Crystal Plane Engineering to Boost Water Cluster Evaporation for Enhanced Solar Steam Generation.

Polymer based low evaporation enthalpy materials have become a universal selection for improving the efficiency of solar steam generation. Although water cluster and intermediate water mechanisms have been proposed to explain the low evaporation enthalpy, the production process and microstructure of activated water are still unclear. Here, crystal plane engineering is used to investigate the intermediate water state and the water cluster activation mechanism. The unique open-closed coordination structure on the optimized crystal surface promotes the generation of firm water clusters by optimizing the intermediate water state. Under the similar solar energy absorption of all materials, crystal plane engineering increased the solar steam generation rate of the evaporator by 31.2% and increased the energy efficiency to 94.8%. Exploring the micro-evaporation process and activated water structure is expected to stimulate the development of the next generation low evaporation enthalpy materials.

Chiral molecule induced valley polarization enhancement of MoS2.

Monolayers of transition metal dichalcogenides (TMDCs) are atomically thin direct-bandgap semiconductors with potential applications in nanoelectronics, opto-electronics, and electrochemical sensing. Recent theoretical and experimental results have suggested that they are ideal systems for exploiting the valley degrees of freedom of Bloch electrons. Here, we report detailed studies of the opto-valleytronic properties of a chiral histidine molecule embedded in monolayer MoS2 single crystals grown via chemical vapor deposition. By irradiating MoS2 with circularly polarized light and measuring the resulting spatially resolved circularly polarized emission, we find the existence of a significantly increased circular polarization for D-histidine doped MoS2. The increased valley contrast is attributed to the selective enhancement of both the excitation and emission rates having one particular handedness of the circular polarization. These results provide a promising pathway to enhance the valley contrast for monolayer TMDCs at room temperature.

Ultrathin Pd3 Pt1 Rh0.1 Nanorings with Strong C-C Bond Breaking Ability for the Ethanol Oxidation Reaction.

Ethanol as a fuel for direct ethanol fuel cells (DEFCs) has the advantages of being highly energetic, environmentally friendly, and low-cost, while the slow anodic ethanol oxidation reaction (EOR), intermediate poisoning effect, and incomplete oxidation of ethanol became obstacles to the development of DEFCs. Herein, a 2D ternary cyclic Pd3 Pt1 Rh0.1 nanorings (NRs) catalyst with efficient EOR performance is prepared via a facile one-pot solvothermal approach, and systematic studies are carried out to reveal the mechanisms of the enhanced performance and C-C bond selectivity. In particular, the optimized catalyst exhibits impressive mass activity, stability, toxicity resistance, and C-C bond cleavage ability. It's proposed that the considerable performance is attributed to the unique hollow structure, providing abundant active sites. The high toxicity resistance is not only attributed to the electronic modulation of the catalyst material by Rh atoms, but also depends on the excellent water activation properties of Rh, which contribute to the removal of intermediates, such as CO. In addition, the density functional theory calculations showed that the introduction of Rh significantly enhances the C-C bond cleavage ability of the catalyst, further improving the EOR activity.

Electrochemical Exfoliation of Two-Dimensional Phosphorene Sheets and its Energy Application.

Recently, single or few-layer phosphorene has attracted intense attention due to its exceptional physicochemical properties. To this end, mass production of high-quality phosphorene nanosheets with specific functionalities represents a pivotal factor for the basic academic studies and practical applications. Among the current synthetic methods, electrochemical exfoliation of black phosphorous is one of the most hopeful ways for mass-production of phosphorene sheets owing to the uncomplicated apparatus, low cost as well as significant efficiency. Especially, regulating the electrochemical parameters not only induces adjustable phosphorene characteristics but also enables them a promising candidate in energy applications. In this Review, a concise and crucial studies of the recent and most representative developments in this domain was introduced, including the relationship between exfoliation philosophy, internal mechanisms, processing techniques, and multiple applications of phosphorene. At the end, a summary discussion and future perspectives is also provided.

Enhanced Photocatalytic Hydrolysis Performance of Chiral Molecule Loaded Titanium Disulfide Nanosheets.

