Soft skins with reversible thickness morphing represent a distinct and underexplored class of adaptive material interfaces. Unlike conventional soft actuators that achieve motion through bending, elongation, or twisting, these systems enable out-of-plane deformation, producing localized protrusion, retraction, and programmable contact mechanics without rigid support structures. This review reframes thickness modulation not merely as an actuation outcome, but as a material-architecture strategy that couples energy transduction, geometry, and compliance to enable new modes of haptic interaction, morphological adaptation, and operation in confined or unstructured environments. We present a comprehensive synthesis of thickness-morphing soft skins, covering actuation stimuli, material platforms, structural architectures, fabrication strategies, modeling frameworks, and system-level integration. Particular emphasis is placed on hierarchical elastomer composites, origami- and kirigami-inspired designs, electrohydraulic and multimodal hybrid systems, and emerging data-driven control approaches that expand the functional design space. Despite rapid progress, key challenges remain in durability under cyclic loading, energy efficiency and autonomy, scalable manufacturing, and integration of sensing, actuation, and computation. Addressing these challenges will enable self-powered, fault-tolerant, and computationally intelligent soft skins capable of embodied perception and safe autonomous operation, positioning thickness morphing as a foundational design axis for next-generation haptics and soft robotic systems.
This work presents a numerical framework for three-phase systems (liquid, gas, visco-elastic solid) using an extended discontinuous Galerkin (XDG) and level-set method. It simulates complex fluid-structure interactions with heat and mass transfer, maintaining strictly sharp phase interfaces without artificial smoothing. After verifying optimal convergence via a fluid-solid Taylor-Couette benchmark, the framework is applied to the Leidenfrost effect. While existing studies typically assume rigid solid surfaces, we investigate deformations induced by localized vapor pressure on soft substrates. We validate quasi-static droplet shapes against existing rigid solid models and derive a novel analytical extension for soft substrates using a Winkler foundation model. Our simulations demonstrate excellent agreement with this new analytical solution. Finally, the framework's robustness is demonstrated by simulating a Leidenfrost droplet sliding down an inclined soft substrate, successfully capturing asymmetric droplet shape, substrate deformation and localized interfacial waves.
Indentation is one of the simplest ways to feel the stiffness of matter. Interpreting indentation, however, requires care, especially for thin films-such as biological cells or soft coatings supported by rigid substrates-because the substrate effect can make a film appear orders of magnitude stiffer than it actually is. To minimize this artifact, the empirical "10% rule of thumb," which limits indentation depth to one-tenth of the film thickness, has often been adopted, though it becomes unreliable and impractical for ultrathin films. Here, we explore the traditionally forbidden regime: deep indentation, where the indentation depth is comparable to the film thickness. We develop an asymptotic theory that incorporates nonlinear geometry and elasticity, elucidating a simple indentation force-depth relation in this deep regime. We further show that the pull-off force in such indentation tests is remarkably independent of both the material law and geometric nonlinearity. The results provide a unified framework for interpreting thin-film mechanics under deep indentation, a regime that is generally much more accessible in experiments on very thin films.
Objective: The objective of this study was to investigate the relationship between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and dynamic contrast-enhanced MRI (DCE-MRI) parameters in soft tissue tumors (STTs). Methods: This retrospective study included patients with histopathologically confirmed STTs who underwent both DCE-MRI and IVIM-DWI between March 2022 and February 2024. Patients with prior therapy and lipomatous tumors were excluded. DCE-MRI parameters (Ktrans, Kep, Ve, iAUC) were obtained from pharmacokinetic maps using manually placed regions of interest (ROIs) in the most perfused tumor areas, avoiding necrotic and cystic regions. Corresponding ROIs were applied to IVIM-DWI maps. IVIM parameters (D, D*, f) were calculated using 11 b-values. Results: Twenty-nine patients (mean age, 56 ± 18 years; 14 malignant, 15 benign) were included. Interobserver agreement was excellent for DCE-MRI parameters, whereas IVIM-DWI parameters showed moderate-to-good agreement, with D showing the lowest reproducibility. In malignant tumors, f demonstrated strong positive correlations with Ktrans (r = 0.81, p < 0.001) and iAUC (r = 0.79, p < 0.001), both of which remained significant after correction for multiple comparisons. fD* was higher in malignant than in benign lesions in the unadjusted group comparison; however, diagnostic performance was not evaluated in the present study. No significant differences were observed for DCE-MRI parameters between benign and malignant tumors. Conclusions: IVIM-DWI parameters demonstrated associations with DCE-MRI metrics in malignant STTs and may provide complementary information regarding tumor perfusion. However, the findings should be interpreted cautiously because ROI analysis was limited to a single representative slice. Further validation using larger cohorts and volumetric tumor assessment is required.
