Disorder-to-order transition induced by spontaneous cooling regulation in robotic active matter

In classical matter systems, typical phase-transition phenomena usually stem from changes in state variables, such as temperature and pressure, induced by external regulations such as heat transfer and volume adjustment. However, in active matter systems, the self-propulsion nature of active particles endows the systems with the ability to induce unique collectivestate transitions by spontaneously regulating individual properties to alter the overall states. Based on an innovative robot-swarm experimental system, we demonstrate a field-driven active matter model capable of modulating individual motion behaviors through interaction with a recoverable environmental resource field by the resource perception and consumption.In the simulated model, by gradually reducing the individual resource-conversion coefficient over time, this robotic active matter can spontaneously decrease the overall level of motion, thereby actively achieving a regulation behavior like the cooling-down control. Through simulation calculations, we discover that the spatial structures of this robotic active matter convert from disorder to order during this process, with the resulting ordered structures exhibiting a high self-adaptability on the geometry of the environmental boundaries.

Orderly hysteresis in field-driven robot swarm active matter

Boundary effect and time-reversal symmetry are hot topics in active matter. We present a biology-inspired robotenvironment-interaction active matter system with the field-drive motion and the rules of resource search, resource consumption, and resource recovery. In an environmental compression–expansion cycle, the swarm emerges a series of boundary-dependent phase transitions, and the whole evolution process is time-reversal symmetry-breaking;we call this phenomenon “orderly hysteresis”. We present the influence of the environmental recovery rate on the dynamic collective behavior of the swarm.

Bio-inspired environmental adaptability of swarm active matter

How biologically active matters survive adaptively in complex and changeable environments is a common concern of scientists.Genetics,evolution and natural selection are vital factors in the process of biological evolution and are also the key to survival in harsh environments.However,it is challenging to intuitively and accurately reproduce such longterm adaptive survival processes in the laboratory.Although simulation experiments are intuitive and efficient,they lack fidelity.Therefore,we propose to use swarm robots to study the adaptive process of active matter swarms in complex and changeable environments.Based on a self-built virtual environmental platform and a robot swarm that can interact with the environment,we introduce the concept of genes into the robot system,giving each robot unique digital genes,and design robot breeding methods and rules for gene mutations.Our previous work[Proc.Natl.Acad.Sci.USA 119 e2120019119(2022)]has demonstrated the effectiveness of this system.In this work,by analyzing the relationship between the genetic traits of the population and the characteristics of environmental resources,and comparing different experimental conditions,we verified in both robot experiments and corresponding simulation experiments that agents with genetic inheritance can survive for a long time under the action of natural selection in periodically changing environments.We also confirmed that in the robot system,both breeding and mutation are essential factors.These findings can help answer the practical scientific question of how individuals and swarms can successfully adapt to complex,dynamic,and unpredictable actual environments.

Phase Transition in a Dense Swarm of Self-Propelled Bots

Swarms of self-organizing bots are becoming important elements in various technical systems,which include the control of bacterial cyborgs in biomedical applications,technologies for creating new metamaterials with internal structure,self-assembly processes of complex supramolecular structures in disordered media,etc.In this work,we theoretically study the effect of sudden fluidization of a dense group of bots,each of which is a source of heat and follows a simple algorithm to move in the direction of the gradient of the global temperature field.We show that,under certain conditions,an aggregate of self-propelled bots can fluidize,which leads to a second-order phase transition.The bots’program,which forces them to search for the temperature field maximum,acts as an effective buoyancy force.As a consequence,one can observe a sudden macroscopic circulation of bots from the edge of the group to its center and back again,which resembles classical Rayleigh-Benard thermal convection.In the continuum approximation,we have developed a mathematical model of the phenomenon,which reduces to the equation of a self-gravitating porous disk saturated with an incompressible fluid that generates heat.We derive governing equations in the Darcy-Boussinesq approximation and formulate a nonlinear boundary value problem.An exact solution to the linearized problem for infinitesimal perturbations of the base state is obtained,and the critical values of the control parameter for the onset of the bot circulation are calculated.Then we apply weakly nonlinear analysis using the method of multiple time scales.We found that as the number of bots increases,the swarm exhibits increasingly complex patterns of circulation.

