Content of INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY in our journal

Published in last 1 year |  In last 2 years |  In last 3 years |  All Please wait a minute... For selected: Download citations EndNote Ris BibTeX Toggle thumbnails Select Simulation of crowd evacuation under attack considering emotion spreading Yang Wang(王杨), Ning Ding(丁宁), Dapeng Dong(董大鹏), and Yu Zhu(朱萸) Chin. Phys. B, 2024, 33 (12): 128901.   DOI: 10.1088/1674-1056/ad84c7 Abstract （248）   HTML （0）    PDF （1254KB）（41）       Knowledge map    In recent years, attacks against crowded places such as campuses and theaters have had a frequent and negative impact on the security and stability of society. In such an event, the crowd will be subjected to high psychological stress and their emotions will rapidly spread to others. This paper establishes the attack-escape evacuation simulation model (AEES-SFM), based on the social force model, to consider emotion spreading under attack. In this model, (1) the attack-escape driving force is considered for the interaction between an attacker and evacuees and (2) emotion spreading among the evacuees is considered to modify the value of the psychological force. To validate the simulation, several experiments were carried out at a university in China. Comparing the simulation and experimental results, it is found that the simulation results are similar to the experimental results when considering emotion spreading. Therefore, the AEES-SFM is proved to be effective. By comparing the results of the evacuation simulation without emotion spreading, the emotion spreading model reduces the evacuation time and the number of casualties by about 30%, which is closer to the real experimental results. The results are still applicable in the case of a 40-person evacuation. This paper provides theoretical support and practical guidance for campus response to violent attacks. Select A macro model of spin-transfer torque magnetic tunnel junction Ming-Bo Chen(陈明博), Kun-Kun Li(李琨琨), Xiao-Lei Yang(杨晓蕾), Xue Peng(彭雪), Wang-Da Li(李旺达), En-Long Liu(刘恩隆), Hui-Zhen Wu(吴惠桢), and Shi-Kun He(何世坤) Chin. Phys. B, 2024, 33 (12): 128502.   DOI: 10.1088/1674-1056/ad8072 Abstract （239）   HTML （0）    PDF （797KB）（119）       Knowledge map    The precise compact modeling of magnetic devices is pivotal for the integrated design of spin-transfer torque magnetic tunnel junction (STT-MTJ) in conjunction with CMOS circuitry. This work presents a macro model for an STT-MTJ which is compatible with SPICE simulation platforms. The model accurately replicates the electrical performance of the MTJ, encompassing the resistance-voltage characteristics and the pulse-width-dependent state switching behavior, and is validated with various experimental data. Additionally, the impact of process variations, particularly those affecting the MTJ diameter and barrier thickness is investigated and summarized in a corner model. Monte Carlo simulations demonstrate that our adaptable and streamlined model can be efficiently incorporated into the design of integrated circuits. Select Quantum-mechanical understanding on structure dependence of image potentials of single-walled boron nitride nanotubes Yu Zhang(张煜), Zhiman Zhang(张芷蔓), Weiliang Wang(王伟良), Shaolin Zhang(张绍林), and Haiming Huang(黄海鸣) Chin. Phys. B, 2024, 33 (12): 128501.   DOI: 10.1088/1674-1056/ad8071 Abstract （238）   HTML （0）    PDF （1590KB）（91）       Knowledge map    The recent discovery of field emission devices based on one-dimensional nanostructures has attracted much interest in emerging applications on next-generation flat panel displays, molecule-based sensors, and so forth. To achieve a comprehensive understanding of surface potentials at the nano-emitters during the tunneling process, in this study we systematically investigated the image potentials of single-walled boron nitride nanotubes with different edges, diameters and lengths in the frame of a composite first-principles calculation. The image potentials of zigzag single-walled boron nitride nanotubes are found to be dependent on the non-equivalent sides. Only the image potentials of isolated armchair single-walled boron nitride nanotube can be well fitted with the image potential of an ideal metal sphere of a size comparable to the tube diameter. On the contrary, the image potentials of zigzag and grounded armchair single-walled boron nitride nanotubes exhibit a strong length-dependence characteristic and are significantly different from that of an ideal metal sphere, which originates from the significant axial symmetry breaking of induced charge at the tip for the long tube. The correlation between the testing electron and electronic structure of single-walled boron nitride nanotube has also been discussed. Select Impact of environmental factors on the coevolution of information-emotions-epidemic dynamics in activity-driven multiplex networks Liang'an Huo(霍良安), Bingjie Liu(刘炳杰), and Xiaomin Zhao(赵晓敏) Chin. Phys. B, 2024, 33 (12): 128903.   