In connected automated vehicle platoon, the acceleration information of the preceding vehicle obtained by the following vehicle through communication acts as a key feedforward signal for the anticipatory longitudinal control of the following vehicle. Once the communication channel is attacked, the feedforward effect is weakened, leaving the platoon more vulnerable to oscillation and traffic jam formation. Under this situation, a car-following model is proposed within the optimal velocity framework by explicitly embedding acceleration attack of the preceding vehicle as well as a cooperative bilateral control scheme incorporating the spacing and velocity information of both the preceding and following vehicles. Then, linear stability analysis of the new model is explored and the corresponding neutral stability condition is derived. The results show that acceleration attack markedly shrinks the stability region, whereas the cooperative control scheme with bilateral traffic information enlarges the stable domain and provides a redeeming effect against acceleration attack. Further, nonlinear perturbation analysis of the new model near the critical state is carried out and the modified Korteweg-de Vries (mKdV) equation is derived, from which the emergent unstable wave is shown to be consistent with the kink-antikink soliton solution of the mKdV equation. In the end, numerical simulations are developed and further confirm the analytical results. It is found that acceleration attack promotes disturbance amplification and aggravates traffic jam, while the cooperative spacing and velocity control schemes can suppress traffic jam independently, and their combined effect is more obviously. The results are beneficial in constructing the coordination control method under degraded connected automated vehicle conditions.
Insufficient conductivity of electrode active materials and incomplete understanding of interfacial carrier injection remain key limitations in composite energy-storage electrodes. Using density functional theory, this work investigates how the active phase and Fe3O4(111) surface termination control interfacial stability, charge redistribution, spin-resolved band alignment, van der Waals (vdW)-gap tunneling, and strain response in Ni(OH)2/Graphene and Fe3O4(111)/Graphene contacts. Ni(OH)2/Graphene is governed by weak vdW coupling: the net charge transfer is only 0.006 e, the graphene Dirac cone is preserved, and an effective p-type Schottky barrier of about 0.19 eV is formed. The Fe3O4 interfaces show pronounced termination dependence. The oct termination extracts 0.2033 e from graphene and forms a spin-polarized p-type Schottky contact with an effective barrier of about 0.12 eV, whereas the tet termination retains half-metallic character and provides near-zero-barrier, Ohmic-like spin-up band alignment together with spin-down blocking. Planar-averaged electrostatic-potential analysis nevertheless reveals a finite vdW tunneling barrier in every equilibrium contact. The estimated WKB tunneling probabilities are 1.64%, 1.67%, and 0.29% for Ni(OH)2/Graphene, oct/Graphene, and tet/Graphene, respectively. Thus, the oct termination combines a small Schottky barrier with a cross-gap tunneling probability comparable to that of Ni(OH)2/Graphene, while the tet termination offers spin-selective band alignment but the strongest cross-gap tunneling limitation. Biaxial strain is further used as an idealized perturbation to reveal continuous Schottky-barrier modulation in Ni(OH)2/Graphene and termination-dependent contact-state reconstruction in Fe3O4(111)/Graphene. The comparison shows that active-phase chemistry and surface termination produce distinct combinations of charge redistribution, band alignment, and vdW-gap tunneling, while biaxial strain further modifies the resulting contact states.
Stochastic resonance (SR), as a nonlinear dynamical mechanism that exploits the constructive role of noise to enhance weak signals, has been extensively investigated in weak signal detection. To address the output saturation induced by high-order nonlinear terms in classical quad-stable stochastic resonance (CQSR) systems, this paper proposes an unsaturated piecewise quad-stable stochastic resonance (UPQSR) system. By introducing a piecewise linearization of the potential function, the proposed system effectively alleviates nonlinear constraints and enhances the amplification capability for weak signals. Based on the adiabatic approximation theory, the steady-state probability density (SPD), mean first passage time (MFPT), and spectral amplification factor (SA) are derived to systematically analyze the influence of system parameters on stochastic resonance behavior. To avoid the randomness associated with manual parameter tuning, a quantum genetic algorithm (QGA) is employed for parameter optimization, and the output signal-to-noise ratio (SNR) is adopted as the performance evaluation metric. Numerical simulations and experimental analyses demonstrate that the proposed UPQSR system exhibits superior weak signal enhancement performance compared with classical quad-stable systems under both Gaussian white noise and Lévy noise environments. Furthermore, by incorporating variational mode decomposition (VMD) as a preprocessing strategy, clearer spectral responses and higher SNR gains can be achieved under strong noise conditions. These results verify the effectiveness of the VMD-UPQSR framework for weak signal detection in complex noise environments and highlight its potential significance in stochastic resonance theory and related engineering applications.
