arXiv subjects

Ludovico Cademartiri

Publications and source records attributed to Ludovico Cademartiri.

6 recordsLinked to original sources

arXiv2026

A Scaling Framework for Mechanical Memristance: Dimensionless Metrics and Material Design Maps

Mechanical memristors are systems whose dissipative response depends on the history of previous loading through an evolving internal state. History-dependent forces and dissipation occur in a wide range of materials and devices, including viscoelastic polymers, shape-memory materials, piezoelectrics, granular media and field-responsive fluids. Determining which of these responses admits a mechanical-memristor representation requires a constitutive test, as well as a comparison of scales. In this work, a fractional-order mechanical memristor model is developed and cast into a nondimensional form to identify the governing parameters controlling memory-dependent dissipation. The formulation leads to a set of dimensionless groups that characterise dissipation magnitude, memory-state scale and memory transfer. These quantities are combined into an effective mechanical memristance screening index $\Mh = βγ|\mathcal H_α(Ω)|$, which provides a conditional measure of local damping modulation at matched response amplitude, constitutive slope and reference scales. Illustrative parameter scenarios are then constructed for material classes including shape-memory polymers, shape-memory alloys, hydrogels, nanocellulose, lignin-rich materials, natural fibres, piezoelectric polymers, piezoelectric ceramics, electrorheological fluids, magnetorheological fluids and granular dampers. The framework establishes a common basis for comparing memory-dependent damping within the adopted constitutive description and identifies the calibration required for its application to candidate materials and devices

physics.app-ph↗

arXiv2026

Is gelation a singularity or a flow induced instability?

Gelation in the Smoluchowski coagulation equation is commonly interpreted as a finite-time singularity marked by mass loss or moment divergence. We instead characterize gelation as a loss of dynamical stability of the Smoluchowski flow, quantified through the time-dependent spectrum of the Jacobian along the evolving aggregation dynamics. Studying homogeneous kernels $K(i,j)=(ij)^α$ together with the classical Smoluchowski, we show that gelation is consistently preceded by the appearance of positive real eigenvalues, indicating a loss of local dynamical stability. While non-gelling kernels exhibit only transient finite-size effects, gelling kernels display persistent spectral destabilization associated with macroscopic gel formation. Our results identify gelation as a genuine dynamical instability of the Smoluchowski flow.

cond-mat.soft↗

arXiv2025

Pseudoperiodic Spherical Boundary Conditions: Efficient And Isotropic 3D Particle Simulations Without Lattice Artifacts

Periodic Boundary Conditions (PBC) introduce well-known lattice artifacts. We present a novel Pseudoperiodic Spherical Boundary Condition (SBC) that is perfectly isotropic. Through detailed comparative simulations, we demonstrate that SBC eliminates the structural and dynamic anisotropy inherent to PBC. For the crowded systems where these artifacts are most prominent, our method is also computationally more efficient than standard Minimum Image Convention implementations. This establishes SBC as a powerful, high-fidelity alternative for simulating isotropic matter.

cond-mat.soft↗

arXiv2024

Modeling Brownian Motion as a Timelapse of the Physical, Persistent, Trajectory

While it is very common to model diffusion as a random walk by assuming memorylessness of the trajectory and diffusive step lengths, these assumptions can lead to significant errors. This paper describes the extent to which a physical trajectory of a Brownian particle can be described by a random flight. Analysis of simple timelapses of physical trajectories (calculated over collisional timescales using a velocity autocorrelation function that captures the hydrodynamic and acoustic effects induced by the solvent) gave us two observations: (i) subsampled trajectories become genuinely memoryless only when the time step is ~200 times larger than the relaxation time, and (ii) the distribution of the step lengths has variances that remain significantly smaller than 2Dt (usually by a factor of ~2). This last fact is due to the combination of two effects: diffusional MSD is mathematically superballistic at short timescales and subsampled trajectories are moving averages of the underlying physical trajectory. In other words, the MSD of the physical trajectory at long time intervals asymptotically approaches 2Dt, but the MSD of the subsampled steps does not, even when the associated time interval is several hundred times larger than the relaxation time. I discuss how to best account for this effect in computational approaches.

cond-mat.stat-mech↗

arXiv2024

On The Effect Of Size On The Kinetics Of Reactions In Solutions

Reactions in solution require "contact" between the reagents. We can predict the rate at which reagents come into "contact" (at least in dilute conditions), but if the initial collision does not lead to reaction, what happens then? The collision rates in solution-phase reactions are generally described (explicitly or implicitly) with the Smoluchowski equation. Unfortunately, that model describes coagulations in gases, not reactions in solutions. The model is memory-less, i.e., collisions are treated as random processes, unaware of each other in space and time. The reality is that unreactive collisions create memory: particles (even molecules) "remember" they just collided, i.e, the probability of collision depends on how far back in time their prior collision happened. As we show here, this purely geometric and statistical fact is valid as long as their size is larger than the Kuhn length of their Brownian motion in solution. Under these conditions, particles in solution form, even in the absence of attractive interactions, relatively long-lived "clusters" kept together by the statistical unlikeliness of separating. We show here through Brownian dynamics simulations that, as a result of this memory, the collision rates and the lifetimes of these clusters, differently from what predicted by Smoluchowski's model, are proportional to the ratio between the radius of the colliders and the Kuhn length of their path in solution, with a coefficient close to unity!

physics.chem-ph↗

arXiv2020

Liquid-like growth of colloidal nanocrystals of coalescence

Our understanding of the growth of crystals is dominated by the classical description according to which individual atoms or molecules, driven by supersaturation, add to crystal facets. As a result, the growth of hard matter is still mostly considered to be fundamentally incomparable to the growth of soft matter, like polymers or liquids. By a combination of experiment and modeling we here show how amine-capped PbS colloidal nanoparticles grow in the absence of supersaturation by coalescence, like droplets in an emulsion. Specifically, we (i) determine that the rates of crystal-crystal coalescence are remarkably high (10^-2 to 10^1 M^-1*s^-1) in spite of the steric stabilization of the particles, and are comparable to those of bimolecular reactions, (thereby providing a new avenue for the development of a form of chemistry where the reactants are colloids rather than molecules), (ii) elucidate the rate limiting steps of crystal-crystal coalescence leading us to propose design rules to control it, and (iii) demonstrate a simple, two-parameter model that predicts quantitatively this process and its dependence on the ligands. Lastly, we use Brownian dynamics simulations to show how crowding effects and the relatively large size of the particles compared to their mean free path explain these remarkably large rates of coalescence and, at the same time, the puzzlingly low values of activation energy previously reported for oriented attachment processes.

physics.chem-ph↗