Active Particles Research Articles

Enabling Efficient Oxygen Evolution via Anchoring Carbon-Layer-Confined RuOx on a Well-Matched Substrate.

Oxygen evolution reaction (OER) is a multistep proton-coupled four-electron process with sluggish kinetics, which seriously limits the hydrogen production efficiency, thus it is of great importance to develop an efficient and stable OER catalyst. In this study, a two-step differential pyrolysis strategy is employed to design a three-dimensional porous microstructured material consisting of RuOx nanoparticles coated by a thin-layer carbon, where the active particles were isolated in separate chambers and the RuOx nanoparticles mainly existed in the form of a heterogeneous interface between RuO2 and partial metallic Ru. The preparation parameters of the catalysts are optimized via combining transient and steady-state polarization properties, and the target catalyst Cat-500-1.5t shows the best OER catalytic performance after ca. 60 h of a chronopotentiometry test in an acidic medium with a much smaller performance change than other samples. The unique design of adopting a carbon layer to form separate reaction chambers largely mitigates the excessive oxidation loss of the active components under strong oxidation potential. The suitability of the catalyst with the loaded substrate and test media is explored, and in an acidic medium, the carbon paper is much better than the titanium fiber, while in an alkaline medium, the titanium fiber is obviously superior to the carbon paper. On both carbon paper and titanium fiber, the performance in an alkaline medium outperforms that in an acidic medium, and the possible reasons for the performance difference are analyzed. Herein, to obtain the actual electrocatalytic performance, the optimal design of the catalyst structure and matching suitable conductive substrate in a specific medium are quite necessary, which provides a feasible strategy for the acquisition of efficient and stable electrocatalysts and the desirable presentation of performance.

Run-and-tumble motion of ellipsoidal microswimmers

A hallmark of bacteria is their so-called “run-and-tumble” motion and its variants, consisting of a sequence of linear directed “runs” and distinct rotation events that constantly alternate due to biochemical feedback. It plays a crucial role in the ability of bacteria to move through chemical gradients and has inspired a fundamental active particle model. Nevertheless, synthetic active particles generally do not exhibit run-and-tumble motion but rather active Brownian motion. We show in experiments that ellipsoidal thermophoretic Janus particles, propelling along their short axis, can yield run-and-reverse motion, i.e., where rotation events flip the direction of motion, even without feedback. Their hydrodynamic wall interactions under strong confinement give rise to an effective double-well potential for the declination of the short axis. The geometry-induced timescale separation of the in-plane rotational dynamics and noise-induced transitions in the potential then yield run-and-reverse motion. Published by the American Physical Society 2024

Playing with active matter

In the past 20 years, active matter has been a very successful research field, bridging the fundamental physics of nonequilibrium thermodynamics with applications in robotics, biology, and medicine. Active particles, contrary to Brownian particles, can harness energy to generate complex motions and emerging behaviors. Most active-matter experiments are performed with microscopic particles and require advanced microfabrication and microscopy techniques. Here, we propose some macroscopic experiments with active matter employing commercially available toy robots (the Hexbugs). We show how they can be easily modified to perform regular and chiral active Brownian motion and demonstrate through experiments fundamental signatures of active systems such as how energy and momentum are harvested from an active bath, how obstacles can sort active particles by chirality, and how active fluctuations induce attraction between planar objects (a Casimir-like effect). These demonstrations enable hands-on experimentation with active matter and showcase widely used analysis methods.

Highly Active Photoreduction of Atmospheric‐Concentration CO2 into CH3COOH over Palladium Particles on Nb2O5 Nanosheets

AbstractThe endeavor to drive CO2 photoreduction towards the synthesis of C2 products is largely thwarted by the colossal energy hurdle inherent in C−C coupling. Herein, we load active metal particles on metal oxide nanosheets to build the dual metal pair sites for steering C−C coupling to form C2 products. Taking Pd particles anchored on the Nb2O5 nanosheets as an example, the high‐angle annular dark‐field image and X‐ray photoelectron spectroscopy demonstrate the presence of Pd−Nb metal pair sites on the Pd‐Nb2O5 nanosheets. Density functional theory calculations reveal these sites exhibit a low reaction energy barrier of only 1.02 eV for C−C coupling, implying that the introduction of Pd particles effectively tailors the reaction step to form C2 products. Therefore, the Pd‐Nb2O5 nanosheets achieve a CH3COOH evolution rate of 13.5 μmol g−1 h−1 in photoreduction of atmospheric‐concentration CO2, outshining all other single photocatalysts reported to date under analogous conditions.

