arXiv subjects

Nicolas Moreno

Publications and source records attributed to Nicolas Moreno.

11 recordsLinked to original sources

arXiv2026

Towards the Multiscale Design of Pressure Sensitive Adhesives

Pressure-sensitive adhesives (PSAs) are soft polymeric materials that exhibit complex rheological and mechanical behavior gov- erned by the interplay between polymer architecture, crosslink density, and entanglement constraints. Predicting their rheological properties from underlying microstructure remains a central challenge in adhesive design. In this work, we adopt a multiscale com- putational framework based on the Lagrangian Heterogeneous Multiscale Method (LHMM), coupling a macroscopic continuum description with a mesoscale polymer network model featuring breakable bonds embedded in a viscous medium. The approach enables consistent information transfer across scales and captures both elastic network response and viscous dissipation. The framework is calibrated using experimental rheological data and tensile measurements for four PSA formulations with varying gel fractions and crosslink densities. The simulations reproduce key experimental trends in storage modulus (G'), loss modulus (G"), and tensile stress-strain behavior under planar extension, while differentiating the distinct mechanical signatures of each formula- tion. The results elucidate how crosslink density and effective network connectivity control stiffness, stress localization, and failure characteristics. Overall, the proposed multiscale methodology provides a predictive platform for linking microstructural design pa- rameters to macroscopic mechanical properties and offers a rational basis for the formulation and optimization of next-generation PSAs.

cond-mat.soft↗

arXiv2025

Lagrangian Heterogeneous Multiscale Method (LHMM) for Simulating Polymer Solutions/Melts Behavior under Complex Flows using DPD-SPH

We present a Lagrangian Heterogeneous Multiscale Method (LHMM) for simulating the non-Newtonian rheology of polymer melts in complex two-dimensional flows. The method couples Dissipative Particle Dynamics (DPD) at the microscale with a GENERIC-compliant Smoothed Particle Hydrodynamics (SPH) at the macroscale, in a concurrent framework, overcoming the limitations of traditional Eulerian-based methods in capturing long-memory and history-dependent effects. At the microscale, DPD serves as a virtual rheometer, employing FENE (Finitely Extensible Nonlinear Elastic) bead-spring polymer chains. This approach provides key rheological properties, including shear-thinning and zero-shear-rate viscosities, relaxation times, and viscoelastic dynamics, which are quantified via Carreau-Yasuda fitting and spectral analysis. The LHMM couples SPH-derived strain rates with microscopic stress responses using the Irving-Kirkwood formalism. This approach enables a concurrent interaction between macroscopic strain rates and microscopic stress tensors, ensuring a consistent viscoelastic response across scales. The method is validated against benchmark flows, including Reverse Poiseuille Flow and flow through a Periodic Array of Cylinders, across Weissenberg numbers $0.5 < \text{Wi} < 30$ and low Reynolds numbers ($\text{Re} < 1$). A final demonstration of flow in a 2D porous medium highlights LHMM's capability to handle highly heterogeneous geometries. The LHMM is implemented in LAMMPS, making it suitable for integrating multiple models to describe microscales. In contrast, large-scale simulations efficiently utilize GPU and CPU resources, managing multiple coupling and time-scaling levels to maintain numerical stability and accuracy. The framework offers a predictive, constitutive-free tool that links microscopic polymer dynamics to macroscopic flow behavior, making it suitable for multiscale applications.

physics.flu-dyn↗

arXiv2025

Mesoscale Simulations of Thrombin Activation and Fibrin Formation in Microvascular and In Vitro Settings

Blood coagulation is governed by tightly regulated reaction networks that unfold within a flowing, heterogeneous microvascular environment. Reduced kinetic models of the intrinsic and extrinsic pathways have seen limited in vitro validation, and their behavior within spatially resolved flow fields remains largely unexplored. Here, we embed two established reduced networks into a recently proposed mesoscale particle-based framework that resolves fluid momentum transport alongside multispecies advection-diffusion-reaction dynamics. We investigate the initiation phase of coagulation by simulating thrombin formation in microvascular geometries and in vitro assays, and we assess the framework's ability to reproduce thrombin generation curves (TGCs) under physiologically relevant conditions. We further examine how variations in fibrinogen levels - an important determinant of clot structure and a biomarker for inflammation and thrombosis - affect thrombin and fibrin formation. Overall, this study provides a unified computational approach for analysing how biochemical kinetics interact with transport processes, offering insights relevant to thrombosis modeling and blood diagnostics.