The photoelectrochemical (PEC) water decomposition is a promising method to produce hydrogen from water. To improve the water decomposition efficiency of the PEC process, it is necessary to inhibit the generation of H2 O2 byproducts and reduce the overpotential required by cheap catalysts and a high current density. Studies have shown that coating the electrode with chiral molecules or chiral films can increase the hydrogen production and reduce the generation of H2 O2 byproducts. This is interpreted as the result of a chiral induced spin selectivity (CISS) effect, which induces a spin correlation between the electrons that are transferred to the anode. Here, we report the adsorption of chiral molecules onto titanium disulfide nanosheets. Firstly, titanium disulfide nanosheets were synthesized via thermal injection and then dispersed through ultrasonic crushing. This strategy combines the CISS with the plasma effect caused by the narrow bandgap of two-dimensional sulfur compounds to promote the PEC water decomposition with a high current density.

A Networked Method for Multi-Evidence-Based Information Fusion.

Dempster-Shafer evidence theory is an effective way to solve multi-sensor data fusion problems. After developing many improved combination rules, Dempster-Shafer evidence theory can also yield excellent results when fusing highly conflicting evidence. However, these approaches still have deficiencies if the conflicting evidence is due to sensor malfunction. This work presents a combination method by integrating information interaction graph and Dempster-Shafer evidence theory; thus, the multiple evidence fusion process is expressed as a network. In particular, the credibility of each piece of evidence is obtained by measuring the distance between the evidence first. After that, the credibility of the evidence is evaluated, keeping the unreliable evidence out of the information interaction network. With the fusion of connected evidence, the accuracy of the fusion result is improved. Finally, application results show that the presented method is effective.

Room-Temperature Phosphorescence with Variable Lifetime of Halogen-Comprising Coordination Polymers.

Materials with lifetime-tunable room-temperature phosphorescence are fascinating for multiple encryption-decryption security applications. Herein, by introducing different halogen ions, that is, Cl, Br, and I, together with organic luminescent units to bond to a zinc center, three coordination polymers were hydro(solvo)thermally synthesized. The results show that three coordination polymers present room-temperature phosphorescence with different lifetimes. Furthermore, a multiple encryption-decryption system combining temporal and spatial resolution characteristics was designed.

A novel complex network link prediction framework via combining mutual information with local naive Bayes.

As an important research direction of complex networks and data mining, link prediction has attracted more and more scholars' attention. In the early research, the common neighbor is regarded as a key factor affecting the formation of links, and the prediction accuracy is improved by distinguishing the contribution of each common neighbor more accurately. However, there is a drawback that the interactions between common neighbors are ignored. Actually, it is not just the interactions between common neighbors, but all the interactions between neighbor sets contribute to the formation of links. Therefore, the core of this work is how to better quantify and balance the contributions caused by common neighbors and the interactions between neighbor sets, so as to improve the accuracy of prediction. Specifically, local naive Bayes and mutual information are utilized to quantify the influence of the two aspects, and an adjustable parameter is introduced to distinguish the two contributions in this paper. Subsequently, the mutual information-based local naive Bayes algorithm is proposed. Simulation experiments are conducted on 5 datasets belonging to different fields, and 9 indexes are utilized for comparison. Numerical simulation results verify the effectiveness of the proposed algorithm for improving link prediction performance.

Green Upconversion Emissions in Er³âº/Yb³âº Co-Doped CaMoO4Prepared by Microwave-Assisted Metathetic Method.

In this study Er³âº doped CaMoO4 (CaMoO4:Er³âº), and Er³âº/Yb³âº-co-doped CaMoO4 (CaMoO4:Er³âºYb³âº) nanoparticles have been synthesized by the microwave-assisted metathetic method. Er³âº/Yb³âº co-doped CaMoO4 nanoparticles sintered at 600 °C showed the strongest photoluminescence intensity, and crystallized well. At the excitation of 980 nm, the CaMoO4 nanoparticles show the strongest green emission at the 520 nm and 550 nm emission bands. Moreover, the green light produced has a better color purity.

