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Shaoting Lin

Publications and source records attributed to Shaoting Lin.

9 recordsLinked to original sources

A discrete crack-tip theory for nonlinear lattice networks

Crack-tip fields govern deformation localization and failure initiation. Classical continuum fracture mechanics describes these fields through theories such as the Hutchinson-Rice-Rosengren (HRR) field for nonlinear power-law solids. However, continuum descriptions break down near cracks in soft and architected materials, where load is transmitted through discrete chains, fibers, or struts. Here, we develop a discrete crack-tip theory for lattice networks with nonlinear chains. The theory has two central components. First, at large deformation, the strain of a representative chain in layer $i$ depends approximately linearly on the applied macroscopic strain, $\varepsilon_i\approx k_i(\lambda-1)$, defining a layer-dependent strain-amplification factor $k_i$. Second, along topology-selected chain directions, termed discrete HRR lines, the layer-to-layer ratios of $k_i$ follow a two-regime scaling law. Together, for a power-law chain force-strain relation with exponent $p$, the inner discrete regime predicts $\varepsilon_i\sim i^{-1/p}$ and $f_i\sim i^{-1}$, which differs from the classical continuum HRR prediction. The theory also explains why the intrinsic fracture energy approaches a size-independent limit as the network size increases. Photoelastic hydrogel experiments further validate our theory. These results reveal a two-regime crack-tip scaling law in nonlinear lattice networks and provide a framework for predicting chain deformation and intrinsic fracture energy.

cond-mat.soft

MVP-Tac: A Miniaturized Dual-Modal Vision and Photoelastic Tactile Sensor for Robot-Assisted Minimally Invasive Surgery

Robot-assisted minimally invasive surgery (RMIS) offers major benefits over open and conventional laparoscopic procedures, yet it still lacks tactile feedback for palpation while operating under strict requirements to preserve reliable vision for navigation and safety. In practice, visual feedback is indispensable, and tactile solutions that cannot coexist with vision are difficult to translate into RMIS tools. To address both needs, we introduce MVP-Tac, a compact, vision-based tactile sensor that provides co-located vision and tactile sensing. MVP-Tac uses reflective photoelastic imaging: a thin photoelastic elastomer produces stress-dependent interferograms under contact that are captured by an embedded camera through a miniaturized reflective polariscope. A semi-transparent membrane and controllable illumination enable switching between visual mode and tactile mode, enabling tactile perception without sacrificing vision. We validate MVP-Tac through force calibration in the 0 to 2 N range and demonstrate its potential for tumor palpation via video-based hardness classification on tissue phantoms, achieving 97% accuracy for exposed-tumor classification and 92% accuracy for subdermal-tumor classification. Finally, we conduct a simulated colonoscopy to validate both visual and tactile modalities in a constrained lumen, including vision-guided 3D photomapping of the luminal wall and in situ hardness classification of localized nodules. Overall, MVP-Tac provides a practical path toward restoring clinically useful palpation in RMIS while maintaining essential visual feedback. The design, fabrication, and firmware of MVP-Tac are open-sourced at https://mvp-tac.github.io/

cs.RO

Topological Mechanics of Entangled Networks

Entangled networks are ubiquitous in tissues, polymers, and fabrics. However, their mechanics remain insufficiently understood due to the complexity of the topological constraints at the network level. Here, we develop a mathematical framework that models entangled networks as graphs, capturing topological constraints of entanglements. We prove that entanglements reduce system energy by enabling uniform tension along chains crossing entanglements and by redistributing stress through sliding. Under this framework, we study elasticity and fracture, validated by experiments on entangled fabrics and hydrogels. For elasticity, entanglements increase strength by enabling stress homogeneity in the network. For fracture, entanglements enhance toughness by mitigating stress concentration around crack tips. We discover counterintuitive physical laws governing crack-tip stretch during crack opening: stress deconcentration at small deformation, constitutive-law independence at intermediate deformation, and linear scaling at large deformation. This framework establishes fundamental principles of linking topology to mechanics of entangled networks and offers a foundational tool for designing reconfigurable materials.

cond-mat.soft

Transformer-Based Inverse Microrheology for Experimental Mechanics at Ultra-High Strain Rates

Traditional rheological tools are often limited in characterizing soft materials under ultra-high strain-rate loading conditions (> 1000 s^-1) due to constraints in spatiotemporal resolution, loading rate, and invasiveness. Recently, inertial microcavitation rheometry (IMR), which utilizes laser-induced inertial cavitation (LIC) to dynamically deform surrounding materials, has emerged as a powerful experimental mechanics technique for probing nonlinear viscoelastic properties under extreme loading conditions. However, conventional IMR relies on computationally expensive iterative inverse fitting procedures, limiting its scalability and real-time applicability. Here, we introduce a new AI-enhanced experimental mechanics framework, called Bubble Dynamics Transformer (BDT), that integrates physics-based cavitation simulations with Transformer neural network architectures to achieve rapid inverse characterization of soft material viscoelasticity from experimentally measured bubble dynamics. The proposed framework directly predicts viscoelastic material parameters from time-resolved bubble radius evolution curves without iterative optimization. The BDT is trained using synthetic datasets generated from physics-based Keller--Miksis cavitation simulations and validated using experimental laser-induced cavitation data obtained from hydrogels and viscous polymer solutions. The proposed AI-driven framework demonstrates excellent agreement with our previous IMR while substantially accelerating constitutive parameter inference. Experimental demonstrations further reveal the capability of the framework to characterize rate-dependent material behavior across a wide range of soft materials, from viscous liquids to various viscoelastic hydrogels, at ultra-high strain rates.