DOI: 10.1088/1674-1056/ad7df5 Abstract （220）   HTML （0）    PDF （1332KB）（27）       Knowledge map    During public health emergencies, the diffusion of negative information can exacerbate the transmission of adverse emotions, such as fear and anxiety. These emotions can adversely affect immune function and, consequently, influence the spread of the epidemic. In this study, we established a coupled model incorporating environmental factors to explore the coevolution dynamic process of information-emotions-epidemic dynamics in activity-driven multiplex networks. In this model, environmental factors refer to the external conditions or pressures that affect the spread of information, emotions, and epidemics. These factors include media coverage, public opinion, and the prevalence of diseases in the neighborhood. These layers are dynamically cross-coupled, where the environmental factors in the information layer are influenced by the emotional layer; the higher the levels of anxious states among neighboring individuals, the greater the likelihood of information diffusion. Although environmental factors in the emotional layer are influenced by both the information and epidemic layers, they come from the factors of global information and the proportion of local infections among surrounding neighbors. Subsequently, we utilized the microscopic Markov chain approach to describe the dynamic processes, thereby obtaining the epidemic threshold. Finally, conclusions are drawn through numerical modeling and analysis. The conclusions suggest that when negative information increases, the probability of the transmission of anxious states across the population increases. The transmission of anxious states increases the final size of the disease and decreases its outbreak threshold. Reducing the impact of environmental factors at both the informational and emotional levels is beneficial for controlling the scale of the spread of the epidemic. Our findings can provide a reference for improving public health awareness and behavioral decision-making, mitigating the adverse impacts of anxious states, and ultimately controlling the spread of epidemics. Select Effects of TMIn flow rate during quantum barrier growth on multi-quantum well material properties and device performance of GaN-based laser diodes Zhenyu Chen(陈振宇), Degang Zhao(赵德刚), Feng Liang(梁锋), Zongshun Liu(刘宗顺), Jing Yang(杨静), and Ping Chen(陈平) Chin. Phys. B, 2024, 33 (12): 128102.   DOI: 10.1088/1674-1056/ad8624 Abstract （218）   HTML （0）    PDF （795KB）（76）       Knowledge map    Multidimensional influences of indium composition in barrier layers on GaN-based blue laser diodes (LDs) are discussed from both material quality and device physics perspectives. LDs with higher indium content in the barriers demonstrate a notably lower threshold current and shorter lasing wavelength compared to those with lower indium content. Our experiments reveal that higher indium content in the barrier layers can partially reduce indium composition in the quantum wells, a novel discovery. Employing higher indium content barrier layers leads to improved luminescence properties of the MQW region. Detailed analysis reveals that this improvement can be attributed to better homogeneity in the indium composition of the well layers along the epitaxy direction. InGaN barrier layers suppress the lattice mismatch between barrier and well layers, thus mitigating the indium content pulling effect in the well layers. In supplement to experimental analysis, theoretical computations are performed, showing that InGaN barrier structures can effectively enhance carrier recombination efficiency and optical confinement of LD structure, thus improving the output efficiency of GaN-based blue LDs. Combining these theoretical insights with our experimental data, we propose that higher indium content barriers effectively enhance carrier recombination efficiency and indium content homogeneity in quantum well layers, thereby improving the output performance of GaN-based blue LDs. Select Screening A-site ordered quadruple perovskites for alkaline hydrogen evolution reaction via unifying electronic configuration descriptor Ning Sun(孙宁), Wenbo Li(李文博), Yang Qin(秦杨), Zhichuan Zheng(郑智钏), Bowen Zhang(张博文), Xiangjiang Dong(董祥江), Peng Wei(魏鹏), Yixiao Zhang(张艺潇), Xian He(何贤), Xinyu Xie(谢新煜), Kai Huang(黄凯), Lailei Wu(吴来磊), Ming Lei(雷鸣), Huiyang Gou(缑慧阳), and Runze Yu(于润泽) Chin. Phys. B, 2024, 33 (12): 128101.   