Van der Waals (vdW) epitaxy can integrate lattice-mismatched crystals with atomically sharp, pristine interfaces. However, translating this concept to atomic layer deposition (ALD), a standard for low-temperature, layer-by-layer growth, remains challenging because precursors adsorb transiently on chemically inert vdW basal planes, leading to physisorption-limited nucleation and poor crystalline ordering. Here, we introduce diffusion-steered epitaxial ALD (Epi-ALD), redefining vdW surfaces as programmable kinetic-thermodynamic landscapes and demonstrate highly crystalline tellurium at 150°C. Epi-ALD couples surface-potential-encoded physisorption with long-range diffusion to promote ordered nucleation and epitaxial alignment. This "soft" pathway enables strain-free tellurium epitaxy with a pristine vdW gap (∼1.4 angstrom) despite lattice mismatch (>3.6%) and generalizes across multiple vdW templates. Retaining hallmark advantages of ALD including scalability and uniformity, we further program in-plane orientation through vdW symmetry engineering to achieve quasi-single-crystalline tellurium films with pronounced anisotropy and a chiral anomaly signature. Our work establishes a universal, low-thermal-budget approach for integrating vdW materials and expands the scope of epitaxy within the ALD paradigm.
Ultrasound-induced degradation of soft polymeric colloids, like microgels, as well as a controlled drug release enabled by mechanoresponsive bonds, has recently attracted considerable attention. However, most examples in the literature focus primarily on the applications rather than examining the underlying mechanisms of the structural changes occurring in microgels due to cavitation─changes that are crucial for developing effective drug delivery systems. In this work, we provide a comprehensive view of how microgel structure governs the susceptibility to rupture and mass loss upon cavitation, investigating both conventional microgels containing mechanoresponsive disulfide bonds and more complex asymmetrically cross-linked core-shell microgels. By combining dynamic and static light scattering, small-angle X-ray scattering, and atomic force microscopy, we demonstrate that an interplay between mechanoresponsive cross-links and the swelling degree determines the microgels' susceptibility to ultrasound-induced damage. Our findings indicate that local stress from cavitation bubbles varies strongly within the microgel dispersion. The majority of microgels undergo gradual erosion at their periphery, resulting in smaller yet structurally intact particles over time, observable by light scattering and AFM. In contrast, microgels closer to a cavitation bubble can experience partial rupture or complete disintegration, producing smaller, more polydisperse fragments, which contribute substantially to the overall mass loss observed. In the core-shell microgels with different cross-linkers in the core and shell, degradation occurs nearly uniformly across both regions, instead of selectively targeting the weaker part. These observations highlight the complexity of the degradation dynamics as well as the similarity to processes seen in linear polymers and bulk hydrogels.
The generalized Langevin equation (GLE) is widely used to model complex soft-matter systems, including biomolecular dynamics, by incorporating memory effects and colored noise into coarse-grained descriptions. However, recent results suggest that combining memory with non-linear forces, which are ubiquitous in soft matter, introduces fundamental analytical inconsistencies. Here, using a simplified model, we investigate the practical numerical consequences of these analytical results in equilibrium systems. We show that non-linear forces generate cross-correlations with the noise, modifying the fluctuation-dissipation theorem and rendering the noise position-dependent and irreversible. This implies that the commonly assumed reversible Gaussian noise in GLE simulations fails to capture essential features of the microscopic fluctuations. For weak non-linearities, these issues can be partially resolved either by using an iterative optimization of memory or by using microscopically consistent noise, which unexpectedly synchronizes GLE trajectories with the underlying microscopic dynamics. For stronger non-linearities, such as high barriers or shoulders in the external potential, however, iterative reconstruction fails and we observe desynchronization, indicating that the non-linear GLE no longer correctly reproduces the microscopic dynamics. Our results show in which situations non-linear GLEs can be accurately applied and when they fail, thus providing practical guidance for their application to coarse-grain soft-matter systems.