A Modular Event-Triggered Containment Control Scheme for Nonlinear Heterogeneous Multiagent Systems With Unknown Leaders.

This article addresses the containment control problem in multiagent systems with nonlinear heterogeneous followers and multiple unknown leaders whose dynamics are exclusively known to their neighbors. The primary goal is to ensure the convergence of each follower to the dynamic convex hull spanned by the leaders under the constraints of limited communication resources. To achieve this, this article introduces a modular event-triggered containment control scheme with three modules. The first module, Module I-signal generator, is designed for each follower to generate a reference signal asymptotically entering the dynamic convex hull without relying on follower dynamics. The second module, Module II-event-triggered mechanism, is tailored to save communication resources effectively by determining when to broadcast information based on perturbed system stability and input-to-state stability theories. The third module, Module III-tracking controller, treats each follower as an independent agent and is crafted to track the reference signal generated by Module I using an output regulation approach. It is established that the system achieves containment control without Zeno behavior under the influence of these modules, and the theoretical results are validated through simulation examples, demonstrating the practical validity of the proposed approach.

Regulating Au coverage for the direct oxidation of methane to methanol.

The direct oxidation of methane to methanol under mild conditions is challenging owing to its inadequate activity and low selectivity. A key objective is improving the selective oxidation of the first carbon-hydrogen bond of methane, while inhibiting the oxidation of the remaining carbon-hydrogen bonds to ensure high yield and selectivity of methanol. Here we design ultrathin PdxAuy nanosheets and revealed a volcano-type relationship between the binding strength of hydroxyl radical on the catalyst surface and catalytic performance using experimental and density functional theory results. Our investigations indicate a trade-off relationship between the reaction-triggering and reaction-conversion steps in the reaction process. The optimized Pd3Au1 nanosheets exhibits a methanol production rate of 147.8 millimoles per gram of Pd per hour, with a selectivity of 98% at 70 °C, representing one of the most efficient catalysts for the direct oxidation of methane to methanol.

Distributed Adaptive Fault-Tolerant Control for Multiagent Systems via Virtual-Actuator-Based Reconfiguration.

This article aims to develop a virtual-actuator-based control scheme for the consensus tracking problem of multiagent systems (MASs) against actuator faults and mismatched disturbances. The proposed scheme has a double-layer structure. In the cyber layer, the nominal controller is designed with neighboring information for the fault-free case. While in the physical layer, the fault compensator, working as the virtual actuator, is applied to reconfigure faulty plants adaptively. This design enjoys the advantages that the nominal controller needs no adjustment and all its properties can be preserved after failure. Moreover, the proposed control scheme is distinguished by the following features: 1) the commonly imposed rank condition on outage faults is removed; 2) the norm bound of the leader's input is allowed to be unknown even though the topologies are switching and directed; and 3) there is no need to use the estimates of faults in the virtual actuator design, which means the negative impacts caused by the inaccurate fault estimation can be avoided. Finally, a numerical example is given to validate the effectiveness of the theoretical results.

A State Space Approach to Decentralized Fault SE-Coprognosability of Partially Observed Discrete Event Systems.

The problem of fault prognosis in the context of discrete event systems (DESs) is a crucial subject to study the security and maintenance of cyber-physical systems. In this article, the decentralized fault prognosis of partially observed DESs is analyzed with a universal state-estimate-based protocol. It follows (M,K) as the performance bound of any expected decentralized prognosers, where any fault can be predicted K steps before its occurrence and the fault is guaranteed to occur within M steps once a corresponding fault alarm is issued. To determine whether expected decentralized prognosers exist, the notion of state-estimate-coprognosability (SE-coprognosability) under the case of one fault type is proposed. Compared with existing other kinds of coprognosability, SE-coprognosability is a more generalized concept. Meanwhile, combining the formal method and algebraic state space approach, a novel state estimation algorithm is presented and based on which, the verification of SE-coprognosability is also solved.