Lactate, a metabolite produced via glycolysis, is continuously generated in the human body during resting metabolism and physical exertion. Excessive lactate buildup in the bloodstream can precipitate lactic acidosis, a condition wherein the body fails to metabolize it promptly. Conventional analytical methods for lactate quantification such as high-performance liquid chromatography, liquid chromatography-mass spectrometry, and spectrophotometry possess high sensitivity but are costly, intricate, and necessitate skilled operators. In contrast, electrochemical biosensors have attracted substantial interest owing to their simplicity and reliability. Predominantly, lactate sensors incorporate enzymes like lactate oxidase and lactate dehydrogenase for selective lactate recognition; however, these enzymes are expensive, susceptible to instability under extreme pH or temperature conditions, and challenging to immobilize during sensor fabrication. Notably, sweat exhibits elevated lactate levels compared to blood plasma and correlates strongly with blood lactate during exercise, as previously documented, thereby enabling non-invasive monitoring. Accordingly, this study develops a non-enzymatic lactate sensor based on an RSM-optimized molecularly imprinted polymer, synthesized via electropolymerization of o-phenylenediamine on a fMWCNT/ZnO modified electrode, using lactate as template and ethylene glycol dimethacrylate as crosslinker. The resultant SPCE/fMWCNT/ZnO/MIP sensor demonstrates a sensitivity of 818.18 μA/M/cm², broad linear range (0-120mM), limit of detection of 1.64 mM, and ∼91.5% recovery after 6 months of storage. Moreover, it affords excellent recovery rates in artificial human sweat.
In two-dimensional (2D) van der Waals heterostructures (vdWHs), semiconductor-semiconductor (S-S) and metal-semiconductor (M-S) contacts represent two fundamental types of interfacial contacts, each containing specific subtypes. Achieving nonvolatile modulation of the contact type is a crucial research topic in the interface engineering of heterostructures. However, previous studies have demonstrated nonvolatile switching only between subtypes within the same fundamental contact type, such as between type-I, type-II, and type-III band alignments in S-S contacts, or between Ohmic and Schottky contacts in M-S contacts. Nonvolatile switching between the S-S and M-S contact types has never been realized. Here, based on first-principles calculations, we predict such switching in vdWHs composed of α-tellurene (α-Te) and Janus ferroelectric In2XY2 (X/Y = S, Te; X ≠ Y) monolayers. By reversing ferroelectric polarization, α-Te/In2XY2 (X/Y = S, Te; X ≠ Y) vdWHs can achieve nonvolatile switching between S-S contacts (type-I or type-II) and M-S contacts (Ohmic, quasi-Ohmic or Schottky contacts). This study reveals a new physical mechanism and provides theoretical guidance for developing novel nanodevices based on nonvolatile contact type switching.
