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Supramolecular polymerization can be controlled in space and time by chemical fuels. A nonassembled monomer is activated by the fuel and subsequently self-assembles into a polymer. Deactivation of the molecule either in solution or inside the polymer leads to disassembly. Whereas biology has already mastered this approach, fully artificial examples have only appeared in the past decade. Here, we map the available literature examples into four distinct regimes depending on their activation/deactivation rates and the equivalents of deactivating fuel. We present increasingly complex mathematical models, first considering only the chemical activation/deactivation rates (i.e., transient activation) and later including the full details of the isodesmic or cooperative supramolecular processes (i.e., transient self-assembly). We finish by showing that sustained oscillations are possible in chemically fueled cooperative supramolecular polymerization and provide mechanistic insights. We hope our models encourage the quantification of activation, deactivation, assembly, and disassembly kinetics in future studies.
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Polímeros , Cinética , Polimerizacion , Polímeros/químicaRESUMEN
The purpose of this article is to analyze a sequence of independent bets by modeling it with a convective-diffusion equation (CDE). The approach follows the derivation of the Kelly Criterion (i.e., with a binomial distribution for the numbers of wins and losses in a sequence of bets) and reframes it as a CDE in the limit of many bets. The use of the CDE clarifies the role of steady growth (characterized by a velocity U) and random fluctuations (characterized by a diffusion coefficient D) to predict a probability distribution for the remaining bankroll as a function of time. Whereas the Kelly Criterion selects the investment fraction that maximizes the median bankroll (0.50 quantile), we show that the CDE formulation can readily find an optimum betting fraction f for any quantile. We also consider the effects of "ruin" using an absorbing boundary condition, which describes the termination of the betting sequence when the bankroll becomes too small. We show that the probability of ruin can be expressed by a dimensionless Péclet number characterizing the relative rates of convection and diffusion. Finally, the fractional Kelly heuristic is analyzed to show how it impacts returns and ruin. The reframing of the Kelly approach with the CDE opens new possibilities to use known results from the chemico-physical literature to address sequential betting problems.
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Lipid vesicles immersed in solute gradients are predicted to migrate from regions of high to low solute concentration due to osmotic flows induced across their semipermeable membranes. This processâknown as osmophoresisâis potentially relevant to biological processes such as vesicle trafficking and cell migration; however, there exist significant discrepancies (several orders of magnitude) between experimental observations and theoretical predictions for the vesicle speed. Here, we seek to reconcile predictions of osmophoresis with observations of vesicle motion in osmotic gradients. We prepare quasi-steady solute gradients in a microfluidic chamber using density-matched solutions of sucrose and glucose to eliminate buoyancy-driven flows. We quantify the motions of giant DLPC vesicles and Brownian tracer particles in such gradients using Bayesian analysis of particle tracking data. Despite efforts to mitigate convective flows, we observe directed motion of both lipid vesicles and tracer particles in a common direction at comparable speeds of order 10 nm/s. These observations are not inconsistent with models of osmophoresis, which predict slower motion at ca. 1 nm/s; however, experimental uncertainty and the confounding effects of fluid convection prohibit a quantitative comparison. In contrast to previous reports, we find no evidence for anomalously fast osmophoresis of lipid vesicles when fluid convection is mitigated and quantified. We discuss strategies for enhancing the speed of osmophoresis using high permeability membranes and geometric confinement.
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Time-varying fields drive the motion of magnetic particles adsorbed on liquid drops due to interfacial constraints that couple magnetic torques to capillary forces. Such magneto-capillary particle dynamics and the associated fluid flows are potentially useful for propelling drop motion, mixing drop contents, and enhancing mass transfer between phases. The design of such functions benefits from the development and validation of predictive models. Here, we apply methods of Bayesian data analysis to identify and validate a dynamical model that accurately predicts the field-driven motion of a magnetic particle adsorbed at the interface of a spherical droplet. Building on previous work, we consider candidate models that describe particle tilting at the interface, field-dependent contributions to the magnetic moment, gravitational forces, and their combinations. The analysis of each candidate is informed by particle tracking data for a magnetic Janus sphere moving in a precessing field at different frequencies and angles. We infer the uncertain parameters of each model, criticize their ability to describe and predict experimental data, and select the most probable candidate, which accounts for gravitational forces and the tilting of the Janus sphere at the interface. We show how this favored model can predict complex particle trajectories with micron-level accuracy across the range of driving fields considered. We discuss how knowledge of this "best" model can be used to design experiments that inform accurate parameter estimates or achieve desired particle trajectories.
