Control of Hybrid Exciton Lifetime in MoSe2/WS2 Moiré Heterostructures.

Hybrid excitons, characterized by their strong oscillation strength and long lifetimes, hold great potential as information carriers in semiconductors. They offer promising applications in exciton-based devices and circuits. MoSe2/WS2 heterostructures represent an ideal platform for studying hybrid excitons, but how to regulate the exciton lifetime has not yet been explored. In this study, layer hybridization is modulated by applying electric fields parallel or antiparallel to the dipole moment, enabling us to regulate the exciton lifetime from 1.36 to 4.60 ns. Furthermore, the time-resolved photoluminescence decay traces are measured at different excitation power. A hybrid exciton annihilation rate of 8.9 × 10-4 cm2 s-1 is obtained by fitting. This work reveals the effects of electric fields and excitation power on the lifetime of hybrid excitons in MoSe2/WS2 1.5° moiré heterostructures, which play important roles in high photoluminescence quantum yield optoelectronic devices based on transition-metal dichalcogenides heterostructures.

Twist angle-dependent interlayer hybridized exciton lifetimes in van der Waals heterostructures.

The interlayer twist angle has a direct effect on exciton lifetimes in van der Waals heterostructures. At small angles, the interlayer and intralayer excitons in MoSe2/WS2 heterostructures are hybridized, resulting in hybridized excitons with long lifetimes and strong resonance. However, the study of twist-angle modulation of hybridized exciton lifetimes is still insufficient, leading to an unclear understanding of the mechanism through which the twist angle between layers influences the lifetime of hybridized excitons. Here, we observed the formation of hybridized excitons by constructing MoSe2/WS2 heterostructures with different twist angles. The exciton lifetime is found to increase from 0.5 ns to 3.3 ns when the twist angle is reduced from 12° to 1°. This work provides a new perspective on the modulation of the exciton lifetime, enabling further exploration in improving the efficiency of optoelectronic devices.

Deciphering and Integrating Functionalized Side Chains for High Ion-Conductive Elastic Ternary Copolymer Solid-State Electrolytes for Safe Lithium Metal Batteries.

A critical challenge in solid polymer lithium batteries is developing a polymer matrix that can harmonize ionic transportation, electrochemical stability, and mechanical durability. We introduce a novel polymer matrix design by deciphering the structure-function relationships of polymer side chains. Leveraging the molecular orbital-polarity-spatial freedom design strategy, a high ion-conductive hyperelastic ternary copolymer electrolyte (CPE) is synthesized, incorporating three functionalized side chains of poly-2,2,2-Trifluoroethyl acrylate (PTFEA), poly(vinylene carbonate) (PVC), and polyethylene glycol monomethyl ether acrylate (PEGMEA). It is revealed that fluorine-rich side chain (PTFEA) contributes to improved stability and interfacial compatibility; the highly polar side chain (PVC) facilitates the efficient dissociation and migration of ions; the flexible side chain (PEGMEA) with high spatial freedom promotes segmental motion and interchain ion exchanges. The resulting CPE demonstrates an ionic conductivity of 2.19 × 10-3 S cm-1 (30 °C), oxidation resistance voltage of 4.97 V, excellent elasticity (2700%), and non-flammability. The outer elastic CPE and the inner organic-inorganic hybrid SEI buffer intense volume fluctuation and enable uniform Li+ deposition. As a result, symmetric Li cells realize a high CCD of 2.55 mA cm-2 and the CPE-based Li||NCM811 full cell exhibits a high-capacity retention (~90%, 0.5 C) after 200 cycles.

Finding influential nodes in complex networks based on Kullback-Leibler model within the neighborhood.

As a research hot topic in the field of network security, the implementation of machine learning, such as federated learning, involves information interactions among a large number of distributed network devices. If we regard these distributed network devices and connection relationships as a complex network, we can identify the influential nodes to find the crucial points for optimizing the imbalance of the reliability of devices in federated learning system. This paper will analyze the advantages and disadvantages of existing algorithms for identifying influential nodes in complex networks, and propose a method from the perspective of information dissemination for finding influential nodes based on Kullback-Leibler divergence model within the neighborhood (KLN). Firstly, the KLN algorithm removes a node to simulate the scenario of node failure in the information dissemination process. Secondly, KLN evaluates the loss of information entropy within the neighborhood after node removal by establishing the KL divergence model. Finally, it assesses the damage influence of the removed node by integrating the network attributes and KL divergence model, thus achieving the evaluation of node importance. To validate the performance of KLN, this paper conducts an analysis and comparison of its results with those of 11 other algorithms on 10 networks, using SIR model as a reference. Additionally, a case study was undertaken on a real epidemic propagation network, leading to the proposal of management and control strategies for daily protection based on the influential nodes. The experimental results indicate that KLN effectively evaluates the importance of the removed node using KL model within the neighborhood, and demonstrate better accuracy and applicability across networks of different scales.