DOI: 10.1088/1674-1056/ad8074 Abstract （218）   HTML （0）    PDF （2977KB）（76）       Knowledge map    Dynamic adsorption processes of reaction intermediates for alkaline hydrogen evolution (HER) catalysts are still confusing to understand. Here, we report a series of $A$-site ordered quadruple perovskite ruthenium-based electrocatalysts $A$Cu$_{3}$Ru$_{4}$O$_{12}$ ($A ={\rm Na}$, Ca, Nd, and La), with the target sample SrCu$_{3}$Ru$_{4}$O$_{12}$ exhibiting a very low overpotential (46 mV @10 mA$\cdot$ cm$^{-2}$) and excellent catalytic stability with little decays after 48-h durability test. Precise tuning $A$-site cations can change the average valence state of Cu and Ru, thus the plot of HER activity $versus$ the average Ru valence number shows a volcano-type relationship. Density functional theory indicates that the Ru 4d orbitals of SrCu$_{3}$Ru$_{4}$O$_{12}$ possesses the most suitable d-band center position among the five samples, which might be the key parameter to determine the catalytic performance. Our work provides further insight into the discovering advanced, efficient hydrogen evolution catalysts through designing precise descriptor. Select Back-side stress to ease p-MOSFET degradation on e-MRAM chips Zhi-Meng Yu(于志猛), Xiao-Lei Yang(杨晓蕾), Xiao-Nan Zhao(赵晓楠), Yan-Jie Li(李艳杰), Shi-Kun He(何世坤), and Ye-Wu Wang(王业伍) Chin. Phys. B, 2024, 33 (12): 128503.   DOI: 10.1088/1674-1056/ad7c2d Abstract （212）   HTML （0）    PDF （1380KB）（63）       Knowledge map    The magnetoresistive random access memory process makes a great contribution to threshold voltage deterioration of metal-oxide-silicon field-effect transistors, especially on p-type devices. Herein, a method was proposed to reduce the threshold voltage degradation by utilizing back-side stress. Through the deposition of tensile material on the back side, positive charges generated by silicon-hydrogen bond breakage were inhibited, resulting in a potential reduction in threshold voltage shift by up to 20%. In addition, it was found that the method could only relieve silicon-hydrogen bond breakage physically, thus failing to provide a complete cure. However, it holds significant potential for applications where additional thermal budget is undesired. Furthermore, it was also concluded that the method used in this work is irreversible, with its effect sustained to the chip package phase, and it ensures competitive reliability of the resulting magnetic tunnel junction devices. Select Subtraction of liposome signals in cryo-EM structural determination of protein-liposome complexes Shouqing Li(李首卿), Ming Li(李明), Yumei Wang(王玉梅), and Xueming Li(李雪明) Chin. Phys. B, 2024, 33 (8): 088702.   DOI: 10.1088/1674-1056/ad4cdb Abstract （208）   HTML （2）    PDF （2521KB）（102）       Knowledge map    Reconstituting membrane proteins in liposomes and determining their structure is a common method for determining membrane protein structures using single-particle cryo-electron microscopy (cryo-EM). However, the strong signal of liposomes under cryo-EM imaging conditions often interferes with the structural determination of the embedded membrane proteins. Here, we propose a liposome signal subtraction method based on single-particle two-dimensional (2D) classification average images, aimed at enhancing the reconstruction resolution of membrane proteins. We analyzed the signal distribution characteristics of liposomes and proteins within the 2D classification average images of protein-liposome complexes in the frequency domain. Based on this analysis, we designed a method to subtract the liposome signals from the original particle images. After the subtraction, the accuracy of single-particle three-dimensional (3D) alignment was improved, enhancing the resolution of the final 3D reconstruction. We demonstrated this method using a PIEZO1-proteoliposome dataset by improving the resolution of the PIEZO1 protein. Select Dynamic partition of urban network considering congestion evolution based on random walk Zhen-Tong Feng(冯振通), Lele Zhang(张乐乐), Yong-Hong Wu(吴永洪), and Mao-Bin Hu(胡茂彬) Chin. Phys. B, 2025, 34 (1): 018902.   