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The oxygen evolution reaction (OER) is essential for the development of renewable energy conversion and storage technologies. Eight N-doped graphenes containing variable numbers of embedded cobalt atoms (Coxy-NG, x = 1-4, y = 1-3, where x represents the number of embedded Co atoms and y represents different configurations) were designed and their OER electrocatalytic activities were systematically studied through density functional theory calculations. The significant roles of the number of Co atoms and their configuration in their OER performance were discussed in detail. Co31-NG occupies the peak of the activity volcano plot with a low overpotential of 0.31 V, which is smaller than Co11-NG with only one Co atom and even superior to the widely used IrO2 (0.56 V). The electronic structure and electron density analysis reveal that the outstanding electrocatalytic performance is due to the orbital hybridization between Co and N atoms and the increased positive charge on in-plane Co due to the out-of-plane Co atoms/clusters. This work clarifies the important role of transition atoms and provides excellent examples for reducing the overpotential through embedding several transition metal atoms onto single-atom electrocatalysts.
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A class of self-similar networks, obtained by recursively replacing each edge of the current network with a well-designed structure (generator) and known as edge-iteration networks, has garnered considerable attention owing to its role in presenting rich network models to mimic real objects with self-similar structures. The generator dominates the structural and dynamic properties of edge-iteration networks. However, the general relationships between these networks' structural and dynamic properties and their generators remain unclear. We study the fractal and first-passage properties, such as the fractal dimension, walk dimension, resistance exponent, spectral dimension, and global mean first-passage time, which is the mean time for a walker, starting from a randomly selected node and reaching the fixed target node for the first time. We disclose the properties of the generators that dominate the fractal and first-passage properties of general edge-iteration networks. A clear relationship between the fractal and first-passage properties of the edge-iteration networks and the related properties of the generators are presented. The upper and lower bounds of these quantities are also discussed. Thus, networks can be customized to meet the requirements of fractal and dynamic properties by selecting an appropriate generator and tuning their structural parameters. The results obtained here shed light on the design and optimization of network structures.
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Bundled networks, obtained by attaching a copy of a fiber structure to each node on the base structure, serve as important realistic models for the geometry and dynamics of nontranslationally invariant systems in condensed matter physics. Here, we analyze the first-passage properties, including the mean first-passage time, the mean-trapping time, the global-mean first-passage time (GFPT), and the stationary distribution, of a biased random walk within such networks, in which a random walker moves to a neighbor on base with probability γ and to a neighbor on fiber with probability 1-γ when the walker at a node on base. We reveal the primary properties of both the base and fiber structure, which govern the first-passage characteristics of the bundled network. Explicit expressions between these quantities in the bundled networks and the related quantities in the component structures are presented. GFPT serves as a crucial indicator for evaluating network transport efficiency. Unexpectedly, bases and fibers with similar scaling of GFPT can construct bundled networks exhibiting different scaling behaviors of GFPT. Therefore, bundled networks can be tailored to accommodate specific dynamic property requirements by choosing a suitable base and fiber structure. These findings contribute to advancing the design and optimization of network structures.
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Nucleic acid amplification is crucial for disease diagnosis, especially lethal infectious diseases such as COVID-19. Compared with PCR, isothermal amplification methods are advantageous for point-of-care testing (POCT). However, complicated primer design limits their application in detecting some short targets or sequences with abnormal GC content. Herein, we developed a novel linear displacement isothermal amplification (LDIA) method using two pairs of conventional primers and Bacillus stearothermophilus (Bst) DNA polymerase, and reactions could be accelerated by adding an extra primer. Pseudorabies virus gE (high GC content) and Salmonella fimW (low GC content) genes were used to evaluate the LDIA assay. Using strand displacement (SD) probes, a LDIA-SD method was developed to realize probe-based specific detection. Additionally, we incorporated a nucleic acid-free extraction step and a pocket-sized device to realize POCT applications of the LDIA-SD method. The LDIA-SD method has advantages including facile primer design, high sensitivity and specificity, and applicability for POCT, especially for amplification of complex sequences and detection of infectious diseases.
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Typical transition-metal dichalcogenides (TMDs) and graphdiyne (GDY) often form type-I heterojunctions, which will limit their applications in optoelectronic devices. Here, type-II heterojunctions based on GDY and TMDs are constructed by introducing Janus structures. An intrinsic type-II heterojunction is presented when the GDY is in contact with a Se-terminated layer, but a type-I heterojunction would appear when it is in contact with the S-terminated surface. Such a difference in band alignment can be attributed to the interaction between the dipole moment formed by the Janus structure and the graphdiyne layer. Furthermore, for heterojunctions in contact with the S-terminated layer, they can be converted into type-II heterojunctions by a small external electric field (for WSSe, only 0.05 V A-1 is required). This approach can suggest a convenient design strategy for the application of graphdiyne in a wider range of applications.
