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Diffusiophoretic motion induced by gradients of dissolved species has enabled the manipulation of colloids over large distances, spanning hundreds of microns. Nonetheless, studies have primarily focused on simple geometries that feature 1D gradients of solutes generated by reactions or selective dissolution. Thus, our understanding of 3D diffusiophoresis remains elusive despite its importance in wide-ranging scenarios, such as cellular transport and nanofluidics. Herein, we present a strategy to generate 3D chemical gradients under electric fields. In this approach, faradaic reactions at electrodes induce global pH gradients that drive long-range transport through electrodiffusiophoresis. Simultaneously, the electric field induces local pH gradients by driving the particle's double layer far from equilibrium. As a result, while global pH gradients lead to 2D focusing away from electrodes, local pH gradients induce aggregation in the third dimension. Resulting interparticle interactions display a strong dependence on surface chemistry, and particle size. Furthermore, pH gradients can be readily tuned by adjusting the voltage and frequency of the electric field. For large P\'eclet numbers, we observed a chemotactic-like collapse. Remarkably, such collapse occurs without reactions at a particle's surface. By mixing particles with different sizes, we also demonstrate the emergence of non-reciprocal interactions through experiments and Brownian dynamics simulations. These findings suggest a wide array of possibilities for the dynamic assembly of materials and the design of responsive matter.

Driven by physical questions pertaining to quantifying particle dynamics, microscopy can now resolve complex systems at the single particle level, from cellular organisms to individual ions. Yet, available analysis techniques face challenges reconstructing trajectories in dense and heterogeneous systems where accurately labelling particles is difficult. Furthermore, the inescapable finite field of view of experiments hinders the measurement of collective effects. Inspired by Smoluchowski, we introduce a broadly applicable analysis technique that probes dynamics of interacting particle suspensions based on a remarkably simple principle: counting particles in finite observation boxes. Using colloidal experiments, advanced simulations and theory, we first demonstrate that statistical properties of fluctuating counts can be used to determine self-diffusion coefficients, so alleviating the hurdles associated with trajectory reconstruction. We also provide a recipe for practically extracting the diffusion coefficient from experimental data at variable particle densities, which is sensitive to steric and hydrodynamic interactions. Remarkably, by increasing the observation box size, counting naturally enables the study of collective dynamics in dense suspensions. Using our novel analysis of particle counts, we uncover a surprising enhancement of collective behaviour, as well as a new length scale associated with hyperuniform-like structure. Our counting framework, the Countoscope, thus enables efficient measurements of self and collective dynamics in dense suspensions and opens the way to quantifying dynamics and identifying novel physical mechanisms in diverse complex systems where single particles can be resolved.

Understanding the motion of particles with ligand-receptors is important for biomedical applications and material design. Yet, even among a single design, the prototypical DNA-coated colloids, seemingly similar micrometric particles hop or roll, depending on the study. We shed light on this problem by observing DNA-coated colloids diffusing near surfaces coated with complementary strands for a wide array of coating designs. We find colloids rapidly switch between 2 modes: they hop - with long and fast steps - and crawl - with short and slow steps. Both modes occur at all temperatures around the melting point and over a wide array of designs. The particles become increasingly subdiffusive as temperature decreases, in line with subsequent velocity steps becoming increasingly anti-correlated. Overall, crawling (or hopping) phases are more predominant at low (or high) temperatures; crawling is also more efficient at low temperatures than hopping to cover large distances. We rationalize this behavior within a simple model: at lower temperatures, the number of bound strands increases, and detachment of all bonds is unlikely, hence, hopping is prevented and crawling favored. We thus reveal the mechanism behind a common design rule relying on increased strand density for long-range self-assembly: dense strands on surfaces are required to enable crawling, possibly facilitating particle rearrangements.