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Dielectric particles in weakly conducting fluids rotate spontaneously when subject to strong electric fields. Such Quincke rotation near a plane electrode leads to particle translation that enables physical models of active matter. In this Letter, we show that Quincke rollers can also exhibit oscillatory dynamics, whereby particles move back and forth about a fixed location. We explain how oscillations arise for micron-scale particles commensurate with the thickness of a field-induced boundary layer in the nonpolar electrolyte. This work enables the design of colloidal oscillators.
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Self-propulsion of micro- and nanoparticles powered by ultrasound provides an attractive strategy for the remote manipulation of colloidal matter using biocompatible energy inputs. Quantitative understanding of particle motion and its dependence on size, shape, and composition requires accurate characterization of the acoustic field, which depends sensitively on the experimental setup. Here, we show how automated experiments based on Bayesian inference and design can accurately and efficiently characterize the acoustic field within resonant chambers used to propel acoustic nanomotors. Repeated cycles of observation, inference, and design (OID) are guided by a physical model that describes the rate at which levitating particles approach the nodal plane. Using video microscopy, we observe the relaxation of tracer particles to this plane following the application of the acoustic field. We use sequential Monte Carlo methods to infer model parameters such as the amplitude and frequency of the resonant chamber while accounting for particle-level measurement noise and population-level heterogeneity in the field. Guided by simulated outcomes, we select the optimal design for the next experiment as to maximize the information gain in the relevant parameters. We show how this iterative process serves to discriminate between competing hypotheses and efficiently converges to accurate parameter estimates using only few automated experiments. We discuss the need for model criticism to ensure the validity of the guiding model throughout automated cycles of observation, inference, and design. This work demonstrates how Bayesian methods can learn the parameters of nonlinear, hierarchical models used to describe video microscopy data of active colloids.
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We describe how spatially uniform, time-periodic magnetic fields can be designed to power and direct the migration of ferromagnetic spheres up (or down) local gradients in the topography of a solid substrate. Our results are based on a dynamical model that considers the time-varying magnetic torques on the particle and its motion through the fluid at low Reynolds number. We use both analytical theory and numerical simulation to design magnetic fields that maximize the migration velocity up (or down) an inclined plane. We show how "topotaxis" of spherical particles relies on differences in the hydrodynamic resistance to rotation about axes parallel and perpendicular to the plane. Importantly, the designed fields can drive multiple independent particles to move simultaneously in different directions as determined by gradients in their respective environments. Experiments on ferromagnetic spheres provide evidence for topotactic motions up inclined substrates. The ability to program the autonomous navigation of driven particles within anisotropic environments is relevant to the design of colloidal robots.
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The symmetry and shape of colloidal particles can direct complex particle motions through fluid environments powered by simple energy inputs. The ability to rationally design or "program" the dynamics of such active colloids is an important step toward the realization of colloidal machines, in which components assemble spontaneously in space and time to perform dynamic (dissipative) functions such as actuation and transport. Here, we systematically investigate the dynamics of polarizable particles of different shapes moving in an oscillating electric field via induced-charge electrophoresis (ICEP). We consider particles from each point group in three dimensions (3D) and identify the different rotational and translational motions allowed by symmetry. We describe how the 3D shape of rigid particles can be tailored to achieve desired dynamics including oscillatory motions, helical trajectories, and complex periodic orbits. The methodology we develop is generally applicable to the design of shape-directed particle motions powered by other energy inputs.
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Spatially uniform magnetic fields induce nonzero forces on magnetic particles adsorbed at curved liquid interfaces thereby driving their motion. Such motions, prohibited in bulk fluids, arise due to interfacial constraints that couple magnetic torques to capillary forces at curved interfaces. Here, we show that time-varying (spatially uniform) magnetic fields can be used to drive a variety of steady particle motions on water drops in decane. Upon application of a precessing field, magnetic Janus particles with amphiphilic surface chemistry move either along circular orbits at the drop poles or along zigzag paths at the drop equator. The different magneto-capillary motions depend on the frequency and precession angle of the field as well as the initial position of the particle on the drop surface. Our experimental observations are reproduced and explained by a mathematical model that accounts for the relevant magnetic, capillary, and hydrodynamic forces and torques that contribute to particle motion. In addition to ferromagnetic Janus particles, we show that similar dynamics can be achieved using superparamagnetic carbonyl iron particles, which are manufactured on industrial scales and respond to even weaker magnetic fields. We demonstrate how the field-driven motion of such particles at the drop interface can induce fluid flows that effectively mix the drop interior. These results suggest that magneto-capillary particle motions could be used to enhance mass transfer within emulsions stabilized by magnetic particles.
