arXiv subjects

Alex Albaugh

Publications and source records attributed to Alex Albaugh.

7 recordsLinked to original sources

arXiv2026

Odd Polycatenanes Tank-Tread in Strong Shear Flow

Polycatenanes are mechanically interlocked polymers composed of ring molecules linked through mechanical bonds. Here, we investigate the single-molecule dynamics of linear polycatenanes under strong steady shear flow using coarse-grained Brownian dynamics simulations with hydrodynamic interactions. We identify a stable tank-treading state in which individual rings rotate continuously while the overall polymer remains highly extended and aligned with the flow direction, adopting conformations typically associated with extensional flow. Remarkably, tank-treading is observed almost exclusively in odd polycatenanes, polycatenanes with an odd number of rings. We attribute this odd-even effect to the orientation of the terminal rings within the flow-gradient plane, where they act as anchors that stabilize polymer extension, a configuration accessible only to odd polycatenanes. Furthermore, our simulations and a Markov state model demonstrate that this dynamic behavior remains stable over long timescales. Finally, we show that tank treading polycatenanes can be used to fully extend other molecules in strong shear flow, hinting at applications of this behavior to manipulate molecules in rotational flows.

cond-mat.soft↗

arXiv2026

It Takes Two to Make a Thing Go Right: Boosting Current in Coupled Motors

Catalysis-driven synthetic molecular motors operate in a loose mechanochemical coupling regime, one in which a decomposition of a fuel molecule does not reliably produce a forward step. In that regime, stochastic backward steps can significantly degrade the motor's current, prompting us to ask whether mechanically coupling multiple such motors can boost their averaged current. By simulating rotaxane-based motors with two classes of models--particle-based nonequilibrium molecular dynamics and jump-diffusion models--we show that current boosts are physically achievable. Our observed boosts, which amplify current by single-digit factors, emerge when coupling between motors can increase the activity, speeding up the rate of both forward and backward steps. In doing so, the bias for preferring forward steps actually degrades, but the lost bias can be largely recovered by raising the fuel concentration, demonstrating a general design strategy: amplify activity through coupling and restore bias through stronger driving.

cond-mat.stat-mech↗

arXiv2025

Mechanically Interlocked Polymers in Dilute Solution under Shear and Extensional Flows: A Brownian Dynamics Study

Mechanically interlocked polymers (MIPs) are a novel class of polymer structures in which the components are connected by mechanical bonds instead of covalent bonds. We measure the single-molecule rheological properties of polyrotaxanes, daisy chains, and polycatenanes under steady shear and steady uniaxial extension using coarse-grained Brownian dynamics simulations with hydrodynamic interactions. We obtain key rheological features, including tumbling dynamics, molecular extension, stress, and viscosity. By systematically varying structural features, we demonstrate how MIP topology governs flow response. Compared to linear polymers, all three MIP architectures exhibit enhanced tumbling in shear flow and lower normal stress differences in extensional flow. While polyrotaxanes show higher shear and extensional viscosities, polycatenanes and daisy chains have lower viscosities. In extensional flow, polyrotaxanes and polycatenanes extend earlier than linear polymers. We find that mechanical bonds suppress shear thinning and alter the coil-stretch transition observed in linear polymers. These effects arise from the mechanically bonded rings in MIPs, which expand the polymer profile in gradient direction and increase backbone stiffness due to ring-backbone repulsions. This study provides key insights into MIP flow properties, providing the foundation for their systematic development in engineering applications.

cond-mat.soft↗

arXiv2023

Limits on the Precision of Catenane Molecular Motors: Insights from Thermodynamics and Molecular Dynamics Simulations

Thermodynamic uncertainty relations (TURs) relate precision to the dissipation rate, yet the inequalities can be far from saturation. Indeed, in catenane molecular motor simulations, we record precision far below the TUR limit. We further show that this inefficiency can be anticipated by four physical parameters: the thermodynamic driving force, fuel decomposition rate, coupling between fuel decomposition and motor motion, and rate of undriven motor motion. The physical insights might assist in designing molecular motors in the future.

cond-mat.stat-mech↗

arXiv2022

Sterically Driven Current Reversal in a Model Molecular Motor

Simulations can help unravel the complicated ways in which molecular structure determines function. Here, we use molecular simulations to show how slight alterations of a molecular motor's structure can cause the motor's typical dynamical behavior to reverse directions. Inspired by autonomous synthetic catenane motors, we study the molecular dynamics of a minimal motor model, consisting of a shuttling ring that moves along a track containing interspersed binding sites and catalytic sites. The binding sites attract the shuttling ring while the catalytic sites speed up a reaction between molecular species, which can be thought of as fuel and waste. When that fuel and waste are held in a nonequilibrium steady-state concentration, the free energy from the reaction drives directed motion of the shuttling ring along the track. Using this model and nonequilibrium molecular dynamics, we show that the shuttling ring's direction can be reversed by simply adjusting the spacing between binding and catalytic sites on the track. We present a steric mechanism behind the current reversal, supported by kinetic measurements from the simulations. These results demonstrate how molecular simulation can guide future development of artificial molecular motors.

cond-mat.stat-mech↗

arXiv2021

Simulating a Chemically-Fueled Molecular Motor with Nonequilibrium Molecular Dynamics

Most computer simulations of molecular dynamics take place under equilibrium conditions--in a closed, isolated system, or perhaps one held at constant temperature or pressure. Sometimes, extra tensions, shears, or temperature gradients are introduced to those simulations to probe one type of nonequilibrium response to external forces. Catalysts and molecular motors, however, function based on the nonequilibrium dynamics induced by a chemical reaction's thermodynamic driving force. In this scenario, simulations require chemostats capable of preserving the chemical concentrations of the nonequilibrium steady state. We develop such a dynamic scheme and use it to observe cycles of a new particle-based classical model of a catenane-like molecular motor. Molecular motors are frequently modeled with detailed-balance-breaking Markov models, and we explicitly construct such a picture by coarse graining the microscopic dynamics of our simulations in order to extract rates. This work identifies inter-particle interactions that tune those rates to create a functional motor, thereby yielding a computational playground to investigate the interplay between directional bias, current generation, and coupling strength in molecular information ratchets.

cond-mat.stat-mech↗

arXiv2019

Estimating Reciprocal Partition Functions to Enable Design Space Sampling

Reaction rates are a complicated function of molecular interactions, which can be selected from vast chemical design spaces. Seeking the design that optimizes a rate is a particularly challenging problem since the rate calculation for any one design is itself a difficult computation. Toward this end, we demonstrate a strategy based on transition path sampling to generate an ensemble of designs and reactive trajectories with a preference for fast reaction rates. Each step of the Monte Carlo procedure requires a measure of how a design constrains molecular configurations, expressed via the reciprocal of the partition function for the design. Though the reciprocal of the partition function would be prohibitively expensive to compute, we apply Booth's method for generating unbiased estimates of a reciprocal of an integral to sample designs without bias. A generalization with multiple trajectories introduces a stronger preference for fast rates, pushing the sampled designs closer to the optimal design. We illustrate the methodology on two toy models of increasing complexity: escape of a single particle from a Lennard-Jones potential well of tunable depth and escape from a metastable tetrahedral cluster with tunable pair potentials.

cond-mat.stat-mech↗