Active glasses are a class of driven nonequilibrium systems that share remarkably similar dynamical behavior as conventional glass-formers in equilibrium. Glasslike dynamical characteristics have been observed in various biological systems from micro to macro length scales. As activity induces additional fluctuations in the system, studying how they couple with density fluctuations is an interesting question to address. Via extensive molecular dynamics simulations, we show that activity enhances density fluctuations more strongly than its passive counterpart. Increasing activity beyond a limit results in the sub-Arrhenius-type relaxation behavior in active glasses. We also propose a unified scaling theory that can rationalize the relaxation spectrum over a broad parameter range using the concept of an effective temperature. In particular, we show that our scaling theory can capture the dynamical crossover from super to sub-Arrhenius relaxation behavior by changing activity from small to large values. Furthermore, we present nontrivial system-size dependencies of the relaxation time at large activity limits that have not been found in any passive systems or even in active systems at small activities.

We study a competitive two-species ($A$ and $B$) reaction-diffusion model on a bipartite square lattice, where cooperative interactions lead to either particle coalescence or dispersal. The model is controlled by a coalescence-dispersion parameter $g$ and a maximum site occupancy per species, $n_o$. We investigate the system's phase transitions from an active to an absorbing state using both a site-based mean field approximation and Monte Carlo (MC) simulations. For single occupancy $(n_o=1)$, we find a discontinuous, first-order phase transition at a transition point $g_c=1$. The mean field calculations reveal a manifold of solutions at this point, leading to bistability between an active phase and an ordered, chessboardlike absorbing state—a mechanism of dynamic bistability confirmed by simulations. For multi-occupancy cases $(n_o\ge 2)$, the transition remains first order but occurs for $g_c<1$. Here, the absorbing phase is an infinitely degenerate manifold of disordered, jammed configurations. MC simulations show that the transition point $g_c$ increases with $n_o$ for $n_o\ge 2$. This trend seems to be driven by the role of coalescence as an antisegregation mechanism. As $n_o$ increases, the system becomes denser, enhancing this mixing effect and thus requiring a stronger dispersal probability (a higher $g_c$) to induce the transition to the segregated absorbing state. In this model, the site's storage capacity strongly alters the macroscopic transition mechanism.

We propose generalized variants of the $XY$ model capable of exhibiting an arbitrary number of phase transitions only by varying temperature. They are constructed by supplementing the magnetic coupling with $n_t-1$ nematic terms of exponentially increasing order with the base $q=2,3,4$, and 5, and increasing interaction strength. It is found that for $q=2,3$, and 4 with sufficiently large coupling strength of the final term, the models exhibit a number of phase transitions equal to the number of the terms in the generalized Hamiltonian. Starting from the paramagnetic phase, the system transitions through the cascade of $n_t-1$ nematic phases of the orders $q^k, k=n_t-1,n_t-2,\cdots ,1$, that are characterized by $q^k$ preferential spin directions symmetrically disposed around the circle, to the ferromagnetic (FM) phase at the lowest temperatures. Besides the Berezinskii-Kosterlitz-Thouless (BKT) transition from the paramagnetic phase, all the remaining transitions have a non-BKT nature: depending on the value of $q$ they belong to either the Ising ($q=2$ and 4) or the three-state Potts ($q=3$) universality class. For $q=5$, due to the interplay between different terms, the phase transitions between the ordered phases observed for $q<5$ split into two, and the number of the ordered phases increases to $2n_t-1$. These phases are characterized by a domain structure with the gradually increasing short-range FM ordering within domains that extends to different kinds of FM ordering in the last two low-temperature phases. The respective transitions do not seem to obey any universality.

Dynamic wetting poses a well-known challenge in classical sharp-interface formulation as the no-slip wall condition leads to a contact line singularity that is typically regularized with a Navier boundary condition, often requiring empirical fitting for the slip length. On the other hand, this paradox does not appear in phase-field models as the contact line moves through diffusive mass transport. In this work, we present a toy model that accounts for mass diffusion at the contact line within a sharp-interface framework. This model is based on a theoretical relation derived from the Cahn-Hilliard equations, which links the total diffusive mass transport to the curvature at the wall. From an estimate of the chemical potential on a curved interface, we obtain an expression for the width of the highly curved region $\delta$ and the apparent angle. In the sharp-interface model, we then introduce a fictitious boundary, displaced by a distance $\delta$ into the domain, where a Navier boundary condition is applied along a dynamic apparent contact angle that accounts for the local interface bending. The robustness of the model is assessed by comparing the toy model results with standard phase-field ones on two cases: the steady state profiles of a liquid bridge between two plates moving in opposite directions and the transient behaviors of a drop spreading on a solid with a prescribed equilibrium angle. This offers a practical and efficient alternative to solve contact line problems at lower cost in a sharp-interface framework with input parameters from phase-field models.