To develop and evaluate a stress-constrained physics-informed UNet framework for voxel-wise, multiparameter hyperelastic characterization of heterogeneous soft tissues from volumetric displacement data and accessible boundary reaction information in controlled synthetic 3D benchmarks. We introduce a physics-informed UNet (PI-UNet) that estimates voxel-wise Mooney-Rivlin parameter maps from multi-loading, strain-derived volumetric inputs. Synthetic finite-element data were generated for three benchmarks: a stiff spherical inclusion in a homogeneous matrix, an anatomically realistic gray/white matter brain embedded in a homogeneous matrix, and an embedded brain containing a synthetic tumor-like inclusion. The loss enforces static equilibrium through the divergence of the first Piola-Kirchhoff stress and incorporates boundary reaction information as face-averaged stress or an equivalent resultant force. Noise robustness was assessed using displacement perturbations and Gaussian smoothing within the loss formulation. PI-UNet reconstructed heterogeneous Mooney-Rivlin fields with high spatial fidelity across the tested synthetic configurations. In the spherical-inclusion benchmark, moderate smoothing reduced noise sensitivity while preserving inclusion geometry. In the gray/white matter benchmark, the framework recovered distinct material signatures for matrix, gray matter, and white matter. In the tumor-like benchmark, scalar fields derived from reconstructed material parameters improved unsupervised identification of the mechanically distinct lesion-like region compared with deformation-derived invariant fields alone. The proposed stress-constrained PI-UNet provides a scalable computational framework for controlled voxel-wise 3D multiparameter hyperelastic inversion from volumetric deformation fields and accessible boundary reaction measurements, supporting future experimental phantom validation, richer constitutive models, uncertainty quantification, and eventual in vivo elastography studies.
Programmable hydrogel actuators represent an innovative group of adaptive soft matter systems, which are able to respond to external stimuli with controllable mechanical movements for biomedical and bioengineering purposes. Natural silk fibroin (SF) is known to be a peculiar biomaterial, since it can exhibit controllable β-sheet-induced structural transitions, hierarchical self-assemblies, high biocompatibility, and mechanical adaptability, thus representing an ideal candidate for the development of dynamic hydrogels. In contrast to earlier reviews which focused more on SF hydrogel synthesis or biomedical applications, this review presents a mechanism-based understanding of programmable bioactuation by carefully correlating molecular design, network formation, stimuli responsiveness, and macroscopic deformation. Recent developments in SF hydrogel actuators are critically compared in terms of actuation principles, deformation behaviors, response dynamics, mechanical robustness, and functionalization, noting the natural compromise between fast response, strength generation, and durability in such materials. Novel concepts like nanocomposite materials, bioinspired designs, shape memory systems, and 4D printing are described as efficient ways to improve programmable deformation and functionality in soft materials. In addition, the biomedical opportunities of responsive SF hydrogels in wound healing, drug delivery, tissue engineering, wearable biosensors, and soft robots are critically discussed in relation to existing barriers for translation into practice. Combining mechanistic understanding with the comparative assessment of the performance of hydrogels is a basis for developing a complete rationale for the design of the next generation of SF hydrogel actuators and smart shape deformations.
Colloidal self-assembly is a powerful strategy to obtain materials with desired softness, porosity and biocompatibility. When soft building blocks are used, these properties can change dramatically, compared to materials produced using hard particles. However, the fate of individual colloids inside these assemblies is not fully understood. Here, asymmetric mixtures of soft microgels with opposite electrical charges are used as model building blocks to assemble colloidal clusters. The changes in the form factor of individual microgels due to cluster formation are analyzed using small-angle neutron scattering with contrast variation, complemented with small-angle X-ray scattering and molecular dynamics simulations. A strong compression of the fuzzy shell of a microgel is observed, which results in a peculiar core-shell architecture of the microgel. In contrast, a reference system of similarly charged microgels shows osmotic deswelling in both the dense core and fuzzy shell, as expected. Molecular dynamics simulations reveal that the polymer density at contact between the oppositely charged microgels increases due to the entropically favorable counterion release. To maximize the number of released counterions, the microgels compress their shells or interpenetrate each other. The results show that the structure of individual soft colloids may be significantly altered during the assembly of clusters, which can influence the larger hierarchical assembly.
