arXiv subjects

Alfredo Alexander-Katz

Publications and source records attributed to Alfredo Alexander-Katz.

At least 19 recordsLinked to original sources

arXiv2026

LCST and Closed-Loop Phase Behavior in Non-Associating Fully Symmetric Multicomponent Polymer Systems

Multicomponent liquids can phase separate upon heating, exhibiting a lower critical solution temperature (LCST). Moreover, a narrow class of materials can undergo disordering transition upon further heating, yielding closed-loop phase diagrams. Previously, it was shown that LCST or closed-loop phase behavior can appear in the models of liquids in which components are asymmetric or interaction potentials have a specifically designed attraction. Here, we show theoretically that LCST and closed-loop phase behavior can occur in a significantly wider set of models. In particular, we found that these phenomena can be exhibited by the simplest and widely used coarse-grained (CG) models of any multicomponent liquid in which species are fully symmetric and where all particles interact via an arbitrary repulsive potential. In addition, we discovered that LCST and closed-loop phase behavior in these models emerges merely due to the basic property of CG liquid models, namely, the appearance of strong monomer-monomer positional correlations at low monomer number density $ρ$. We simulated the models of fully symmetric binary blends and diblock copolymer melts where nonbonded monomers interacted via a generic T-independent purely repulsive harmonic potential. As predicted, LCST and closed-loop phase behavior emerged at $ρ$ sufficiently low to cause strong monomer-monomer correlations leading to a strong T-dependence of the effective coordination number, which, in turn, induced a nonmonotonic T-dependence of the Flory-Huggins parameter. To summarize, we discovered that the simplest fully symmetric non-associating CG models of multicomponent liquids can exhibit complex temperature response due to a mechanism stemming from the basic nature of any CG liquid model. This mechanism might contribute to the emergence of LCST and closed-loop phase behavior in many existing polymer materials.

cond-mat.soft↗

arXiv2026

Programmable transport of rotating particles in obstacle arrays

Rotating colloids, or spinners, in obstacle arrays exhibit frequency-set stationary orbits and currents set by the competition between an inertial, Magnus-like lift and short-range attraction. Fully resolved lattice-Boltzmann simulations reveal the hydrodynamic coupling and identify the lift mechanism, while a symmetry-based Langevin model captures the resulting balance. In periodic lattices, the superposition of scalar and vector potentials produces two robust orbital regimes: corner states, in which spinners orbit individual posts, and inner states, in which orbits couple across four neighboring obstacles. Slow frequency modulation toggles these states and produces directed, stepwise transport across the grid. This establishes a minimal hydrodynamic mechanism, controlled by a single driving parameter, for programmable guidance of active rotors in structured environments.

cond-mat.soft↗

arXiv2026

Surface-Adsorbed Nanodroplets of Symmetric Diblock Copolymers Form Versatile and Stimuli-Responsive Nanostructures

Block copolymers often create droplets when placed on a substrate. Such nanostructured droplets can be arranged into regular microstructured arrays, thereby forming hierarchically organized materials that can be used in microelectronics, plasmonics, sensing, photonics, metamaterials production, and even cryptography. However, it is unclear if such materials can be stimuli-responsive, i.e., be able to change their nanostructure on a single droplet level upon applying external stimuli. In this work, we discovered that small (10-100 nm) surface-adsorbed droplets of symmetric diblock copolymers can form a multitude of different externally switchable nanostructures. We obtained a near-equilibrium, comprehensive 4D diagram of droplet morphologies by performing large-scale self-consistent field theory (SCFT) calculations under various wetting and phase separation conditions. The SCFT modeling was augmented with a computational algorithm that established an equilibrium droplet morphology in a given system without assuming potentially equilibrium structures prior to simulation. The discovered droplet nanostructures agreed excellently with previously published experimental data. Crucially, we showed that direct and reversible transitions between different droplet morphologies are possible upon changing the interaction strength between components, which can be tuned externally in experiments by adding surfactants or controlling temperature. We confirmed experimental realizability of such stimuli-responsiveness by modeling surfactant addition that led to a switch between droplet nanostructures. This work demonstrates that even the simplest symmetric diblock copolymers are able to produce versatile and stimuli-responsive structures on a surface when confined to a small nanodroplet. This opens the possibility to produce smart coatings with externally switchable hierarchical micro- and nanostructures.

