Daniel Balzani

Background: Determining the optimal number of classical biaxial tests and the selection of appropriate stress ratios for characterizing the complex behavior of coated woven fabrics is a challenge. Thus, the reliability of models calibrated using these homogeneous tests in predicting engineering structural performance may be limited. Objective: A recently proposed experimental-numerical approach has been shown in a feasibility study to offer a new perspective for the characterization of nonlinear anisotropic thin materials (Makhool and Balzani Experimental Mech 64:353–375 2025). The goal here is not only to validate the robustness and efficiency of this much less expensive identification framework using real experimental data from a single experiment on coated woven fabrics, but also to demonstrate that the parameters obtained based thereon may even improve the accuracy of structural analysis. Methods: On the basis of the Equilibrium Gap Method, provided that the material parameters are linear in the constitutive equations, a quadratic objective function is formulated, enabling a unique identification. Key of this framework are inhomogeneous full-field kinematics obtained from a single experimental setup designed to excite all essential deformation modes in the material model. Prior to incorporating the data into the discretized equilibrium equations, a pre-processing step is conducted, involving interpolation and extrapolation of the displacements on the scattered speckle pattern to map the values onto the computational grid. Results: The analysis validates the efficiency of the framework for the identification of material parameters using a single inhomogeneous displacement field captured by Digital Image Correlation. Further, through examining a boundary value problem replicating a modified experimental setup, highly predictive numerical results that closely match experimental data are obtained incorporating the identified parameters. In contrast, the acquired response using parameters derived from a classical fitting method shows notable deviations. The difference becomes particularly significant for a complex roof structure investigated as an example engineering problem. Conclusion: Based on real experiments, the experimental-numerical framework turns out to indeed allow for an efficient and unique identification of material parameters in hyperelastic models for coated woven fabrics. Since a variety of different stress-ratios are integrated at once in the experiment by considering inhomogeneous kinematics, also an improved accuracy in structural simulations is found.

Metastases arise from a multistep process during which tumour cells face several microenvironmental mechanical challenges, which influence metastatic success. However, how circulating tumour cells (CTCs) adapt their mechanics to such microenvironments is not fully understood. Here we report that the deformability of CTCs affects their haematogenous dissemination and identify mechanical phenotypes that favour metastatic extravasation. Combining intravital microscopy with CTC-mimicking elastic beads, mechanical tuning in tumour lines and profiling of tumour-patient-derived cells, we demonstrate that the inherent mechanical properties of circulating objects dictate their ability to enter constraining vessels. We identify cellular viscosity as a rheostat of CTC circulation and arrest, and show that cellular viscosity is crucial for efficient extravasation. Moreover, we find that mechanical properties that favour extravasation and subsequent metastatic outgrowth can be opposite. Altogether, our results establish CTC viscosity as a key biomechanical parameter that shapes several steps of metastasis.

Viscoelastic hydrogels mimic the dynamic mechanical properties of native extracellular matrices, making them essential for biomedical applications. However, characterizing their scale‐dependent mechanical properties remains challenging, despite their critical influence on cell‐material interactions and biomaterial performance. Here, an integrated experimental‐computational approach is presented to quantify and model the viscoelastic behavior of interpenetrating polymer network hydrogels across micro‐ and macro‐scales. Atomic force microscopy‐based stress relaxation tests revealed that microgels exhibit rapid, localized relaxation, while macroscopic bulk gels displayed prolonged relaxation dominated by poroelastic effects. Finite element simulations accurately replicated experimental conditions, enabling the extraction of key parameters: fully relaxed elastic modulus, relaxation modulus, and relaxation time constant. A novel analytical model is further developed to predict viscoelastic parameters from experimental data with minimal error (<6%), significantly streamlining characterization. The findings highlight the necessity of scale‐specific mechanical analysis and provide a robust platform for designing biomaterials with tailored viscoelasticity for tissue engineering and regenerative medicine.