DOI: 10.1088/1674-1056/ad94e1 Abstract （201）   HTML （2）    PDF （1754KB）（208）       Knowledge map    The successful application of perimeter control of urban traffic system strongly depends on the macroscopic fundamental diagram of the targeted region. Despite intensive studies on the partitioning of urban road networks, the dynamic partitioning of urban regions reflecting the propagation of congestion remains an open question. This paper proposes to partition the network into homogeneous sub-regions based on random walk algorithm. Starting from selected random walkers, the road network is partitioned from the early morning when congestion emerges. A modified Akaike information criterion is defined to find the optimal number of partitions. Region boundary adjustment algorithms are adopted to optimize the partitioning results to further ensure the correlation of partitions. The traffic data of Melbourne city are used to verify the effectiveness of the proposed partitioning method. Select Identify information sources with different start times in complex networks based on sparse observers Yuan-Zhang Deng(邓元璋), Zhao-Long Hu(胡兆龙), Feilong Lin(林飞龙), Chang-Bing Tang(唐长兵), Hui Wang(王晖), and Yi-Zhen Huang(黄宜真) Chin. Phys. B, 2024, 33 (11): 118901.   DOI: 10.1088/1674-1056/ad7af4 Abstract （199）   HTML （2）    PDF （2434KB）（59）       Knowledge map    The dissemination of information across various locations is an ubiquitous occurrence, however, prevalent methodologies for multi-source identification frequently overlook the fact that sources may initiate dissemination at distinct initial moments. Although there are many research results of multi-source identification, the challenge of locating sources with varying initiation times using a limited subset of observational nodes remains unresolved. In this study, we provide the backward spread tree theorem and source centrality theorem, and develop a backward spread centrality algorithm to identify all the information sources that trigger the spread at different start times. The proposed algorithm does not require prior knowledge of the number of sources, however, it can estimate both the initial spread moment and the spread duration. The core concept of this algorithm involves inferring suspected sources through source centrality theorem and locating the source from the suspected sources with linear programming. Extensive experiments from synthetic and real network simulation corroborate the superiority of our method in terms of both efficacy and efficiency. Furthermore, we find that our method maintains robustness irrespective of the number of sources and the average degree of network. Compared with classical and state-of-the art source identification methods, our method generally improves the AUROC value by 0.1 to 0.2. Select Node ranking based on graph curvature and PageRank Hongbo Qu(曲鸿博), Yu-Rong Song(宋玉蓉), Ruqi Li(李汝琦), Min Li(李敏), and Guo-Ping Jiang(蒋国平) Chin. Phys. B, 2025, 34 (2): 028901.   DOI: 10.1088/1674-1056/ad9a9b Abstract （197）   HTML （0）    PDF （1007KB）（137）       Knowledge map    Identifying key nodes in complex networks is crucial for understanding and controlling their dynamics. Traditional centrality measures often fall short in capturing the multifaceted roles of nodes within these networks. The PageRank algorithm, widely recognized for ranking web pages, offers a more nuanced approach by considering the importance of connected nodes. However, existing methods generally overlook the geometric properties of networks, which can provide additional insights into their structure and functionality. In this paper, we propose a novel method named Curv-PageRank (C-PR), which integrates network curvature and PageRank to identify influential nodes in complex networks. By leveraging the geometric insights provided by curvature alongside structural properties, C-PR offers a more comprehensive measure of a node's influence. Our approach is particularly effective in networks with community structures, where it excels at pinpointing bridge nodes critical for maintaining connectivity and facilitating information flow. We validate the effectiveness of C-PR through extensive experiments. The results demonstrate that C-PR outperforms traditional centrality-based and PageRank methods in identifying critical nodes. Our findings offer fresh insights into the structural importance of nodes across diverse network configurations, highlighting the potential of incorporating geometric properties into network analysis. Select Critical station identification of metro networks based on the integrated topological-functional algorithm: A case study of Chengdu Zi-Qiang Zeng(曾自强), Sheng-Jie He(何圣洁), and Wang Tian(田旺) Chin. Phys. B, 2025, 34 (2): 028902.   