Understanding particle motion in narrow channels is essential to guide progress in numerous applications, from filtration to vascular transport. Thermal or active fluctuations of channel walls for fluid-filled channels can slow down or increase the dispersion of tracer particles. Entropic trapping in the wall bulges slows dispersion, and hydrodynamic flows induced by wall fluctuations enhance dispersion. Previous studies primarily concentrated on the case of a single Brownian tracer either embedded in an incompressible fluid or in the ideal case where the presence of fluid is ignored. Here we address the question of what happens when there is a large ensemble of interacting Brownian tracers -- a common situation in applications. Introducing repulsive interactions between the tracer particles, while ignoring the presence of a background fluid, leads to an effective flow field. This flow field enhances tracer dispersion, a phenomenon strongly reminiscent of that seen in incompressible background fluid. We characterise the dispersion by the long-time diffusion coefficient of a single tracer, numerically and analytically with a mean-field density functional analysis. We find a surprising effect where an increased particle density enhances the diffusion coefficient, challenging the notion that crowding effects tend to reduce diffusion. Here, inter-particle interactions push particles closer to the fluctuating channel walls. Then, interactions between the fluctuating wall and the now-nearby particles drive particle mixing. Our mechanism is sufficiently general that we expect it to apply to various systems. In addition, the perturbation theory we derive quantifies dispersion in generic advection-diffusion systems with arbitrary spatiotemporal drift., Comment: 18 pages + Appendices + Supplemental Material

Understanding vascular adaptation, namely what drives veins to shrink or grow, is key for the self-organization of flow networks and their optimization. From the top-down principle of minimizing flow dissipation at a fixed metabolic cost within flow networks, flow shear rate resulting from the flows pervading veins is hypothesized to drive vein adaptation. Yet, there is no bottom-up derivation of how flow forces impact vein dynamics. From the physical principle of force balance, shear rate acts parallel to vein walls, and hence, naively shear rate could only stretch veins and not dilate or shrink them. We, here, resolve this paradox by theoretically investigating force balance on a vein wall in the context of the vascular network of the model organism Physarum polycephalum. We propose, based on previous mechanical studies of cross-linked gels, that shear induces a nonlinear, anisotropic response of the actomyosin gel, making up vein walls that can indeed drive vein dilatation. Furthermore, our force balance approach allows us to identify that shear feedback occurs with a typical timescale and with a typical target shear rate that are not universal properties of the material but instead depend smoothly on the location of the vein within the network. In particular, the target shear rate is related to the vein's hydrostatic pressure, which highlights the role of pressure in vascular adaptation. Finally, since our derivation is based on force balance and fluid mechanics, we believe our approach can be extended to vascular adaptation in other organisms.

Observing finite regions of a bigger system is a common experience, from microscopy to molecular simulations. In the latter especially, there is ongoing interest in predicting thermodynamic properties from tracking fluctuations in finite observation volumes. However, kinetic properties have received less attention, especially not in ionic solutions, where electrostatic interactions play a decisive role. Here, we probe ionic fluctuations in finite volumes with Brownian dynamics and build an analytical framework that reproduces our simulation results and is broadly applicable to other systems with pairwise interactions. Particle number and charge correlations exhibit a rich phenomenology with time, characterized by a diversity of timescales. The noise spectrum of both quantities decays as $1/f^{3/2}$, where $f$ is the frequency. This signature of fractional noise shows the universality of $1/f^{3/2}$ scalings when observing diffusing particles in finite domains. The hyperuniform behaviour of charge fluctuations, namely that correlations scale with the area of the observation volume, is preserved in time. Correlations even become proportional to the box perimeter at sufficiently long times. Our results pave the way to understand fluctuations in more complex systems, from nanopores to single-particle electrochemistry.

Transient bonds between fast linkers and slower particles are widespread in physical and biological systems. In spite of their diverse structure and function, a commonality is that the linkers diffuse on timescales much faster compared to the overall motion of the particles they bind to. This limits numerical and theoretical approaches that need to resolve these diverse timescales with high accuracy. Many models, therefore, resort to effective, yet ad-hoc, dynamics, where linker motion is only accounted for when bound. This paper provides a mathematical justification for such coarse-grained dynamics that preserves detailed balance at equilibrium. Our derivation is based on multiscale averaging techniques and is broadly applicable. We verify our results with simulations on a minimal model of fast linker binding to a slow particle. We show how our framework can be applied to various systems, including those with multiple linkers, stiffening linkers upon binding, or slip bonds with force-dependent unbinding. Importantly, the preservation of detailed balance only sets the ratio of the binding to the unbinding rates, but it does not constrain the detailed expression of binding kinetics. We conclude by discussing how various choices of binding kinetics may affect macroscopic dynamics., Comment: updated: 7 figures, 15 pages main text, 8 page supplement

Inertia does not generally affect the long-time diffusion of passive overdamped particles in fluids. Yet a model starting from the Langevin equation predicts a surprising property of particles coated with ligands, that bind reversibly to surface receptors -- heavy particles diffuse more slowly than light ones of the same size. We show this by simulation and by deriving an analytic formula for the mass-dependent diffusion coefficient in the overdamped limit. We estimate the magnitude of this effect for a range of biophysical ligand-receptor systems, and find it is potentially observable for tailored micronscale DNA-coated colloids.