cond-mat.soft↗

arXiv2026

Rapid Neural Network Prediction of Linear Block Copolymer Free Energies

Free energies are fundamental quantities governing phase behavior and thermodynamic stability in polymer systems, yet their accurate computation often requires extensive simulations and post-processing techniques such as the Bennett Acceptance Ratio (BAR). While BAR provides reliable estimates when applied between closely related thermodynamic states, evaluating free energies across large changes in interaction strength typically requires a sequence of intermediate simulations to maintain sufficient phase-space overlap, substantially increasing computational cost. In this work we develop a machine learning framework for rapidly predicting excess free energies of linear diblock copolymer systems from simulation-derived energetic descriptors. Using dissipative particle dynamics simulations of freely-jointed chain polymers, we construct a dataset of per-chain energetic statistics, including heterogeneous interaction energies, homogeneous interaction energies, and bonded spring energies, and train feed-forward neural networks to learn the relationship between these descriptors and free energies computed using a stratified BAR procedure. The resulting models accurately reproduce the reference free energies across a range of chain lengths, compositions, and densities, including polymer architectures held out from training. In regimes where direct, brute-force BAR estimates become unreliable due to poor phase-space overlap, the neural network predictions remain consistent with the reference values. These results demonstrate that physically informed machine learning models can serve as efficient surrogates for expensive free-energy calculations and provide a promising approach for accelerating thermodynamic analysis of polymer systems.

cond-mat.soft↗

arXiv2026

SAFT-P: A plaquette level perturbation for self-assembly in patchy colloids

We introduce SAFT-P, a plaquette-level extension of Statistical Associating Fluid Theory for patchy particles. By treating local clusters as associating superparticles and contracting their free energy back to monomer densities, SAFT-P retains information about patch topology that is lost in conventional SAFT. Grand-canonical Monte Carlo simulations of binary and ternary mixtures show that SAFT-P captures topology-dependent critical points and coexistence curves and discriminates between particles with identical valence but different patch layouts. Beyond topology, incorporating plaquette-scale correlations also improves predictions in regimes where patch specific interactions are absent. Results indicate that resolving correlations at the plaquette scale provides an analytical route to model complex condensates and self-assembly with topology-sensitive local structure.

cond-mat.soft↗

arXiv2025

Rolling, sliding and trapping of driven particles in square obstacle lattices

Transport phenomena in complex and dynamic microscopic environments are fundamentally shaped by hydrodynamic interactions. In particular, microparticle transport in porous media is governed by the delicate interplay between particle-substrate friction and pressure forces. Here, we systematically investigate the motion of externally driven rotating magnetic microparticles near a substrate patterned with a square lattice of cylindrical obstacles, a model porous medium. Remarkably, we observe a reversal in the direction of particle translation as obstacle spacing decreases, highlighting a sensitive competition between shear-induced forward rolling and pressure-driven backward sliding due to flow-field symmetry breaking. These results demonstrate the crucial role of structured environments in determining microscale active particle transport, offering novel strategies for microfluidic design, targeted cargo delivery, and tunable active materials.

cond-mat.soft↗

arXiv2025

Potential of mean force and underscreening of polarizable colloids in concentrated electrolytes

This study uses advanced numerical methods to estimate the mean force potential (PMF) between charged, polarizable colloidal particles in dense electrolytes. We observe that when the Debye screening length, $λ_{\mathrm{D}}$, is below the hydrated ion size, the PMF shows discernible oscillations of purely electrostatic origin as opposed to chemical affinity, in addition to the expected decay in DLVO theory. Moreover, our findings suggest concentrated electrolytes are significantly less efficient at muting electrostatic interactions in electrostatically stabilized colloidal suspensions, potentially having significant implications for our understanding of colloidal stability and the forces that govern the behavior of concentrated charged soft matter systems beyond DLVO theory.