physics.flu-dyn

An Extreme Toughening Mechanism for Soft Materials

Soft yet tough materials are ubiquitous in nature and everyday life. The ratio between fracture toughness and intrinsic fracture energy of a soft material defines its toughness enhancement. Soft materials' toughness enhancement has been long attributed to their bulk stress-stretch hysteresis induced by dissipation mechanisms such as Mullins effect and viscoelasticity. With a combination of experiments and theory, here we show that the bulk dissipation mechanisms significantly underestimate the toughness enhancement of soft tough materials. We propose a new mechanism and scaling law to account for the extreme toughening of diverse soft materials. We show that the toughness enhancement of soft materials relies on both bulk hysteric dissipation, and near-crack dissipation due to mechanisms such as polymer-chain entanglement. Unlike the bulk hysteric dissipation, the near-crack dissipation does not necessarily induce large stress-stretch hysteresis of the bulk material. The extreme toughening mechanism can be universally applied to various soft tough materials, ranging from double-network hydrogels, interpenetrating-network hydrogels, entangled-network hydrogels and slide-ring hydrogels, to unfilled and filled rubbers.

cond-mat.soft

Photomolecular Effect Leading to Water Evaporation Exceeding Thermal Limit

We report the discovery of photomolecular effect: cleavage of water clusters off surfaces by photons. This effect is demonstrated through surprising absorption of partially wetted hydrogel in the visible spectrum where both water and hydrogel materials' absorption are negligible. Illumination of hydrogel under solar or visible-spectrum light-emitting-diode leads to evaporation rates exceeding the thermal evaporation limit, even in hydrogels without additional absorbers. Measurements of temperature and transmission spectrum of vapor above evaporating surfaces show clear signatures of water clusters. The photomolecular effect happens at liquid-vapor interface due to large electrical field gradients and quadrupole force on molecular clusters. This photomolecular evaporation process might be happening widely in nature, potentially impacting climate and plants growth, and can be exploited for clean water and drying technologies.

physics.chem-ph

Fracture and fatigue of entangled and unentangled polymer networks

Entanglement of polymer chains is ubiquitous in elastomers, gels, and biological tissues. While the effects of chain entanglement on elasticity and viscoelasticity of polymer networks have been intensively studied, it remains elusive how chain entanglement affects fracture and fatigue of polymer networks. In this paper, using polyacrylamide hydrogels as a model material, we systematically compare fracture toughness and fatigue threshold of polymer networks with various levels of chain entanglement. We find that the fracture toughness and fatigue threshold of an unentangled polymer network are almost the same, although the unentangled polymer network still contains non-ideal features including topological defects (i.e., dangling chains and cyclic loops) and structural heterogeneity (i.e., non-uniform chain lengths and non-uniform functionalities). In contrast, the fracture toughness of an entangled polymer network can be over ten times (up to 16 times) higher than its fatigue threshold, indicating substantial toughness enhancement due to chain entanglement. Different from the conventional toughness enhancement due to bulk dissipation of polymer networks, the toughness enhancement by chain entanglement requires low stress-stretch hysteresis (<10%) of the bulk entangled polymer networks. We attribute the toughness enhancement in entangled polymer networks to a new dissipation mechanism, near-crack dissipation, which is possibly induced by pull-out of chains and delocalized damage of chains around the crack tip.

cond-mat.soft

Anti-fatigue-fracture hydrogels

The emerging applications of hydrogels in devices and machines require these soft materials to maintain robustness under cyclic mechanical loads. Whereas hydrogels have been made tough to resist fracture under a single cycle of mechanical load, these toughened gels still suffer from fatigue fracture under multiple cycles of loads. The reported fatigue threshold (i.e., the minimal fracture energy at which crack propagation occurs under cyclic loads) for synthetic hydrogels is on the order of 1-100 J/m2, which is primarily associated with the energy required to fracture a single layer of polymer chains per unit area. Here, we demonstrate that the controlled introduction of crystallinity in hydrogels can significantly enhance their fatigue thresholds, since the process of fracturing crystalline domains for fatigue-crack propagation requires much higher energy than fracturing a single layer of polymer chains. The fatigue threshold of polyvinyl alcohol (PVA) with a crystallinity of 18.9 wt.% in the swollen state can exceed 1,000 J/m2. We further develop a strategy to enhance the anti-fatigue-fracture properties of PVA hydrogels, but still maintain their high water contents and low moduli by patterning highly-crystalline regions in the hydrogels. The current work not only reveals an anti-fatigue-fracture mechanism in hydrogels but also provides a practical method to design anti-fatigue-fracture hydrogels for diverse applications.

physics.app-ph

Predicting Fracture Energies and Crack-Tip Fields of Soft Tough Materials

Soft materials including elastomers and gels are pervasive in biological systems and technological applications. Whereas it is known that intrinsic fracture energies of soft materials are relatively low, how the intrinsic fracture energy cooperates with mechanical dissipation in process zone to give high fracture toughness of soft materials is not well understood. In addition, it is still challenging to predict fracture energies and crack-tip strain fields of soft tough materials. Here, we report a scaling theory that accounts for synergistic effects of intrinsic fracture energies and dissipation on the toughening of soft materials. We then develop a coupled cohesive-zone and Mullins-effect model capable of quantitatively predicting fracture energies of soft tough materials and strain fields around crack tips in soft materials under large deformation. The theory and model are quantitatively validated by experiments on fracture of soft tough materials under large deformations. We further provide a general toughening diagram that can guide the design of new soft tough materials.

cond-mat.soft