Interfacial-Assembly-Induced In Situ Transformation from Aligned 1D Nanowires to Quasi-2D Nanofilms.

As the dimensionality of materials generally affects their characteristics, thin films composed of low-dimensional nanomaterials, such as nanowires (NWs) or nanoplates, are of great importance in modern engineering. Among various bottom-up film fabrication strategies, interfacial assembly of nanoscale building blocks holds great promise in constructing large-scale aligned thin films, leading to emergent or enhanced collective properties compared to individual building blocks. As for 1D nanostructures, the interfacial self-assembly causes the morphology orientation, effectively achieving anisotropic electrical, thermal, and optical conduction. However, issues such as defects between each nanoscale building block, crystal orientation, and homogeneity constrain the application of ordered films. The precise control of transdimensional synthesis and the formation mechanism from 1D to 2D are rarely reported. To meet this gap, we introduce an interfacial-assembly-induced interfacial synthesis strategy and successfully synthesize quasi-2D nanofilms via the oriented attachment of 1D NWs on the liquid interface. Theoretical sampling and simulation show that NWs on the liquid interface maintain their lowest interaction energy for the ordered crystal plane (110) orientation and then rearrange and attach to the quasi-2D nanofilm. This quasi-2D nanofilm shows enhanced electric conductivity and unique optical properties compared with its corresponding 1D geometry materials. Uncovering these growth pathways of the 1D-to-2D transition provides opportunities for future material design and synthesis at the interface.

Rotation and Self-Assembly Driving NLRP3 Activation.

As a critical sensor protein, NLRP3 detects cellular perturbation caused by diverse exogenous and endogenous stimuli. NLRP3 activation requires domain rotation within the NEK7-bound NLRP3 monomer and assembly. However, a detailed molecular mechanism for NLRP3 assembly and activation remains elusive, particularly in terms of dynamics and energetics. In this work, all-atom molecular dynamics (MD) simulations are executed to describe large-amplitude closed-to-open conformational transitions along the rotational pathway. From the MD trajectories, the computed potential of mean force (PMF) shows that NLRP3 activation through monomeric domain rotation is an uphill process, during which the active conformation of the NLRP3-NEK7 monomer cannot be stabilized. Further binding free-energy calculations for two neighboring NLRP3-NEK7 subunits in a disc assembly with the C10 symmetry reveal that the protein self-assembly starts approximately at the 86.5° position on the rotary pathway, along which the NLRP3 activation becomes a downhill process to the active state at 90.5°. The active NLRP3-NEK7 monomeric conformation in the disc assembly is stabilized because of the interactions between the neighboring subunits, involving mainly FISNA loop 1 in one subunit and a "crocodile-clip" structure formed by the NBD helix-loop-strand motif (residues 351-373) and the WHD ß-hairpin loop (residues 501-521) in the other. Our simulations also demonstrate that NEK7 plays an important role in the NLRP3 cage dissociation in the centrosome, which is consistent with biological experiments. The computational results provide kinetic, energetic, and structural insights into the molecular mechanisms of the activation of NLRP3 and the NEK7-driven dissociation of inactive NLRP3 cages. The activation mechanism of NLRP3 proposed in this work is significantly different from those of previous structural studies.

Quorum sensing-induced transition from colloidal waves to Turing-like patterns in chemorepulsive active colloids.

The study of active systems, especially in the presence of a chemical background field, is garnering significant attention. Traditionally, the self-propelled velocity of active colloids was assumed to be constant, independent of the local density of colloids. In this work, we introduce a chemotactic active system that features quorum sensing (QS), wherein particles act as chemorepellents. Interestingly, these particles lose their activity in regions of high local particle density. Our findings reveal that QS leads to a transition from an oscillatory colloidal wave to a Turing-like pattern, with the observation of an intermediate state. With the variation of the sensing threshold, both the mean oscillation frequency of the system and the number of clusters exhibit non-monotonic dependence. Furthermore, the QS-induced pattern differs markedly from systems without QS, primarily due to the competitive interplay between diffusion and chemotaxis. The dynamics of this phenomenon are explained using a coarse-grained mean field model.

Nonlinear chemical reaction induced abnormal pattern formation of chemotactic particles.