Fluctuating hydrodynamics of an autophoretic particle near a permeable interface

We study the autophoretic motion of a spherical active particle interacting chemically and hydrodynamically with its fluctuating environment in the limit of rapid diffusion and slow viscous flow. Then, the chemical and hydrodynamic fields can be expressed in terms of integrals. The resulting boundary-domain integral equations provide a direct way of obtaining the traction on the particle, requiring the solution of linear integral equations. An exact solution for the chemical and hydrodynamic problems is obtained for a particle in an unbounded domain. For motion near boundaries, we provide corrections to the unbounded solutions in terms of chemical and hydrodynamic Green's functions, preserving the dissipative nature of autophoresis in a viscous fluid for all physical configurations. Using this, we give the fully stochastic update equations for the Brownian trajectory of an autophoretic particle in a complex environment. First, we analyse the Brownian dynamics of particles capable of complex motion in the bulk. We then introduce a chemically permeable planar surface of two immiscible liquids in the vicinity of the particle and provide explicit solutions to the chemo-hydrodynamics of this system. Finally, we study the case of an isotropically phoretic particle hovering above an interface as a function of interfacial solute permeability and viscosity contrast.

PVDF and PEO Catholytes in Solid‐State Cathodes Made by Conventional Slurry Casting

AbstractAll‐solid‐state Li batteries are desired for better safety and energy density than Li‐ion batteries. However, the lack of a penetrating liquid electrolyte requires a much different approach to the design of cathodes. The solid catholyte must enable good Li+ conduction, form good interfaces with active material particles, and have the strength to bind the cathode together during repeated volume changes. Catholyte formulation is often simply adapted from Li‐ion design principles, adding a Li salt to the PVDF binder. Here we show that such a PVDF binder at 10 wt % loading is a starved catholyte condition that compromises cell performance. By substituting a 70 : 30 blend of PVDF:PEO, performance is improved while maintaining nearly the same areal loading of LFP active material. Increasing the catholyte fraction to 16 % can also improve performance, but in this case the benefit of including PEO is lessened, with PVDF alone being an adequate catholyte. EIS analysis shows that PEO helps to form charge transfer interfaces at 10 % catholyte, but that its inclusion can degrade interfaces when there is ample catholyte at 16 %. It is also shown that catholyte agglomeration can impede bulk Li conduction, indicating that microstructural factors are of critical importance.

Anomalous diffusion of active Brownian particles in responsive elastic gels: Nonergodicity, non-Gaussianity, and distributions of trapping times

Anomalous diffusion of active Brownian particles in responsive elastic gels: Nonergodicity, non-Gaussianity, and distributions of trapping times

Spatial‐Dependent Coupling of Electrochemistry, Mass Transport, and Stress in Silicon‐Graphite Composite Electrodes for Lithium‐Ion Batteries

AbstractThe commercialization of high‐capacity silicon materials in lithium‐ion batteries is hindered by significant volume changes. Composite anodes made from silicon and graphite, which increase battery capacity and maintain electrode structural stability, are receiving considerable attention. However, the spatial configuration of the active particles in the electrode is few investigated due to the complexity of experiments at the microscopic scale. Herein, this work focuses on electrochemical, mass transport, and stress coupling mechanisms by considering different spatial configurations of silicon and graphite. In situ electrochemical and stress measurements are first conducted to demonstrate the impact of the active material arrangement. Then, a 2D electrochemical‐mechanical model is developed considering the heterogeneity of electrochemical processes at the particle‐electrolyte interface. The results show that placing silicon in the upper active layer significantly reduces the ion transport resistance, while the graphite layer near the current collector provides a good conductive network for electron transport in the silicon layer, enhancing the performance of the composite electrode structure. By combining electrochemical and mechanical field models with experimental verification, this study deepens the understanding of composite electrode structure design, offering practical guidance for optimizing the spatial configuration of electrode materials to significantly improve battery performance.

Learning protocols for the fast and efficient control of active matter

Exact analytic calculation shows that optimal control protocols for passive molecular systems often involve rapid variations and discontinuities. However, similar analytic baselines are not generally available for active-matter systems, because it is more difficult to treat active systems exactly. Here we use machine learning to derive efficient control protocols for active-matter systems, and find that they are characterized by sharp features similar to those seen in passive systems. We show that it is possible to learn protocols that effect fast and efficient state-to-state transformations in simulation models of active particles by encoding the protocol in the form of a neural network. We use evolutionary methods to identify protocols that take active particles from one steady state to another, as quickly as possible or with as little energy expended as possible. Our results show that protocols identified by a flexible neural-network ansatz, which allows the optimization of multiple control parameters and the emergence of sharp features, are more efficient than protocols derived recently by constrained analytical methods. Our learning scheme is straightforward to use in experiment, suggesting a way of designing protocols for the efficient manipulation of active matter in the laboratory.