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The Watts-Strogatz networks are important models that interpolate between regular lattices and random graphs, and Barabási-Albert networks are famous models that explain the origin of the scale-free networks. Here, we consider the first encounters between two particles (e.g., prey A and predator B) embedded in the Watts-Strogatz networks and the Barabási-Albert networks. We address numerically the mean first-encounter time (MFET) while the two particles are moving and the mean first-passage time (MFPT) while the prey is fixed, aiming at uncovering the impact of the prey's motion on the encounter time, and the conditions where the motion of the prey would accelerate (or slow) the encounter between the two particles. Different initial conditions are considered. In the case where the two particles start independently from sites that are selected randomly from the stationary distribution, on the Barabási-Albert networks, the MFET is far less than the MFPT, and the impact of prey's motion on the encounter time is enormous, whereas, on the Watts-Strogatz networks (including Erdos-Rényi random networks), the MFET is about 0.5-1 times the MFPT, and the impact of prey's motion on the encounter time is relatively small. We also consider the case where prey A starts from a fixed site and the predator starts from a randomly drawn site and present the conditions where the motion of the prey would accelerate (or slow) the encounter between the two particles. The relation between the MFET (or MFPT) and the average path length is also discussed.
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Similar to most semiconductors, low-dimensional GaN materials also have the problem of asymmetric doping, that is, it is quite difficult to form p-type conductivity compared to n-type conductivity. Here, we have discussed the geometry, structure, and electronic defect properties of a two-dimensional graphene-like gallium nitride (g-GaN) monolayer belonging to the group III-V compounds, doped with different elements (In, Mg, Zn) at the Ga site. Based on first principles calculations, we found that substituting Ga (low concentration impurities) with Mg would be a better choice for fabricating a p-type doping semiconductor under N-rich conditions, which is essential for understanding the properties of impurity defects and intrinsic defects in the g-GaN monolayer (using the "transfer to real state" model). Moreover, the g-GaN monolayer is dynamically stable and can remain stable even in high-temperature conditions. This research provides insight for increasing the hole concentration and preparing potential high-performance optoelectronic devices using low-dimensional GaN materials.
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In this work, we consider a class of recursively grown fractal networks Gn(t) whose topology is controlled by two integer parameters, t and n. We first analyse the structural properties of Gn(t) (including fractal dimension, modularity, and clustering coefficient), and then we move to its transport properties. The latter are studied in terms of first-passage quantities (including the mean trapping time, the global mean first-passage time, and Kemeny's constant), and we highlight that their asymptotic behavior is controlled by the network's size and diameter. Remarkably, if we tune n (or, analogously, t) while keeping the network size fixed, as n increases (t decreases) the network gets more and more clustered and modular while its diameter is reduced, implying, ultimately, a better transport performance. The connection between this class of networks and models for polymer architectures is also discussed.
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The first return time (FRT) is the time it takes a random walker to first return to its original site, and the global first passage time (GFPT) is the first passage time for a random walker to move from a randomly selected site to a given site. We find that in finite networks, the variance of FRT, Var(FRT), can be expressed as Var(FRT) = 2⟨FRT⟩⟨GFPT⟩ - ⟨FRT⟩2 - ⟨FRT⟩, where ⟨·⟩ is the mean of the random variable. Therefore a method of calculating the variance of FRT on general finite networks is presented. We then calculate Var(FRT) and analyze the fluctuation of FRT on regular branched networks (i.e., Cayley tree) by using Var(FRT) and its variant as the metric. We find that the results differ from those in such other networks as Sierpinski gaskets, Vicsek fractals, T-graphs, pseudofractal scale-free webs, (u, v) flowers, and fractal and non-fractal scale-free trees.
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Fractal (or transfractal) features are common in real-life networks and are known to influence the dynamic processes taking place in the network itself. Here, we consider a class of scale-free deterministic networks, called (u, v)-flowers, whose topological properties can be controlled by tuning the parameters u and v; in particular, for u > 1, they are fractals endowed with a fractal dimension df, while for u = 1, they are transfractal endowed with a transfractal dimension dÌf. In this work, we investigate dynamic processes (i.e., random walks) and topological properties (i.e., the Laplacian spectrum) and we show that, under proper conditions, the same scalings (ruled by the related dimensions) emerge for both fractal and transfractal dimensions.