Enabling an Inorganic-Rich Interface via Cationic Surfactant for High-Performance Lithium Metal Batteries.

An anion-rich electric double layer (EDL) region is favorable for fabricating an inorganic-rich solid-electrolyte interphase (SEI) towards stable lithium metal anode in ester electrolyte. Herein, cetyltrimethylammonium bromide (CTAB), a cationic surfactant, is adopted to draw more anions into EDL by ionic interactions that shield the repelling force on anions during lithium plating. In situ electrochemical surface-enhanced Raman spectroscopy results combined with molecular dynamics simulations validate the enrichment of NO3-/FSI- anions in the EDL region due to the positively charged CTA+. In-depth analysis of SEI structure by X-ray photoelectron spectroscopy and time-of-flight secondary ion mass spectrometry results confirmed the formation of the inorganic-rich SEI, which helps improve the kinetics of Li+ transfer, lower the charge transfer activation energy, and homogenize Li deposition. As a result, the Li||Li symmetric cell in the designed electrolyte displays a prolongated cycling time from 500 to 1300 h compared to that in the blank electrolyte at 0.5 mA cm-2 with a capacity of 1 mAh cm-2. Moreover, Li||LiFePO4 and Li||LiCoO2 with a high cathode mass loading of > 10 mg cm-2 can be stably cycled over 180 cycles.

Stretchable and negative-Poisson-ratio porous metamaterials.

Highly stretchable porous materials are promising for flexible electronics but their fabrication is a great challenge. Herein, several kinds of highly stretchable conductive porous elastomers with low or negative Poisson's ratios are achieved by uniaxial, biaxial, and triaxial hot-pressing strategies. The reduced graphene oxide/polymer nanocomposite elastomers with folded porous structures obtained by uniaxial hot pressing exhibit high stretchability up to 1200% strain. Furthermore, the meta-elastomers with reentrant porous structures combining high biaxial (or triaxial) stretchability and negative Poisson's ratios are achieved by biaxial (or triaxial) hot pressing. The resulting elastomer-based wearable strain sensors exhibit an ultrawide response range (0-1200%). The materials can be applied for smart thermal management and electromagnetic interference shielding, which are achieved by regulating the porous microstructures via stretching. This work provides a versatile strategy to highly stretchable and negative-Poisson-ratio porous materials with promising features for various applications such as flexible electronics, thermal management, electromagnetic shielding, and energy storage.

Direct Visualization of Dark Interlayer Exciton Transport in Moiré Superlattices.

Moiré superlattices have emerged as an unprecedented manipulation tool for engineering correlated quantum phenomena in van der Waals heterostructures. With moiré potentials as a naturally configurable solid-state that sustains high exciton density, interlayer excitons in transition metal dichalcogenide heterostructures are expected to achieve high-temperature exciton condensation. However, the exciton degeneracy state is usually optically inactive due to the finite momentum of interlayer excitons. Experimental observation of dark interlayer excitons in moiré potentials remains challenging. Here we directly visualize the dark interlayer exciton transport in WS2/h-BN/WSe2 heterostructures using femtosecond transient absorption microscopy. We observe a transition from classical free exciton gas to quantum degeneracy by imaging temperature-dependent exciton transport. Below a critical degeneracy temperature, exciton diffusion rates exhibit an accelerating downward trend, which can be explained well by a nonlinear quantum diffusion model. These results open the door to quantum information processing and high-precision metrology in moiré superlattices.

Safe control of logical control networks with random impulses.

Under the framework of a hybrid-index model, this paper investigates safe control problems of state-dependent random impulsive logical control networks (RILCNs) on both finite and infinite horizons, respectively. By using the ξ-domain method and the constructed transition probability matrix, the necessary and sufficient conditions for the solvability of safe control problems have been established. Further, based on the technique of state-space partition, two algorithms are proposed to design feedback controllers such that RILCNs can achieve the goal of safe control. Finally, two examples are shared to demonstrate the main results.

Influential nodes identification method based on adaptive adjustment of voting ability.