The chemotactic behavior of particles is a widespread and important phenomenon that enables them to interact with the chemical species present in the environment. These chemical species can undergo chemical reactions and even form some non-equilibrium chemical structures. In addition to chemotaxis, particles can also produce or consume chemicals, which allows them to further couple with chemical reaction fields and thus influence the dynamics of the whole system. In this paper, we consider a model of chemotactic particle coupling with nonlinear chemical reaction fields. Intriguingly, we find the aggregation of particles occurs when they consume substances and move toward high-concentration areas, which is quite counterintuitive. In addition, dynamic patterns can also be found in our system. These results imply that the interaction between chemotactic particles and nonlinear reactions can result in much novel behavior and may further extend to explain the complex phenomena in certain systems.

Mode-coupling theory for the dynamics of dense underdamped active Brownian particle system.

We present a theory to study the inertial effect on glassy dynamics of the underdamped active Brownian particle (UABP) system. Using the assumption of the nonequilibrium steady-state, we obtain an effective Fokker-Planck equation for the probability distribution function (PDF) as a function of positions and momentums. With this equation, we achieve the evolution equation of the intermediate scattering function through the Zwanzig-Mori projection operator method and the mode-coupling theory (MCT). Theoretical analysis shows that the inertia of the particle affects the memory function and corresponding glass transition by influencing the structure factor and a velocity correlation function. The theory provides theoretical support and guidance for subsequent simulation work.

Cascade-enhanced transport efficiency of biochemical systems.

Recent developments in nonequilibrium thermodynamics, known as thermodynamic uncertainty relations, limit the system's accuracy by the amount of free-energy consumption. A transport efficiency, which can be used to characterize the capacity to control the fluctuation by means of energy cost, is a direct result of the thermodynamic uncertainty relation. According to our previous research, 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. Here, we demonstrate that the performance of noise-induced oscillations propagating can be further improved through a cascade reaction mechanism. It has been discovered that it is possible to considerably enhance the transport efficiency of the biochemical reactions attained at the terminal cell, allowing the cell to use the cascade reaction mechanism to operate more precisely and efficiently. Moreover, an optimal reaction coupling strength has been predicted to maximize the transport efficiency of the terminal cell, uncovering a concrete design strategy for biochemical systems. By using the local mean field approximation, we have presented an analytical framework by extending the stochastic normal form equation to the system perturbed by external signals, providing an explanation of the optimal coupling strength.

Surface Engineering on Commercial Cu Foil for Steering C2H4/CH4 Ratio in CO2 Electroreduction.

Designing catalysts with high selectivity toward C2 products in CO2 electroreduction is crucial to energy storage and sustainable development. Here, we propose a Cu foil kinetic model with abundant nanocavities possessing higher reaction rate constant k to steer the ratio of C2H4 to the competing CH4 during CO2 electroreduction. Chemical kinetic simulation demonstrates that the nanocavities could enrich the adsorbed CO surface concentration (θCOad), while the higher k helps to lower the C-C coupling barrier for CO intermediates, thus favoring the formation of C2H4. The commercial Cu foil treated with cyclic voltammetry is used to match this model, displaying a remarkable C2H4/CH4 ratio of 4.11, which is 18 times larger than that on the pristine Cu foil. This work offers a handy strategy for surface modification and provides new insights into the C-C coupling and the C2H4 selectivity in terms of mass transfer flux and energy barrier.

Improved estimation for energy dissipation in biochemical oscillations.

Biochemical oscillations, regulating the timing of life processes, need to consume energy to achieve good performance on crucial functions, such as high accuracy of the phase period and high sensitivity to external signals. However, it is a great challenge to precisely estimate the energy dissipation in such systems. Here, based on the stochastic normal form theory, we calculate the Pearson correlation coefficient between the oscillatory amplitude and phase, and a trade-off relation between transport efficiency and phase sensitivity can then be derived, which serves as a tighter form than the estimator resulting from the conventional thermodynamic uncertainty relation. Our findings demonstrate that a more precise energy dissipation estimation can be obtained by enhancing the sensitivity of the biochemical oscillations. Moreover, the internal noise and amplitude power effects have also been discovered.

Microchemical Engineering in a 3D Ordered Channel Enhances Electrocatalysis.

The kinetics of electrode reactions including mass transfer and surface reaction is essential in electrocatalysis, as it strongly determines the apparent reaction rates, especially on nanostructured electrocatalysts. However, important challenges still remain in optimizing the kinetics of given catalysts with suitable constituents, morphology, and crystalline design to maximize the electrocatalytic performances. We propose a comprehensive kinetic model coupling mass transfer and surface reaction on the nanocatalyst-modified electrode surface to explore and shed light on the kinetic optimization in electrocatalysis. Moreover, a theory-guided microchemical engineering (MCE) strategy has been demonstrated to rationally redesign the catalysts with optimized kinetics. Experimental measurements for methanol oxidation reaction in a 3D ordered channel with tunable channel sizes confirm the calculation prediction. Under the optimized channel size, mass transfer and surface reaction in the channeled microreactor are both well regulated. This MCE strategy will bring about a significant leap forward in structured catalyst design and kinetic modulation.

