arXiv subjects

Noy Cohen

Publications and source records attributed to Noy Cohen.

8 recordsLinked to original sources

arXiv2026

Towards end-to-end optimization in multimaterial 3D printing

Multimaterial 3D printing enables the fabrication of functionally graded components, but optimizing their spatial material distribution alongside structural topology remains a formidable challenge due to high-dimensional design spaces and complex constitutive modeling. This paper presents an end-to-end computational framework integrating sparsified physics-augmented neural networks with finite-element-based topology optimization. By extracting closed-form, composition-aware hyperelastic constitutive laws from experimental data, this approach facilitates exact symbolic differentiation via the adjoint state method implemented with FEniCSx, efficiently circumventing the bottlenecks of applying neural network constitutive models. This pipeline is deployed on soft robotic gripper applications, demonstrating continuous composition optimization for highly anisotropic contact responses, and the concurrent optimization of macroscopic topology and material distribution under non-failure stretch constraints. This methodology could replace laborious empirical prototyping, establishing interpretable machine-learning models as practical, robust design primitives for advanced multimaterial additive manufacturing.

physics.comp-ph↗

arXiv2026

Stiffness by design in biological fibers: the influence of microstructure and temperature

Biological fibers exhibit exceptional mechanical properties such as high stiffness, toughness, and elasticity. The stiffness of bio-fibers is governed by a hierarchical microstructure that is highly sensitive to the extraction method, post-processing, and environmental factors such as temperature. Commonly, the microstructure features an amorphous matrix comprising polypeptide chains that interact through weak intermolecular bonds and interconnect via crystalline domains. In this work, we develop a microscopically motivated energy-based model that sheds light on the underlying mechanisms governing the stiffness of bio-fibers. The initial deformation is driven by (1) the entropic extension of polypeptide chains, (2) the elastic stretching and rotation of rigid crystalline domains, and (3) the distortion of weak intermolecular interactions, leading to the relative sliding of polypeptide chains. The model captures the influence of key physical microstructural quantities such as chain alignment, chain stretch, intermolecular bond strength, and crystallite size on the overall stiffness. The merit of the model is demonstrated through a comparison to spider silk and cocoon silk fibers. We also employ the model to show that the reeling speed during the extraction of spider silk fibers governs the microstructure and, therefore, leads to different stiffnesses. We follow with a parametric analysis that sheds light on how different microstructural quantities affect the stiffness. Lastly, the framework is extended to account for thermally-induced microstructural changes and the model predictions are compared to experimental data on the stiffness of cocoon silk fibers as a function of temperature. The findings from this work delineate the role of microstructure on the overall stiffness and offer a pathway for the efficient design of tunable and optimized biomimetic fibers for target applications.

physics.bio-ph↗

arXiv2026

Rethinking failure in polymer networks: a probabilistic view on progressive damage

The mechanics of single-chain stretching and rupture are central to understanding the resilience of biological polymers and designing strong and tough soft materials such as double-network gels and multi-network elastomers. In this work, we develop a statistical mechanics based model that enables one to determine the distribution of forces along the chain segments. By combining the force distribution with a tilted bond potential that captures the stretch energy stored in these bonds, we calculate the corresponding activation energy required for bond dissociation. This allows us to determine the probability of bond (and consequently chain) failure. The proposed approach is simple, direct, and readily adaptable for constructing higher-level coarse-grained descriptions of damage and fracture in polymer networks. We demonstrate this by applying the theory to two problems of practical interest: (1) toughening networks via sacrificial bond rupture in polymer chains and (2) incorporation of the local chain model into a 3-dimensional constitutive relation that captures damage in elastomers. The latter was implemented through the micro-sphere framework, which accounts for different chain orientations, as well as the computationally inexpensive eight chain model. The findings from this work provide a physically-based model to quantify the stretching and failure of a single chain and pave the way to the integration of local damage models into 3-dimensional networks.

cond-mat.soft↗

arXiv2026

Plasticity, hysteresis, and recovery mechanisms in spider silk fibers

Spider silk is a remarkable biomaterial with exceptional stiffness, strength, and toughness stemming from a unique microstructure. While recent studies show that silk fibers exhibit plasticity, hysteresis, and recovery under cyclic loading, the underlying microstructural mechanisms are not yet fully understood. In this work, we propose a mechanism explaining the loading-unloading-relaxation response through microstructural evolution: initial loading distorts intermolecular bonds, resulting in a linear elastic regime. Upon reaching the yield stress, these bonds dissociate and the external load is transferred to the polypeptide chains, which deform entropically to allow large deformations. Unloading is driven by entropic shortening until a traction free state with residual stretch is achieved. Subsequently, the fiber recovers as chains reorganize and bonds reform, locking the microstructure into a new stable equilibrium that increases stiffness in subsequent cycles. Following these mechanisms, we develop a microscopically motivated, energy-based model that captures the macroscopic response of silk fibers under cyclic loading. The response is decoupled into two parallel networks: (1) an elasto-plastic network of inter- and intramolecular bonds governing the initial stiffness and yield stress, and (2) an elastic network of entropic chains that enable large deformations. The model is validated against experimental data from Argiope bruennichi dragline silk. The findings from this work are three-fold: (1) explaining the mechanisms that govern hysteresis and recovery and linking them to microstructural evolution; (2) quantifying the recovery process of the fiber, which restores and enhances mechanical properties; and (3) establishing a predictive foundation for engineering synthetic fibers with customized properties.