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We derive a perturbation solution to the one-dimensional Poisson-Nernst-Planck (PNP) equations between parallel electrodes under oscillatory polarization for arbitrary ionic mobilities and valences. Treating the applied potential as the perturbation parameter, we show that the second-order solution yields a nonzero time-average electric field at large distances from the electrodes, corroborating the recent discovery of Asymmetric Rectified Electric Fields (AREFs) via numerical solution to the full nonlinear PNP equations [Hashemi Amrei et al., Phys. Rev. Lett., 2018, 121, 185504]. Importantly, the first-order solution is analytic, while the second-order AREF is semi-analytic and obtained by numerically solving a single linear ordinary differential equation, obviating the need for full numerical solutions to the PNP equations. We demonstrate that at sufficiently high frequencies and electrode spacings the semi-analytical AREF accurately captures both the complicated shape and the magnitude of the AREF, even at large applied potentials.
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Contact charge electrophoresis (CCEP) uses steady electric fields to drive the oscillatory motion of conductive particles and droplets between two or more electrodes. In contrast to traditional forms of electrophoresis and dielectrophoresis, CCEP allows for rapid and sustained particle motions driven by low-power dc voltages. These attributes make CCEP a promising mechanism for powering active components for mobile microfluidic technologies. This Feature Article describes our current understanding of CCEP as well as recent strategies to harness it for applications in microfluidics and beyond.
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A homogeneous magnetic field can exert no net force on a colloidal particle. However, by coupling the particle's orientation to its position on a curved interface, even static homogeneous fields can be used to drive rapid particle motions. Here, we demonstrate this effect using magnetic Janus particles with amphiphilic surface chemistry adsorbed at the spherical interface of a water drop in decane. Application of a static homogeneous field drives particle motion to the drop equator where the particle's magnetic moment can align parallel to the field. As explained quantitatively by a simple model, the effective magnetic force on the particle scales linearly with the curvature of the interface. For particles adsorbed on small droplets such as those found in emulsions, these magneto-capillary forces can far exceed those due to magnetic field gradients in both magnitude and range. This mechanism may be useful in creating highly responsive emulsions and foams stabilized by magnetic particles.
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Small autonomous machines like biological cells or soft robots can convert energy input into control of function and form. It is desired that this behavior emerges spontaneously and can be easily switched over time. For this purpose we introduce an active matter system that is loosely inspired by biology and which we term an active colloidal cell. The active colloidal cell consists of a boundary and a fluid interior, both of which are built from identical rotating spinners whose activity creates convective flows. Similarly to biological cell motility, which is driven by cytoskeletal components spread throughout the entire volume of the cell, active colloidal cells are characterized by highly distributed energy conversion. We demonstrate that we can control the shape of the active colloidal cell and drive compartmentalization by varying the details of the boundary (hard vs. flexible) and the character of the spinners (passive vs. active). We report buckling of the boundary controlled by the pattern of boundary activity, as well as formation of core-shell and inverted Janus phase-separated configurations within the active cell interior. As the cell size is increased, the inverted Janus configuration spontaneously breaks its mirror symmetry. The result is a bubble-crescent configuration, which alternates between two degenerate states over time and exhibits collective migration of the fluid along the boundary. Our results are obtained using microscopic, non-momentum-conserving Langevin dynamics simulations and verified via a phase-field continuum model coupled to a Navier-Stokes equation.
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The zeta potential of a particle characterizes its motion in an electric field and is often thought to be negligible at high ionic strength (several moles per liter) due to thinning of the electrical double layer (EDL). Here, we describe zeta potential measurements on polystyrene latex (PSL) particles at monovalent salt concentrations up to saturation (â¼5 M NaCl) using electrophoresis in sinusoidal electric fields and high-speed video microscopy. Our measurements reveal that the zeta potential remains finite at even the highest concentrations. Moreover, we find that the zeta potentials of sulfated PSL particles continue to obey the classical Gouy-Chapman model up to saturation despite significant violations in the model's underlying assumptions. By contrast, amidine-functionalized PSL particles exhibit qualitatively different behaviors such as zero zeta potentials at high concentrations of NaCl and KCl and even charge inversion in KBr solutions. The experimental results are reproduced and explained by Monte Carlo simulations of a simple lattice model of the EDL that accounts for effects due to ion size and ion-ion correlations. At high salt conditions, the model suggests that quantitative changes in the magnitude of surface charge can result in qualitative changes in the zeta potential-most notably, charge inversion of highly charged surfaces. These findings have important implications for electrokinetic phenomena such as diffusiophoresis within salty environments such as oceans, geological reservoirs, and living organisms.