cond-mat.soft↗

arXiv2024

Rolling vesicles: From confined rotational flows to surface-enabled motion

The interaction of surfaces in relative motion in wet environments is dominated by lubrication forces, which play a pivotal role in the dynamics of microscopic systems. Here, we develop motile vesicles that exploit lubrication forces to roll on substrates. The activity of the vesicle comes from the confined rotational flow generated by a driven rotating particle encapsulated within the vesicle by droplet-microfluidics. Lubrication forces driving vesicle rolling are controlled by membrane mechanics and its tribological properties. This provides the design principles for motile vesicles that exploit frictional forces to efficiently navigate through complex environments.

cond-mat.soft↗

arXiv2024

Simple Calibration of Block Copolymer Melt Models

According to the universality hypothesis, the phase behavior of different block copolymer melt models having fixed composition depends solely on two parameters: the invariant chain length $\bar{N}$ and the effective interaction parameter $χN$. If models behave universally, they can be compared to each other and can predict experiment quantitatively. Here, we present a simple way to achieve this universality for coarse-grained models. Our method relies on the properties of the monomer interaction potential energy $z$ distribution. In particular, models having near-symmetric $z$-distributions exhibit universal phase behavior using the standard linear definition of the Flory-Huggins parameter $χ\proptoα$, where $α= ε_{AB}-(ε_{AA}+ε_{BB})/2$, and $ε_{xy}$ is the interaction energy between monomers of type $x$ and $y$. Previously, universality had been achieved using a nonlinear $χ(α)$ function which is difficult to obtain and interpret physically. The main parameter controlling the symmetry of the $z$-distribution is the monomer density $ρ$. Above certain $ρ$, models have symmetric $z$-distributions, and their order-disorder transition points follow the universal curve predicted by Fredrickson-Helfand theory in the experimentally relevant $\bar{N} > 10^2$ range. On the other hand, low-$ρ$ models exhibit skewed $z$-distributions, and the simple $χ\proptoα$ formula is no longer universally applicable to them. Our results can be used for correct block copolymer model building leading to a simple and direct comparison of simulations to experiments, which will facilitate the screening of new block copolymer morphologies and support materials design.

cond-mat.soft↗

arXiv2022

Symmetry-Breaking and Self-Sorting in Block Copolymer-based Multicomponent Nanocomposites

Co-assembly of inorganic nanoparticles (NPs) and nanostructured polymer matrix represents an intricate interplay of enthalpic or entropic forces. Particle size largely affects the phase behavior of the nanocomposite. Theoretical studies indicate that new morphologies would emerge when the particles become comparable to the soft matrix's size, but this has rarely been supported experimentally. By designing a multicomponent blend composed of NPs, block copolymer-based supramolecules, and small molecules, a 3-D ordered lattice beyond the native BCP's morphology was recently reported when the particle is larger than the microdomain of BCP. The blend can accommodate various formulation variables. In this contribution, when the particle size equals the microdomain size, a symmetry-broken phase appears in a narrow range of particle sizes and compositions, which we named the "train track" structure. In this phase, the NPs aligned into a 3-D hexagonal lattice and packed asymmetrically along the c axis, making the projection of the ac and the bc plane resemble train tracks. Computation studies show that the broken symmetry reduces the polymer chain deformation and stabilizes the metastable hexagonally perforated lamellar morphology. Given the mobility of the multicomponent blend, the system shows a self-sorting behavior: segregating into two macroscopic phases with different nanostructures based on only a few nanometers NP size differences. Smaller NPs form "train track" morphology, while larger NPs form "simple hexagon" structure, where the NPs take a symmetric hexagonal arrangement. Detailed structural evolution and simulation studies confirm the systematic-wide cooperativity across different components, indicating the strong self-regulation of the multicomponent system.

