arXiv subjects

Xinzhi Li

Publications and source records attributed to Xinzhi Li.

4 recordsLinked to original sources

arXiv2026

Tunable Hyperuniformity and Hidden Information in Random Cellular Structures

Hyperuniform systems possess the isotropic microstructure of liquids while suppressing large-scale density fluctuations with crystal-like precision, endowing them with exotic optical and transport properties. However, generating these states typically relies on top-down algorithmic optimizations that lack physical realism, leaving the fundamental mechanical and thermodynamic limits of such disordered order largely unexplored. Here, we utilize a mechanical vertex model to explore physical conditions that drive self-organized hyperuniformity in this model. By tuning cortical elasticity and interfacial tension, we engineer a continuous spectrum of effectively hyperuniform states. Crucially, hyperuniformity and rigidity are independently tunable in this system: hyperuniform states occur on both sides of the solid--fluid transition, and the degree of hyperuniformity is set by cell mechanics rather than by the onset of rigidity. Building on these states, we introduce the Hyperuniform Poisson Ensemble (HyPE), constructed by overlaying independent hyperuniform subsets. HyPE states preserve long-range hidden order while asymptotically approaching Poissonian randomness at short length scales, establishing universal scaling relations for density fluctuations. As the most disordered hyperuniform systems reported, HyPEs exhibit vanishing configurational entropy, establishing a fundamental thermodynamic lower bound for the information content of hyperuniform matter. By bridging cellular mechanics with the statistical physics of hidden information, this framework provides a universal blueprint for designing multifunctional metamaterials, with direct applications in photonic bandgap engineering, phononic control, and stress-responsive composites.

cond-mat.dis-nn↗

arXiv2023

Network physics of attractive colloidal gels: Resilience, Rigidity, and Phase Diagram

Attractive colloidal gels exhibit solid-like behavior at vanishingly small fractions of solids, owing to ramified space-spanning networks that form due to particle-particle interactions. These networks give the gel its rigidity, and as the attraction between the particles grows, so does the elasticity of the colloidal network formed. The emergence of this rigidity can be described through a mean field approach; nonetheless, fundamental understanding of how rigidity varies in gels of different attraction strengths is lacking. Moreover, recovering an accurate gelation phase diagram based on the system's variables have been an extremely challenging task. Understanding the nature of these fractal clusters, and how rigidity emerges from their connections is key to controlling and designing gels with desirable properties. Here, we employ well-established concepts of network science to interrogate and characterize the network of colloidal gels. We construct a particle-level network, having all the spatial coordinates of colloids with different attraction levels, and also identify polydisperse rigid fractal clusters using a Gaussian Mixture Model, to form a coarse-grained cluster network that distinctly shows main physical features of the colloidal gels. A simple mass-spring model then is used to recover quantitatively the elasticity of colloidal gels from these cluster networks. Interrogating the resilience of these gel networks show that the elasticity of a gel (a dynamic property) is directly correlated to its cluster network's resilience (a static measure). Finally, we use the resilience investigations to devise [and experimentally validate] a fully resolved phase diagram for colloidal gelation, with a clear solid-liquid phase boundary using a single volume fraction of particles well beyond this phase boundary.

cond-mat.soft↗

arXiv2019

Mechanical heterogeneity in tissues promotes rigidity and controls cellular invasion

We study the influence of cell-level mechanical heterogeneity in epithelial tissues using a vertex-based model. Heterogeneity in single cell stiffness is introduced as a quenched random variable in the preferred shape index($p_0$) for each cell. We uncovered a crossover scaling for the tissue shear modulus, suggesting that tissue collective rigidity is controlled by a single parameter $f_r$, which accounts for the fraction of rigid cells. Interestingly, the rigidity onset occurs at $f_r=0.21$, far below the contact percolation threshold of rigid cells. Due to the separation of rigidity and contact percolations, heterogeneity can enhance tissue rigidity and gives rise to an intermediate solid state. The influence of heterogeneity on tumor invasion dynamics is also investigated. There is an overall impedance of invasion as the tissue becomes more rigid. Invasion can also occur in the intermediate heterogeneous solid state and is characterized by significant spatial-temporal intermittency.

physics.bio-ph↗

arXiv2018

A biological tissue-inspired tunable photonic fluid

Inspired by how cells pack in dense biological tissues, we design 2D and 3D amorphous materials which possess a complete photonic band gap. A physical parameter based on how cells adhere with one another and regulate their shapes can continuously tune the photonic band gap size as well as the bulk mechanical properties of the material. The material can be tuned to go through a solid-fluid phase transition characterized by a vanishing shear modulus. Remarkably, the photonic band gap persists in the fluid phase, giving rise to a photonic fluid that is robust to flow and rearrangements. Experimentally this design should lead to the engineering of self-assembled non-rigid photonic structures with photonic band gaps that can be controlled in real time via mechanical and thermal tuning.

cond-mat.soft↗