A scalable and anti-fouling silver-nickel/cellulose paper with synergy photothermal effect for efficient solar distillation.

Solar interfacial evaporation is one of the most efficient and environmentally-friendly clean freshwater production technologies. Plasma metal nanoparticles are excellent optical absorption materials, but their high cost and inherent resonance narrow bandwidth absorption limit their application. In this work, commercial cellulose papers are used as substrates to synthesize Ag-Ni/cellulose paper by the seed-mediated method. The Ag-Ni/cellulose paper exhibits high light absorption at the full wavelength (200-2500 nm) resulting from the synergistic effect of localized surface plasmon resonance (LSPR) of Ag NPs and the interband transitions (IBTs) of Ni. Under one-sun irradiation (1 kW m-2), the energy utilization efficiency of Ag-Ni/cellulose paper is as high as 93.8%, and the water evaporation rate is 1.87 kg m-2 h-1. Diffusion inhibition experiment results show that the Ag-Ni/cellulose paper exhibits excellent antibacterial performance, and the antibacterial performance is highly related with Ag NPs content. These provide new opportunities for commercial production of competitive cost, green, and portable solar evaporators for different application sceneries.

Multifunctional nanoparticles with anti-inflammatory effect for improving metabolic syndromes.

Metabolic syndromes are a group of metabolic disorders for which the molecular mechanisms are still unclear. An increasing number of studies have implicated metabolic syndrome in the association with inflammation. Currently, lipsomes is known to improve nanoparticle hydrophobicity. Meanwhile, in drug delivery systems the application of cholesterol, which is commonly used to stabilise liposomal structures, has essentially no pharmacological effect on liposomes. Herein, we developed an 'anti-inflammatory liposome' (Phy-Lip) to effectively handle these challenges via employing Phytosterol instead of cholesterol. Different with the conventional liposomes, Phy-Lip is a much more brilliant nanoparticle with anti-inflammatory functions. In Phy-Lip, cholesterol was substituted by Phy, which works as membrane stabiliser, anti-inflammatory adjuvant at the same time. The experimental results show that Phy-Lip has a strong anti-inflammatory effect, and improves Metabolic syndromes. This study aims to provide a way to solve the challenge.

Multimetallic Single-Atom Catalysts for Bifunctional Oxygen Electrocatalysis.

Multimetallic alloys have demonstrated promising performance for the application of metal-air batteries, while it remains a challenge to design multimetallic single-atom catalysts (MM-SACs). Herein, metal-C3N4 and nitrogen-doped carbon are employed as cornerstones to synthesize MM-SACs by a general two-step method, and the inherent features of atomic dispersion and the strong electronic reciprocity between the multimetallic sites have been verified. The trimetallic FeCoZn-SACs and quatermetallic FeCoCuZn-SACs are both found to deliver superior oxygen evolution reaction and oxygen reduction reaction activity, respectively, as well as outstanding bifunctional durability. Density functional theory calculations elucidate the crucial contribution of Co sites of FeCoCuZn-SACs to the efficient catalysis of both the ORR and the OER. More importantly, Zn-air batteries with FeCoCuZn-SACs as cathodic catalysts exhibit a high power density (252 mW cm-2), high specific capacity (817 mAh gZn-1), and considerable stability (over 225 h) for charging-discharging processes. This work provides a visual perspective for the advantages of MM-SACs toward oxygen electrocatalysis.

Composite Learning Adaptive Tracking Control for Full-State Constrained Multiagent Systems Without Using the Feasibility Condition.

This article proposes a distributed consensus tracking controller for a class of nonlinear multiagent systems under a directed graph, in which all agents are subject to time-varying asymmetric full-state constraints, internal uncertainties, and external disturbances. The feasibility condition generally required in the existing constrained control is removed by using the proposed nonlinear mapping function (NMF)-based state reconstruction technology, and the Lipschitz condition usually needed in the consensus tracking is also canceled based on the adaptive command-filtered backstepping framework. The composite learning of the neural network-based function approximator (NN-FAP) and the finite-time smooth disturbance observer (DOB) provides a novel scheme for handling internal and external uncertainties simultaneously. One advantage of this scheme is that the use of online historical data of the closed-loop system strengthens the excitation of NN's learning. Another advantage is that the DOB with NN-FAP embedding realizes that the finite-time observation for external disturbance in the case of the system dynamics is unknown. A complete controller design, sufficient stability analysis, and numerical simulation are provided.

