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Mengjie Zu

Publications and source records attributed to Mengjie Zu.

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Unravelling the multiscale surface mechanics of soft solids

Soft solids and their surface deformations control the response of many natural and artificial systems. Yet, their underlying properties are vigorously debated, particularly for polymer networks. While molecular-scale theories predict no interfacial changes with macroscopic deformation, multiple experiments suggest otherwise. To settle this issue, we measure displacement fields near the interface of a silicone gel, in the limit of small deformations. We discover an unexpected multiscale response. The shear modulus decreases smoothly by half with 20 microns of the interface. At the same time we observe a surface excess elasticity, that depends on history and outer medium composition. These results reveal the fundamentally multiscale nature of polymeric surfaces, and call for further experimental and theoretical investigations into the basic understanding of soft solid interfaces

cond-mat.soft

Learning by training: emergent return-point memory from cyclically tuning disordered sphere packings

Many living and artificial systems improve their fitness or performance by adapting to changing environments or diverse training data. However, it remains unclear how such environmental variation influences adaptation, what is learned in the process, and whether memory of past conditions is retained. In this work, we investigate these questions using athermal disordered systems that are subject to cyclic inverse design, enabling them to attain target elastic properties spanning a chosen range. We demonstrate that such systems evolve toward a marginally absorbing manifold (MAM), which encodes memory of the training range that closely resembles return-point memory observed in cyclically driven systems. We further propose a general mechanism for the formation of MAMs and the corresponding memory that is based on gradient discontinuities in the trained quantities. Our model provides a simple and broadly applicable physical framework for understanding how adaptive systems learn under environmental change and how they retain memory of past experiences.

physics.comp-ph

Intelligent Soft Matter: Towards Embodied Intelligence

Intelligent soft matter stands at the intersection of materials science, physics, and cognitive science, promising to change how we design and interact with materials. This transformative field seeks to create materials that possess life-like capabilities, such as perception, learning, memory, and adaptive behavior. Unlike traditional materials, which typically perform static or predefined functions, intelligent soft matter dynamically interacts with its environment. It integrates multiple sensory inputs, retains experiences, and makes decisions to optimize its responses. Inspired by biological systems, these materials intend to leverage the inherent properties of soft matter: flexibility, self-evolving, and responsiveness to perform functions that mimic cognitive processes. By synthesizing current research trends and projecting their evolution, we present a forward-looking perspective on how intelligent soft matter could be constructed, with the aim of inspiring innovations in fields such as biomedical devices, adaptive robotics, and beyond. We highlight new pathways for integrating design of sensing, memory and action with internal low-power operations and discuss challenges for practical implementation of materials with "intelligent behavior". These approaches outline a path towards to more robust, versatile and scalable materials that can potentially act, compute, and "think" by their inherent intrinsic material behaviour beyond traditional smart technologies relying on external control.

cond-mat.soft

Fully independent response in disordered solids

Unlike in crystals, it is difficult to trace emergent material properties of amorphous solids to their underlying structure. Nevertheless, one can tune features of a disordered spring network, ranging from bulk elastic constants to specific allosteric responses, through highly precise alterations of the structure. This has been understood through the notion of independent bond-level response -- the observation that in many cases, different springs have different effects on different properties. While this idea has motivated inverse design in numerous contexts, it has not been formalized and quantified in a general context that not just informs but enables and predicts inverse design. Here, we show how to quantify independent response by linearizing the simultaneous change in multiple emergent features, and introduce the much stronger notion of fully independent response. Remarkably, we find that the mechanical properties of disordered solids are always fully independent across a wide array of scenarios, regardless of the target features, tunable parameters, and details of particle-particle interactions. Furthermore, our formulation quantifies the susceptibility of feature changes to parameter changes, which we find to be correlated with the maximum linear tunability. These results formalize our understanding of a key fundamental difference between ordered and disordered solids while also creating a practical tool to both understand and perform inverse design.

physics.comp-ph

Designing athermal disordered solids with automatic differentiation

The ability to control forces between sub-micron-scale building blocks offers considerable potential for designing new materials through self-assembly. A typical paradigm is to first identify a particular (crystal) structure that has some desired property, and then design building-block interactions so that this structure assembles spontaneously. While significant theoretical and experimental progress has been made in assembling complicated structures in a variety of systems, this two-step paradigm fundamentally fails for structurally disordered solids, which lack a well-defined structure to use as a target. Here we show that disordered solids can still be treated from an inverse self-assembly perspective by targeting material properties directly. Using the Poisson's ratio, $ν$, as a primary example, we show how differentiable programming connects experimentally relevant interaction parameters with emergent behavior, allowing us to iteratively "train" the system until we find the set of interactions that leads to the Poisson's ratio we desire. Beyond the Poisson's ratio, we also tune the pressure and a measure of local 8-fold structural order, as well as multiple properties simultaneously, demonstrating the potential for nontrivial design in disordered solids. This approach is highly robust, transferable, and scalable, can handle a wide variety of model systems, properties of interest, and preparation dynamics, and can optimize over 100s or even 1000s of parameters. This result connects the fields of disordered solids and inverse self-assembly, indicating that many of the tools and ideas that have been developed to understand the assembly of crystals can also be used to control the properties of disordered solids.