cond-mat.soft↗

arXiv2020

Metamaterials for Active Colloid Transport

Transport phenomena in out-of-equilibrium systems is immensely important in a myriad of applications in biology, engineering and physics. Complex environments, such as the cytoplasm or porous media, can substantially affect the transport properties of such systems. In particular, recent interest has focused on how such environments affect the motion of active systems, such as colloids and organisms propelled by directional driving forces. Nevertheless, the transport of active matter with non-directional (rotational) activity is yet to be understood, despite the ubiquity of rotating modes of motion in synthetic and natural systems. Here, we report on the discovery of spatiotemporal metamaterial systems that are able to dictate the transport of spinning colloids in exquisite ways based on solely two parameters: frequency of spin modulation in time and the symmetry of the metamaterial. We demonstrate that dynamic modulations of the amplitude of spin on a colloid in lattices with rotational symmetry give rise to non-equilibrium ballistic transport bands, reminiscent of those in Floquet-Bloch systems. By coupling these temporal modulations with additional symmetry breaking in the lattice, we show selective control from 4-way to 2-way to unidirectional motion. Our results provide critical new insights into the motion of spinning matter in complex (biological) systems. Furthermore, our work can also be used for designing systems with novel and unique transport properties for application in, for example, smart channel-less microfluidics, micro-robotics, or colloidal separations.

cond-mat.soft↗

arXiv2019

Dissipative Particle Dynamics for Directed Self-Assembly of Block Copolymers

The dissipative particle dynamics (DPD) simulation method has been shown to be a promising tool to study self-assembly of soft matter systems. In particular, it has been used to study block copolymer (BCP) self-assembly. However, previous parametrizations of this model are not able to capture most of the rich phase behaviors of block copolymers in thin films nor in directed self-assembly (chemoepitaxy or graphoepitaxy). Here we extend the applicability of the DPD method for BCPs to make it applicable to thin films and directed self-assembly. Our new reparametrization is able to reproduce the bulk phase behavior, but also manages to predict thin film structures obtained experimentally from chemoepitaxy or graphoepitaxy. A number of different complex structures, such as bilayer nanomeshes, 90° bend structures, circular cylinders/lamellae and Frank-Kasper phases directed by trenches, post arrays or chemically patterned substrate have all been reproduced in this work. This reparametrized DPD model should serves as a powerful tool to predict BCP self-assembly, especially in some complex systems where it is difficult to implement SCFT.

cond-mat.soft↗

arXiv2018

Self-assembly of cylinder forming diblock copolymers on modulated substrates: a simulation study

Self-consistent field theory (SCFT) and strong segregation theory (SST) are used to explore the parameter space governing the self-assembly of cylinder forming block copolymers (BCPs) on a modulated substrate. The stability of in-plane cylinders aligning parallel or perpendicular to substrate corrugation is investigated for different barrier height and spacing for a weakly preferential substrate. Within the conditions of our simulations, the results indicate that cylinder alignment orthogonal to substrate undulation is promoted at low barrier height when substrate is preferential to minority block, independent of barrier spacing. Commensurability is shown to play a limited role in the assembly of orthogonal meshes. Parallel alignment is readily achieved at larger barrier height, near condition of commensuration between barrier spacing and polymer equilibrium period. This is particularly true when substrate is attractive to majority block. The interplay between barrier shape and substrate affinity can be utilized in nanotechnology application such as mesh creation, density multiplication, and 3D BCP morphologies.

cond-mat.mtrl-sci↗

arXiv2018

Diffusion of self-propelled particles in complex media

The diffusion of active microscopic organisms in complex environments plays an important role in a wide range of biological phenomena from cell colony growth to single organism transport. Here, we investigate theoretically and computationally the diffusion of a self-propelled particle (the organism) embedded in a complex medium comprised of a collection of non-motile solid particles that mimic soil or other cells. Under such conditions we find that the rotational relaxation time of the swimming direction depends on the swimming velocity and is drastically reduced compared to a pure Newtonian fluid. This leads to a dramatic increase (of several orders of magnitude) in the effective rotational diffusion coefficient of the self-propelled particles, which can lead to "self-trapping" of the active particles in such complex media. An analytical model is put forward that quantitatively captures the computational results. Our work sheds light on the role that the environment plays in the behavior of active systems and can be generalized in a straightforward fashion to understand other synthetic and biological active systems in heterogenous environments.