The self-assembly of DNA-coated colloids into highly-ordered structures offers great promise for advanced optical materials. However, control of disorder, defects, melting, and crystal growth is hindered by the lack of a microscopic understanding of DNA-mediated colloidal interactions. Here we use total internal reflection microscopy to measure in situ the interaction potential between DNA-coated colloids with nanometer resolution and the macroscopic melting behavior. The range and strength of the interaction are measured and linked to key material design parameters, including DNA sequence, polymer length, grafting density, and complementary fraction. We present a first-principles model that quantitatively reproduces our experimental data without fitting parameters over a wide range of DNA ligand designs. Our theory identifies a subtle competition between DNA binding and steric repulsion and accurately predicts adhesion and melting at a molecular level. Combining experimental and theoretical results, our work provides a quantitative and predictive approach for guiding material design with DNA-nanotechnology and can be further extended to a diversity of colloidal and biological systems.

Electroosmosis is a fascinating effect where liquid motion is induced by an applied electric field. Counter ions accumulate in the vicinity of charged surfaces, triggering a coupling between liquid mass transport and external electric field. In nanofluidic technologies, where surfaces play an exacerbated role, electroosmosis is thus of primary importance. Its consequences on the transport properties in biological and synthetic nanopores are subtle and intricate. Thorough understanding is therefore challenging yet crucial to fully assess the mechanisms at play. Here, we review recent progress on computational techniques for the analysis of electroosmosis and discuss technological applications, in particular for sensing devices.

Particles with ligand-receptor contacts bind and unbind fluctuating "legs" to surfaces, whose fluctuations cause the particle to diffuse. Quantifying the diffusion of such "nanoscale caterpillars" is a challenge, since binding events often occur on very short time and length scales. Here we derive an analytical formula, validated by simulations, for the long time translational diffusion coefficient of an overdamped nanocaterpillar, under a range of modeling assumptions. We demonstrate that the effective diffusion coefficient, which depends on the microscopic parameters governing the legs, can be orders of magnitude smaller than the background diffusion coefficient. Furthermore it varies rapidly with temperature, and reproduces the striking variations seen in existing data and our own measurements of the diffusion of DNA-coated colloids. Our model gives insight into the mechanism of motion, and allows us to ask: when does a nanocaterpillar prefer to move by sliding, where one leg is always linked to the surface, and when does it prefer to move by hopping, which requires all legs to unbind simultaneously? We compare a range of systems (viruses, molecular motors, white blood cells, protein cargos in the nuclear pore complex, bacteria such as Escherichia coli, and DNA-coated colloids) and present guidelines to control the mode of motion for materials design.

Fluctuations affect nanoporous transport in complex and intricate ways, making optimization of signal-to-noise in artificial designs challenging. Here we focus on the simplest nanopore system, where non-interacting particles diffuse through a pore separating reservoirs. We find that the concentration difference between both sides (akin to the osmotic pressure drop) exhibits fractional noise in time $t$ with mean square average that grows as $t^{1/2}$. This originates from the diffusive exchange of particles from one region to another. We fully rationalize this effect, with particle simulations and analytic solutions. We further infer the parameters (pore radius, pore thickness) that control this exotic behavior. As a consequence, we show that the number of particles within the pore also exhibits fractional noise. Such fractional noise is responsible for noise spectral density scaling as $1/f^{3/2}$ with frequency $f$, and we quantify its amplitude. Our theoretical approach is applicable to more complex nanoporous systems (for example with adsorption within the pore) and drastically simplifies both particle simulations and analytic calculus.