Local Field Induced Mass Transfer: New Insight into Nano-electrocatalysis.

Unravelling the complex kinetics of electrocatalysis is essential for the design of electrocatalysts with high performance. Mass transfer and electron transfer are two primary factors that need to be optimized in order to enhance electrocatalytic reactions. The use of nanocatalysts proves to be a promising way of promoting the performance of electrocatalytic reactions, this improvement is usually attributed to their ability to enhance electron transfer. However, when catalysts are taken down to the nanoscale, their size is comparable to the thickness of an electrical double layer, so any curvature can lead to an inhomogeneous local electric field on the electrode, which then changes the mass transfer essentially. In this article, we introduce the new concept of local-field-induced mass transfer in nano-electrocatalytic systems, and provide a brief review of recent progress, revealing its effect on nano-electrocatalysis, which may bring new insight into the future design of nano-electrocatalysts.

Designing circle swimmers: Principles and strategies.

Various microswimmers move along circles rather than straight lines due to their swimming mechanisms, body shapes, or hydrodynamic effects. In this paper, we adopt the concepts of stochastic thermodynamics to analyze circle swimmers confined to 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.

Radial Nanowire Assemblies under Rotating Magnetic Field Enabled Efficient Charge Separation.

Developing efficient charge separation strategies is essential to achieve high-power conversion efficiency in the fields of chemistry, biology, and material science. Herein, we develop a facile strategy for fabrication of unique wafer-scale radial nanowire assemblies by exploiting shear force in rotary solution. The assembly mechanism can be well revealed by the large-scale stochastic dynamics simulation. Free electrons can be rapidly generated to produce quantitatively tunable current output when the radial nanowire assemblies rotate under the magnetic field. Moreover, the photoconductive performance of the radial semiconductor nanowire assemblies can be remarkably enhanced as the electron-hole recombination was retrained by the efficient charge separation under the rotating magnetic field. Such large-scale unique nanowire assemblies will facilitate the design of an efficient charge separation process in biosystem, sensors, and photocatalysis.

Hidden Mechanism Behind the Roughness-Enhanced Selectivity of Carbon Monoxide Electrocatalytic Reduction.

High roughness has been proved to be an effective design strategy for electrocatalyst in many systems. Especially, high selectivity of carbon monoxide reduction (CORR) in competition with the hydrogen evolution reaction has been observed on high roughness electrocatalysts. However, the two well-known mechanisms, i.e., decreasing the energy barrier of CORR and increasing local pH, failed to understand the roughness-enhanced selectivity in a recent experiment. Herein we unravel the hidden mechanism by establishing a comprehensive kinetic model for CORR on catalysts with different roughness factors. We conclude that the roughness-enhanced CORR selectivity is actually kinetic controlled by local-electric-field-directed mass transfer of adsorbed species on the electrode surface. Several ways to optimize CORR selectivity are predicted. Our work highlights the kinetics in electrocatalysis on nanocatalysts, and provides a conceptually new principle for future catalyst design.

Rod-assisted heterogeneous nucleation in active suspensions.

Motility induced phase separation as well as the nucleation process in active particle systems has gained extensive research attention very recently. Most studies so far have considered homogeneous cases without the influence of foreign seeds or impurities; however, the heterogeneous nucleation process, widely studied in passive systems, has not been systematically investigated yet. Here we study the heterogeneous nucleation process and phase behaviors of a suspension of active Brownian particles by introducing a rod-like passive seed. We found that such a seed can exponentially accelerate the nucleation rate and thus readily induce phase separation of a dilute active system, while a homogeneous one with the same volume fraction still maintains a single phase. It is observed that the seed would automatically detach from the dense phase after the completion of phase separation instead of staying inside as an impurity. Interestingly, we found that the phase behavior is re-entrant with the activity: single-phase states exist at both high and low activities, with phase separated states in between. Our results demonstrate that heterogeneous nucleation in an active system can show novel behaviors with respect to its passive counterpart, and pave the way for more future studies in relevant fields.

Non-monotonic dependence of polymer chain dynamics on active crowder size.