Comparative study on active soil organic matter in Chinese fir plantation and native broad-leaved forest in subtropical China

Active soil organic matter (ASOM) has a main effect on biochemical cycles of soil nutrient elements such as N, P and S, and the quality and quantity of ASOM reflect soil primary productivity. The changes of ASOM fractions and soil nutrients in the first rotation site and the second rotation site of Chinese fir plantation and the native broad-leaved forest were investigated and analyzed by soil sampling at the Huitong Experimental Station of Forestry Ecology (at latitude 26°48′N and longitude 109°30′E under a subtropical climate conditions), Chinese Academy of Sciences in March, 2004. The results showed that values of ASOM fractions for the Chinese fir plantations were lower than those for the broad-leaved forest. The contents of easily oxidisable carbon (EOC), microbial biomass carbon (MBC), water soluble carbohydrate (WSC) and water-soluble organic carbon (WSOC) for the first rotation of Chinese fir plantation were 35.9%, 13.7%, 87.8% and 50.9% higher than those for the second rotation of Chinese fir plantation, and were 15.8%, 47.3%, 38.1% and 30.2% separately lower than those for the broad-leaved forest. For the three investigated forest sites, the contents of MBC and WSOC had a larger decrease, followed by WSC, and the change of EOC was least. Moreover, soil physico-chemistry properties such as soil nutrients in Chinese fir plantation were lower than those in broad-leaved forest. It suggested that soil fertility declined after Chinese fir plantation replaced native broad-leaved forest through continuous artificial plantation.

Microglia activation mediated by toll-like receptor-4 impairs brain white matter tracts in rats

Microglia activation and white matter injury coexist after repeated episodes of mild brain trauma and ischemic stroke. Axon degeneration and demyelination can activate microglia; however, it is unclear whether early microglia activation can impair the function of white matter tracts and lead to injury. Rat corpus callosum（CC） slices were treated with lipopolysaccharide（LPS） or LPS ＋ Rhodobacter sphaeroides（RS）-LPS that is a toll-like receptor 4（TLR-4） antagonist. Functional changes reflected by the change of axon compound action potentials（CAPs） and the accumulation of β-amyloid precursor protein（β-APP） in CC nerve fibers. Microglia activation was monitored by ionized calcium binding adaptor-1 immunofluorescent stain, based on well-established morphological criteria and paralleled proportional area measurement. Input-output（I/O） curves of CAPs in response to increased stimuli were significantly downshifted in a dose-dependent manner in LPS（0.2, 0.5 and 1.0μg/mL）-treated slices, implying that axons neurophysiological function was undermined. LPS caused significant β-APP accumulation in CC tissues,reflecting the deterioration of fast axon transport. LPS-induced I/O curve downshift and P-APP accumulation were significantly reversed by the pre-treatment or co-incubation with RS-LPS. RS-LPS alone did not change the I/O curve.The degree of malfunction was correlated with microglia activation, as was shown by the measurements of proportional areas. Function of CC nerve fibers was evidently impaired by microglia activation and reversed by a TLP-4 antagonist, suggesting that the TLP-4 pathway lead to microglia activation.

Graph dynamical networks for forecasting collective behavior of active matter

After decades of theoretical studies,the rich phase states of active matter and cluster kinetic processes are still of research interest.How to efficiently calculate the dynamical processes under their complex conditions becomes an open problem.Recently,machine learning methods have been proposed to predict the degree of coherence of active matter systems.In this way,the phase transition process of the system is quantified and studied.In this paper,we use graph network as a powerful model to determine the evolution of active matter with variable individual velocities solely based on the initial position and state of the particles.The graph network accurately predicts the order parameters of the system in different scale models with different individual velocities,noise and density to effectively evaluate the effect of diverse condition.Compared with the classical physical deduction method,we demonstrate that graph network prediction is excellent,which could save significantly computing resources and time.In addition to active matter,our method can be applied widely to other large-scale physical systems.

Variation in soil organic matter accumulation and metabolic activity along an elevation gradient in the Santa Rosa Mountains of Southern California, USA

Variations in soil organic matter accumulation across an elevation can be used to explain the control of substrate supply and variability on soil metabolic activity. We investigated geographic changes in soil organic matter and metabolic rates along an elevation gradient（289–2,489 m） in the Santa Rosa Mountains, California, USA from subalpine and montane pine forests through chaparral to desert. From base（289 m） to summit（2,489 m）, 24 sites were established for collecting soil samples under canopies and inter-canopy spaces, at 0–5 and 5–15 cm soil depths increments. Soil organic matter（SOM） content was determined using weight loss on ignition at 550°C and soil CO2 efflux（R） was measured at day 5（R5） and day 20（R20） of incubation. Changes in SOM content along the elevation gradient showed a significant relationship（P〈0.05） but R5 and R20 were not related to either elevation or SOM content. However, the ratio of R and SOM（R5/SOM） showed a strong relationship across the mountains at both soil depths. R5/SOM, as an indicator of carbon use efficiency, may be applicable to other semi-arid transects at larger scale modeling of soil metabolic processes.

