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.

Root endophyte-mediated alteration in plant H2O2 homeostasis regulates symbiosis outcome and reshapes the rhizosphere microbiota.

Endophytic symbioses between plants and fungi are a dominant feature of many terrestrial ecosystems, yet little is known about the signaling that defines these symbiotic associations. Hydrogen peroxide (H2O2) is recognized as a key signal mediating the plant adaptive response to both biotic and abiotic stresses. However, the role of H2O2 in plant-fungal symbiosis remains elusive. Using a combination of physiological analysis, plant and fungal deletion mutants, and comparative transcriptomics, we reported that various environmental conditions differentially affect the interaction between Arabidopsis and the root endophyte Phomopsis liquidambaris, and link this process to alterations in H2O2 levels and H2O2 fluxes across root tips. We found that enhanced H2O2 efflux leading to a moderate increase in H2O2 levels at the plant-fungal interface is required for maintaining plant-fungal symbiosis. Disturbance of plant H2O2 homeostasis compromises the symbiotic ability of plant roots. Moreover, the fungus-regulated H2O2 dynamics modulate the rhizosphere microbiome by selectively enriching for the phylum Cyanobacteria, with strong antioxidant defenses. Our results demonstrated that the regulation of H2O2 dynamics at the plant-fungal interface affects the symbiotic outcome in response to external conditions and highlight the importance of the root endophyte in reshaping the rhizosphere microbiota.

Iron/Molybdenum Sulfide Nanozyme Cocatalytic Fenton Reaction for Photothermal/Chemodynamic Efficient Wound Healing.

The issue of bacterial infectious diseases remains a significant concern worldwide, particularly due to the misuse of antibiotics, which has caused the emergence of antibiotic-resistant strains. Fortunately, the rapid development of nanomaterials has propelled significant progress in antimicrobial therapy, offering promising solutions. Among them, the utilization of nanoenzyme-based chemodynamic therapy (CDT) has become a highly hopeful approach to combating bacterial infectious diseases. Nevertheless, the application of CDT appears to be facing certain constraints for its low efficiency in the Fenton reaction at the infected site. In this study, we have successfully synthesized a versatile nanozyme, which was a composite of molybdenum sulfide (MoS2) and iron sulfide (FeS2), through the hydrothermal method. The results showed that iron/molybdenum sulfide nanozymes (Fe/Mo SNZs) with desirable peroxidase (POD) mimic activity can generate cytotoxic reactive oxygen species (ROS) by successfully triggering the Fenton reaction. The presence of MoS2 significantly accelerates the conversion of Fe2+/Fe3+ through a cocatalytic reaction that involves the participation of redox pairs of Mo4+/Mo6+, thereby enhancing the efficiency of CDT. Additionally, based on the excellent photothermal performance of Fe/Mo SNZs, a near-infrared (NIR) laser was used to induce localized temperature elevation for photothermal therapy (PTT) and enhance the POD-like nanoenzymatic activity. Notably, both in vitro and in vivo results demonstrated that Fe/Mo SNZs with good broad-spectrum antibacterial properties can help eradicate Gram-negative bacteria like Escherichia coli and Gram-positive bacteria like Staphylococcus aureus. The most exciting thing is that the synergistic PTT/CDT exhibited astonishing antibacterial ability and can achieve complete elimination of bacteria, which promoted wound healing after infection. Overall, this study presents a synergistic PTT/CDT strategy to address antibiotic resistance, providing avenues and directions for enhancing the efficacy of wound healing treatments and offering promising prospects for further clinical use in the near future.

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.

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.

Deciphering the photoactive species-directed antibacterial mechanism of bismuth oxychloride with modulated nanoscale thickness.

As an environmentally benign disinfection strategy, photocatalytic bacterial inactivation using nanoparticles involves photogenerated reactive species that cause cellular oxidative stress. Rationalising the structural performance of photocatalysts for the practical uses such as wastewater treatment has attracted significant attention; however, the contribution of reactive species to their photocatalytic antibacterial activities at the molecular and transcriptomic levels remains unclear. In this study, nontoxic bismuth oxychloride (BiOCl) photocatalysts with different nanoscale thicknesses, including nanosheets (Ns, ∼5.4 nm), nanoplates (Np, ∼1.8 nm), and ultra-nanosheets (Uns, ∼1.1 nm), were synthesised under hydrothermal conditions. Among the three samples, BiOCl Uns exhibited the most effective photocatalytic degradation efficiency with the calculated apparent rate constant of 0.0294 min-1, ∼4 times faster than that of Ns, whereas BiOCl Ns possessed the most pronounced bactericidal effect (5.4 log inactivation). Such findings indicate the distinct role of the photoactive species responsible for photocatalytic bacterial inactivation. Moreover, transcriptome analysis of Escherichia coli after photocatalytic treatment revealed that the underlying photocatalytic antibacterial mechanism at the genetic expression level involves cellular component biosynthesis, energy metabolism, and material transportation. Notably, the differences between BiOCl Ns and BiOCl Uns were significantly enriched in purine metabolism. Therefore, the cost-effective preparation of BiOCl nanosheets with nanoscale thickness-modulated photocatalytic antibacterial activity has remarkable potential for sustainable environmental and biomedical applications.