Identification of m6A-related long non-coding RNAs for predicting prognosis and immune characterizations in gastric cancer.

Background: N6-methyladenosine (m6A) mRNA modification triggers malignant behavior in tumor cells, which promotes malignant progression and migration of gastric cancer (GC). Nevertheless, studies on the prognostic value of m6A-related long non-coding RNA (MRlncRNA) in GC remain quite restricted. The study aimed to develop a reasonable predictive model to explore the prognostic potential of MRlncRNAs in predicting the prognosis of GC patients and monitoring the efficacy of immunotherapy. Methods: Transcriptomic and clinical data for GC were derived from TCGA. Next, univariate Cox, LASSO and multivariate Cox regression analyses were next used to identify prognostic MRlncRNAs, calculate risk scores and build risk assessment models. The predictive power of the risk models was then validated by Kaplan-Meier analysis, ROC curves, DCA, C-index, and nomogram. We attempted to effectively differentiate between groups in terms of immune cell infiltration status, ICI-related genes, immunotherapy responses, and common anti-tumor drug sensitivity. Results: A risk model based on 11 MRlncRNAs was developed with an AUC of 0.850, and the sensitivity and specificity of this model in predicting survival probability is satisfactory. The Kaplan-Meier analysis revealed that the low-risk group in the model had a significantly higher survival rate, and the model was highly associated with survival status, clinical features, and clinical stage. Furthermore, the model was verified to be an independent prognostic risk factor, and the low-risk group in the model had a remarkable positive correlation with a variety of immune cell infiltrates. The expression levels of ICI-related genes differed significantly between the different groups. Lastly, immunotherapy responses and common anti-tumor drug sensitivity also differed significantly between different groups. Conclusion: The risk model on the basis of 11-MRlncRNAs can serve as independent predictors of GC prognosis and may be useful in developing personalized treatment strategies for patients.

Semi-Global Bipartite Fault-Tolerant Containment Control for Heterogeneous Multiagent Systems With Antagonistic Communication Networks and Input Saturation.

Semi-global bipartite fault-tolerant containment control framework on antagonistic communication networks is proposed in this article for heterogeneous multiagent systems (MASs) under the influence of input saturation and actuator faults. An observer is constructed to estimate the leaders' states on signed digraph, where the communication networks are antagonistic. A fully distributed virtual control approach is developed to acquire the containment trajectory. Based on the observer, a semi-global containment control method is developed to compensate for the detrimental impacts of both input saturation and actuator faults. Besides, the dynamics and state-space dimensions of the agents can be different. The proposed framework overcomes two drawbacks of the conventional containment control: 1) the containment trajectory is obtained under general antagonistic communication networks, which is more general in engineering applications and 2) both actuator faults and input saturation are solved for heterogeneous agents, which relaxes the limitation of homogeneous dynamics. Finally, a simulation example is conducted to test and verify the feasibility of the proposed method framework.

Luminescence Reduced Graphene Oxide Based Photothermal Purification of Seawater for Drinkable Purpose.

Getting drinking water from seawater is a hope and long-term goal that has long been explored. Here, we report graphene-loaded nonwoven fabric membranes for seawater purification based on photothermal heating. The photothermal membrane of non-woven fabric loaded with graphene oxide has high light absorption and strong heating effect, and its evaporation rate about 5 times higher than that of non-woven fabric. Under the condition of light intensity of 1 kW m-2, the evaporation rate can reach 1.33 kg m-2 h-1. The results of cell activity test showed that the concentration of bacteria after photothermal membrane treatment decreased significantly. The photothermal membrane can be used for many times without greatly reducing the evaporation efficiency, which means that it is suitable for regional water purification and seawater desalination.