Carbonaceous dusty nanoparticles spontaneously grow in nonthermal plasmas from a gas mixture of argon and acetylene. These particles levitate and grow within the bulk plasma for a duration known as the growth cycle ($T_c$), after which they gradually move away. In experiments operating at 500 milliTorr, the particles reach a maximum radius of approximately 250 nm for $T_c\sim$ 121 s. However, the introduction of weak magnetic fields reduces both the maximum radius and $T_c$. The modified electron Hall parameter ($H_e^{\prime }$), which quantifies the degree of electron magnetization, increases linearly with the magnetic field strength, transitioning from unmagnetized electrons ($H_e^{\prime }<1$) to magnetized electrons ($H_e^{\prime }>1$). $T_c$ gradually decreases to around 40 s until $H_e^{\prime }\sim 1$ at approximately 330 Gauss, after which it remains roughly constant for fields up to about 1020 Gauss. Additionally, with increasing magnetic field strength, the dust growth rate initially decreases to $H_e^{\prime }\sim 1$, then increases slightly again. These results demonstrate that the onset of electron magnetization at can control the growth of nanoparticles from chemical precursors in nonthermal plasmas, which is relevant for industrial applications.

In this paper, a lattice Boltzmann model with a single-relaxation-time collision operator is proposed for two-phase flows at high Reynolds numbers based on the quasi-incompressible phase-field theory. The proposed model consists of two lattice Boltzmann equations (LBEs), one for the Cahn-Hilliard equation with singular mobility, and the other for the quasi-incompressible Navier-Stokes equations (qINSE). Particularly, the LBE for the qINSE adopts an equilibrium distribution function containing a free parameter related to the flow compressibility. As a result, the bulk viscosity of fluid can be independently adjusted to improve the numerical stability of the model. Several numerical tests including double periodic shear layers, static droplet, Rayleigh-Taylor instability, and rising bubble are conducted to verify the accuracy and stability of the proposed model. The results demonstrate that the enhanced bulk viscosity successfully suppresses high-frequency oscillations in the velocity and pressure fields, improving the numerical stability of the proposed model in simulating two-phase flows at high Reynolds numbers.

Ligand-coated metal nanoparticles assembled into lattices are known to exhibit properties arising from their particulate organization, where interparticle distances play a key role. Precisely controlling these distances through organic ligands is a compelling approach for designing self-assembled functional materials. Although this technique has been frequently employed, studies involving extended aromatic ligands that induce large interparticle separations remain uncommon. This work focuses on calculating the interaction potentials between solvated polycatenar-functionalized gold nanoparticles by introducing an analytical model based on attractive van der Waals forces and ligand-driven repulsive steric interactions. The equilibrium distances are shown to mainly depend on the ligand length, the overlap of ligand shells, and the conformational angle of the ligands with respect to the nanoparticle surface. The calculated equilibrium distances are found to be in good agreement with experimental data obtained by analyzing Langmuir-Blodgett monolayer films.

As a fundamental thermodynamic principle, speed limits reveal the lower bound of entropy production (EP) required for a system to transition from a given initial state to a final state. While various speed limits have been developed for continuous-time Markov processes, their application to discrete-time Markov chains remains unexplored. In this study, we investigate the speed limits in discrete-time Markov chains, focusing on two types of EP commonly used to measure the irreversibility of a discrete-time process: time-reversed EP and time-backward EP. We find that time-reversed EP satisfies the speed limit for the continuous-time Markov processes, whereas time-backward EP does not. Additionally, for time-reversed EP, we derive practical speed limits applicable to systems driven by cyclic protocols or with unidirectional transitions, where conventional speed limits become meaningless or invalid. We show that these relations also hold for continuous-time Markov processes by taking the time-continuum limit of our results. Finally, we validate our findings through several examples: toy models, experimentally established cell-state dynamics, and theoretical computation.