For quantum states exhibiting highly non-Gaussian photon-number statistics, the quantum Ziv-Zakai Bound (QZZB) for phase estimation can provide a tighter precision limit compared to the corresponding Bayesian Quantum Cramér-Rao Bound (BQCRB). This work extends this finding to the displacement parameter estimation. Specifically, we investigate the QZZB for displacement parameter estimation in both ideal and photon-loss environments. Using the characteristic-function formalism, we derive a tractable expression of the QZZB for displaced quantum states after photon loss. We then apply this framework to three representative probe states: the Fock state (FS), the single-mode squeezed vacuum state (SMSVS), and the two-mode squeezed vacuum state (TMSVS). Our results show that photon loss increases the QZZB and thus degrades the attainable precision limit, whereas increasing the mean photon number lowers the QZZB. Under a fixed mean-photon-number, the SMSVS provides a smaller QZZB than the TMSVS in the parameter region considered, while the TMSVS exhibits better robustness against photon loss. For Gaussian probes, we further show that the Bayesian Cramér-Rao bound based on homodyne detection coincides with the corresponding BQCRB, indicating that the BQCRB is an experimentally attainable local benchmark in these cases. In contrast, for the FS, the QZZB can become tighter than the BQCRB in the ideal scenario, demonstrating the usefulness of the QZZB as a global Bayesian lower bound for displacement estimation.
Asymmetric transmission waveguides enable direction-dependent electromagnetic wave propagation and play an important role in electromagnetic systems. This work proposes a novel design approach for asymmetric transmission waveguides based on stacked gradient metasurfaces. Compared with existing methods, the proposed gradient-metasurface waveguide does not rely on high-permittivity materials, while the stacked configuration effectively mitigates the inherently high loss associated with classical metal-insulator-metal (MIM) structures. Both simulation and experimental results demonstrate that the asymmetric transmission performance is well preserved in the stacked gradient-metasurface waveguide. Specifically, a forward reflection coefficient of -12.59 dB in simulation and -11.97 dB in experiment, together with a backward reflection coefficient of -0.24 dB in simulation and -1.51 dB in experiment, are achieved using a double-MIM stacked metasurface waveguide. Furthermore, owing to the shunting effect of the stacked structure, the forward and backward losses of the double-MIM stacked metasurface waveguide are reduced by 37% and 69%, respectively, compared with those of a single-MIM metasurface waveguide. As a result, a 54% reduction in the maximum temperature rise of the waveguide is realized under high-power microwave heating experiments.
We develop a kinetic model to investigate the impact of personal knowledge and trading propensity on wealth distribution. A nonlinear knowledge interaction rule is introduced to describe the evolution of agents’ knowledge under the combined influence of behavioral choice, psychological response, environmental learning, and randomness. On this basis, we formulate binary wealth exchange rules in which agents’ trading propensity depends on their behavioral characteristics. Starting from the microscopic interactions, we derive a Boltzmann-type equation governing the joint distribution of knowledge and wealth and, via scaling, obtain the corresponding Fokker–Planck equation. The model allows us to explore the interplay between knowledge accumulation and heterogeneous trading propensity in shaping stationary wealth distributions. We show that different propensity specifications lead to markedly different distributional outcomes, especially in terms of concentration and tail formation. Numerical experiments further indicate that a higher level of knowledge generally mitigates wealth concentration, whereas heterogeneous trading propensity may amplify or weaken inequality depending on its functional form. The results highlight the importance of incorporating both knowledge dynamics and behavioral heterogeneity into kinetic descriptions of wealth evolution.
Hydrogen-rich hydrides are promising candidates for high-temperature superconductivity within the framework of conventional phonon-mediated Bardeen–Cooper–Schrieffer (BCS) theory. However, the structural stability of these systems typically requires extreme pressures, which severely limits their practical applications. Consequently, considerable research effort has been devoted to identifying hydride superconductors that can remain stable and superconducting at lower pressures. Building on our previous study of LiMgZr2H12 at ambient pressure, we constructed a series of LiMgM2H12 structures with Pmmm symmetry through atomic substitution. High-throughput screening based on first-principles calculations was subsequently performed at pressures of 0, 20, 50, 100, and 200 GPa. Ultimately, nine dynamically stable structures were identified: LiMgM2H12 (M = Zr, Hf, Nb, Ta, Sn, Ti, V, As, and P). All nine compounds are predicted to be superconducting. Notably, LiMgHf2H12 and LiMgTa2H12 exhibit high superconducting critical temperatures of 104.9 and 90.4 K, respectively, at a relatively low pressure of 50 GPa. More importantly, our results suggest that early transition metals, especially 4d and 5d elements from groups IVB and VB, are more favorable for achieving higher Tc values at lower pressures. This work elucidates how elemental substitution tunes the structural stability and superconducting properties of the LiMgM2H12 series and provides theoretical guidance for designing new multicomponent hydrogen-rich superconductors.