physics.flu-dyn↗

arXiv2025

Smoothed Dissipative Particle Dynamics for Mesoscale Advection-Diffusion-Reaction Problems

Smoothed dissipative particle dynamics (SDPD) is a widely used particle-based method for modelling soft matter systems at mesoscopic and macroscopic scales, offering thermodynamic consistency and direct control over the fluid's transport properties. Here, we present an SDPD model that incorporates the transport of reactants on scales smaller than the discretising particles, including the evolution of compositional fields. The proposed methodology is well-suited for modelling complex systems governed by advection-diffusion-reaction (ADR) dynamics. Implemented in LAMMPS, the model is validated using a range of benchmark problems spanning diffusion-dominated, reaction-dominated, and coupled ADR regimes. Our simulation results demonstrate that the implemented SDPD model effectively captures complex behaviours, such as Turing pattern formation. The proposed model holds promise for applications across various fields, including biology, chemistry, materials science, and environmental engineering.

physics.flu-dyn↗

arXiv2025

Computational Modelling of Thixotropic Multiphase Fluids

Multiphase systems are ubiquitous in engineering, biology, and materials science, where understanding their complex interactions and rheological behavior is crucial for advancing applications ranging from emulsion stability to cellular phase separation. This study presents a numerical methodology for modeling thixotropic multiphase fluids, emphasizing the transient behavior of viscosity and the intricate interactions between phases. The model incorporates phase-dependent viscosities, interfacial tension effects, and the dynamics of phase separation, coalescence, and break-up, making it suitable for simulating systems with complex flow regimes. A key feature of the methodology is its ability to capture thixotropic behavior, where viscosity evolves over time due to microstructural changes induced by shear history. This approach enables the simulation of aging and recovery processes in materials such as gels, emulsions, and biological tissues. The model is rigorously validated against benchmark cases, demonstrating its accuracy in predicting multiphase systems under static and dynamic conditions. Subsequently, the methodology is applied to investigate systems with varying levels of microstructural evolution, revealing the impact of thixotropic dynamics on overall system behavior. The results provide new insights into the time-dependent rheology of multiphase fluids and highlight the versatility of the model for applications in industrial and biological systems involving complex fluid interactions.

physics.flu-dyn↗

arXiv2025

Simulating non-Brownian suspensions with non-homogeneous Navier slip boundary conditions

Fluid-structure interactions are commonly modeled using no-slip boundary conditions. However, small deviations from these conditions can significantly alter the dynamics of suspensions and particles, especially at the micro and nano scales. This work presents a robust implicit solvent method for simulating non-colloidal suspensions with non-homogeneous Navier slip boundary conditions. Our approach is based on a regularized boundary integral formulation, enabling accurate and efficient computation of hydrodynamic interactions. This makes the method well-suited for large-scale simulations. We validate the method by comparing computed drag forces on homogeneous and Janus particles with analytical results. Additionally, we consider the effective viscosity of suspensions with varying slip lengths, benchmarking against available analytical no-slip and partial-slip theories.

cond-mat.soft↗

arXiv2024

Sedimentation dynamics of triply-twisted M\"obius bands: Geometry versus topology

Chiral objects have intrigued scientists across several disciplines, including mathematics, crystallography, chemistry, and biology. A M\"obius band, an emblematic chiral structure, can be made by connecting the ends of a strip after applying an odd number of twists. Traditionally, the direction of the twist governs its rotational behaviour during sedimentation in a fluid. Here, we present experimental and computational investigations of triply-twisted M\"obius bands boasting threefold rotational symmetry that challenge this prevailing understanding. We explore three types of bands with different curvatures, each defined by its construction method. Experimental observations reveal that all three types of bands align axially and exhibit rotational motion during sedimentation. Surprisingly, for only one type of band the spinning direction (chiral hydrodynamic response) departs from expectations; it is not solely determined by the twist direction but changes with the aspect ratio of the band. Numerical simulations corroborate this observation, and an in-depth analysis of the resistance tensors of each type of band sheds light on the possible causes of this transition. We propose that modifications in fluid-induced drag, combined with inertial effects, underpin this phenomenon. Our study challenges existing knowledge of chiral object hydrodynamics, enriching our understanding of complex fluid dynamics. Moreover, it offers transformative potential across diverse fields, promising advancements in mixing, separation processes, and innovative passive swimmers.

physics.flu-dyn↗

arXiv2023

Morphological transitions of block copolymer micelles: implications for isoporous membrane ordering