Configuration dynamics of flexible polymer chains is of ubiquitous importance in many biological processes. Here, we investigate a polymer chain immersed in a bath of size-changed active particles in two dimensional space using Langevin dynamics simulations. Particular attention is paid to how the radius of gyration Rg of the polymer chain depends on the size σc of active crowders. We find that Rg shows nontrivial non-monotonic dependence on σc: The chain first swells upon increasing σc, reaching a fully expanded state with maximum Rg, and then, Rg decreases until the chain collapses to a compact coil state if the crowder is large enough. Interestingly, the chain may oscillate between a collapse state and a stretched state at moderate crowder size. Analysis shows that it is the competition between two effects of active particles, one stretching the chain from inside due to persistence motion and the other compressing the chain from outside, that leads to the non-monotonic dependence. Besides, the diffusion of the polymer chain also shows nontrivial non-monotonic dependence on σc. Our results demonstrate the important interplay between particle activity and size associated with polymer configurations in active crowding environments.

Ordered Nanostructure Enhances Electrocatalytic Performance by Directional Micro-Electric Field.

Designing high-efficiency catalyst is at the heart of a transition to future renewable energy systems. Great achievements have been made to optimize thermodynamics to reduce energetic barriers of the catalytic reactions. However, little attention has been paid to design catalysts to improve kinetics to enrich the local concentration of reactant molecules surrounding electrocatalysts. Here, we find that well-designed nanocatalysts with periodic structures can optimize kinetics to accelerate mass-transport from bulk electrolyte to the catalyst surface, leading to the enhanced catalytic performance. This achievement stems from regulation of the surface reactant flux due to the gradient of the microelectric field directing uniformly to the nearest catalyst on ordered pattern, so that all of the reactant molecules are utilized sufficiently for reactions, enabling the boost of the electrocatalytic performance. This novel concept is further confirmed in various catalytic systems and nanoassemblies, such as nanoparticles, nanorods, and nanoflakes.

Disordered hyperuniform obstacles enhance sorting of dynamically chiral microswimmers.

Disordered hyperuniformity, a brand new type of arrangement 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.

Assembled superlattice with dynamic chirality in a mixture of biased-active and passive particles.

We introduce a general model of biased-active particles (BAPs) with anisotropic interactions, where the direction of the active force has a nonzero biased angle from the principal orientation of the anisotropic interaction between particles, and investigate the self-assembly behaviors of a mixture of BAPs with passive particles by using Langevin dynamics simulations. Remarkably, a highly ordered superlattice consisting of small hexagonal clusters with dynamic chirality emerges within a proper range of active force, given that the biased angle is not too small. In addition, there exists an optimal level of particle activity, being dependent on the biased-angle, which is the most favorable for both the long-range order and global dynamic chirality of the system. Our results demonstrate that fascinating collective behaviors can be explored through a proper design of new active particle models.

Study of active Brownian particle diffusion in polymer solutions.

The diffusion behavior of an active Brownian particle (ABP) in polymer solutions is studied using Langevin dynamics simulations. We find that the long time diffusion coefficient D can show a non-monotonic dependence on the particle size R if the active force Fa is large enough, wherein a bigger particle would diffuse faster than a smaller one which is quite counterintuitive. By analyzing the short time dynamics in comparison to the passive one, we find that such non-trivial dependence results from the competition between persistent motion of the ABP and the length-scale dependent effective viscosity that the particle experiences in the polymer solution. We have also introduced an effective viscosity ηeff experienced by the ABP phenomenologically. Such an active ηeff is found to be larger than a passive one and strongly depends on R and Fa. In addition, we find that the dependence of D on propelling force Fa presents a good power-law scaling at a fixed R and the scaling factor changes non-monotonically with R. Such results demonstrate that the active process plays rather subtle roles in the diffusion of nano-particles in complex solutions.

Configuration dynamics of a flexible polymer chain in a bath of chiral active particles.

We investigate the 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 ω besides self-propulsion, by Langevin dynamics simulations in a two dimensional space. Particular attention is paid to how the radius of gyration Rg changes with the propulsion velocity v0, the angular velocity ω, and the chain length N. We find that in a chiral bath with a typical nonzero ω, the chain first collapses into a small compact cluster and then swells again with increasing v0, in quite contrast to the case for a normal achiral bath (ω = 0) wherein a flexible chain swells with increasing v0. More interestingly, the polymer can even form a closed ring if the chain length N is large enough, which may oscillate with the cluster if v0 is large. Consequently, the gyration radius Rg shows nontrivial nonmonotonic dependences on v0, 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 R0 = v0/ω plays an important role in that the compact clusters and closed-rings are both observed at nearly the same values of R0 for different ω.