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In this paper, we consider discrete time random walks on the pseudofractal scale-free web (PSFW) and we study analytically the related first passage properties. First, we classify the nodes of the PSFW into different levels and propose a method to derive the generation function of the first passage probability from an arbitrary starting node to the absorbing domain, which is located at one or more nodes of low-level (i.e., nodes with large degree). Then, we calculate exactly the first passage probability, the survival probability, the mean, and the variance of first passage time by using the generating functions as a tool. Finally, for some illustrative examples corresponding to given choices of starting node and absorbing domain, we derive exact and explicit results for such first passage properties. The method we propose can as well address the cases where the absorbing domain is located at one or more nodes of high-level on the PSFW, and it can also be used to calculate the first passage properties on other networks with self-similar structure, such as (u, v) flowers and recursive scale-free trees.
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Efficiently controlling the diffusion process is crucial in the study of diffusion problem in complex systems. In the sense of random walks with a single trap, mean trapping time (MTT) and mean diffusing time (MDT) are good measures of trapping efficiency and diffusion efficiency, respectively. They both vary with the location of the node. In this paper, we analyze the effects of node's location on trapping efficiency and diffusion efficiency of T-fractals measured by MTT and MDT. First, we provide methods to calculate the MTT for any target node and the MDT for any source node of T-fractals. The methods can also be used to calculate the mean first-passage time between any pair of nodes. Then, using the MTT and the MDT as the measure of trapping efficiency and diffusion efficiency, respectively, we compare the trapping efficiency and diffusion efficiency among all nodes of T-fractal and find the best (or worst) trapping sites and the best (or worst) diffusing sites. Our results show that the hub node of T-fractal is the best trapping site, but it is also the worst diffusing site; and that the three boundary nodes are the worst trapping sites, but they are also the best diffusing sites. Comparing the maximum of MTT and MDT with their minimums, we find that the maximum of MTT is almost 6 times of the minimum of MTT and the maximum of MDT is almost equal to the minimum for MDT. Thus, the location of target node has large effect on the trapping efficiency, but the location of source node almost has no effect on diffusion efficiency. We also simulate random walks on T-fractals, whose results are consistent with the derived results.
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Two-dimensional van der Waals (2D vdW) heterostructure photodetectors have garnered significant attention for their potential applications in next-generation optoelectronic systems. However, current 2D vdW photodetectors inevitably encounter compromises between responsivity, detectivity, and response time due to the absence of multilevel regulation for free and photoexcited carriers, thereby restricting their widespread applications. To address this challenge, we propose an efficient 2D WS2/CuInP2S6 vdW heterostructure photodetector by combining band engineering and ferroelectric modulation. In this device, the asymmetric conduction and valence band offsets effectively block the majority carriers (free electrons), while photoexcited holes are efficiently tunneled and rapidly collected by the bottom electrode. Additionally, the ferroelectric CuInP2S6 layer generates polarization states that reconfigure the built-in electric field, reducing dark current and facilitating the separation of photocarriers. Moreover, photoelectrons are trapped during long-distance lateral transport, resulting in a high photoconductivity gain. Consequently, the device achieves an impressive responsivity of 88 A W-1, an outstanding specific detectivity of 3.4 × 1013 Jones, and a fast response time of 37.6/371.3 µs. Moreover, the capability of high-resolution imaging under various wavelengths and fast optical communication has been successfully demonstrated using this device, highlighting its promising application prospects in future optoelectronic systems.
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Photodetectors based on two-dimensional van der Waals (2D vdW) heterostructures with high detectivity and rapid response have emerged as promising candidates for next-generation imaging applications. However, the practical application of currently studied 2D vdW heterostructures faces challenges related to insufficient light absorption and inadequate separation of photocarriers. To address these challenges, we present a sandwiched WS2/MoTe2/WS2 heterostructure with a completely depleted interlayer, integrated on a mirror electrode, for a highly efficient photodetector. This well-designed structure enhances light-matter interactions while facilitating effective separation and rapid collection of photocarriers. The resulting photodetector exhibits a broadband photoresponse spanning from deep ultraviolet to near-infrared wavelengths. When operated in self-powered mode, the device demonstrates an exceptional response speed of 22/34 µs, along with an impressive detectivity of 8.27 × 1010 Jones under 635 nm illumination. Additionally, by applying a bias voltage of -1 V, the detectivity can be further increased to 1.49 × 1012 Jones, while still maintaining a rapid response speed of 180/190 µs. Leveraging these outstanding performance metrics, high-resolution visible-near-infrared light imaging has been successfully demonstrated using this device. Our findings provide valuable insights into the optimization of device architecture for diverse photoelectric applications.