DOI: 10.1088/1674-1056/ad9734 Abstract （197）   HTML （0）    PDF （2086KB）（101）       Knowledge map    As a key mode of transportation, urban metro networks have significantly enhanced urban traffic environments and travel efficiency, making the identification of critical stations within these networks increasingly essential. This study presents a novel integrated topological-functional (ITF) algorithm for identifying critical nodes, combining topological metrics such as K-shell decomposition, node information entropy, and neighbor overlapping interaction with the functional attributes of passenger flow operations, while also considering the coupling effects between metro and bus networks. Using the Chengdu metro network as a case study, the effectiveness of the algorithm under different conditions is validated. The results indicate significant differences in passenger flow patterns between working and non-working days, leading to varying sets of critical nodes across these scenarios. Moreover, the ITF algorithm demonstrates a marked improvement in the accuracy of critical node identification compared to existing methods. This conclusion is supported by the analysis of changes in the overall network structure and relative global operational efficiency following targeted attacks on the identified critical nodes. The findings provide valuable insight into urban transportation planning, offering theoretical and practical guidance for improving metro network safety and resilience. Select Anisotropy of average potential energy of passive plate in bacterial suspensions Luhui Ning(宁鲁慧), Ziwei Xiao(肖紫薇), Yuxin Tian(田宇鑫), Hongwei Zhu(朱红伟), Yi Peng(彭毅), Peng Liu(刘鹏), Ning Zheng(郑宁), Mingcheng Yang(杨明成), and Junqing Chen(陈君青) Chin. Phys. B, 2025, 34 (4): 048201.   DOI: 10.1088/1674-1056/adbee6 Abstract （195）   HTML （0）    PDF （823KB）（75）       Knowledge map    We conduct optical-tweezers experiments to investigate the average potential energies of passive plates harmonically trapped in bacterial suspensions. Our results show that the mean potential energies along both the major and minor axes increase with bacterial concentration but decrease with trap stiffness. Notably, the average potential energy along the major axis consistently exceeds that along the minor axis. This discrepancy from equilibrium systems is primarily attributed to the distinct bacterial flow fields and direct bacterium-plate collisions near the major and minor axes, as evidenced by the higher orientational order around the plate along the major compared to the minor axis, despite identical bacterial densities in these regions. Our findings highlight the critical role of hydrodynamic interactions in determining the potential energy of passive objects immersed in an active bath. Select Multiscale structural complexity analysis of neuronal activity in suprachiasmatic nucleus: Insights from tetrodotoxin-induced disruptions Ping Wang(王萍), Changgui Gu(顾长贵), and Huijie Yang(杨会杰) Chin. Phys. B, 2025, 34 (4): 048701.   DOI: 10.1088/1674-1056/adaccd Abstract （192）   HTML （0）    PDF （797KB）（26）       Knowledge map    The suprachiasmatic nucleus in the hypothalamus is the master circadian clock in mammals, coordinating physiological processes with the 24-hour day-night cycle. Comprising various cell types, the suprachiasmatic nucleus (SCN) integrates environmental signals to maintain complex and robust circadian rhythms. Understanding the complexity and synchrony within SCN neurons is essential for effective circadian clock function. Synchrony involves coordinated neuronal firing for robust rhythms, while complexity reflects diverse activity patterns and interactions, indicating adaptability. Interestingly, the SCN retains circadian rhythms in vitro, demonstrating intrinsic rhythmicity. This study introduces the multiscale structural complexity method to analyze changes in SCN neuronal activity and complexity at macro and micro levels, based on Bagrov et al.'s approach. By examining structural complexity and local complexities across scales, we aim to understand how tetrodotoxin, a neurotoxin that inhibits action potentials, affects SCN neurons. Our method captures critical scales in neuronal interactions that traditional methods may overlook. Validation with the Goodwin model confirms the reliability of our observations. By integrating experimental data with theoretical models, this study provides new insights into the effects of tetrodotoxin (TTX) on neuronal complexities, contributing to the understanding of circadian rhythms. Select Study of leakage current degradation based on stacking faults expansion in irradiated SiC junction barrier Schottky diodes Maojiu Luo(罗茂久), Yourun Zhang(张有润), Yucheng Wang(王煜丞), Hang Chen(陈航), Rong Zhou(周嵘), Zhi Wang(王智), Chao Lu(陆超), and Bo Zhang(张波) Chin. Phys. B, 2024, 33 (10): 108401.   