A rapid-convergent particle swarm optimization approach for multiscale design of high-permeance seawater reverse osmosis systems

Directly solving sophisticated partial differential equation constrained optimization problems is not only extremely time-consuming, but also very hard to find unique optimal solutions. Here, we propose stable and efficient surrogate models for seawater reverse osmosis desalination processes that enable thorough quantitative description of hydrodynamics and local transport characteristics in narrow flow channels. Without iteratively solving complex multi-physics simulation problem taking several hours, the proposed multi-scale design optimization framework significantly reduces the problem complexity by computing the surrogate models in seconds. Moreover, a fast-converging active subspace particle swarm optimization framework is proposed to address the optimal design problem. Compared to the standard particle swarm optimization algorithm, the proposed method enhances the average optimum by 14% and the standard deviation of optimum results for multiple runs is reduced by no less than ten times. The optimized desalination system achieves 9% reduction on energy consumption and 30% improvement on water production efficiency.

Optimizing Circular Rotations in Confined Systems via Enhanced Self-Driven Speed of Active Nematics

Abstract Active matter exhibits collective motions at various scales. Geometric confinement has been identified as an effective way to control and manipulate active fluids, with much attention given to external factors. However, the impact of the inherent properties of active particles on collective motion under confined conditions remains elusive. Here, we use a highly tunable active nematics model to study active systems under confinement, focusing on the effect of self-driven speed of active particles. We identify three distinct states characterized by unique particle and flow fields within confined active nematic systems, among which circular rotation emerges as a collective motion involving rotational movement in both particle and flow fields. The theoretical phase diagram shows that increasing the self-driven speed of active particles significantly enhances the region of circular rotation state and improves its stability. Our results provide insights into the formation of high quality vortices in confined active nematic systems.

Macrotransport of active particles in periodic channels and fields: Rectification and dispersion.

Transport and dispersion of active particles in structured environments, such as corrugated channels and porous media, are important for the understanding of both natural and engineered active systems. Owing to their continuous self-propulsion, active particles exhibit rectified transport under spatially asymmetric confinement. While progress has been made in experiments and particle-based simulations, a theoretical understanding of the effective long-time transport dynamics in spatially periodic geometries remains less developed. In this paper, we apply generalized Taylor dispersion theory to analyze the long-time effective transport dynamics of active Brownian particles (ABPs) in periodic channels and fields. We show that the long-time transport behavior is governed by an effective advection-diffusion equation. The derived macrotransport equations allow us to characterize the average drift and effective dispersion coefficient. For the case of ABPs subject to a no-flux boundary condition at the channel wall, we show that regardless of activity, the average drift is given by the net diffusive flux along the channel. For ABPs, their activity is the driving mechanism that sustains a density gradient, which ultimately leads to rectified motion along the channel. Our continuum theory is validated against direct Brownian dynamics simulations of the Langevin equations governing the motion of each ABP.

Entropy production of active Brownian particles going from liquid to hexatic and solid phases

Abstract Due to its inherent intertwinement with irreversibility, entropy production is a prime observable to monitor in systems of active particles. In this numerical study, entropy production in the liquid, hexatic and solid phases of a two-dimensional system of active Brownian particles is examined at both average and fluctuation level. The trends of averages as functions of density show no singularity and marked changes in their derivatives at the hexatic-solid transition. Distributions show instead peculiar tail structures interpreted by looking at microscopic configurations. Particles in regions of low local order generate tail values according to different dynamical mechanisms: they move towards empty regions or bounce back and forth into close neighbours. The tail structures are reproduced by a simple single-particle model including an intermittent harmonic potential.

Dynamical clustering and wetting phenomena in inertial active matter

Dynamical clustering is a key feature of active matter systems composed of self-propelled agents that convert environmental energy into mechanical motion. At the micron scale, where overdamped dynamics dominate, particles with opposite motility can obstruct each other’s movement, leading to transient dynamical arrest. This arrest can promote cluster formation and motility-induced phase separation. However, in macroscopic agents, where inertia plays a significant role, clustering is heavily influenced by bounce-back effects during collisions, which can impede cluster growth. Here we present an experiment based on active granular particles, in which inertia can be systematically tuned by changing the shaker frequency. As a result, a set of phenomena driven and controlled by inertia emerges. Before the suppression of clustering, inertia induces a transition in the cluster’s inner structure. For small inertia, clusters are characterized by the crystalline order typical of overdamped particles, while for large inertia clusters with liquid-like order are observed. In addition, in contrast to microswimmers, where active particles wet the boundary by primarily forming clusters attached to the container walls, in an underdamped inertial active system, walls do not favor cluster formation and effectively annihilate motility-induced wetting phenomena. As a consequence, inertia suppresses cluster nucleation at the system boundaries.

