arXiv subjects

Xiaoming Mao

Publications and source records attributed to Xiaoming Mao.

At least 19 recordsLinked to original sources

arXiv2026

In situ local learning of dynamic network materials

Functional materials realize functionalities through pre-designed structures, whereas physical neural networks are trained by prescribing input-output behavior. Unifying these views would allow materials to acquire functions directly from dynamical tasks. Here we introduce an in situ local learning framework for dynamic network materials. A forward drive and a time-reversed adjoint error drive are applied to the same mechanical network, enabling the material to compute gradients of a time-domain loss through its own dynamics. The resulting update rules are local, compatible with the principle of physical learning. Each bond or node requires only co-located forward and adjoint fields. The method trains spring constants, nodal masses, bond damping coefficients and nodal damping coefficients, and programs dynamical functions including broadband wave cloaking, evanescent-wave imaging, passive transient output enhancement and vowel classification. These examples involve distinct physical mechanisms, such as wave scattering, near-field information transfer, dissipative non-normal dynamics and machine learning, but are obtained by simply changing the loss function, rather than leveraging expert knowledge. Therefore, dynamic network materials can act both as programmable matter and as physical neural networks, providing a route to material systems that learn temporal responses in situ.

cond-mat.soft↗

arXiv2025

Mechanochemical feedback drives complex inertial dynamics in active solids

Active solids combine internal active driving with elasticity to realize states with nonequilibrium mechanics and autonomous motion. They are often studied in overdamped settings, e.g., in soft materials, and the role of inertia is less explored. We construct a model of a chemically active solid that incorporates mechanochemical feedback and show that, when feedback overwhelms mechanical damping, autonomous inertial dynamics can spontaneously emerge through sustained consumption of chemical fuel. By combining numerical simulations, analysis and dynamical systems approaches, we show how active feedback drives complex nonlinear dynamics on multiple time-scales, including limit cycles and chaos. Our results suggest design principles for creating ultrafast actuators and autonomous machines from soft, chemically-powered solids.

cond-mat.soft↗

arXiv2025

Lyapunov exponents explain disorder-induced polarization and soliton teleportation in a mechanical Markov system

Using a mapping between spatial disorder and temporal stochasticity, we develop a new framework using Lyapunov exponents to explain exotic wave localization and mobility phenomena in disordered one-dimensional (1D) mechanical systems that can be constructed via a spatial analog of a Markov process, which we call ``mechanical Markov systems.'' We show that disorder induces robust polarization of zero modes (ZMs) in these mechanical Markov systems, and this phenomenon is explained using Lyapunov exponents. Remarkably, these ZMs become mobile solitons in the nonlinear regime despite the disorder-controlled localization of all other modes, and display a set of new nonlinear dynamics features including reflectionless chirality-dependent teleportation, which can also be explained using Lyapunov exponents. Our results establish the Markov formalism as a powerful tool to explain and design localization and dynamics in disordered mechanical systems, opening opportunities for programmable metamaterials with novel linear and nonlinear responses.

cond-mat.soft↗

arXiv2025

Chiral quantum magnets with optically and catalytically active spin ladders

Chiral quantum magnets with spin-states separated by a large energy gap are technologically attractive but difficult to realize. Geometrically frustrated topological states with nanoscale chirality may offer a chemical pathway to such materials. However, room temperature spin misalignment, weakness of Dzyaloshinskii-Moriya interactions, and high energy requirements for lattice distortions set high physicochemical barriers for their realization. Here, we show that layered iron oxyhydroxides (LIOX) address these challenges due to chirality transfer from surface ligands into spin-states of dimerized FeO6 octahedra with zig-zag stacking. The intercalation of chiral amino acids induces angular displacements in the antiferromagnetic spin pairs with a helical coupling of magnetic moments along the screw axis of the zig-zag chains, or helical spin-ladders. Unlike other chiral magnets, the spin states in LIOX are chemically and optically accessible, they display strong optical resonances with helicity-matching photons and enable spin-selective charge transport. The static rather than dynamic polarization of spin ladders in LIOX makes them particularly suitable for catalysis. Room-temperature spin pairing, field-tunability, environmental robustness, and synthetic simplicity make LIOX and its intercalates a uniquely practical family of quantum magnets.