DOI: 10.1088/1674-1056/ad6255 Abstract （190）   HTML （1）    PDF （1372KB）（65）       Knowledge map    A comprehensive investigation was conducted to explore the degradation mechanism of leakage current in SiC junction barrier Schottky (JBS) diodes under heavy ion irradiation. We propose and verify that the generation of stacking faults (SFs) induced by the recombination of massive electron-hole pairs during irradiation is the cause of reverse leakage current degradation based on experiments results. The irradiation experiment was carried out based on Ta ions with high linear energy transfer (LET) of 90.5 MeV/(mg/cm$^{2}$). It is observed that the leakage current of the diode undergoes the permanent increase during irradiation when biased at 20% of the rated reverse voltage. Micro-PL spectroscopy and PL micro-imaging were utilized to detect the presence of SFs in the irradiated SiC JBS diodes. We combined the degraded performance of irradiated samples with SFs introduced by heavy ion irradiation. Finally, three-dimensional (3D) TCAD simulation was employed to evaluate the excessive electron-hole pairs (EHPs) concentration excited by heavy ion irradiation. It was observed that the excessive hole concentration under irradiation exceeded significantly the threshold hole concentration necessary for the expansion of SFs in the substrate. The proposed mechanism suggests that the process and material characteristics of the silicon carbide should be considered in order to reinforcing against the single event effect of SiC power devices. Select Mutation in a non-force-bearing region of protein L influences force-dependent unfolding behavior Huanjie Jiang(蒋环杰), Yanwei Wang(王艳伟), Jiayuan Chen(陈家媛), Dan Hu(胡丹), Hai Pan(潘海), Zilong Guo(郭子龙), and Hu Chen(陈虎) Chin. Phys. B, 2024, 33 (7): 078201.   DOI: 10.1088/1674-1056/ad3dcd Abstract （183）   HTML （0）    PDF （1429KB）（159）       Knowledge map    Single-molecule magnetic tweezers (MTs) have revealed multiple transition barriers along the unfolding pathway of several two-state proteins, such as GB1 and Csp. In this study, we utilized MTs to measure the force-dependent folding and unfolding rates of both protein L (PLWT) and its Y47W mutant (PLY47W) where the mutation point is not at the force-bearing $\beta$-strands. The measurements were conducted within a force range of 3-120 pN. Notably, the unfolding rates of both PLWT and PWY47W exhibit distinct force sensitivities below 50 pN and above 60 pN, implying a two-barrier free energy landscape. Both PLWT and PLY47W share the same force-dependent folding rate and the same transition barriers, but the unfolding rate of PLY47W is faster than that of PLWT. Our finding demonstrates that the residue outside of the force-bearing region will also affect the force-induced unfolding dynamics. Select Significant increase in thermal conductivity of cathode material LiFePO4 by Na substitution: A machine learning interatomic potential-assisted investigation Shi-Yi Li(李诗怡), Qian Liu(刘骞), Yu-Jia Zeng(曾育佳), Guofeng Xie(谢国锋), and Wu-Xing Zhou(周五星) Chin. Phys. B, 2025, 34 (2): 028201.   DOI: 10.1088/1674-1056/ad9e99 Abstract （181）   HTML （0）    PDF （2155KB）（83）       Knowledge map    LiFePO$_{4}$ is a cathode material with good thermal stability, but low thermal conductivity is a critical problem. In this study, we employ a machine learning potential approach based on first-principles methods combined with the Boltzmann transport theory to investigate the influence of Na substitution on the thermal conductivity of LiFePO$_{4}$ and the impact of Li-ion de-embedding on the thermal conductivity of Li$_{3/4}$Na$_{1/4}$FePO$_{4}$, with the aim of enhancing heat dissipation in Li-ion batteries. The results show a significant increase in thermal conductivity due to an increase in phonon group velocity and a decrease in phonon anharmonic scattering by Na substitution. In addition, the thermal conductivity increases significantly with decreasing Li-ion concentration due to the increase in phonon lifetime. Our work guides the improvement of the thermal conductivity of LiFePO$_{4}$, emphasizing the crucial roles of both substitution and Li-ion detachment/intercalation for the thermal management of electrochemical energy storage devices. Select Influences of short-term and long-term plasticity of memristive synapse on firing activity of neuronal network Zhi-Jun Li(李志军) and Jing Zhang(张晶) Chin. Phys. B, 2024, 33 (12): 128701.   