cond-mat.soft

Information density, structure and entropy in equilibrium and non-equilibrium systems

During a spontaneous change, a macroscopic physical system will evolve towards a macro-state with more realizations. This observation is at the basis of the Statistical Mechanical version of the Second Law of Thermodynamics, and it provides an interpretation of entropy in terms of probabilities. However, we cannot rely on the statistical-mechanical expressions for entropy in systems that are far from equilibrium. In this paper, we compare various extensions of the definition of entropy, which have been proposed for non-equilibrium systems. It has recently been proposed that measures of information density may serve to quantify entropy in both equilibrium and nonequilibrium systems. We propose a new "bit-wise" method to measure the information density for off lattice systems. This method does not rely on coarse-graining of the particle coordinates. We then compare different estimates of the system entropy, based on information density and on the structural properties of the system, and check if the various entropies are mutually consistent and, importantly, whether they can detect non-trivial ordering phenomena. We find that, except for simple (one-dimensional) cases, the different methods yield answers that are at best qualitatively similar, and often not even that, although in several cases, different entropy estimates do detect ordering phenomena qualitatively. Our entropy estimates based on bit-wise data compression contain no adjustable scaling factor, and show large quantitative differences with the thermodynamic entropy obtained from equilibrium simulations. Hence, our results suggest that, at present, there is not yet a single, structure-based entropy definition that has general validity for equilibrium and non equilibrium systems.

cond-mat.stat-mech

Self-assembling two-dimensional quasicrystals in simple systems of monodisperse soft-core disks

In previous approaches to form quasicrystals, multiple competing length scales involved in particle size, shape or interaction potential are believed to be necessary. It is unexpected that quasicrystals can be self-assembled by monodisperse, isotropic particles interacting via a simple potential without multiple length scales. Here we report the surprising finding of the self-assembly of such quasicrystals in two dimensional systems of soft-core disks interacting via repulsions. We find not only dodecagonal but also octagonal quasicrystals, which have not been found yet in soft quasicrystals. In the self-assembly of such unexpected quasicrystals, particles tend to form pentagons, which are essential elements to form the quasicrystalline order. Our findings pave an unexpected and simple way to form quasicrystals and pose a new challenge for theoretical understanding of quasicrystals.

cond-mat.soft

Role of disorder in determining the vibrational properties of mass-spring networks

By introducing four fundamental types of disorders into a two-dimensional triangular lattice separately, we determine the role of each type of disorder in the vibration of the resulting mass-spring networks. We are concerned mainly with the origin of the boson peak and the connection between the boson peak and the transverse Ioffe-Regel limit. For all types of disorders, we observe the emergence of the boson peak and Ioffe-Regel limits. With increasing disorder, the boson peak frequency $ω_{BP}$, transverse Ioffe-Regel frequency $ω_{IR}^T$, and longitudinal Ioffe-Regel frequency $ω_{IR}^L$ all decrease. We find that there are two ways for the boson peak to form: developing from and coexisting with (but remaining independent of) the transverse van Hove singularity without and with local coordination number fluctuation. In the presence of a single type of disorder, $ω_{IR}^T\ge ω_{BP}$, and $ω_{IR}^T\approx ω_{BP}$ only when the disorder is sufficiently strong and causes spatial fluctuation of the local coordination number. Moreover, if there is no positional disorder, $ω_{IR}^T\approx ω_{IR}^L$. Therefore, the argument that the boson peak is equivalent to the transverse Ioffe-Regel limit is not general. Our results suggest that both local coordination number and positional disorder are necessary for the argument to hold, which is actually the case for most disordered solids such as marginally jammed solids and structural glasses. We further combine two types of disorders to cause disorder in both the local coordination number and lattice site position. The density of vibrational states of the resulting networks resembles that of marginally jammed solids well. However, the relation between the boson peak and the transverse Ioffe-Regel limit is still indefinite and condition-dependent.

cond-mat.soft

Density affects the nature of the hexatic-liquid transition in two-dimensional melting of core-softened systems

We find that both continuous and discontinuous hexatic-liquid transitions can happen in the melting of two-dimensional solids of soft-core disks. For three typical model systems, Hertzian, harmonic, and Gaussian-core models, we observe the same scenarios. These systems exhibit reentrant crystallization (melting) with a maximum melting temperature $T_m$ happening at a crossover density $ρ_m$. The hexatic-liquid transition at a density smaller than $ρ_m$ is discontinuous. Liquid and hexatic phases coexist in a density interval, which becomes narrower with increasing temperature and tends to vanish approximately at $T_m$. Above $ρ_m$, the transition is continuous, in agreement with the Kosterlitz-Thouless-Halperin-Nelson-Young theory. For these soft-core systems, the nature of the hexatic-liquid transition depends on density (pressure), with the melting at $ρ_m$ being a plausible transition point from discontinuous to continuous hexatic-liquid transition.

cond-mat.soft