The brittle nature of today's displays, solar cells, and touchscreens leads to adverse economic and environmental impacts, driving the need for thin-film, flexible optoelectronics that are resistant to strain, impact, sharp objects, and liquids. This vision requires cost-effective, scalable production of ultra-resilient transparent conductors capable of withstanding millions of deformation cycles-challenges that nanowire-based electrodes have yet to overcome. In nature, particular insect wings achieve a unique blend of transparency, resilience, and lightness. This inspired us to develop liquid metal-based transparent conductors with nature-inspired gyroid-like nanostructures that outperformed nanowire-based counterparts significantly in conductivity and stretchability (7×), withstanding a record-breaking strain of 1400% and unprecedented stability over 100,000 strain cycles. Unlike nanowire-based electrodes, this electrode is simple, low-cost, scalable, and recyclable. The formation of such a nano-scaffold is beyond the reach of lithographic techniques but is enabled by our unconventional technique: graphene-assisted self-assembly of liquid metal nanodroplets into a porous 3D microstructure. We demonstrate mechanically resilient soft-matter electroluminescent displays with high light intensity and extend their applications to soft robotics, light-emitting muscles, energy harvesting, transparent heaters, and UV sensors. By harnessing the deformability of liquid metal, we demonstrate a transparent pressure-sensing film that converts any display into a pressure-sensing interface.
Nature builds functional materials through simple yet powerful processes that generate structured architecture across scales-from the lamellar patterns in seashells to the zonal organization of living tissues. Emulating such complexity in engineered systems remains challenging and often requires microfabricated components, external fields, or specialized hardware. Previously, we introduced chaotic printing as a deterministic and flow- and geometry-driven strategy for fabricating structured filaments, using static mixers embedded within extrusion printheads-primarily in the context of biofabrication. We broaden the architectural and functional scope of chaotic printing by exploring diverse static mixer designs and demonstrating its compatibility with three distinct deposition modes: wet-printing, dripping, and direct ink writing. These modalities enable the generation of material constructs with chemically and biologically relevant internal organization. We showcase examples ranging from zonally arranged mammalian cells that prefigure microtissue compartments to spatially patterned bacterial consortia composed of strict and facultative anaerobes and localized mineral precipitation within hydrogel filaments. These proof-of-concept-demonstrations underscore the potential of chaotic printing for fabricating structured soft matter where internal microarchitecture enables biologically and chemically relevant processes. This study positions chaotic printing as a modular, scalable, accessible platform for generating architected materials across fields ranging from cell culture and microbiology to functional soft materials.
Aromatic interactions organize molecules into ordered supramolecular architectures, while peptides form functional soft materials through hydrogen bonding and water-mediated assembly. In peptide-based systems, strong aromatic stacking is typically achieved by terminal capping, whereas terminally uncapped peptides organize water through polar end groups but rarely form highly ordered materials. Here we show that a π-extended aromatic unit can be integrated into a terminally uncapped peptide to create a class of supramolecular hydrogels with structural order. A pyrene-modified dipeptide hierarchically assembles into monodisperse helical nanofibers and self-healing hydrogels. Cryo-electron microscopy resolves the nanofibers at near-atomic precision (1.7 Å), revealing tightly packed protofilaments, continuous ordered water channels, and a unidirectional dipole extending along the fiber. These results demonstrate how reinforced aromatic stacking, polar interactions, and cooperative water organization can be orchestrated to generate emergent electrostatics and mechanical resilience, bridging conjugated materials and biomolecular matter, enabling functional soft materials inaccessible to either domain alone.