Spatial distribution order parameter prediction of collective system using graph network

In the past few decades, the study of collective motion phase transition process has made great progress. It is also important for the description of the spatial distribution of particles. In this work, we propose a new order parameter φ to quantify the degree of order in the spatial distribution of particles. The results show that the spatial distribution order parameter can effectively describe the transition from a disorderly moving phase to a phase with a coherent motion of the particle distribution and the same conclusion could be obtained for systems with different sizes. Furthermore, we develop a powerful molecular dynamic graph network(MDGNet) model to realize the long-term prediction of the self-propelled collective system solely from the initial particle positions and movement angles. Employing this model, we successfully predict the order parameters of the specified time step. And the model can also be applied to analyze other types of complex systems with local interactions.

Emergent phenomena in chiral active matter

In recent years,there has been growing interest in the study of chiral active materials,which consist of building blocks that show active dynamics featuring chiral symmetry breaking,e.g.,particles that rotate in a common direction.These materials exhibit fascinating phenomena such as odd viscosity,odd diffusivity,active turbulence in fluids,vivid dislocation dynamics or odd elasticity in crystals or elastic materials,and hyperuniform states.The systematic study of soft chiral active matter systems is relatively new,starting around 2017,but has already shown promising applications in robust cargo transport,segregation and mixing dynamics,or manipulation of metamaterials.In this review,we summarize recent experimental and theoretical advances in this field,highlighting the emergence of anti-symmetric and odd stresses and ensuring effects such as odd viscosity or topologically protected edge modes.We further discuss the underlying mechanisms and provide insights into the potential of chiral active matter for various applications.

Macroscopic,artificial active matter

Artificial active matters on a macroscopic scale,including vibrating particles,robots,and camphor boats,have attracted increasing attentions due to their uniform properties,rich and easily controllable parameters,convenient observation,and the independence of biochemical processes from physical processes,especially providing these unique advantages for researching the collective behaviors under strong confinement and crowded surroundings.In this review,we present an overview of motion models,mechanisms,and dynamic characteristics of various active particles,both in free and complex media.Additionally,we delve into the collective behaviors of“dry”active matter,covering structural and dynamic properties observed in experiments and theoretical models.We summarize the impact of hydrodynamic interactions on the dynamics and structures of these active particles within hydrodynamic environments.Lastly,we discuss emerging opportunities and challenges for future advancement of macroscopic artificial active matter.

Physical principles at bio-nano interfaces with active matter

Active matter is characterized by out-of-equilibrium behaviors,offering an attractive,alternative route for revolutionizing disease diagnostics and therapy.A better understanding of how active matter interacts with cell membranes is critical to elucidating the underlying physical mechanisms and broadening the potential biomedical applications.This review provides a conceptual framework on the physiochemical mechanisms underlying active matter-biomembrane interactions.We briefly introduce the physical models of active matter and lipid membranes,and summarize the typical phenomena emerging from various active matter,including artificial active particles,cellular cytoskeletons,bacteria,and membrane proteins.Moreover,the remaining challenges and future perspectives of such non-equilibrium systems in living organisms are discussed.The findings and fundamental principles discussed in this review shed light on the rational design of activity-mediated cellular interaction,and could trigger better strategies to design and develop novel functional systems and materials toward advantageous biomedical applications.

Asymmetric nucleation processes in spontaneous mode switch of active matter

Flocking and vortical are two typical motion modes in active matter.Although it is known that the two modes can spontaneously switch between each other in a finite-size system,the switching dynamics remain elusive.In this work,by computer simulation of a two-dimensional Vicsek-like system with 1000 particles,we find from the perspective of the classical nucleation theory that the forward and backward switching dynamics are asymmetric:going from flocking to vortical is a one-step nucleation process,while the opposite is a two-step nucleation process,with the system staying in a metastable state before reaching the final flocking state.

Effects of Different Land Use Types on Soil Organic Carbon and Carbon Management Index in Karst Area

[Objective] The aim was to reveal changes of soil organic matter fraction and their corresponding carbon management indexes as affected by different land use types.[Method]Soil organic carbon,active soil organic carbon and soil carbon management index（CMI）of different land use types in Guilin Maocun karst area were studied.Sampling with field investigation and laboratory testing was carried out.Heavy potassium chromate method was adopted to determine soil organic matter.333 mmol/L KMnO4 oxidation method was used to determine active organic carbon.[Result]With active soil organic matter increasing,the differences of CMI between different land use types were bigger.The CMI value of different land uses was shrubforest paddy fielddry farmland.The statistical analysis showed that labile organic matter was related with major soil properties at a significant level.[Conclusion]Labile organic matter could be used to reveal the influence of different land use types on soil organic matter and carbon management index in karst area.