Classification of disease recurrence using transition likelihoods with expectation-maximization algorithm.

When an infectious disease recurs, it may be due to treatment failure or a new infection. Being able to distinguish and classify these two different outcomes is critical in effective disease control. A multi-state model based on Markov processes is a typical approach to estimating the transition probability between the disease states. However, it can perform poorly when the disease state is unknown. This article aims to demonstrate that the transition likelihoods of baseline covariates can distinguish one cause from another with high accuracy in infectious diseases such as malaria. A more general model for disease progression can be constructed to allow for additional disease outcomes. We start from a multinomial logit model to estimate the disease transition probabilities and then utilize the baseline covariate's transition information to provide a more accurate classification result. We apply the expectation-maximization (EM) algorithm to estimate unknown parameters, including the marginal probabilities of disease outcomes. A simulation study comparing our classifier to the existing two-stage method shows that our classifier has better accuracy, especially when the sample size is small. The proposed method is applied to determining relapse vs reinfection outcomes in two Plasmodium vivax treatment studies from Cambodia that used different genotyping approaches to demonstrate its practical use.

Complications With Surgical Treatment of Pediatric Supracondylar Humerus Fractures: Does Surgeon Training Matter?

INTRODUCTION: National trends reveal increased transfers to referral hospitals for surgical management of pediatric supracondylar humerus (SCH) fractures. This is partly because of the belief that pediatric orthopaedic surgeons (POs) deliver improved outcomes compared with nonpediatric orthopaedic surgeons (NPOs). We compared early outcomes of surgically treated SCH fractures between POs and NPOs at a single center where both groups manage these fractures. METHODS: Patients ages 3 to 10 undergoing surgery for SCH fractures from 2014 to 2020 were included. Patient demographics and perioperative details were recorded. Radiographs at surgery and short-term follow-up assessed reduction. Primary outcomes were major loss of reduction (MLOR) and iatrogenic nerve injury (INI). Complications were compared between PO-treated and NPO-treated cohorts. RESULTS: Three hundred and eleven fractures were reviewed. POs managed 132 cases, and NPOs managed 179 cases. Rate of MLOR was 1.5% among POs and 2.2% among NPOs (P=1). Rate of INI was 0% among POs and 3.4% among NPOs (P=0.041). All nerve palsies resolved postoperatively by mean 13.1 weeks. Rates of reoperation, infection, readmission, and open reduction were not significantly different. Operative times were decreased among POs (38.1 vs. 44.6 min; P=0.030). Pin constructs were graded as higher quality in the PO group, with a higher mean pin spread ratio (P=0.029), lower rate of "C" constructs (only 1 "column" engaged; P=0.010) and less frequent crossed-pin technique (P<0.001). Multivariate analysis revealed minimal positive associations only for operative time with MLOR (odds ratio=1.021; P=0.005) and INI (odds ratio=1.048; P=0.009). CONCLUSIONS: Postsurgical outcomes between POs and NPOs were similar. Rates of MLOR were not different between groups, despite differences in pin constructs. The NPO group experienced a marginally higher rate of INI, though all injuries resolved. Pediatric subspecialty training is not a prerequisite for successfully treating SCH fractures, and overall value of orthopaedic care may be improved by decreasing transfers for these common injuries. LEVEL OF EVIDENCE: Level III-retrospective cohort study.

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.

A Metallic Ion-Induced Self-Assembly Enabling Nanowire-Based Aerogels.

The controlled assembly of nanowires is one of the key challenges in the development of a range of functional 3D aerogels with unique physicochemical properties for practical applications. However, the deep understanding of the dynamic assemble process for fabricating nanowire aerogels remains elusive. Herein, a facile strategy is presented for the metallic ion-induced assembly of nanowires into macroscopic aerogels via a solution-based process. This method enables the interconnecting between polymer-decorated nanowires via metallic coordination, resulting in plenty of nanowire bundles with the same orientation. Besides, the coordinated binding strength of nanowires with different metallic ions is also discussed. The assembly mechanism that the metallic ions induced dynamic behavior of nanowires is revealed via molecular dynamics theoretical evaluation. These findings benefit for constructing nanowire-based aerogels with unique structural features and multi-function, which pave new opportunities for other material systems.

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.

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.

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.

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.