The objective of the present study was to determine the ruminal passage rate (Kp) of undegraded NDF (uNDF) and the methane (CH4) emissions of cows consuming diets containing triticale silages of different maturities. Triticale was harvested at the boot (BT) and soft-dough (SFT) stages of maturity, and ensiled. Sixteen primiparous (609 ± 45 kg BW, 156 ± 27 DIM) and 8 multiparous (673 ± 52 kg BW, 169 ± 65 DIM) Holstein dairy cows were randomly assigned to one of 2 experimental diets (BT vs. SFT) in a crossover design with 2 28-d periods and a 7-d preceding covariate period. Methane emissions were measured using a single GreenFeed system accessible to all cows within the pen with 24 stalls. Ruminal contents from 12 rumen-cannulated cows were evacuated at 2 h before feeding and at 2 h after feeding (d 17 and d 24) to determine ruminal pool sizes. A pulse dose of marked fiber was thoroughly mixed with ruminal contents, and the passage of undegraded NDF (uNDF) was determined as the dilution rate of the marker among uNDF over time. All variables were analyzed using the MIXED procedure of SAS, and the model included the fixed effect of diet and the random effects of cow and period. The BT triticale silage contained 16.4% CP, 53.1% NDF, and 19.3% uNDF (NDF basis), whereas the SFT triticale silage contained 9.3% CP, 63.2% NDF, and 42.4% uNDF. Cows consuming BT triticale silage produced 3.3 kg/d more milk than cows consuming SFT triticale silage (39.6 vs. 36.3 kg/d). Forage maturity did not affect the concentration of milk fat (4.47%) or milk protein (3.22%). Cows consuming BT triticale silage produced 3.4 kg more ECM than cows consuming SFT triticale silage (45.6 vs. 42.2 kg/d). Dry matter intake did not differ (24.9 kg/d) between cows fed diets containing BT and SFT triticale silages. Cows consuming BT triticale silage showed improved total-tract digestibilities of DM (64.1 vs. 57.8%), CP (54.1 vs. 44.5%), NDF (51.8 vs. 43.7%), and pdNDF (65.4 vs. 60.4%) compared with cows consuming SFT triticale silage. Cows consuming BT triticale silage had a 0.9-kg smaller ruminal pool of DM (7.9 vs. 8.8 kg), a 0.8-kg smaller ruminal pool of NDF (4.9 vs. 5.7 kg), and a 0.9-kg smaller ruminal pool of uNDF (2.5 vs. 3.4 kg) but a similar ruminal pool of pdNDF (2.4 kg) compared with cows consuming SFT triticale silage. The Kp of uNDF assessed with marked corn silage did not differ between the experimental diets (4.03%/h). Cows consuming BT triticale silage produced 5% less enteric CH4 (332 vs. 348 g/d), tended to yield 6% less CH4 on a DMI basis (13.6 vs. 14.5 g/kg DMI), yielded 17% less CH4 on a DM digested basis (21.3 vs. 25.6 g/kg DMI), and had a 10% lower CH4 intensity (7.8 vs. 8.7 g/kg ECM) than consuming SFT stage triticale. Feeding diets containing BT triticale silage reduced enteric CH4 emissions compared with feeding diets containing SFT triticale silage, while maintaining ruminal Kp of uNDF and enhancing ruminal and total-tract NDF digestibility.
This review explores the use of staining techniques for polymers in transmission electron microscopy, with a focus on commonly employed staining agents and their mechanisms of interaction with polymeric materials. It offers detailed insights into contrast generation, emphasizing how specific stains selectively enhance electron density in distinct polymer phases to reveal morphological and structural features. Established contrast enhancement methods, such as heavy metal staining with agents like osmium tetroxide and ruthenium tetroxide, are discussed in depth. The review also highlights recent advancements in alternative staining strategies, illustrating emerging trends and expanding possibilities for high-resolution imaging in soft matter characterization.
Confocal microscopy enables high-resolution imaging deep within samples but is fundamentally limited by its low frame rate, making the visualization of fast dynamics challenging. We developed a synchronization-based image reconstruction method that extends conventional laser scanning confocal microscopes to three-dimensional and two-dimensional wide-field imaging of periodically moving objects at frequencies beyond the nominal frame rate. The method synchronizes a confocal microscope with a function generator to ensure consistent initial phase alignment across image sequences acquired at different focal depths or fields of view. Using this approach, we visualized the three-dimensional motion of silica particles attached to an aluminum bar oscillating at 100 Hz and the two-dimensional wide-field response of colloidal particles subjected to periodic pulsed excitation. Quantitative analysis of particle trajectories confirmed that the reconstructed images captured the underlying particle dynamics. Because the method requires no additional specialized imaging hardware and preserves the intrinsic imaging performance of confocal microscopy, it can be readily integrated with conventional confocal microscopes for investigating the fast dynamics of periodic processes in biological and soft-matter systems.