Influential nodes identification technology is one of the important topics which has been widely applied to logistics node location, social information dissemination, transportation network carrying, biological virus dissemination, power network anti-destruction, etc. At present, a large number of influential nodes identification methods have been studied, but the algorithms that are simple to execute, have high accuracy and can be better applied to real networks are still the focus of research. Therefore, due to the advantages of simple to execute in voting mechanism, a novel algorithm based on adaptive adjustment of voting ability (AAVA) to identify the influential nodes is presented by considering the local attributes of node and the voting contribution of its neighbor nodes, to solve the problem of low accuracy and discrimination of the existing algorithms. This proposed algorithm uses the similarity between the voting node and the voted node to dynamically adjust its voting ability without setting any parameters, so that a node can contribute different voting abilities to different neighbor nodes. To verify the performance of AAVA algorithm, the running results of 13 algorithms are analyzed and compared on 10 different networks with the SIR model as a reference. The experimental results show that the influential nodes identified by AAVA have high consistency with SIR model in Top-10 nodes and Kendall correlation, and have better infection effect of the network. Therefore, it is proved that AAV algorithm has high accuracy and effectiveness, and can be applied to real complex networks of different types and sizes.

High capacity adsorption of antimony in biomass-based composite and its consequential utilization as battery anode.

Antimony is more than an emerging pollutant in water but a scare resource. In this study, we report an adsorbent with the record capacity so far from the balanced view of Sb(III) and Sb(V). The composite adsorbent was fabricated by encapsulating hollow Fe3O4 nanosphere with the EDTA grafted chitosan, and it has superhigh adsorption capacity of for 657.1 mg/g for Sb(III) and 467.3 mg/g for Sb(V), respectively. The mechanism study reveals that the adsorption of Sb initializes from the Fe3O4, propagates along the chitosan with hydrogen bond, and terminates at the inner sphere complex with the EDTA moiety in the adsorbent. In view of the ultra-high adsorption capacity of the adsorbent, the recovered adsorbent that contains abundant (>36.4%) highly dispersed antimony nanoparticles (600-FCSE-Sb) is applied to Li-ion battery anode after reduction. This article provides a new idea for connecting water treatment and electric energy storage.

P-induced bottom-up growth of Fe-doped Ni12P5 nanorod arrays for urea oxidation reaction.

Synthesis of regular morphology catalysts with self-growing substrates is one of the effective methods to solve the problem of easy shedding of heterogeneous catalysts. In this study, Fe-doped Ni12P5 nanorods were prepared by depositing 1,1' -bis (diphenylphosphine) ferrocene (DPPF) on N-doped C/NF. The bottom-up growth of the nanorod is ascribed to the preferential adsorption of DPPF with a P site to NF that is surface-doped with the solid-solving C, and the length of nanorods can reach tens of microns and has good robustness. The N-doped carbon-constrained rod-shaped Fe-doped Ni12P5 catalyst (Fe-Ni12P5/NdC/NF-800) that grows on NF has excellent catalytic performance for the urea oxidation reaction. In addition, the current density can be maintained as high as 100 mA cm-2 and the current attenuation is weak for 12 h, and the rod shape remains good. This work provides a new idea for synthesizing self-growing catalysts with regular morphology to improve the performance of heterogeneous catalysts.

Exploring influential nodes using global and local information.

In complex networks, key nodes are important factors that directly affect network structure and functions. Therefore, accurate mining and identification of key nodes are crucial to achieving better control and a higher utilization rate of complex networks. To address this problem, this paper proposes an accurate and efficient algorithm for critical node mining. The influential nodes are determined using both global and local information (GLI) to solve the shortcoming of the existing key node identification methods that consider either local or global information. The proposed method considers two main factors, global and local influences. The global influence is determined using the K-shell hierarchical information of a node, and local influence is obtained considering the number of edges connected by the node and the given values of adjacent nodes. The given values of adjacent nodes are determined based on the degree and K-shell hierarchical information. Further, the similarity coefficient of neighbors is considered, which enhances the differentiation degree of the adjacent given values. The proposed method solves the problems of the high complexity of global information-based algorithms and the low accuracy of local information-based algorithms. The proposed method is verified by simulation experiments using the SIR and SI models as a reference, and twelve typical real-world networks are used for the comparison. The proposed GLI algorithm is compared with several common algorithms at different periods. The comparison results show that the GLI algorithm can effectively explore influential nodes in complex networks.

Fe, Ni-modified ZIF-8 as a tensive precursor to derive N-doped carbon as Na and Li-ion batteries anodes.