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We investigate the dynamics of metallodielectric Janus particles moving via contact charge electrophoresis (CCEP) between two parallel electrodes. CCEP uses a constant voltage to repeatedly charge and actuate conductive particles within a dielectric fluid, resulting in rapid oscillatory motion between the electrodes. In addition to particle oscillations, we find that micrometer-scale Janus particles move perpendicular to the field at high speeds (up to 600 µm/s) and over large distances. We characterize particle motions and propose a mechanism based on the rotation-induced translation of the particle following charge transfer at the electrode surface. The propulsion mechanism is supported both by experiments with fluorescent particles that reveal their rotational motions and by simulations of CCEP dynamics that capture the relevant electrostatics and hydrodynamics. We also show that interactions among multiple particles can lead to repulsion, attraction, and/or cooperative motions depending on the position and phase of the respective particle oscillators. Our results demonstrate how particle asymmetries can be used to direct the motions of active colloids powered by CCEP.
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Function at all scales: Hierarchical assemblies of nanoparticles provide routes to multifunctional materials, in which structures at different scales impart different functions. Plasmonic vesicles formed by nanoparticle "strings" are useful both as contrast agents for photoacoustic imaging and as light-activated drug-delivery vehicles.
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Nanomedicina , Oro/química , Nanopartículas del MetalRESUMEN
Contact charge electrophoresis (CCEP) uses steady electric fields to drive the continuous, oscillatory motion of conductive particles and droplets between two or more electrodes. These rapid oscillations can be rectified to direct the motion of objects within microfluidic environments using low-power, dc voltage. Here, we compare high precision experimental measurements of CCEP within a microfluidic system to equally detailed theoretical predictions on the motion of a conductive particle between parallel electrodes. We use a simple, capillary microfluidic platform that combines high-speed imaging with precision electrical measurements to enable the synchronized acquisition of both the particle location and the electric current due to particle motion. The experimental results are compared to those of a theoretical model, which relies on a Stokesian dynamics approach to accurately describe both the electrostatic and hydrodynamic problems governing particle motion. We find remarkable agreement between theory and experiment, suggesting that particle motion can be accurately captured by a combination of classical electrostatics and low-Reynolds number hydrodynamics. Building on this agreement, we offer new insight into the charge transfer process that occurs when the particle nears contact with an electrode surface. In particular, we find that the particle does not make mechanical contact with the electrode but rather that charge transfer occurs at finite surface separations of >0.1 µm by means of an electric discharge through a thin lubricating film. We discuss the implications of these findings on the charging of the particle and its subsequent dynamics.
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Active matter comprised of many self-driven units can exhibit emergent collective behaviors such as pattern formation and phase separation in both biological (e.g., mussel beds) and synthetic (e.g., colloidal swimmers) systems. While these behaviors are increasingly well understood for ensembles of linearly self-propelled "particles", less is known about the collective behaviors of active rotating particles where energy input at the particle level gives rise to rotational particle motion. A recent simulation study revealed that active rotation can induce phase separation in mixtures of counter-rotating particles in 2D. In contrast to that of linearly self-propelled particles, the phase separation of counter-rotating fluids is accompanied by steady convective flows that originate at the fluid-fluid interface. Here, we investigate the influence of these flows on the coarsening dynamics of actively rotating binary liquids using a phenomenological, hydrodynamic model that combines a Cahn-Hilliard equation for the fluid composition with a Navier-Stokes equation for the fluid velocity. The effect of active rotation is introduced though an additional force within the Navier-Stokes equations that arises due to gradients in the concentrations of clockwise and counter-clockwise rotating particles. Depending on the strength of active rotation and that of frictional interactions with the stationary surroundings, we observe and explain new dynamical behaviors such as "active coarsening" via self-generated flows as well as the emergence of self-propelled "vortex doublets". We confirm that many of the qualitative behaviors identified by the continuum model can also be found in discrete, particle-based simulations of actively rotating liquids. Our results highlight further opportunities for achieving complex dissipative structures in active materials subject to distributed actuation.