软凝聚态物质
Crystal nucleation studies using hard-sphere and Lennard-Jones models have shown that the pressure within the nucleus is lower than that in the surrounding liquid. Here, we use the mechanical route to obtain it for an ice nucleus in…
In this study, we apply, for the first time, the fully atomistic force field approach to modeling light-induced deformations of azo-polymers, thereby establishing a relationship between macroscopic parameters and the microscopic molecular…
Drawing inspiration from the concept of the "primitive path" of a linear chain in melt conditions, we introduce here a numerical protocol which allows us to detect, in an unambiguous manner, the "primitive shapes" of ring polymers in…
The stabilization of macromolecules is fundamental to developing biological formulations, such as vaccines and protein therapeutics. In this study, we employ coarse grained polymer models to investigate the impact of four sugars:…
We investigate the static and dynamic properties of dendrimers diffusing through a network of linear associative polymers using coarse-grained Brownian dynamics simulations. Both dendrimers and network chains are modelled as bead-spring…
Understanding and mitigating the failure of reinforced elastomers has been a long-standing challenge in many industrial applications. In an early attempt to shed light on the fundamental mechanisms of failure, Gent and Park presented a…
Materials, at their essence, are networks defined by homogeneity: uniform bonds, fixed thicknesses, and discrete length scales. Mechanical metamaterials, while representing structurally more diverse microstructures, remain defined by the…
Liquid-liquid phase separation of aqueous two-phase system (ATPS) is fundamental across physical and biological sciences. While well understood for passive systems, how this process is regulated by active agents such as motile bacteria…
The study of synthetic active matter systems holds the promise for designing smart materials and devices with emergent characteristics akin to those of living organisms, eventually opening the doors to the realization of artificial life.…
Impacted with sufficiently large stress, a dense, initially liquid-like suspension can be forced into a solid-like state through the process of shear jamming. While the onset of shear jamming has been investigated extensively, less is known…
Colloidal particles at fluid interfaces can enhance the stability of drops and bubbles. Yet, their effect on mass transfer in these multiphase systems remains ambiguous, with some experiments reporting strongly hindered diffusion, while…
Understanding the flow behaviors of supercooled liquids presents a major challenge in liquid-state physics due to the strong nonlinearity and rich phenomena. To unravel this complexity, we introduce the concept of local configurational…
In many biological systems localized mechanical information is transmitted by mechanically neutral chemical signals. Typical examples include contraction waves in acto-myosin cortex at cellular scale and peristaltic waves at tissue level.…
We show how dynamic heterogeneities (DH), a hallmark of glass-forming materials, depend on chain flexibility and chain length in polymers. For highly flexible polymers, a relatively large number of monomers ($N_c\sim500$) undergo correlated…
Dripping-onto-Substrate (DoS) rheometry is a well-established method for measuring the extensional rheology of low-viscosity liquids. However, clear guidelines on the capabilities and limitations of the technique are lacking. In the present…
The filtration membranes are often elaborated through a phase separation process where a polymer rich phase and a polymer poor phase spontaneously form through spinodal decomposition. One process that is still not well understood from a…
We develop and validate a simulation framework for colloidal gelation. We first reproduce the benchmark results of Santos, Campanella, and Carignano for spherical, gel-forming particles, then extend the methodology to more complex systems…
Using molecular dynamics simulations, we show that a widely-accepted theoretical prediction for glassy-polymeric strain hardening moduli ($G_R \propto \rho_e$, where $\rho_e$ is the entanglement density) fails badly for semiflexible…
We develop a variational neural-network framework to determine the most probable path (MPP) of a 3D active Brownian particle (ABP) by directly minimizing the Onsager-Machlup integral (OMI). To obtain the OMI, we use the Onsager-Machlup…
A deep learning-based computational method is proposed for soft matter dynamics -- the deep Onsager-Machlup method (DOMM). It combines the brute forces of deep neural networks (DNNs) with the fundamental physics principle -- Onsager-Machlup…