Unlike absorption colors, which are produced by light-absorbing dyes and pigments, structural colors arise from the wavelength-dependent interference of light scattered by microstructures produced through the self-organization of soft matter systems, like colloids or chiral liquid crystals. However, applications of structural colors require forming structures with micron-scale periodicities that are well-ordered and defect-free over large areas, which can only be achieved through complex sample processing methods. Here, we demonstrate another approach based on the striated linear topological defects appearing in thin liquid crystal smectic films under hybrid anchoring conditions. We produced structural colors in both reflection and transmission geometries simply by spin-coating the widespread commercial achiral molecular liquid crystal 8CB over glass slides. Optical microscopy, AFM, and optical diffraction techniques show that the colors are due to the modulation period along the defect axis being comparable to the wavelengths of visible light. Our approach dispenses with the tedious synthesis or purification of chiral organic compounds and with achieving ideal periodic microstructures because it relies on the spontaneous formation and uniform modulation of topological defects, allowing for upscaling to the large areas required for applications.
Artificial molecular motors convert light into rotary motion and are central components of synthetic molecular machineries. Their rotation frequency is key to their performance and is typically rationalized in terms of intrinsic molecular structure and solvent viscosity, while the influence of supramolecular organization remains largely unexplored. Here, we show that motor rotation is governed not only by viscosity but also by the supramolecular organisation of the surrounding medium. Thermodynamic analysis reveals that, beyond the viscosity-related increase observed in the isotropic phase of the same host, nematic order introduces an additional enthalpic penalty of 10-14 kJ mol-1 for the rate-determining thermal helix inversion. The magnitude of this penalty follows the alignment of the metastable cis-states involved in helix inversion, consistent with an order-dependent elastic resistance. These findings identify supramolecular order as a kinetic control parameter for artificial molecular motors and reveal reciprocal coupling between molecular-machine operation and soft-matter organization.
Ionic liquids (ILs) can modulate protein phase behavior, including crystallization and aggregation. However, crystallization outcomes are often difficult to predict because nucleation is stochastic and strongly affected by specific ion effects. Here, we examine the crystallization pathway of lysozyme in ethylammonium nitrate (EAN) using a multi-modal small-angle X-ray scattering (SAXS) strategy that integrates high-throughput 96-well screening, in situ capillary thermal treatment, and time-resolved kinetic monitoring. To address batch-to-batch variability in these soft-matter samples, we implemented a standardized workflow for extracting complementary SAXS descriptors, including a fixed-window pseudo-Rg descriptor of low-q scattering evolution and a crystallinity index based on Bragg-feature intensity. The SAXS data are consistent with a two-step nucleation-like pathway in which EAN-induced association precedes the appearance of long-range crystalline order, while thermal treatment disrupts metastable clusters without restoring a simple native monomeric state. Machine-learning models were used as within-system interpolation and screening-prioritization tools for the measured lysozyme-EAN composition grid. Linear models failed to reproduce the non-linear trends, whereas ensemble methods reproduced the main features of the measured crystallization region. Feature-importance analysis identified EAN concentration as the dominant control variable (approximately 70% contribution). Together, these results provide a SAXS-based descriptor-extraction and data-analysis workflow for mapping composition-dependent crystallization behavior in the lysozyme-EAN system.
Finite element (FE) modeling is widely used in biomechanical research, enabling computational investigations of anatomical structures. To develop accurate FE models, high-resolution medical imaging such as computed tomography (CT) is essential. However, CT exposes patients to ionizing radiation. Recently, radiation-free three-dimensional zero-echo-time magnetic resonance imaging (3D ZTE MRI) has shown promising results for bone visualization. Therefore, this feasibility study investigated whether 3D ZTE MRI is reliable for creating subject-specific FE models. Human femora from four female subjects were imaged using 3D ZTE MRI. Static FE analyses of the femora were performed in Abaqus/CAE, assuming a biphasic homogenous linear-elastic material. A sensitivity analysis was conducted to evaluate varying bone material properties. After loading with 2000 N, the mean displacement of the femoral head amounted to -1.30 ± 0.26 mm (vertical) and -9.03 ± 2.21 mm (horizontal), while the femoral neck exhibited compressive (inferior: -1366.03 ± 182.70 µm/m) and tensile (superior: 1038.69 ± 135.82 µm/m) strains. Overall, the results demonstrate displacement and strain predictions similar to previous experimental and computational studies based on CT data. Therefore, despite several simplifications, these findings confirm the feasibility of radiation-free 3D ZTE MRI for subject-specific FE modeling, enabling future simultaneous assessment of bone morphology and surrounding soft tissues.