physics.flu-dyn↗

arXiv2017

Anisotropic nanoparticle distribution in block copolymer model defects

In this article, we study the thermodynamic behavior of anisotropic shape (rod and disk) nanoparticle within the block copolymer matrix by using self-consistent field theory (SCFT) simulation. In particular, we introduce various defect structures of block copolymers to precisely control the location of anisotropic particles. Different from the previous studies using spherical nanoparticles within the block copolymer model defects, anisotropic particles are aligned with preferred orientation near the defect center due to the combined effects of stretching and interfacial energy of block copolymers. Our results are important for precise controlling of anisotropic nanoparticle arrays for designing various functional nano materials.

cond-mat.soft↗

arXiv2017

Aggregation Dynamics of Active Rotating Particles in Dense Passive Media

Active matter systems are able to exhibit emergent non-equilibrium states due to activity-induced effective interactions between the active particles. Here we study the aggregation and dynamical behavior of active rotating particles, spinners, embedded in 2D passive colloidal monolayers, which constitutes one such non-equilibrium process. Using both experiments and simulations we observe aggregation of active particles or spinners whose behavior resembles classical 2D coarsening. The aggregation behavior and spinner attraction depends on the mechanical properties of the passive monolayer and the activity of spinners. Spinner aggregation only occurs when the passive monolayer behaves elastically and when the spinner activity exceeds a minimum activity threshold. Interestingly for the spinner concentrations investigated here, the spinner concentration doesn't seem to change the dynamics of the aggregation behavior. There is also a characteristic cluster size at which the dynamics of spinner aggregation is maximized as drag through the passive monolayer is minimized and the stress applied on the passive medium is maximized. We also show that a ternary mixture of passive particles, co-rotating, and counter-rotating spinners also aggregates into clusters of co and counter-rotating spinners respectively.

cond-mat.soft↗

arXiv2015

Dynamical bond cooperativity enables very fast and strong binding between sliding surfaces

Cooperative binding affects many processes in biology, but it is commonly addressed only in equilibrium. In this work we explore dynamical cooperativity in driven systems, where the cooperation occurs because some of the bonds change the dynamical response of the system to a regime where the other bonds become active. To investigate such cooperativity we study the frictional binding between two flow driven surfaces that interact through a large population of activated bonds. In particular, we study systems where each bond can have two different modes: one mode corresponds to a fast forming yet weak bond, and the other is a strong yet slow forming bond. We find considerable cooperativity between both types of bonds. Under some conditions the system behaves as if there were only one binding mode, corresponding to a strong and fast forming bond. Our results may have important implications on the friction and adhesion between sliding surfaces containing complementary binding motifs, such as in the case of cells binding to the vessel walls under strong flowing conditions.

physics.bio-ph↗

arXiv2014

Artificial Tribotactic Microscopic Walkers

Friction, the resistive force between two surfaces sliding past each other, is at the core of a wide diversity of locomotion schemes. While such schemes are somewhat understood for homogeneous environments, locomotion based on friction in inhomogeneous environments has not received much attention. Here, we introduce and demonstrate the concept of tribotaxis by utilizing microwalkers that detect gradients in the friction coefficient controlled by the density of biological receptors on the substrate. When actuated stochastically, these microwalkers migrate to regions of higher friction, effectively performing chemotaxis. Simulations and theory based on biased random walks are in excellent agreement with experiments. Our results may have important implications in artificial and natural locomotion in biological environments because interfaces are a prominent motif in nature.

cond-mat.soft↗