cond-mat.soft↗

arXiv2025

Phase coexistence in thermo-responsive PNIPAM hydrogels triggered by mechanical forces

Poly(N-isopropylacrylamide) (PNIPAM) is a temperature-responsive polymer that undergoes large volumetric deformations through a transition from a swollen to a collapsed state at the volume phase transition temperature (VPTT). Locally, these deformations stem from the coil-to-globule transition of individual chains. In this contribution, I revisit the study of Suzuki and Ishii ("Phase coexistence of neutral polymer gels under mechanical constraint"), which demonstrated that a PNIPAM rod can exhibit phase coexistence (i.e. comprise swollen and collapsed domains) near the VPTT when subjected to mechanical constraints. Specifically, that paper showed that (1) collapsed domains gradually form in a fixed swollen rod with time and (2) swollen domains can nucleate in a collapsed rod that under uniaxial extension. These behaviors originate from the local thermo-mechanical response of the chains, which transition between states in response to the applied mechanical loading. Here, I develop a statistical-mechanics based framework that captures the behavior of individual chains below and above the VPTT and propose a probabilistic model based on the local chain response that sheds light on the underlying mechanisms governing phase nucleation and growth. The model is validated through comparison with experimental data. The findings from this work suggest that in addition to the classical approaches, in which the VPTT is programmed through chemical composition and network topology, the transition can be tuned by mechanical constraints. Furthermore, the proposed framework offers a pathway to actively tailor the VPTT through the exertion of mechanical forces, enabling improved control and performance of PNIPAM hydrogels in modern applications.

cond-mat.soft↗

arXiv2025

Physics Augmented Machine Learning Discovery of Composition-Dependent Constitutive Laws for 3D Printed Digital Materials

Multi-material 3D printing, particularly through polymer jetting, enables the fabrication of digital materials by mixing distinct photopolymers at the micron scale within a single build to create a composite with tunable mechanical properties. This work presents an integrated experimental and computational investigation into the composition-dependent mechanical behavior of 3D printed digital materials. We experimentally characterize five formulations, combining soft and rigid UV-cured polymers under uniaxial tension and torsion across three strain and twist rates. The results reveal nonlinear and rate-dependent responses that strongly depend on composition. To model this behavior, we develop a physics-augmented neural network (PANN) that combines a partially input convex neural network (pICNN) for learning the composition-dependent hyperelastic strain energy function with a quasi-linear viscoelastic (QLV) formulation for time-dependent response. The pICNN ensures convexity with respect to strain invariants while allowing non-convex dependence on composition. To enhance interpretability, we apply $L_0$ sparsification. For the time-dependent response, we introduce a multilayer perceptron (MLP) to predict viscoelastic relaxation parameters from composition. The proposed model accurately captures the nonlinear, rate-dependent behavior of 3D printed digital materials in both uniaxial tension and torsion, achieving high predictive accuracy for interpolated material compositions. This approach provides a scalable framework for automated, composition-aware constitutive model discovery for multi-material 3D printing.

cs.LG↗

arXiv2020

Giant Superelastic Piezoelectricity in Flexible Ferroelectric $BaTiO_3$ Membranes

Mechanical displacement in commonly used piezoelectric materials is typically restricted to linear or biaxial in nature and to a few percent of the material dimensions. Here, we show that free-standing BaTiO$_3$ membranes exhibit non-conventional electromechanical coupling. Under an external electric field, these superelastic membranes undergo controllable and reversible 'sushi-rolling-like' 180$^\circ$ folding-unfolding cycles. This crease-free folding is mediated by charged ferroelectric domains, leading to a giant > 3.8 and 4.6 $μ$m displacements for a 30-nm thick membrane at room temperature and 60$^\circ$C, respectively. Further increasing the electric field above the coercive value changes the fold curvature, hence augmenting the effective piezoresponse. Finally, it is found that the membranes fold with increasing temperature followed by complete immobility of the membrane above the Curie temperature, allowing us to model the ferroelectric-domain origin of the effect.

physics.app-ph↗

arXiv2015

Towards a physics-based modelling of the electro-mechanical coupling in EAPs

Due to the increasing number of industrial applications of electro-active polymers (EAPs), there is a growing need for electromechanical models which accurately capture their behavior. To this end, we compare the predicted behavior of EAPs undergoing homogenous deformations according to three electromechanical models. The first model is a continuum based model composed of the mechanical Gent model and a linear relationship between the electric field and the polarization. The electrical and the mechanical responses according to the second model are based on the polymer microstructure, whereas the third model incorporates a neo-Hookean mechanical response and a microstructural based long-chains model for the electrical behavior. In the microstructural motivated models the integration from the microscopic to the macroscopic levels is accomplished by the micro-sphere technique. Four types of homogeneous boundary conditions are considered and the behaviors determined according to the three models are compared. The differences between the predictions of the models are discussed, highlighting the need for an in-depth investigation of the relations between the structure and the behaviors of the EAPs at microscopic level and their overall macroscopic response.

cond-mat.soft↗