From kinetic flocking model of Cucker–Smale type to self-organized hydrodynamic model

We investigate the hydrodynamic limit problem for a kinetic flocking model. We develop a GCI-based Hilbert expansion method, and establish rigorously the asymptotic regime from the kinetic Cucker–Smale model with a confining potential in a mesoscopic scale to the macroscopic limit system for self-propelled individuals, which is derived formally by Aceves-Sánchez et al. in 2019. In the traditional kinetic equation with collisions, for example, Boltzmann-type equations, the key properties that connect the kinetic and fluid regimes are: the linearized collision operator (linearized collision operator around the equilibrium), denoted by [Formula: see text], is symmetric, and has a nontrivial null space (its elements are called collision invariants) which include all the fluid information, i.e. the dimension of Ker([Formula: see text]) is equal to the number of fluid variables. Furthermore, the moments of the collision invariants with the kinetic equations give the macroscopic equations. The new feature and difficulty of the corresponding problem considered in this paper is: the linearized operator [Formula: see text] is not symmetric, i.e. [Formula: see text], where [Formula: see text] is the dual of [Formula: see text]. Moreover, the collision invariants lies in Ker([Formula: see text]), which is called generalized collision invariants (GCI). This is fundamentally different with classical Boltzmann-type equations. This is a common feature of many collective motions of self-propelled particles with alignment in living systems, or many active particle system. Another difficulty (also common for active system) is involved by the normalization of the direction vector, which is highly nonlinear. In this paper, using Cucker–Smale model as an example, we develop systematically a GCI-based expansion method, and micro–macro decomposition on the dual space, to justify the limits to the macroscopic system, a non-Euler-type hyperbolic system. We believe our method has wide applications in the collective motions and active particle systems.

Small Strain Stiffness of Sand‐Rubber Mixtures With Particle Size Disparity Effect

ABSTRACTThis study systematically investigates the small‐strain stiffness of sand‐rubber mixtures, focusing on combined particle disparity—both larger sand with smaller rubber and smaller sand with larger rubber—using the discrete element method. The effectiveness of various state variables in capturing stiffness behavior across different rubber contents and size disparities (SDs) is evaluated. Conventional state variables developed for natural sands, such as void ratio and mechanical void ratio were found to be less effective in describing the small‐strain stiffness characteristics of sand‐rubber mixtures due to distinct properties of rubber. This study then demonstrates that the stiffness contribution of rubber materials could be negligible, emphasizing that particle property disparity is more significant than SD between sand and rubber materials. Therefore, an adapted state variable, considering only active sand particles, shows improved performance for capturing the correlation between small‐strain stiffness with increasing rubber contents, suggesting its potential utility over conventional variables. Additionally, a refined void ratio, including inactive sand particles but excluding rubber, offers a practical alternative for capturing small‐strain stiffness in experimental and engineering practices, aligning with previous experimental observations. These findings underscore the need for developing more effective state variables that accurately reflect the interactions within heterogeneous materials like sand‐rubber mixtures.

Interrogating the Role of Stack Pressure in Transport‐Reaction Interaction in the Solid‐State Battery Cathode

AbstractAs solid‐state batteries (SSBs) emerge as leading contenders for next‐generation energy storage, chemo‐mechanical challenges and instabilities at solid‐solid interfaces remain a critical bottleneck. Ensuring sufficient interfacial contact within composite cathode architectures often requires the application of high stack pressures, posing a significant hurdle in the development of viable, large‐scale SSBs. In this work, the impact of stack pressure is investigated on the performance of solid‐state composite cathodes comprised of single‐crystal LiNi0.5Mn0.3Co0.2O2 (SC‐NMC532) active material particles and a Li6PS5Cl (LPSCl) solid electrolyte phase. By unraveling the complex interplay between stack pressure and microstructure‐dependent mechanisms, the profound influence on interfacial resistances, cathode utilization dynamics, current constriction effects, and lithiation heterogeneities are revealed. Through a comprehensive examination of coupled reaction kinetics and transport interactions at the electrode and particle length scales, the implications of stack pressure at different C‐rates and microstructural arrangements are elucidated, thereby delineating the limiting mechanisms that are prevalent at low stack pressures. This work underscores the critical role of optimizing the cathode microstructure to mitigate the chemo‐mechanical challenges associated with SSB operation at low stack pressures, offering valuable insights and design guidelines for the development of high‐performance SSBs.