The characteristics of microstructure morphology of micro‐heterogeneous materials may vary over the macroscopic length scale and thus result in macroscopically distributed, uncertain material properties. Hence, multiscale approaches for the structural analysis of such materials, for example, in terms of the ‐method, should not be based on a single representative volume element. In this contribution a method is proposed, which considers different, artificial statistically similar volume elements at each macroscopic integration point which mimic the microstructure variability of the real material as a random field. For this purpose, the microstructure variation of the real material is quantified first in terms of the distribution of a scalar measure containing deviations of statistical measures of higher order, and then this distribution is used to construct a set of artificial microstructures to be used as volume elements within the multiscale simulation. To avoid manual discretization of the large amount of statistically similar volume elements, the finite cell method is combined with concurrent computational homogenization following the ‐method. The proposed method is demonstrated for two examples, a simpler tensile experiment for testing purposes and a simplified, idealized deep drawing process.

Piezo1 ion channels are voltage‐modulated, stretch‐activated ion channels involved in a variety of important physiological and pathophysiological processes, as, for example, cardiovascular development and homeostasis. Since their discovery, it has been known that this type of ion channel desensitizes when exposed to stretch. However recent experiments on Piezo1 ion channels have uncovered that their stretch response is qualitatively different when exposed to positive electrochemical driving forces, where the desensitization is reset. In this work we propose a novel voltage‐modulated mathematical model of Piezo1 based on a continuous‐time Markov chain. We show that our Piezo1 model is able to quantitatively reproduce a wide range of experimental observations. Furthermore we integrate our new ion channel model into the Mahajan–Shiferaw ventricular cardiomyocyte model to study the effect of electromechanical pacing at the cellular scale. This integrated cell model is able to qualitatively reproduce some aspects of the experimental observations regarding the rate‐dependence of electromechanical pacing protocols. Our studies suggest that the Piezo1 ion channel is an important component that significantly contributes to the electromechanical coupled response of cardiomyocytes. image Key points: PIEZO ion channels are voltage‐modulated, mechanically gated ion channels involved in a large variety of mechanically regulated physiological processes and diseases. Recent experiments on Langendorff‐perfused rabbit hearts by A. Quinn and P. Kohl [2016] suggest a non‐trivial relation between the number of captured mechanical stimuli and the electromechanical pacing protocol. We present a novel thermodynamically consistent in silico model of the Piezo1 ion channel with electromechanical gating that can reproduce a large variety of experimental observations during combined exposure to electrical and mechanical stimuli. The new ion channel model is integrated into the well‐established Mahajan–Shiferaw rabbit ventricular cardiomyocyte model to study its role during normal heart beat and during electromechanical pacing protocols. Our in silico studies suggest that the Piezo1 ion channel alone may not be sufficient to explain the experimental observations made by A. Quinn and P. Kohl.

Viscoelastic hydrogels mimic the dynamic mechanical properties of native extracellular matrices, making them essential for biomedical applications. However, characterizing their scale-dependent mechanical properties remains challenging, despite their critical influence on cell-material interactions and biomaterial performance. Here, we present an integrated experimental-computational approach to quantify and model the viscoelastic behavior of interpenetrating polymer network hydrogels across micro- and macro-scales. Atomic force microscopy-based stress relaxation tests revealed that microgels exhibit rapid, localized relaxation, while macroscopic bulk gels displayed prolonged relaxation dominated by poroelastic effects. Finite element simulations accurately replicated experimental conditions, enabling the extraction of key parameters: instantaneous elastic modulus, relaxation modulus, and relaxation time constant. We further developed a novel analytical model to predict viscoelastic parameters from experimental data with minimal error (< 5%), significantly streamlining characterization. Our findings highlight the necessity of scale-specific mechanical analysis and provide a robust platform for designing biomaterials with tailored viscoelasticity for tissue engineering and regenerative medicine.