cond-mat.mtrl-sci↗

arXiv2025

A unified model for linear responses of physical networks

Many physical systems--from mechanical lattices and electrical circuits to biological tissues and architected metamaterials--can be understood as networks transmitting physical quantities. We present a unified mathematical framework for describing linear responses of such physical networks using tools from algebraic graph theory. This approach captures static and dynamic behaviors across multiple domains, including mechanical, electrical, thermal, and diffusive responses using node and edge variables (e.g., potentials, flows). Our formalism connects multiscale and multi-domain responses to the underlying network structure. We demonstrate how this framework enables efficient, generalizable solutions to a wide class of linear response problems, including stress propagation, charge transport, and wave dynamics, and provide insights into network duality and entropy production.

cond-mat.soft↗

arXiv2025

Topological mechanical neural networks as classifiers through in situ backpropagation learning

Recently, a new frontier in computing has emerged with physical neural networks(PNNs) harnessing intrinsic physical processes for learning. Here, we explore topological mechanical neural networks(TMNNs) inspired by the quantum spin Hall effect(QSHE) in topological metamaterials, for machine learning classification tasks. TMNNs utilize pseudospin states and the robustness of the QSHE, making them damage-tolerant for binary classification. We first demonstrate data clustering using untrained TMNNs. Then, for specific tasks, we derive an in situ backpropagation algorithm - a two-step, local-rule method that updates TMNNs using only local information, enabling in situ physical learning. TMNNs achieve high accuracy in classifications of Iris flowers, Penguins, and Seeds while maintaining robustness against bond pruning. Furthermore, we demonstrate parallel classification via frequency-division multiplexing, assigning different tasks to distinct frequencies for enhanced efficiency. Our work introduces in situ backpropagation for wave-based mechanical neural networks and positions TMNNs as promising neuromorphic computing hardware for classification tasks.

cond-mat.dis-nn↗

arXiv2025

Pinch-point Singularities in Stress-Stress Correlations Reveal Rigidity in Colloidal Gels

We demonstrate that the spatial correlations of microscopic stresses in 2D model colloidal gels obtained in computer simulations can be quantitatively described by the predictions of a theory for emergent elasticity of pre-stressed solids (vector charge theory). By combining a rigidity analysis with the characterization provided by the stress correlations, we show that the theoretical predictions are able to distinguish rigid from floppy gels, and quantify that distinction in terms of the size of a pinch-point singularity emerging at large length scales, which, in the theory, directly derives from the constraints imposed by mechanical equilibrium on the internal forces. We also use the theoretical predictions to investigate the coupling between stress-transmission and rigidity, and we explore the possibility of a Debye-like screening mechanism that would modify the theory predictions below a characteristic length scale.

cond-mat.soft↗

arXiv2025

Observation of mechanical kink control and generation via phonons

Kinks (or domain walls) are localized transitions between distinct ground states associated with a topological invariant, and are central to many phenomena across physics, from condensed matter to cosmology. While phonon (i.e., small-amplitude vibration) wave packets have been theorized to deterministically interact with kinks and initiate their movement, this interaction has remained elusive in experiments, where only uncontrollable stochastic kink motion generated by thermal phonons or dislocation glide by low-frequency quasi-static loading have been observed. This is partly because all physical systems that support kinks are, at some level, discrete, making deterministic phonon control of kinks extremely challenging due to the existence of Peierls-Nabarro (PN) barrier. Here, we demonstrate, for the first time, experimental observation of phonon-mediated control and generation of mechanical kinks, which we enable using a topological metamaterial that constitutes an elastic realization of the Kane-Lubensky chain model. Our metamaterial overcomes the PN barrier by supporting a single, topologically protected kink that requires zero energy to form and move. Using simulations that show close agreement with our experimental observations, we also reveal unique dynamics of phonon interplay with highly discrete kinks, including long-duration motion and a continuous family of internal modes, features absent in other discrete nonlinear systems. This work introduces a new paradigm for topological kink control, with potential applications in material stiffness tuning, shape morphing, locomotion, and robust signal transmission.

nlin.PS↗

arXiv2025

Robustness of stress focusing in soft lattices under topology-switching deformation