Isoporous membranes made from diblock copolymers have numerous applications, including water treatment and protein separation, and are successfully produced at a laboratory scale under controlled conditions. However, achieving optimal conditions for membrane preparation remains a challenge due to the complexity of the involved phenomena. Experimental studies have shown that the self-assembly of block copolymers in solution significantly affects the final membrane structure. Despite extensive research, understanding the multiscale phenomena leading to the characteristic morphology is still elusive. We address this gap by using mesoscale computational simulations to investigate the self-assembly of block copolymers in selective solvents, consistent with isoporous membrane preparation. We focus on the interplay between entropic and enthalpic interactions and their effects on the morphology of the micellar aggregates in solution. Our computational results are consistent with experimental evidence, revealing a morphological transition of the aggregates as the polymer concentration and solvent affinity change. We propose different phase parameters to characterize the emergence of monodisperse-spherical micelles in solution and describe the order of crew-cut micelles using a rigid-sphere approximation. Our study provides valuable insights into the self-assembly of diblock copolymers to optimize the preparation of isoporous membranes.

cond-mat.soft↗

arXiv2022

Computational modelling of passive transport of functionalized nanoparticles

Functionalized nanoparticles (NPs) are complex objects present in a variety of systems ranging from synthetic grafted nanoparticles to viruses. The morphology and number of the decorating groups can vary widely between systems. Thus, the modelling of functionalized NPs typically considers simplified spherical objects as a first-order approximation. At the nanoscale label, complex hydrodynamic interactions are expected to emerge as the morphological features of the particles change, and they can be further amplified when the NPs are confined or near walls. Direct estimation of these variations can be inferred via diffusion coefficients of the NPs. However, the evaluation of the coefficients requires an improved representation of the NPs morphology to reproduce important features hidden by simplified spherical models. Here, we characterize the passive transport of free and confined functionalized nanoparticles using the Rigid Multi-Blob (RMB) method. The main advantage of RMB is its versatility to approximate the mobility of complex structures at the nanoscale with significant accuracy and reduced computational cost. In particular, we investigate the effect of functional groups distribution, size and morphology over nanoparticle translational and rotational diffusion. We identify that the presence of functional groups significantly affects the rotational diffusion of the nanoparticles, moreover, the morphology of the groups and number induce characteristic mobility reduction compared to non-functionalized nanoparticles. Confined NPs also evidenced important alterations in their diffusivity, with distinctive signatures in the off-diagonal contributions of the rotational diffusion. These results can be exploited in various applications, including biomedical, polymer nanocomposite fabrication, drug delivery, and imaging

cond-mat.mes-hall↗

arXiv2022

Generalized Lagrangian Heterogenous Multiscale Modeling of Complex Fluids

We introduce a full-Lagrangian heterogeneous multiscale method (LHMM) to model complex fluids with microscopic features that can extend over large spatio-temporal scales, such as polymeric solutions and multiphasic systems. The proposed approach discretizes the fluctuating Navier-Stokes equations in a particle-based setting using Smoothed Dissipative Particle Dynamics (SDPD). This multiscale method uses microscopic information derived on-the-fly to provide the stress tensor of the momentum balance in a macroscale problem, therefore bypassing the need for approximate constitutive relations for the stress. We exploit the intrinsic multiscale features of SDPD to account for thermal fluctuations as the characteristic size of the discretizing particles decrease. We validate the LHMM using different flow configurations (reverse Poiseuille flow, flow passing a cylinder array, and flow around a square cavity) and fluid (Newtonian and non-Newtonian). We showed the framework's flexibility to model complex fluids at the microscale using multiphase and polymeric systems. We showed that stresses are adequately captured and passed from micro to macro scales, leading to richer fluid response at the continuum. In general, the proposed methodology provides a natural link between variations at a macroscale, whereas accounting for memory effects of microscales.

physics.flu-dyn↗

arXiv2014

Geometrically-Consistent Model Reduction of Polymer Chains in Solution. Application to Dissipative Particle Dynamics: Model Description

We introduce a framework for model reduction of chain models for dissipative particle dynamics (DPD) simulations, where the characteristic size of the chain, pressure, density, and temperature are preserved. The proposed methodology reduces the number of degrees of freedom required to represent a particular system with complex molecules (e.g., linear polymers). Based on geometrical considerations we map fine-grained models to a reference state through a consistent scaling of the system, where short length and fast time scales are disregarded while the properties governing the phase equilibria are preserved. Following this coarse graining process we consistently represent high molecular weight DPD chains (i.e., >200 beads per chain) with a significant reduction in the number of particles required (i.e., > 20 times the original system).

cond-mat.soft↗