Carbon materials derived from metal-organic frameworks have attracted increasing attention as anodes for energy storage. In this study, Fe, Ni-doped ZIF-8 is carbonized at high temperature to obtain bimetallic Fe and Ni modified tension -relaxed carbon (FeNi@trC). Fe and Ni have opposite structural modification effects when the metal ions are doped into the ZIF-8 dodecahedron. The obtained carbon material maintains the regular dodecahedron morphology, which means the relaxation of tension and strong thermal stability during annealing. Moreover, the presence of nickel enhances the carbonization degree and electrochemical stability of FeNi@trC, while the calcination of the tensive ZIF-8 precursor offers more defect sites. The discharge capacities of FeNi@trC materials are stable at 182.9 mAh·g-1and 567.9 mAh·g-1for sodium-ion batterie (SIB) and lithium-ion batterie (LIB) at 0.05 A·g-1. Compared with the current density of 0.05 A·g-1, the discharge capacity of SIB and LIB attenuates by 29.4% and 55.9% at 1 A·g-1, respectively, and the FeNi@trC shows good performance stability in the following cycles.

Non-contact friction energy dissipation via hysteretic behavior on a graphite surface.

For non-contact friction, energy is usually dissipated through phonon excitation, Joule dissipation and van der Waals friction. Although some new dissipation mechanisms related to the quantum phenomenon have been discovered, the contribution of hysteretic behavior to non-contact friction energy dissipation is lacking in research. In this paper, the distance dependence of non-contact friction on the graphite surface is studied by using a quartz tuning fork with lateral vibration in the atmosphere. It is found that energy dissipation begins to increase when the distance is less than 2 nm, showing the form of phonon dissipation. However, when the distance is further decreased, the dissipation deviates from phonon dissipation and presents a huge friction energy dissipation peak, which is caused by the hysteretic behavior between the vibration of the surface atoms and the oscillation of the tip. This work expands the understanding of the energy dissipation mechanism of non-contact friction.

Highly reversible Li metal anode using a binary alloy interface.

Suppressing lithium (Li) dendrite growth is a central issue for achieving stable Li metal batteries (LMBs). Here, we propose a binary alloy interface that consists of Ag inner nucleation cores and Zn outer diffusion shells through which a Li solubility gradient is created appropriately to enable simultaneous high lithiophilicity and stability. These merits provide the superior cycling stability of the as-generated Li-Ag-Zn electrode compared with the bare Li or Li-Ag counterparts, resulting in the long-term cycling stability of LMBs.

P-Induced Permeation of Nickel into WO3 Octahedra to Form a Synergistic Catalyst for Urea Oxidation.

Small-molecule induction can lead to the oriented migration of metal elements, which affords functional materials with synergistic components. In this study, phosphating nickel foam (NF)-supported octahedral WO3 with phosphine affords P-WO3 /NF electrocatalyst. Ni is found to form Ni-P bonds that migrate from NF to WO3 under the induction of P, resulting in the complex oxides W1.3 Ni0.24 O4 and Ni2 P2 O7 in the particle interior and nickel phosphide on the octahedral grain surface. The catalytic activity of P-WO3 /NF in the urea oxidation reaction (UOR) is improved by synergistic action of the components in the synthesized hybrid particles. A current density of 10 mA cm-2 can be reached at a potential of 1.305 V, the double layer capacitance of the catalyst is significantly increased, and the electron transfer impedance in catalytic UOR is reduced. This work demonstrates that small-molecule induction is suitable for constructing co-catalysts with complex components in a simple protocol, which provides a new route for the design of highly efficient urea oxidation electrocatalysts.

A semi-encapsulated PdRh alloy heterojunction for the selective catalytic hydrogenation of nitrophenylacetylene to nitrostyrene.

Semi-hydrogenation usually requires an effective catalyst to ensure selectivity, especially when reducible groups coexist in a molecule. Pd is widely used in the semi-hydrogenation of alkynes to synthesize alkenes, but the selectivity control is still challenging. Herein, we design a catalyst with a semi-encapsulated PdRh alloy heterojunction in a carbon layer for the selective semi-hydrogenation of 3-nitrophenylacetylene (3-NPA). Benefiting from the presence of a PdRh alloy heterojunction and a semi-encapsulated structure, the catalyst delivers good selectivity and maintains high activity. In addition, the carbon shell can ensure the stability of the catalyst and prolong the service life. This study provides ideas for the rational design of a catalyst to achieve a selective hydrogenation reaction for practical applications.