We study an active Brownian run-and-tumble particle (ABRTP) model that consists of an active Brownian run state, during which the active velocity of the particle diffuses on the unit circle, and a tumble state, during which the active velocity is zero, both with exponentially distributed time. Additionally, we add a harmonic trap as an external potential. In the appropriate limits the ABRTP model reduces either to the active Brownian particle model or the run-and-tumble particle model. Using the method of direct integration the equation of motion, pioneered by Kac, we obtain exact moments for the Laplace transform of the time-dependent ABRTP in the presence or absence of a harmonic trap. In addition, we estimate the distribution moments with the help of the Chebyshev polynomials. Our results are in excellent agreement with the experiments.

We establish a general lower bound for the entropy production rate (EPR) based on the Kullback-Leibler divergence and the logarithmic-Sobolev constant that characterizes the timescale of relaxation. This bound can be considered as an enhanced second law of thermodynamics. When applied to thermal relaxation, it reveals a universal trade-off relation between the dissipation rate and the intrinsic relaxation timescale. From this relation, a thermodynamic upper bound on the relaxation time between two given states emerges, acting as an inverse speed limit over the entire time region. We also obtain a quantum version of this upper bound, which is always tighter than its classical counterpart, incorporating an additional term due to decoherence. Remarkably, we further demonstrate that the trade-off relation remains valid for any generally non-Markovian coarse-grained relaxation dynamics, highlighting its significant applications in thermodynamic inference. This trade-off relation is a new tool in inferring EPRs in molecular dynamics simulations and practical experiments.

Time crystals are many-body systems whose ground state spontaneously breaks time-translation symmetry and thus exhibits long-range spatiotemporal order and robust periodic motion. Using hydrodynamics, we have recently shown how an $m$-th-order external packing field coupled to density fluctuations in driven diffusive fluids can induce the spontaneous emergence of time-crystalline order in the form of $m$ rotating condensates, which can be further controlled and modulated. Here, we analyze this phenomenon at the microscopic level in a paradigmatic model of particle diffusion under exclusion interactions, a generalization of the weakly asymmetric simple exclusion process with a configuration-dependent field called the time-crystal lattice gas. Using extensive Monte Carlo simulations, we characterize the nonequilibrium phase transition to these complex time-crystal phases for different values of $m$, including the order parameter, the susceptibility, and the Binder cumulant, from which we measure the critical exponents, which turn out to be within the Kuramoto universality class for oscillator synchronization. We also elucidate the condensate density profiles and velocities, confirming along the way a scaling property predicted for the higher-order condensate shapes in terms of first-order ones, discussing also some possibilities for this promising route to time crystals.

Hyperuniform continuous random fields suppress large‐scale fluctuations while preserving rich local disorder, making them highly attractive for next‐generation photonic, thermal, and mechanical materials. However, traditional construction techniques rendering digital realizations of the random fields often suffer from limited spectral control or excessive computational cost, especially in high‐resolution two- and three-dimensional settings. In this work we present a generative algorithm based on generalized superellipse spectral filtering, which allows independent tuning of isotropic and anisotropic spectral envelopes without resorting to costly iterative schemes. We demonstrate our method on a comprehensive set of two- and three-dimensional examples, showing precise manipulation of spectral band shape and speedup of orders of magnitude compared to existing approaches. Furthermore, we examine simple sign thresholding of the continuous fields and report the resulting $\pm 1$ two-phase maps, which inherit shell-shaped spectral motifs while generally not preserving exact hyperuniformity. This work opens new avenues for large‐scale simulation and optimized design of advanced hyperuniform materials.

We investigate the thermodynamics of overdamped systems weakly driven by time-dependent protocols while interacting with viscoelastic heat baths. Using a generalized Langevin equation with memory, we derive the conditions under which the friction kernel ensures thermodynamic consistency, notably requiring the addition of a Dirac delta. Within linear response theory, we compute the relaxation function and relaxation time for two classes of protocols: moving and stiffening harmonic traps. Surprisingly, we find that viscoelastic memory does not always hinder relaxation; in certain cases, it accelerates it by reducing the effective relaxation time, leading to lower dissipation. We also derive optimal protocols that minimize the irreversible work and show how they are modified by the presence of the persistence time of the viscoelastic heat bath. Our results reveal that memory effects in the overdamped regime leave measurable thermodynamic signatures, depending on the protocol, with direct implications for controlling complex systems.