Symmetry properties of fluctuations in an actively driven rotor

We investigate rotational dynamics of an actively driven rotor through experiments and numerical simulations. While probability density distributions of rotor angular velocity are strongly non-Gaussian, relative probabilities of observing rotation in opposite directions are shown to be linearly related to the angular velocity magnitude. We construct a stochastic model to describe transitions between different states from rotor angular velocity data and use the stochastic model to show that symmetry properties in probability density distributions are related to the detailed fluctuation relation(FR) of entropy productions.

Reconstructing Environmental Changes of a Coastal Lagoon with Coral Reefs in Southeastern Hainan Island

Coastal lagoons with small catchment basins are highly sensitive to natural processes and anthropogenic activities. To figure out the environmental changes of a coastal lagoon and its contribution to carbon burial, two sediment cores were collected in Xincun Lagoon, southeastern Hainan Island and (210) ~Pb activities, grain size parameters, total organic carbon(TOC), total nitrogen(TN), total inorganic carbon(TIC) and stable carbon isotopes(δ^(13)C) were measured. The results show that in 1770–1815, the decreasing water exchange capacity with outer open water, probably caused by the shifting and narrowing of the tidal inlet, not only diminished the currents and fined the sediments in the lagoon, but also reduced the organic matter of marine sources. From 1815 to 1950, the sedimentary environment of Xincun Lagoon was frequently influenced by storm events. These extreme events resulted in the high fluctuation of sediment grain size and sorting, as well as the great variation in contributions of terrestrial(higher plants, soils) and marine sources(phytoplankton, algae, seagrass). The extremely high content of TIC, compared to TOC before 1950 could be attributed to the large-scale coverage of coral reefs. However, with the boost of seawater aquaculture activities after 1970, the health growth of coral species was severely threatened, and corresponding production and inorganic carbon burial flux reduced. The apparent enhanced inorganic carbon burial rate after 1990 might result from the concomitant carbonate debris produced by seawater aquaculture. This result is important for local government long-term coastal management and environmental planning.

Anomalous boundary deformation induced by enclosed active particles

We simulate a two-dimensional model of a round soft boundary enclosed with self-propelled particles. Persistent motion drives these particles to accumulate near the boundary, thereby dramatically deforming the boundary shape through collisions. Quantitative analyses of the boundary shape and the particle distribution show that there are two typical regimes in the variation of the morphology with the increase of self-propulsion of particles. One is under small forces, characterized by the radially inhomogeneous distribution of particles and the suppression of local fluctuations of the almost round boundary, and the other is under large forces, featured by the angularly inhomogeneous distribution of particles and the global shape deformation of the boundary. These two features are strongly cooperative. We also find different mechanisms in the particle relocation at low and high particle concentrations.

Active thermophoresis and diffusiophoresis

Thermophoresis and diffusiophoresis respectively refer to the directed drift of suspended particles in solutions with external thermal and chemical gradients, which have been widely used in the manipulation of mesoscopic particles. We here study a phoretic-like motion of a passive colloidal particle immersed in inhomogeneous active baths, where the thermal and chemical gradients are replaced separately by activity and concentration gradients of the active particles. By performing simulations, we show that the passive colloidal particle experiences phoretic-like forces that originate from its interactions with the inhomogeneous active fluid, and thus drifts along the gradient field, leading to an accumulation. The results are similar to the traditional phoretic effects occurring in passive colloidal suspensions, implying that the concepts of thermophoresis and diffusiophoresis could be generalized into active baths.

Simulation of microswimmer hydrodynamics with multiparticle collision dynamics

In this review we discuss the recent progress in the simulation of soft active matter systems and in particular the hydrodynamics of microswimmers using the method of multiparticle collision dynamics,which solves the hydrodynamic flows around active objects on a coarse-grained level.We first present a brief overview of the basic simulation method and the coupling between microswimmers and fluid.We then review the current achievements in simulating flexible and rigid microswimmers using multiparticle collision dynamics,and briefly conclude and discuss possible future directions.

Collective motion of active particles in environmental noise

We study the collective motion of active particles in environmental noise, where the environmental noise is caused by noise particles randomly diffusing in two-dimensional space. We show that active particles in a noisy environment can self organize into three typical phases： polar liquid, band, and disordered gas states. In our model, the transition between band and disordered gas states is discontinuous. Giant number fluctuation is observed in the polar liquid phase. We also compare our results with the Vicsek model and show that the interaction with noise particles can stabilize the band state to very low noise condition. This band structure could recruit most of the active particles in the system, which greatly enhances the coherence of the system. Our findings of complex collective behaviors in environmental noise help us to understand how individuals modify their self-organization by environmental factors, which may further contribute to improving the design of collective migration and navigation strategies.