Search

Active matter systems are inherently out of equilibrium and break the detailed balance (DB) at the microscopic scale, exhibiting vital collective phenomena such as motility-induced phase separation (MIPS). Here, we introduce a coarse-grained mapping method to probe DB breaking in the density-energy phase space, which allows us to reveal the dynamic and thermodynamic origins of MIPS based on nonequilibrium potential and flux landscape theory. Hallmarks of nonequilibrium properties are manifested by identifying the visible probability flux in the coarse-grained phase space. Remarkably, the flux for the system with the activity lower than the MIPS threshold tends to ``tear up" the single potential well of the uniform-density phase to create two wells of phases with different densities, presenting directly that the nonequilibrium flux is the dynamic origin of MIPS. Moreover, we find that the obtained entropy production rate (EPR) of the system undergoes a transition from nearly independent of activity to increasing proportionally as activity increases after the single well is "teared up". The transition of EPR's scaling behavior might provide a hint of the thermodynamic origin of MIPS in the coarse-grained space. Our findings propose a new route to explore the nonequilibrium nature of active systems, and provide new insights into dynamic and thermodynamic properties of MIPS., Comment: 4 figures

Active Brownian particles (ABPs) with pure repulsion is an ideal model to understand the effect of nonequilibrium on collective behaviors. It has long been established that activity can create effective attractions leading to motility-induced phase separation (MIPS), whose role is similar to that of (inverse) temperature in the simplest equilibrium system with attractive inter-particle interactions. Here, our theoretical analysis based on a kinetic theory of MIPS shows that a new type of activity-induced nonequilibrium vaporization is able to hinder the formation of dense phase when activity is large enough. Such nonequilibrium vaporization along with the activity-induced effective attraction thus lead to a MIPS reentrance. Numerical simulations verify such nonequilibrium effect induced solely by activity on phase behaviors of ABPs, and further demonstrate the dependence of MIPS on activity and the strength of inter-particle interaction predicted by our theoretical analysis. Our findings highlight the unique role played by the nonequilibrium nature of activity on phase behaviors of active systems, which may inspire deep insights into the essential difference between equilibrium and nonequilibrium systems., Comment: 4 pages, 2 figures

Various microswimmers move along circles rather than straight lines due to their swimming mechanisms, body shapes or hydrodynamic effects. Here, we adopt the concepts of stochastic thermodynamics to analyze circle swimmers confined in a two-dimensional plane, and study the trade-off relations between various physical quantities such as precision, energy cost and rotational speed. Based on these findings, we predict principles and strategies for designing microswimmers of special optimized functions under limited energy resource conditions, which will bring new experimental inspiration for designing smart motors., Comment: 8 pages, 4 figures

Motility-induced phase separation (MIPS) is of great importance and has been extensively researched in overdamped systems, nevertheless, what impacts inertia will bring on kinetics of MIPS is lack of investigation. Here, we find that, not only the phase transition changes from continuous to discontinuous, but also the formation of clusters exhibits a nucleation-like process without any coarsening regime, different from spinodal decomposition in the overdamped case. This remarkable kinetics stems from a competition between activity-induced accumulation of particles and inertia-induced suppression of clustering process. More interestingly, the discontinuity of MIPS still exists even when the ratio of particle mass to the friction coefficient reduces to be very small such as 0.0001. Our findings emphasize the importance of inertia in kinetics of MIPS, and may open a new perspective on understanding the nature of MIPS in active systems., Comment: 5 pages, 4 figures

As biochemical systems may frequently suffer from limited energy resources so that internal molecular fluctuation has to be utilized to induce random rhythm, it is still a great theoretical challenge to understand the elementary principles for biochemical systems with limited energy resources to maintain phase accuracy and phase sensitivity. Here, we address the issue by deriving the energy accuracy and the sensitivity-accuracy trade-off relations for a general biochemical model, analytically and numerically. We find that, biochemical systems consume much lower energy cost by noise-induced oscillations to keep almost equal efficiency to maintain precise processes than that by normal oscillations, elucidating clearly the survival mechanism when energy resources are limited. Moreover, an optimal system size is predicted where both the highest sensitivity and accuracy can be reached at the same time, providing a new strategy for the design of biological networks with limited energy sources.