Recent advances in nanofluidics have allowed exploration of ion transport down to molecular scale confinement, yet artificial porins are still far from reaching the advanced functionalities of biological ion machinery. Achieving single ion transport that is tuneable by an external gate -- the ionic analogue of electronic Coulomb blockade (CB) -- would open new avenues in this quest. However, an understanding of ionic CB beyond the electronic analogy is still lacking. Here we show that the many-body dynamics of ions in a charged nanochannel result in a quantised and strongly nonlinear ionic transport, in full agreement with molecular simulations. We find that ionic CB occurs when, upon sufficient confinement, oppositely charged ions form 'Bjerrum pairs', and the conduction proceeds through a mechanism reminiscent of Onsager's Wien effect. Our findings open the way to novel nanofluidic functionalities, such as an ionic-CB-based ion pump inspired by its electronic counterpart.

To overcome the traditional paradigm of filtration, where separation is essentially performed upon steric sieving principles, we explore the concept of dynamic osmosis through active membranes. A partially permeable membrane presents a time-tuneable feature that changes the effective pore interaction with the solute and thus actively changes permeability with time. In general we find that slow flickering frequencies effectively decrease the osmotic pressure, and large flickering frequencies do not change it. In the presence of an asymmetric membrane, we find a resonant frequency where pumping of solute is performed and can be analyzed in terms of ratchet transport. We discuss and highlight the properties of this resonant osmotic transport. Furthermore, we show that dynamic osmosis allows to pump solute at the nanoscale using less energy than reverse osmosis. This opens new possibilities to build advanced filtration devices and design artificial ionic machinery.

Electro- and diffusio- phoresis of particles correspond respectively to the transport of particles under electric field and solute concentration gradients. Such interfacial transport phenomena take their origin in a diffuse layer close to the particle surface, and the motion of the particle is force-free. In the case of electrophoresis, it is further expected that the stress acting on the moving particle vanishes locally as a consequence of local electroneutrality. But the argument does not apply to diffusiophoresis, which takes its origin in solute concentration gradients. In this paper we investigate further the local and global force balance on a particle undergoing diffusiophoresis. We calculate the local tension applied on the particle surface and show that, counter-intuitively, the local force on the particle does not vanish for diffusiophoresis, in spite of the global force being zero as expected. Incidentally, our description allows to clarify the osmotic balance in diffusiophoresis, which has been a source of debates in the recent years. We explore various cases, including hard and soft interactions, as well as porous particles, and provide analytic predictions for the local force balance in these various systems. The existence of local stresses may induce deformation of soft particles undergoing diffusiophoresis, hence suggesting applications in terms of particle separation based on capillary diffusiophoresis.

Osmosis is a universal phenomenon occurring in a broad variety of processes and fields. It is the archetype of entropic forces, both trivial in its fundamental expression - the van 't Hoff perfect gas law - and highly subtle in its physical roots. While osmosis is intimately linked with transport across membranes, it also manifests itself as an interfacial transport phenomenon: the so-called diffusio-osmosis and -phoresis, whose consequences are presently actively explored for example for the manipulation of colloidal suspensions or the development of active colloidal swimmers. Here we give a global and unifying view of the phenomenon of osmosis and its consequences with a multi-disciplinary perspective. Pushing the fundamental understanding of osmosis allows to propose new perspectives for different fields and we highlight a number of examples along these lines, for example introducing the concepts of osmotic diodes, active separation and far from equilibrium osmosis, raising in turn fundamental questions in the thermodynamics of separation. The applications of osmosis are also obviously considerable and span very diverse fields. Here we discuss a selection of phenomena and applications where osmosis shows great promises: osmotic phenomena in membrane science (with recent developments in separation, desalination, reverse osmosis for water purification thanks in particular to the emergence of new nanomaterials); applications in biology and health (in particular discussing the kidney filtration process); osmosis and energy harvesting (in particular, osmotic power and blue energy as well as capacitive mixing); applications in detergency and cleaning, as well as for oil recovery in porous media., Comment: review on osmotic phenomena, accepted for publication to Chemical Society Reviews (final version)