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Salmonella is a foodborne pathogen that causes salmonellosis, of which retail chicken meat is a major source. However, the prevalence of Salmonella in different retail chicken supply modes and the threat posed to consumers remains unclear. The prevalence, serotype distribution, antibiotic resistance, and genomic characteristics of Salmonella in three supply modes of retail chicken (live poultry, frozen, and chilled) were investigated using whole-genome sequencing (WGS) and machine learning (ML). In this study, 480 retail chicken samples from live poultry, frozen, and chilled supply modes in Guangzhou from 2020 to 2021, as well as 253 Salmonella isolates (total isolation rate = 53.1 %), were collected. The prevalence of isolates in the live poultry mode (67.5 %, 81/120) was statistically higher than in the frozen (50.0 %, 120/240) and chilled (43.3 %, 52/120) (P < 0.05) modes. Serotype identification showed significant differences in the serotype distribution of Salmonella in different supply modes. S. Enteritis (46.7 %) and S. Indiana (14.2 %) were predominant in the frozen mode. S. Agona (23.5 %) and S. Saintpaul (13.6 %) were predominant in live poultry, while S. Enteritis (40.4 %) and S. Kentucky (17.3 %) were predominant in chilled mode. Antibiotic testing showed that frozen mode isolates were more resistant; the multidrug-resistant (MDR) rate of isolates in the frozen mode reached 91.8 %, significantly higher than in the chilled (86.5 %) and live (74.1 %) (P < 0.05) modes. WGS was performed on 155 top serotypes (S. Enteritidis, S. Kentucky, S. Indiana, and S. Agona). The antibiotic resistance gene analysis showed that the abundance and carrying rate of antibiotic resistance genes of Salmonella in the frozen mode (54 types, 16.1 %) were significantly higher than in other modes (live poultry: 36 types, 9.4 %, P < 0.05; chilled: 31 types, 11.6 %). The blaNDM-1 and blaNDM-9 genes encoding carbapenem resistance were found in frozen mode isolates on a complex transposon consisting of TnAS3-IS26. Virulence factors and plasmid replicons were abundant in the studied frozen mode isolates. In addition, single nucleotide polymorphism (SNP) phylogenetic tree results showed that in the frozen supply mode, the S. Enteritidis clonal clade continued to contaminate retail chicken meat and was homologous to S. Enteritidis strains found in farm chicken embryos, slaughterhouse chicken carcasses, and patients from hospitals in China (SNP 0 = 10). Notably, the pan-genome-based ML model showed that characteristic genes in frozen and live poultry isolates differed. The narZ gene was a key characteristic gene in frozen isolates, encoding nitrate reductase, relating to anaerobic bacterial growth. The ydgJ gene is a key characteristic gene in the live mode and encodes an oxidoreductase related to oxidative function in bacteria. The high prevalence of live poultry mode Salmonella and the transmission of frozen mode MDR Salmonella in this study pose serious risks to food safety and public health, emphasizing the importance of improving disinfection and cold storage measures to reduce Salmonella contamination and transmission. In conclusion, the continued surveillance of Salmonella across different supply models and the development of an epidemiological surveillance system based on WGS is necessary.
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Galinhas , Microbiologia de Alimentos , Aprendizado de Máquina , Salmonella , Sequenciamento Completo do Genoma , Animais , Galinhas/microbiologia , Salmonella/genética , Salmonella/isolamento & purificação , Salmonella/efeitos dos fármacos , Prevalência , Sorogrupo , Carne/microbiologia , Antibacterianos/farmacologia , Farmacorresistência Bacteriana/genética , China/epidemiologia , Genoma BacterianoRESUMO
Two-dimensional (2D) gallium selenide (GaSe) holds great promise for pioneering advancements in photodetection due to its exceptional electronic and optoelectronic properties. However, in conventional photodetectors, 2D GaSe only functions as a photosensitive layer, failing to fully exploit its inherent photosensitive potential. Herein, we propose an ultrasensitive photodetector based on out-of-plane 2D GaSe/MoSe2 heterostructure. Through interfacial engineering, 2D GaSe serves not only as the photosensitive layer but also as the photoconductive gain and passivation layer, introducing a photogating effect and extending the lifetime of photocarriers. Capitalizing on these features, the device exhibits exceptional photodetection performance, including a responsivity of 28â¯800 A/W, specific detectivity of 7.1 × 1014 Jones, light on/off ratio of 1.2 × 106, and rise/fall time of 112.4/426.8 µs. Moreover, high-resolution imaging under various wavelengths is successfully demonstrated using this device. Additionally, we showcase the generality of this device design by activating the photosensitive potential of 2D GaSe with other transition metal dichalcogenides (TMDCs) such as WSe2, WS2, and MoS2. This work provides inspiration for future development in high-performance photodetectors, shining a spotlight on the potential of 2D GaSe and its heterostructure.