We investigate configuration dynamics of a flexible polymer chain in a bath of active particles with dynamic chirality, i.e., particles rotate with a deterministic angular velocity $\omega$ besides self-propulsion,by Langevin dynamics simulations in two dimensional space. Particular attentions are paid to how the gyration radius $R_{g}$ changes with the propulsion velocity $v_{0}$,angular velocity $\omega$ and chain length. We find that in a chiral bath with a typical nonzero $\omega$, the chain first collapses into a small compact cluster and swells again with increasing $v_{0}$, in quite contrast to the case for a normal achiral bath $(\omega=0)$ wherein a flexible chain swells with increasing $v_{0}$. More interestingly, the polymer can even form a closed ring if the chain length is large enough,which may oscillate with the cluster if $v_{0}$ is large. Consequently, the gyration radius $R_{g}$ shows nontrivial non-monotonic dependences on $v_{0}$, i.e., it undergoes a minimum for relatively short chains, and two minima with a maximum in between for longer chains. Our analysis shows that such interesting phenomena are mainly due to the competition between two roles played by the chiral active bath: while the persistence motion due to particle activity tends to stretch the chain, the circular motion of the particle may lead to an effective osmotic pressure that tends to collapse the chain. In addition, the size of the circular motion $R_{0}=v_{0}/\omega$ shows an important role in that the compact clusters and closed-rings are both observed at nearly the same values of $R_{0}$ for different $\omega$.

Understanding stochastic thermodynamics of active Brownian particles (ABPs) system has been an important topic in very recent years. In this article we study a general model of active Brownian particle systems by introducing a coarse-grained Fokker-Planck equation, which allows us to identify an effective entropy production along a stochastic trajectory, wherein an activity and configuration dependent diffusion coefficient comes into play with an important role. Although the hidden component between the true entropy production and the effective one is dominant, the effective entropy production still act as a reliable measure to quantify the dynamical irreversibility, capturing important phenomenon such as the interface and defects of motility induced phase separation (MIPS). Furthermore, in this framework, we are able to obtain the entropic bound as well as TUR associated with any generalized currents in the systems. We expect the new conceptual quantities proposed here to be broadly used in the context of active matter., Comment: 9 pages, 4 figure

Formation of highly ordered structures usually needs to overcome a high free-energy barrier that is greatly beyond the ability of thermodynamic fluctuation, such that the system would be easily trapped into a state with many defects and the annealing process of which often occurs on unreachable long time-scales. Here we report a fascinating example theoretically that active core corona particles can successfully self-assemble into a large-scaled and highly ordered stripe or trimer lattice, which is hardly achieved in a non-driven equilibrium system. Besides, such an activity-induced ordered structure shows an interesting self-healing feature of defects. In addition, there exists an optimal level of activity that most favorably enhance the formation of ordered self-assembly structures. Since core corona particles act as important units for self-assembly in real practice, we believe our study opens a new design-strategy for highly ordered materials., Comment: 8 pages, 6 figures

Disordered hyperuniformity, a brand new type of arrangements with novel physical properties, provides various practical applications in extensive fields. To highlight the great potential of applying disordered hyperuniformity to active systems, a practical example is reported here by an optimal sorting of dynamically chiral microswimmers in disordered hyperuniform obstacle environments in comparison with regular or disordered ones. This optimal chirality sorting stems from a competition between advantageous microswimmer-obstacle collisions and disadvantageous trapping of microswimmers by obstacles. Based on this mechanism, optimal chirality sorting is also realized by tuning other parameters including the number density of obstacles, the strength of driven force and the noise intensity. Our findings may open a new perspective on both theoretical and experimental investigations for further applications of disordered hyperuniformity in active systems., Comment: 6 pages, 5 figures

Efficient chirality sorting is now highly demanded to separate assembled mesoscopic chiral structures which are of very special physical properties rather than their achiral counterparts or those at the single-particle level. However, the efficiency of conventional methods usually suffers from the thermal or external noise. Here, we propose a mechanism utilizing external noise to attain a tunable sorting of mesoscopic chiral particles in an achiral periodic potential. The complete chirality-separation stems from the path selection by a noise-induced biased flux in a nonequilibrium landscape. Such mechanism provides a practicable way to control the motion of chiral particles by simply adjusting the noise intensity, which is demonstrated by simultaneous separation of several kinds of enantiomorphs with different degrees of chirality. The robustness and generalizability of noise-tuned chirality sorting is further verified in systems with other types of periodic potentials or spatially/temporally correlated noise., Comment: 7 figures

We introduce for the first time a general model of biased-active particles, where the direction of the active force has a biased angle from the principle orientation of the anisotropic interaction between particles. We find that a highly ordered living superlattice consisting of small clusters with dynamic chirality emerges in a mixture of such biased-active particles and passive particles. We show that the biased-propulsion-induced instability of active-active particle pairs and rotating of active-passive particle pairs are the very reason for the superlattice formation. In addition, a biased-angle-dependent optimal active force is most favorable for both the long-range order and global dynamical chirality of the system. Our results demonstrate the proposed biased-active particle providing a great opportunity to explore a variety of new fascinating collective behaviors beyond conventional active particles.