Channels are fundamental building blocks from biophysics to soft robotics, often used to transport or separate solutes. As solute particles inevitably transverse between streamlines along the channel by molecular diffusion, the effective diffusion of the solute along the channel is enhanced - an effect known as Taylor dispersion. Here, we investigate how the Taylor dispersion effect can be suppressed or enhanced in different settings. Specifically, we study the impact of flow profile and active or pulsating channel walls on Taylor dispersion. We derive closed analytic expressions for the effective dispersion equation in all considered scenarios providing hands-on effective dispersion parameters for a multitude of applications. In particular, we find that active channel walls may lead to three regimes of dispersion: either dispersion decrease by entropic slow down at small Peclet number, or dispersion increase at large Peclet number dominated either by shuttle dispersion or by Taylor dispersion. This improves our understanding of solute transport e.g. in biological active systems such as blood flow and opens a number of possibilities to control solute transport in artificial systems such as soft robotics.

Molecular separation traditionnally relies on sieving processes across passive nanoporous membranes. Here we explore theoretically the concept of non-equilibrium active sieving. We investigate a simple model for an active noisy nanopore, where gating - in terms of size or charge - is externally driven at a tunable frequency. Our analytical and numerical results unveil a rich sieving diagram in terms of the forced gating frequency. Unexpectedly, the separation ability is strongly increased as compared to its passive (zero frequency) counterpart. It points also to the possibility of tuning dynamically the osmotic pressure. Active separation outperforms passive sieving and represents a promising avenue for advanced filtration., Comment: 11 pages, 9 figures

In this paper, we explore osmotic transport by means of molecular dynamics (MD) simulations. We first consider osmosis through a membrane, and investigate the reflection coefficient of an imperfectly semi-permeable membrane, in the dilute and high concentration regimes. We then explore the diffusion-osmotic flow of a solute-solvent fluid adjacent to a solid surface, driven by a chemical potential gradient parallel to the surface. We propose a novel non-equilibrium MD (NEMD) methodology to simulate diffusion-osmosis, by imposing an external force on every particle, which properly mimics the chemical potential gradient on the solute in spite of the periodic boundary conditions. This NEMD method is validated theoretically on the basis of linear-response theory by matching the mobility with their Green-Kubo expressions. Finally, we apply the framework to more realistic systems, namely a water-ethanol mixture in contact with a silica or a graphene surface., Comment: Accepted for publication in the Journal of Chemical Physics

In this paper, we explore various forms of osmotic transport in the regime of high solute concentration. We consider both the osmosis across membranes and diffusio-osmosis at solid interfaces, driven by solute concentration gradients. We follow a mechanical point of view of osmotic transport, which allows us to gain much insight into the local mechanical balance underlying osmosis. We demonstrate in particular how the general expression of the osmotic pressure for mixtures, as obtained classically from the thermodynamic framework, emerges from the mechanical balance controlling non-equilibrium transport under solute gradients. Expressions for the rejection coefficient of osmosis and the diffusio-osmotic mobilities are accordingly obtained. These results generalize existing ones in the dilute solute regime to mixtures with arbitrary concentrations., Comment: Accepted for publication in the Journal of Chemical Physics

How do the topology and geometry of a tubular network affect the spread of particles within fluid flows? We investigate patterns of effective dispersion in the hierarchical, biological transport network formed by Physarum polycephalum. We demonstrate that a change in topology - pruning in the foraging state - causes a large increase in effective dispersion throughout the network. By comparison, changes in the hierarchy of tube radii result in smaller and more localized differences. Pruned networks capitalize on Taylor dispersion to increase the dispersion capability., Comment: 5 pages, 4 figures, 11 pages supplemental material

In this paper, we investigate the physical mechanisms underlying one of the most efficient filtration devices: the kidney. Building on a minimal model of the Henle loop - the central part of the kidney filtration - we investigate theoretically the detailed out-of-equilibrium fluxes in this separation process in order to obtain absolute theoretical bounds for its efficiency in terms of separation ability and energy consumption. We demonstrate that this separation process operates at a remarkably small energy cost as compared to traditional sieving processes while working at much smaller pressures. This unique energetic efficiency originates in the double-loop geometry of the nephron, which operates as an active osmotic exchanger. The principles for an artificial-kidney-inspired filtration device could be readily mimicked based on existing soft technologies to build compact and low-energy artificial dialytic devices. Such a "kidney on a chip" also points to new avenues for advanced water recycling, targeting, in particular, sea-water pretreatment for decontamination and hardness reduction.