Recent developments in topological mechanics have demonstrated the ability of Maxwell lattices to effectively focus stress along domain walls between differently polarized domains. The focusing ability can be exploited to protect the lattice bulk from accidental stress concentration -- and eventually onset and propagation of fracture -- at structural hot spots such as defects and cracks. A recent study has revisited the problem for structural lattices featuring non-ideal hinges, showing that the focusing remains robust, albeit diluted in strength. Realizing that the problem of domain wall localization has been traditionally framed in the context of linear elasticity, in this work we extend the study to the realm of soft structures undergoing nonlinear finite deformation. Through experiments performed on silicone hyperelastic prototypes, we assess and quantify the robustness of the phenomenon against the macroscopic shape changes induced by large deformation, with special attention to deformation levels that alter the topology of the bulk, lifting the topological protection. Furthermore, we identify a simple geometric indicator for this transition.

cond-mat.soft↗

arXiv2024

Novel mechanical response of parallelogram-face origami governed by topological characteristics

Origami principles are used to create strong, lightweight structures with complex mechanical response. However, identifying the fundamental physical principles that determine a sheet's behavior remains a challenge. We introduce a new analytic theory in which commonly studied origami sheets fall into distinct topological classes that predict sharply varying mechanical behavior, including effective stiffness and smoothness of mechanical response under external loads. Origami sheets with negative Poisson's ratios, such as the Miura ori, have conventional, smooth mechanical response amenable to continuum-based approaches. In contrast, positive Poisson's ratio, as in the Eggbox ori, generates a topological transition to lines of doubly degenerate zero modes that lead to dramatically softer structures with uneven, complex patterns of spatial response. These patterns interact in complicated ways with origami boundary conditions and source terms, leading to rich physical phenomena in experimentally accessible systems. This approach highlights topological mechanics, with deep connections to topologically protected quantum-mechanical systems, as a design principle for controlling the mechanical response of thin, complex sheets.

cond-mat.soft↗

arXiv2024

Statistical mechanics of frustrated assemblies and incompatible graphs

Geometrically frustrated assemblies where building blocks misfit have been shown to generate intriguing phenomena from self-limited growth, fiber formation, to structural complexity. We introduce a graph theory formulation of geometrically frustrated assemblies, capturing frustrated interactions through the concept of incompatible flows, providing a direct link between structural connectivity and frustration. This theory offers a minimal yet comprehensive framework for the fundamental statistical mechanics of frustrated assemblies. Through numerical simulations, the theory reveals new characteristics of frustrated assemblies, including two distinct percolation transitions for structure and stress, a crossover between cumulative and non-cumulative frustration controlled by disorder, and a divergent length scale in their response.

cond-mat.soft↗

arXiv2024

Universal spectral moment theorem and its applications in non-Hermitian systems

The high sensitivity of the spectrum and wavefunctions to boundary conditions, termed the non-Hermitian skin effect, represents a fundamental aspect of non-Hermitian systems. While it endows non-Hermitian systems with unprecedented physical properties, it presents notable obstacles in grasping universal properties that are robust against microscopic details and boundary conditions. In this Letter, we introduce a pivotal theorem: in the thermodynamic limit, for any non-Hermitian systems with finite-range interactions, all spectral moments are invariant quantities, independent of boundary conditions, posing strong constraints on the spectrum. Utilizing this invariance, we propose a new criterion for bulk dynamical phases based on experimentally observable features and applicable to any dimensions and any boundary conditions. Based on this criterion, we define the bulk dispersive-to-proliferative phase transition, which is distinct from the real-to-complex spectral transition and contrary to traditional expectations. We verify these findings in 1D and 2D lattice models.

cond-mat.mes-hall↗

arXiv2024

Training all-mechanical neural networks for task learning through in situ backpropagation

Recent advances unveiled physical neural networks as promising machine learning platforms, offering faster and more energy-efficient information processing. Compared with extensively-studied optical neural networks, the development of mechanical neural networks (MNNs) remains nascent and faces significant challenges, including heavy computational demands and learning with approximate gradients. Here, we introduce the mechanical analogue of in situ backpropagation to enable highly efficient training of MNNs. We demonstrate that the exact gradient can be obtained locally in MNNs, enabling learning through their immediate vicinity. With the gradient information, we showcase the successful training of MNNs for behavior learning and machine learning tasks, achieving high accuracy in regression and classification. Furthermore, we present the retrainability of MNNs involving task-switching and damage, demonstrating the resilience. Our findings, which integrate the theory for training MNNs and experimental and numerical validations, pave the way for mechanical machine learning hardware and autonomous self-learning material systems.