Emergence of collective dynamical chirality (CDC) at mesoscopic scales plays a key role in many formation processes of chiral structures in nature, which may also provide possible routines for people to fabricate complex chiral architectures. So far, most of reported CDCs are found in systems of active objects with individual structure chirality or/and dynamical chirality, and whether CDC can arise from simple and achiral units is still an attractive mystery. Here, we report a spontaneous formation of CDC in a system of both dynamically and structurally achiral particles motivated by active motion of cells. Active moving, confinement and hydrodynamic interaction are found to be the three key factors. Detailed analysis shows that the system can support abundant collective dynamical behaviors, including rotating droplet, rotating bubble, CDC oscillation, array of collective rotation, as well as interesting transitions such as chirality transition, structure transition and state reentrance., Comment: 5 pages, 4 figures

Epitaxial growth via chemical vapor deposition is considered to be the most promising way towards synthesizing large area graphene with high quality. However, it remains a big theoretical challenge to reveal growth kinetics with atomically energetic and large-scale spatial information included. Here, we propose a minimal kinetic Monte Carlo model to address such an issue on an active catalyst surface with graphene/substrate lattice mismatch, which facilitates us to perform large scale simulations of the growth kinetics over two dimensional surface with growth fronts of complex shapes. A geometry-determined large-scale growth mechanism is revealed, where the rate-dominating event is found to be $C_{1}$-attachment for concave growth front segments and $C_{5}$-attachment for others. This growth mechanism leads to an interesting time-resolved growth behavior which is well consistent with that observed in a recent scanning tunneling microscopy experiment., Comment: 5 pages, 3 figures

We develop a mode coupling theory(MCT) to study the nonequilibrium glass transition behavior of a mono-disperse mixture of active-passive hard-sphere particles. The MCT equations clearly demonstrate that the glass transition is shifted to higher values of total volume fraction when doping a passive system with active particles. Interestingly, we find that the glass transition point may show a non-monotonic dependence on the effective diffusivity of the active component, indicating a nontrivial type of activity induced reentrance behavior. Analysis based on the nonergodic parameters suggest that the glassy state at small activity is due to the caging effect, while that at high activity could result from activity induced dynamic clustering., Comment: 11 pages, 2 figures

Rare events such as nucleation processes are of ubiquitous importance in real systems. The most popular method for nonequilibrium systems, forward flux sampling (FFS), samples rare events by using interfaces to partition the whole transition process into sequence of steps along an order parameter connecting the initial and final states. FFS usually suffers from two main difficulties: low computational efficiency due to bad interface locations and even being not applicable when trapping into unknown intermediate metastable states. In the present work, we propose an approach to overcome these difficulties, by self-adaptively locating the interfaces on the fly in an optimized manner. Contrary to the conventional FFS which set the interfaces with euqal distance of the order parameter, our approach determines the interfaces with equal transition probability which is shown to satisfy the optimization condition. This is done by firstly running long local trajectories starting from the current interface $\l_i$ to get the conditional probability distribution $P_c$, and then determining $\l_{i+1}$ by equalling $P_c$ to a give value $p_0$. With these optimized interfaces, FFS can be run in a much efficient way. In addition, our approach can conveniently find the intermediate metastable states by monitoring some special long trajectories that nither end at the initial state nor reach the next interface, the number of which will increase sharply from zero if such metastable states are encountered. We apply our approach to a model two-state system and a two-dimensional lattice gas Ising model. Our approach is shown to be much more efficient than the conventional FFS method without losing accuracy, and it can also well reproduce the two-step nucleation scenario of the Ising model with easy identification of the intermidiate metastable state., Comment: 6 pages, 6 figures

Although the corresponding carbon-metal interactions can be very different, a similar nonlinear growth behavior of graphene has been observed for different metal substrates. To understand this interesting experimental observation, a multiscale $\lq\lq$standing-on-the-front" kinetic Monte Carlo study is performed. An extraordinary robust geometry effect is identified, which solely determines the growth kinetics and makes the details of carbon-metal interaction not relevant at all. Based on such a geometry-determined mechanism, epitaxial growth behavior of graphene can be easily predicted in many cases. As an example, an orientation-sensitive growth kinetics of graphene on Ir(111) surface has been studied. Our results demonstrate that lattice mismatch pattern at the atomic level plays an important role for macroscopic epitaxial growth., Comment: 5 pages, 3 figures, 2 tables