DOI: 10.1088/1674-1056/ad84c5 Abstract （180）   HTML （0）    PDF （5348KB）（101）       Knowledge map    Synaptic plasticity can greatly affect the firing behavior of neural networks, and it specifically refers to changes in the strength, morphology, and function of synaptic connections. In this paper, a novel memristor model, which can be configured as a volatile and nonvolatile memristor by adjusting its internal parameter, is proposed to mimic the short-term and long-term synaptic plasticity. Then, a bi-neuron network model, with the proposed memristor serving as a coupling synapse and the external electromagnetic radiation being emulated by the flux-controlled memristors, is established to elucidate the effects of short-term and long-term synaptic plasticity on firing activity of the neuron network. The resultant seven-dimensional (7D) neuron network has no equilibrium point and its hidden dynamical behavior is revealed by phase diagram, time series, bifurcation diagram, Lyapunov exponent spectrum, and two-dimensional (2D) dynamic map. Our results show the short-term and long-term plasticity can induce different bifurcation scenarios when the coupling strength increases. In addition, memristor synaptic plasticity has a great influence on the distribution of firing patterns in the parameter space. More interestingly, when exploring the synchronous firing behavior of two neurons, the two neurons can gradually achieve phase synchronization as the coupling strength increases along the opposite directions under two different memory attributes. Finally, a microcontroller-based hardware system is implemented to verify the numerical simulation results. Select Triadic percolation in computer virus spreading dynamics Jie Gao(高杰), Jianfeng Luo(罗建锋), Xing Li(李星), Yihong Li(李毅红), Zunguang Guo(郭尊光), and Xiaofeng Luo(罗晓峰) Chin. Phys. B, 2025, 34 (2): 028701.   DOI: 10.1088/1674-1056/ad9ff8 Abstract （177）   HTML （0）    PDF （975KB）（122）       Knowledge map    In recent years, the threats posed by computer viruses have become increasingly diverse and complex. While classic percolation theory provides a novel perspective for analyzing epidemics and information dissemination, it fails to capture the temporal dynamics of these systems and the effects of virus invasion and governmental regulation. Triadic percolation theory, a recent advancement, addresses these limitations. In this paper, we apply this new percolation mechanism to model the diffusion of computer viruses, deriving a precise mathematical formulation of the triadic percolation model and providing an analytical solution of the triadic percolation threshold. Additionally, we investigate the impact of nonlinear transmission probability characteristics on virus propagation. Numerical simulations demonstrate that reducing the network's average degree (or the positive regulation) or increasing regulatory interventions raises the outbreak threshold for computer viruses while decreasing their final size. Moreover, the study reveals that nonlinear transmission probabilities result in an increased number of solutions for the final size of the computer viruses. Our findings contribute new insights into controlling the spread of computer viruses. Select A physical memristor model for Pavlovian associative memory Jiale Lu(卢家乐), Haofeng Ran(冉皓丰), Dirui Xie(谢頔睿), Guangdong Zhou(周广东), and Xiaofang Hu(胡小方) Chin. Phys. B, 2025, 34 (1): 018703.   DOI: 10.1088/1674-1056/ad8b37 Abstract （176）   HTML （0）    PDF （2025KB）（23）       Knowledge map    Brain-inspired intelligence is considered to be a computational model with the most promising potential to overcome the shortcomings of the von Neumann architecture, making it a current research hotspot. Due to advantages such as nonvolatility, high density, low power consumption, and high response ratio, memristors are regarded as devices with promising applications in brain-inspired intelligence. This paper proposes a physical Ag/HfO$_{x}$/FeO$_{x}$/Pt memristor model. The Ag/HfO$_{x}$/FeO$_{x}$/Pt memristor is first fabricated using magnetron sputtering, and its internal principles and characteristics are then thoroughly analyzed. Furthermore, we construct a corresponding physical memristor model which achieves a simulation accuracy of up to 99.72% for the physical memristor. We design a fully functional Pavlovian associative memory circuit, realizing functions including generalization, primary differentiation, secondary differentiation, and forgetting. Finally, the circuit is validated through PSPICE simulation and analysis. page Page 1 of 3 Total 54 records First page Prev page Next page Last page