with reorientable magnetic field to facilely print smart LCE structures. We propose a new LCE precursor solution that maintains a liquid crystalline nematic phase and an adequate flowability at room temperature. The resin prior to photopolymerization can be sufficiently aligned by a magnetic field with a strength of 500 mT in seconds without temperature elevating or cycling. Consequential printed structures are capable of presenting an impressive reversible thermal actuation of more than 30 %. The local and arbitrary magnetic-field alignment in layers during DLP printing is characterized, which renders us the ability to construct smart structures with more delicate LC alignments. Furthermore, we introduce the selective deformation of LCE structures with programmed molecular orientation using the photo-thermal effect. Our reported approach reveals the significant potential for fabricating morphing structures in various fields, including soft robotics, biomedical structures, and microelectronics. (†These authors contributed equally.)

cond-mat.soft↗

arXiv2023

Finite Element Modeling of Pneumatic Bending Actuators for Inflated-Beam Robots

Inflated-beam soft robots, such as tip-everting vine robots, can control curvature by contracting one beam side via pneumatic actuation. This work develops a general finite element modeling approach to characterize their bending. The model is validated across four pneumatic actuator types (series, compression, embedded, and fabric pneumatic artificial muscles), and can be extended to other designs. These actuators employ two bending mechanisms: geometry-based contraction and material-based contraction. The model accounts for intricate nonlinear effects of buckling and anisotropy. Experimental validation includes three working pressures (10, 20, and 30 kPa) for each actuator type. Geometry-based contraction yields significant deformation (92.1% accuracy) once the buckling pattern forms, reducing slightly to 80.7% accuracy at lower pressures due to stress singularities during buckling. Material-based contraction achieves smaller bending angles but remains at least 96.7% accurate. The open source models available at http://www.vinerobots.org support designing inflated-beam robots like tip-everting vine robots, contributing to waste reduction by optimizing designs based on material properties and stress distribution for effective bending and stress management.

cs.RO↗