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The pseudofractal scale-free web (PSFW) is a well-known model for a scale-free network with small-world characteristics. Understanding the dynamic properties of this network can provide valuable insights into dynamic processes occurring in general scale-free and small-world networks. In this study we investigate search processes using discrete-time random walks on the PSFW to reveal the impact of the resetting position on optimizing search efficiency, as measured by the mean first-passage time (MFPT). At each step the walker has two options: with a probability of 1-γ, it moves to one of the neighboring sites, and with a probability of γ, it resets to the predefined resetting position. We explore various choices for the resetting position, present rigorous results for the MFPT to a given node of the network, determine the optimal resetting probability γ^{*} where the MFPT reaches its minimum, and evaluate the ratio of the minimum for MFPT to the MFPT without resetting for each case. Results show that, in large PSFWs, both the degree of the resetting position and the distance between the target and the resetting position significantly affect the search efficiency. A higher degree of the resetting position leads to a slower convergence of the walker to the target, while a greater distance between the target and the resetting position also results in a slower convergence. Additionally, we observe that resetting to a vertex randomly selected from the stationary distribution can significantly expedite the process of the walker reaching the target. The findings presented in this study shed light on optimizing stochastic search processes on large networks, offering valuable insights into improving search efficiency in real-world applications, where the target node's location is unknown.
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Fractals are ubiquitous in nature and random walks on fractals have attracted lots of scientific attention in the past several years. In this work, we consider discrete random walks on a class of fractal scale-free trees (FST), whose topologies are controlled by two integer parameters (i.e., u≥2 and v≥1) and exhibit a wide range of topological properties by suitably varying the parameters u and v. The mean trapping time (MTT), referred to as T_{y}, which is the mean time it takes the walker to be absorbed by the trap fixed at site y of the FST, is addressed analytically on the FST, and the effects of the trap location y on the MTT for the FST and for the general trees are also analyzed. First, a method, which is based on the connection between the MTT and the effective resistances, to derive analytically T_{y} for an arbitrary site y of the FST is presented, and some examples are provided to show the effectiveness of the method. Then, we compare T_{y} for all the possible site y of the trees, and find the sites where T_{y} achieves the minimum (or maximum) on the FST. Finally, we analyze the effects of trap location on the MTT in general trees and find that the average path length (APL) from an arbitrary site to the trap is the decisive factor which dominates the difference in the MTTs for different trap locations on general trees. We find, for any tree, the MTT obtains the minimum (or maximum) at sites where the APL achieves the minimum (or maximum).
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Defects are inevitable in two-dimensional materials due to the growth condition, which results in many unexpected changes in materials' properties. Here, we have mainly discussed the nonradiative recombination dynamics of PtSe2 monolayer without/with native point defects. Based on first-principles calculations, a shallow p-type defect state is introduced by a Se antisite, and three n-type defect states with a double-degenerate shallow defect state and a deep defect state are introduced by a Se vacancy. Significantly, these defect states couple strongly to the pristine valence band maximum and lead to the enhancement of the in-plane vibrational Eg mode. Both factors appreciably increase the nonadiabatic coupling, accelerating the electron-hole recombination process. An explanation of PtSe2-based photodetectors with the slow response, compared to conventional devices, is provided by studying this nonradiative transitions process.
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Zero (or near-zero) Poisson's ratio (ZPR) materials have important applications in the field of precision instruments because one of their faces is stable and will not be affected by strain. However, ZPR materials are extremely rare. Here, we report a novel ZPR material, two-dimensional P2/m arsenene, by first principles calculations. Its Poisson's ratio is -0.00021 (strain along zigzag direction), which is smaller than all the known near-zero Poisson's ratio crystal materials, and even 10 times smaller than Me-graphene (0.002). This feature makes it have huge potential applications in the field of precision instruments such as aviation, medicine, and flexible electronic devices. Besides, the band-gap range of P2/m arsenene is 1.420-2.154 eV (the corresponding wavelength is 873-575 nm) under strain from -5% to 5% along the zigzag direction, which is suitable for infrared and visible optoelectronic devices.