arXiv subjects

Andres F. Arrieta

Publications and source records attributed to Andres F. Arrieta.

8 recordsLinked to original sources

arXiv2026

The Group of Closed Symmetric Flat Foldable Non-Euclidean Curved Crease Origami is not Rigid Foldable: A Simple Geometric Proof

We present a novel parabolic reflector system capable of generating a broader class of shapes beyond canonical parabolas. Using a discretized framework, we construct meshes corresponding to key families of developable surfaces, including generalized cylinders, tangent developables, and generalized cones. Both Euclidean and non-Euclidean crease patterns are examined, and we demonstrate that no isometric transformation exists between distinct configurations within this system. This result highlights a fundamental limitation of purely developable models and motivates the incorporation of controlled stretching. We propose that enabling stretch accommodation would allow transitions between configurations, laying the groundwork for a generalized theory of curved-crease stretching. Such a framework has potential applications in understanding complex biological folding systems, including the deployment mechanics of the earwig wing.

cond-mat.soft↗

arXiv2026

Transition Waves for Energy Trapping and Harvesting

The presence of multiple stable states and associated nonlinear phenomena, such as hysteresis, in multistable mechanical metamaterials enables frequency-independent energy harvesting and shock absorption. This study focuses on shock absorption achieved by locking transition waves to trap energy at designed locations within a multistable metamaterial. We further demonstrate that the same system can simultaneously harvest energy from impact loading, thereby exhibiting multifunctionality. The model of the multistable metamaterial is a one-dimensional chain of bistable units whose transition wave dynamics are related to topological solitary waves governed by the $ϕ^4$ equation. This connection enables analytical estimation of critical design parameters required for energy trapping and also the amount of energy trapped. Numerical simulations and experiments show that trapping energy in transition waves leads to enhanced damping performance compared to corresponding linear metamaterials. We further propose design variations to increase the amount of energy trapped in the transition wave. Additionally, we identify energy splitting as a damping mechanism that arises when there are repeated impulses or a single high-amplitude impulse that generates multiple transition waves. The transition waves interact to produce localized, fast-dissipating breathers, leading to a damped response. Furthermore, experiments demonstrate that multistable metamaterials can simultaneously achieve improved energy harvesting and better damping performance compared to their linear counterparts. Together, these results highlight the use of transition waves for creating multifunctional multistable metamaterials.

nlin.PS↗

arXiv2025

Embodying Control in Soft Multistable Robots from Morphofunctional Co-design

Soft robots are distinguished by their flexibility and adaptability, allowing them to perform nearly impossible tasks for rigid robots. However, controlling their behavior is challenging due to their nonlinear material response and infinite degrees of freedom. A potential solution to these challenges is to discretize the infinite-dimensional configuration space into a finite but sufficiently large number of functional modes with programmed dynamics. We present a strategy for co-designing the desired tasks and morphology of pneumatically actuated soft robots with multiple encoded stable states and dynamic responses. Our approach introduces a general method to capture the soft robots' response using an energy-based analytical model, the parameters of which are obtained using Recursive Feature Elimination. The resulting lumped-parameter model facilitates inverse co-design of the robot's morphology and planned tasks by embodying specific dynamics upon actuation. We illustrate our approach's ability to explore the configuration space by co-designing kinematics with optimized stiffnesses and time responses to obtain robots capable of classifying the size and weight of objects and displaying adaptable locomotion with minimal feedback control. This strategy offers a framework for simplifying the control of soft robots by exploiting the nonlinear mechanics of multistable structures and embodying mechanical intelligence into soft material systems

cs.RO↗

arXiv2023

Connecting the Branches of Multistable Non-Euclidean Origami by Crease Stretching

Non-Euclidean origami is a promising technique for designing multistable deployable structures folded from nonplanar developable surfaces. The impossibility of flat foldability inherent to non-Euclidean origami results in two disconnected solution branches each with the same angular deficiency but opposite handedness. We show that these regions can be connected via "crease stretching" wherein the creases exhibit extensibility in addition to torsional stiffness. We further reveal that crease stretching acts as an energy storage method capable of passive deployment and control. Specifically, we show that in a Miura-Ori system with a single stretchable crease, this is achieved via two unique, easy to realize, equilibrium folding pathways for a certain wide set of parameters. In particular, we demonstrate that this connection mostly preserves the stable states of the non-Euclidean system, while resulting a third stable state enabled only by the interaction of crease torsion and stretching. Finally, we show that this simplified model can be used as an efficient and robust tool for inverse design of multistable origami based on closed-form predictions that yield the system parameters required to attain multiple, desired stable shapes. This facilitates the implementation of multistable origami for applications in architecture materials, robotics, and deployable structures.