Gene expression noise, the inherent randomness in protein levels, plays a crucial role in cellular heterogeneity and diverse responses to environmental conditions. While transcriptional bursts and their impact on noise have been extensively studied over the past two decades, recent experiments suggest that mRNA folding-unfolding kinetics can also create bursts in gene translation. This means mRNA can switch between active and inactive states, while gene translation occurs only when mRNA is in the active state. However, the combined influence of transcriptional and translational bursts on gene expression noise remains largely unexplored. To address this, we present a gene expression model that integrates both transcriptional and translational bursting phenomena to provide a detailed understanding of the factors governing protein noise. Using the generating function technique, we solve the model and derive analytical expressions for mean protein levels and noise in protein copy numbers. Our findings show that translational bursting significantly contributes to overall noise and the noise from transcriptional bursts further amplifies the relative contribution of translational noise. We also find that translation efficiency, defined as the rate of protein synthesis from a single mRNA transcript, increases the overall noise of gene expression at fixed protein levels. This dependence of gene expression noise on translation efficiency suggests that both translation and transcription kinetics are required to be tuned simultaneously to achieve specific protein levels and gene expression noise. Thus, this study improves our understanding of the factors regulating gene expression noise, providing insights into how transcriptional and translational bursting shape this noise.

Fractal features of permeable (e.g., porous or/and fractured) medium strongly affect the imbibition behavior in the Lucas-Washburn-like scaling regime. Mapping a spontaneous imbibition in a fractally permeable medium onto a fractal continuum flow allows us to establish the relations between the imbibition exponents and the fractal attributes of the pore-fracture network. In this way we found that the mass imbibition exponent is determined by the network topology, whereas the imbibition length exponent depends also on the geodesic metric along the imbibition streamlines. Our findings allow for the estimation of fractal attributes of natural reservoirs from the data of imbibition experiments and/or field observations, or vice versa.

Heteroatom-containing derivatives of 4-phenylmorpholine are cost-effective phosphorescent materials. In this study, femtosecond transient absorption (TA) spectroscopy of 4-phenylmorpholine reveals that the excited-state absorption signal at 625 nm decays as the triplet-triplet absorption (TTA) at 475 nm increases, thereby confirming that intersystem crossing (ISC) occurs within 2.27 ns. Subsequent nanosecond-TA measurements show that the TTA signal decays within 363.9 ns. To further understand how intermolecular interactions influence triplet excitons in crystalline environments, quantum-mechanics/molecular-mechanics simulations were performed. The simulations indicate that configurational changes are significantly smaller in crystals (0.15 Å) than in acetonitrile (0.38 Å), due to stronger intermolecular interactions that suppress molecular vibrations and reduce high-frequency recombination energy. Moreover, the ISC rate in crystals is 6 times higher ($6.85\times {10}^7{\mathrm{s}}^{-1}$) than in acetonitrile ($1.1\times {10}^7{\mathrm{s}}^{-1}$), attributed due to enhanced spin-orbit coupling and reduced energy gaps. These factors collectively suppress nonradiative transitions and extend exciton lifetimes.

We show that, for a standard continuously polydisperse model with particle-diameter distribution $P\left(\sigma \right)\propto {\sigma }^{-3}$ and polydispersity index $\mathrm{\Delta }$, employing a combination of standard SWAP moves and transient degree of freedom (TDOF) moves during a Lubachevsky-Stillinger-like particle-growth process dramatically increases the generated packings' jamming densities ${\varphi }_{\mathrm{J}}\left(\mathrm{\Delta }\right)$ and coordination numbers $Z_{\mathrm{J}}\left(\mathrm{\Delta }\right)$, for a wide range of $\mathrm{\Delta }$. The fractional increase in ${\varphi }_{\mathrm{J}}\left(\mathrm{\Delta }\right)$ obtained by employing these moves first increases rapidly with $\mathrm{\Delta }$, then plateaus at $6–7\%$ over the range $0.1\lesssim \mathrm{\Delta }\le 0.5$; the obtained ${\varphi }_{\mathrm{J}}$ are as high as 0.747 (for $\mathrm{\Delta }=0.50$). These density increases are achieved without producing clearly noticeable crystallization or increased fractionation, despite the fact that the packings are quite hyperstatic for all $\mathrm{\Delta }>0$. SWAP and TDOF moves also reduce packings' rattler populations by as much as 99% and increase their bulk moduli by as much as 80%.