Using zero nano-valent iron/thin film composite (ZNVI/TFC) membrane for brackish water desalination and purification

This study looked at the use of synthetic Zero Nano-valent Iron (ZNVI) particles in a unique interfacial polymerization technique on a polyamide thin film PA(TF) composite membrane for the treatment and desalination of brackish wastewater. Zero nano-valent iron (ZNVI) particles were created utilizing chemical reduction technique. ZNVI/PA(TF) NCs membrane is the outcome of advancing the PA(TF) membrane by combining with different concentration of ZNVI particles into the organic phase 1,3,5-benzenetricarbonyl trichloride (TMC). ZNVI/PA(TF) NCs membranes and ZNVI particles' surface properties were examined by the use of mechanical activity, contact angle, BET, FTIR, SEM, XRD, zeta potential, TEM analysis, and EDX studies. Using a variety of salt solutions, such as NaCl, Na2SO4, MgSO4, NaHCO3, CaSO4, CaCl2, and MgCl2, the ZNVI/PA(TF) NCs membrane performance towards salt rejection, flux (at varying pressure), anti-fouling activity, and ZNVI particles stability was assessed. This work investigated the removal efficiency of four dyes: methylene blue (MB), methyl orange (MO), Congo red (CR), and malachite green oxalate (MG). The water flux of the pristine PA(TF) membrane improved from 22 to 35 L/m2.h at 15 bar, indicating a 63% flux enhancement and the NaCl rejection was improved from 88.5 to 98.6%, indicating an 11.4% rejection improvement by incorporation of 0.3 wt.% of ZNVI particles into PA(TF) matrix. The ZNVI/PA(TF) NCs membrane's separation performances were evaluated using 5000 mg/L feed solutions of various salts at 15 bar. It was discovered that the water flux and salt rejection are, respectively, 33.4, 33, 32.7, 32, 31, 30 and 29 L/m2.h for CaSO4, MgSO4, Na2SO4, NaCl, CaCl2, MgCl2, and NaHCO3, and 97.4, 97, 96.5, 96, 94, 93.2, and 92.8%. It demonstrates that the flux recovery ratio (FRR) of the ZNVI/PA(TF) NCs membrane is greater than that of pristine PA(TF) (78%), coming in at 87%. High stability and fixing of the ZNVI particles on the modified membrane surface is indicated by the low overall ZNVI particles release rate over the course of the 10-day experiment.

Capture behavior of self-propelled particles into a hexatic ordering obstacle

Abstract Computer simulations are utilized to investigate the dynamic behavior of self-propelled particles (SPPs) within a complex obstacle environment. The findings reveal that SPPs exhibit three distinct aggregation states within the obstacle, each contingent on specific conditions. A phase diagram outlining the aggregation states concerning self-propulsion conditions is presented. The results illustrate a transition of SPPs from a dispersion state to a transition state as persistence time increases within the obstacle. Conversely, as the driving strength increases, self-propelled particles shift towards a cluster state. A systematic exploration of the interplay between driving strength, persistence time, and matching degree on the dynamic behavior of self-propelled particles is conducted. Furthermore, an analysis is performed on the spatial distribution of SPPs along the y-axis, capture rate, maximum capture probability, and mean-square displacement. The insights gained from this research serve as valuable contributions to understanding the capture and collection of active particles.

Mutability of Nucleation Particles in Reactive Salt Hydrate Phase Change Materials.

Nucleation particles, solid phases dispersed throughout a medium to decrease the energy barrier for solidification or other reversible phase transitions, are generally selected on the basis of structural or interfacial energy considerations between the host phase and the solid phase that is crystallizing. However, the existence of chemical reactions between the nucleation particles and the host phase can obscure these underlying relationships, thereby complicating the process of selection of active nucleation particle phases. Here, we reveal the origin of nucleation activity of barium-based nucleation particles in the salt hydrate calcium chloride hexahydrate (CCH), a candidate for near room temperature thermal energy storage. We demonstrate that these compounds undergo a series of cation exchange and secondary precipitation reactions, resulting in an assemblage of solid precipitates with some degree of limited solid solution, which collectively dramatically reduce undercooling in CCH, but which obscure the identification of a single crystalline phase primarily responsible for the nucleation of crystalline CCH from the liquid. Importantly, this result illustrates a pathway to harness in situ chemical reactions to generate stable active nucleation particles in reactive phase change materials, which may not be readily synthesized by alternative methods, or which may not be active or remain stable when added in isolation.