cond-mat.soft↗

arXiv2022

Neuromorphic metamaterials for mechanosensing and perceptual associative learning

Physical systems exhibiting neuromechanical functions promise to enable structures with directly encoded autonomy and intelligence. We report on a class of neuromorphic metamaterials embodying bioinspired mechanosensing, memory, and learning functionalities obtained by leveraging mechanical instabilities and flexible memristive materials. Our prototype system comprises a multistable metamaterial whose bistable units filter, amplify, and transduce external mechanical inputs over large areas into simple electrical signals using piezoresistivity. We record these mechanically transduced signals using non-volatile flexible memristors that remember sequences of mechanical inputs, providing a means to store spatially distributed mechanical signals in measurable material states. The accumulated memristance changes resulting from the sequential mechanical inputs allow us to physically encode a Hopfield network into our neuromorphic metamaterials. This physical network learns a series of external spatially distributed input patterns. Crucially, the learned patterns input into our neuromorphic metamaterials can be retrieved from the final accumulated state of our memristors. Therefore, our system exhibits the ability to learn without supervised training and retain spatially distributed inputs with minimal external overhead. Our system's embodied mechanosensing, memory, and learning capabilities establish an avenue for synthetic neuromorphic metamaterials enabling the learning of touch-like sensations covering large areas for robotics, autonomous systems, wearables, and morphing structures.

cs.ET↗

arXiv2021

Magnetically driven in-plane modulation of the 3D orientation of vertical ferromagnetic flakes

External magnetic fields are known to attract and orient magnetically responsive colloidal particles. In the case of 2D microplatelets, rotating magnetic fields are typically used to orient them parallel to each other in a brick-and-mortar fashion. Thanks to this microstructure, the resulting composites achieve enhanced mechanical and functional properties. However, parts with complex geometry require their microstructure to be specifically tuned and controlled locally in 3D. Although the tunability of the microstructure along the vertical direction has already been demonstrated using magnetic orientation combined with sequential or continuous casting, controlling the particle orientation in the horizontal plane in a fast and effective fashion remains challenging. Here, we propose to use rotating magnetic arrays to control the in-plane orientation of ferromagnetic Nickel flakes distributed in uncured polymeric matrices. We experimentally studied the orientation of the flakes in response to magnets rotating at various frequencies and precessing angles. Then, we used COMSOL to model the magnetic field from rotating magnetic arrays and predicted the resulting in-plane orientations. To validate the approach, we created composites with locally oriented flakes. This work could initiate reverse-engineering methods to design the microstructure in composite materials with intricate geometrical shapes for structural or functional applications.

cond-mat.soft↗

arXiv2021

Programmable multistability for 3D printed reinforced multifunctional composites with reversible shape change

4D printing empowers 3D printed structures made of hydrogels, liquid crystals or shape memory polymers, with reversible morphing capabilities in response to an external stimulus. To apply reversible shape-change to stiff lightweight materials such as microfiber reinforced polymers, we developed a composite ink that can be printed using direct-ink-writing (DIW), and that exhibits multistability around its glass transition temperature. After curing at room temperature, the flat print thermally morphs into a predefined shape upon heating at an actuation temperature and cooling down. The sample can then reversibly snap between multiple stable shapes when heated above its glass transition temperature thanks to prestress-induced multistability. The key that allows thermal morphing and prestress multistability is the microstructuring of the 3D printed composites by shear-induced alignment of reinforcing microfibers. This alignment leads to local anisotropy in thermomechanical properties and the build-up of prestresses. Furthermore, the ink composition can be tuned to generate shape-dependant reversible functional properties, such as electrical conductivity. Based on finite element modelling and experimental results, the method proposed here can be used for variety of compositions and designs, for applications where stiffness, reconfigurability and shape-dependent functionalities can be exploited.

physics.app-ph↗

arXiv2021

Taming geometric frustration by leveraging structural elasticity

Geometric frustration appears in a broad range of systems, generally emerging as disordered ground configurations, thereby impeding understanding of the phenomenon's underlying mechanics. We report on a continuum system featuring locally bistable units that allows for the controlled and self-sustained manifestation of macroscopic geometric frustration. The patterning of the units encodes a finite set of ordered ground configurations (spin-ice states) and a unique family of co-existing higher-order frustrated states (spin-liquid states), which are both activated upon unit inversion. We present a strategy for accessing any globally frustrated state on-demand by controlling the constitutive units' inversion sequence. This control strategy allows for observing the unfolding of geometric frustration as the microstructural features evolve due to the energy minimization of the constitutive units' interactions. More broadly, our model system offers a blueprint for "taming" macroscopic geometric frustration, enabling novel applications such as path-driven computation and solving optimisation problems using structural systems.

physics.app-ph↗