cs.LG↗

arXiv2024

Nanoscale Imaging of Phonons and Reconfiguration in Topologically-Engineered, Self-Assembled Nanoparticle Lattice

Topologically-engineered mechanical frames are important model constructs for architecture, machine mechanisms, and metamaterials. Despite significant advances in macroscopically fashioned frames, realization and phonon imaging of nanoframes have remained challenging. Here we extend for the first time the principles of topologically-engineered mechanical frames to lattices self-assembled from nanoparticles. Liquid-phase transmission electron microscopy images the vibrations of nanoparticles in self-assembled Maxwell and hexagonal lattices at the nanometer resolution, measuring a series of otherwise inaccessible properties such as phonon spectra and nonlinear lattice deformation paths. These properties are experimentally modulated by ionic strength, captured by our discrete mechanical model considering the complexity of nanoscale interactions and thermal fluctuations. The experiment-theory integration bridges mechanical metamaterials and colloidal self-assembly, opening new opportunities to manufacture phononic devices with solution processibility, transformability, light weight, and emergent functions, at underexplored length, frequency, and energy scales.

cond-mat.mtrl-sci↗

arXiv2024

Topological pumping in origami metamaterials

In this study, we present a mechanism of topological pumping in origami metamaterials with spatial modulation by tuning the rotation angles. Through coupling spatially modulated origami chains along an additional synthetic dimension, the pumping of waves from one topological edge state to another is achieved, where the Landau-Zener transition is demonstrated by varying the number of coupled origami chains. Besides, the inherent nonlinearity of origami metamaterials enable the excitation-dependent Landau-Zener tunneling probability. Furthermore, with the increase of nonlinearity, the topological states tend to localize in several regions in a way reminiscent of discrete breathers. Our findings pave the way towards inter-band transitions and associated topological pumping features in origami metamaterials.

physics.app-ph↗

arXiv2024

Complexity, Disorder, and Functionality of Nanoscale Materials

Nature hosts a wealth of materials showcasing intricate structures intertwining order, disorder, and hierarchy, delivering resilient multifunctionality surpassing perfect crystals or simplistic disordered materials. The engineering of such materials through nanoparticle assembly represents a burgeoning field, poised with potential to yield sustainable material systems rivaling or exceeding biological functionalities. This review delineates the fundamental concept of complexity in the context of nanoscale materials. It examines methodologies for characterizing complexity and functionality, explores pragmatic approaches to create complex nanomaterials, and offers a perspective on their potential applications, guiding the trajectory of future research endeavors.

cond-mat.soft↗

arXiv2023

Stress control in non-ideal topological Maxwell lattices via geometry

Topological mechanical metamaterials have demonstrated exotic and robust mechanical properties which led to promising engineering applications. One of such properties is the focusing of stress at the interface connecting domains of topological Maxwell lattices of opposite topological polarizations, which protects the bulk of the material against fracturing. Here we generalize this theory to non-ideal Maxwell lattices, incorporate real material features that leads to interactions beyond previous ideal models. By quantitative analysis of stress distributions of topological Maxwell lattices with self-stress interfaces theoretically and computationally, we propose a design rule that minimizes stress in the bulk of the material. This design rule can guide the realization of stress focusing and fracturing protection in real materials.

cond-mat.soft↗

arXiv2023

Mirror-symmetry protected higher-order topological zero-frequency boundary and corner modes in Maxwell lattices

Maxwell lattices, where the number of degrees of freedom equals the number of constraints, are known to host topologically-protected zero-frequency modes and states of self stress, characterized by a topological index called topological polarization. In this letter, we show that in addition to these known topological modes, with the help of a mirror symmetry, the inherent chiral symmetry of Maxwell lattices creates another topological index, the mirror-graded winding number (MGWN). This MGWN is a higher order topological index, which gives rise to topological zero modes and states of self stress at mirror-invariant domain walls and corners between two systems with different MGWNs. We further show that two systems with same topological polarization can have different MGWNs, indicating that these two topological indices are fundamentally distinct.

cond-mat.soft↗