Oligo-layer graphene stabilized fully exposed Fe-sites for ultra-sensitivity electrochemical detection of dopamine.

Neurotransmitter dopamine (DA) has been implicated in a variety of physiological and pathological processes, realizing its low detection limit and high sensitivity analysis is of great significance for early disease diagnosis. Herein, we propose a simple pyrolysis approach for dispersing Fe-sites onto the N-doped graphene support (denoted as Fe/N-GR) to construct an electrochemical biosensor for DA detection. The fully exposed Fe-sites guaranteed the well-defined active center for electrochemical oxidation of DA. The Fe/N-GR electrochemical biosensor achieves an ultra-low detection limit for DA of 27 pM with a linear range of 50 pM-15 nM. Specifically, the Fe/N-GR electrochemical biosensor exhibits favorable sensitivity and enzyme-level molecular identification ability in the selective detection of DA versus other typical redox-active interferents. What's more, the detection of dopamine in real human serum samples verifies the applicability of the developed sensor. Our results demonstrate a promising means of using fully exposed metal-site subnanometric catalysts for electrochemical sensing applications.

Monoelemental two-dimensional boron nanomaterials beyond theoretical simulations: From experimental preparation, functionalized modification to practical applications.

During the past decade, there is an explosive growth of theoretical and computational studies on 2D boron-based nanomaterials. In terms of extensive predictions from theoretical simulations, borophene, boron nanosheets and 2D boron derivatives show excellent structural, electronic, photonic and nonlinear optical characteristics, and potential applications in a wide range of fields. In recent years, previous studies have reported the successful experimental preparations, superior properties, multi-functionalized modifications of various 2D boron and its derivatives, which show many practical applications in significant fields. To further promote the ever-increasing experimental studies, this present review systematically summarizes recent progress on experimental preparation methods, functionalized modification strategies and practical applications of 2D boron-based nanomaterials and multifunctional derivatives. Firstly, this review summarizes the experimental preparation methods, including molecular beam epitaxy, chemical vapor deposition, liquid-phase exfoliation, chemical reaction, and other auxiliary methods. Then, various strategies for functionalized modification are introduced overall, focusing on borophene derivatives, boron-based nanosheets, atom-introduced, chemically-functionalized borophene and boron nanosheets, borophene or boron nanosheet-based heterostructures, and other functionalized 2D boron nanomaterials. Subsequently, various potential applications are discussed in detail, involving energy storage, catalysis conversion, photonics, optoelectronics, sensors, bio-imaging, biomedicine therapy, and adsorption. We comment the state-of-the-art related studies concisely, and also discuss the current status, probable challenges and perspectives rationally. This review is timely, comprehensive, in-depth and highly attractive for scientists from multiple disciplines and scientific fields, and can facilitate further development of advanced functional low-dimensional nanomaterials and multi-functionalized systems toward high-performance practical applications in significant fields.

Urate oxidase-loaded MOF electrodeposited on boron nanosheet-doxorubicin complex as multifunctional nano-enzyme platform for enzymatic and ratiometric electrochemical biosensing.

In this work, a novel multifunctional nano-enzyme platform was developed and used for enzymatic and ratiometric electrochemical biosensing of uric acid (UA). Boron nanosheets (BNSs) were prepared through ultrasound-assisted liquid-phase exfoliation, followed by the loading of doxorubicin (DOX) to form BNSs-DOX complex. The complex was drop-casted on glassy carbon electrode (GCE) surface to prepare BNSs-DOX/GCE. Cobalt-based metal-organic framework (MOF) with encapsulation of urate oxidase (UOx) was in-situ copolymerized and electrodeposited on the BNSs-DOX surface to construct UOx@MOF/BNSs-DOX nanohybrid-modified GCE. The modified electrode serves as an artificial nano-enzyme sensing platform and presents multifunctional functions, including DOX-loaded BNSs carrier, UOx-enzyme immobilization, enzymatic redox and ratiometric electrochemical sensing of UA. The platform was explored as a new ratiometric electrochemical biosensor to detect UA in the concentration range of 0.1-200 µM, with a low limit of detection of 0.025 µM. Experimental results testify high selectivity, sensitivity and stability toward efficient detection of UA over potential interferents, revealing high detection accuracy and repeatability. The explored biosensor shows superior detection performances in real biological samples, together with high detection recoveries. Excellent properties and functions endow the biosensor with great prospects for precise screening and early diagnosis of UA-relevant malignant diseases in clinic.