We report the realization of a room-temperature exchange bias (EB) effect in D019-Mn3Ga/CoFeB bilayer thin films grown on SiO2/Si substrates. By systematically modulating the crystallographic orientation and interfacial strain through Ru and Ta seed layers, we demonstrate a direct correlation between structural characteristics and macroscopic magnetic response evaluated under a consistent signed convention. Our results show that while the Ru layer promotes (002) texture, the Ta layer influences the crystalline phases and alters the effective contribution of parasitic ferromagnetic clusters (FMCs). In the Mn3Ga single-layer thin films, the EB field reaches a magnitude of +38 Oe at 60 nm, driven by enhanced AFM-FMC exchange coupling along the (201) direction. For the bilayer heterostructures, a strain-mediated polarity reversal of the EB field is observed, with a maximum negative EB field of -72.6 Oe achieved at a Mn3Ga thickness of 40.0 nm in the Ru-seeded configuration. This reversal is plausibly correlated with a mathematically derived modification of the interplanar angle (Φ ∼ 61.2゜) between the (002) and (201) planes. Furthermore, as the Mn3Ga thickness varies, the EB field and coercivity exhibit distinct nonmonotonic variations governed by the threshold of strain relaxation. By correlating structural evolution with macroscopic magnetic response, this work provides a physically grounded framework for tailoring noncollinear antiferromagnetic interactions, offering valuable insights for the engineering of room-temperature spintronic architectures.
Many nonlinear dynamical systems exhibit complex periodic motions and chaos, which can be undesirable. We demonstrate that these complex periodic dynamics and chaos can be controlled by feedback perturbations of a small fixed amplitude (ϵ) on the relevant parameter. In particular, period-2 dynamics can be suppressed by creating a small confining attractor, higher-period states can be controlled to lower ones, and chaos can be tamed to the desired periodic states. In addition, the critical values of ϵ can be calculated analytically. Results of the control on the logistic map are presented with exact explicit expressions for critical ϵc for period-2 suppression and period-4 to period-2 control. The phase diagram for stable periodic regions under the control is obtained analytically and verified numerically. Furthermore, the control method is demonstrated experimentally, without prior knowledge of the equation of motion, for the complex motions of a compass under an oscillating magnetic field. The robustness of the method suggests that small regulatory effects can suppress undesirable higher-period and chaotic dynamics in complex dynamical systems, and the relevant biological or physiological implications are discussed.
Driving nanoparticle-laden biological fluids through electrically actuated microchannels is central to drug delivery, biosensing, and organ-on-chip devices, yet no prior study has obtained exact mathematical solutions for the fluid speed, temperature, and particle concentration simultaneously under oscillatory electric driving and magnetic damping. This work fills that gap with precise closed-form analytical formulas for all three fields in a parallel-plate microchannel via a natural cascade: an oscillating electric field drives the fluid, generating resistive Joule heat that in turn pushes nanoparticles thermophoretically toward the cooler channel walls. Four neural networks trained solely on the governing equations — with no access to the analytical results — independently confirm the solutions, achieving errors below 2.1% for velocity, 0.015% for temperature, and 9.94% for concentration. Principal results include: a heat-transfer coefficient fixed at a universal constant regardless of all operating conditions; wall friction unaffected by nanoparticle loading; a two-to-one wall-to-centre particle accumulation ratio invariant across all parameters; a 99% shrinkage in core thermal oscillation with increasing frequency; and over 98% velocity suppression at moderate magnetic field strength. A single explicit formula enables engineers to select channel operating conditions for a prescribed nanoparticle wall dose, offering an exact, independently verified design tool for magnetically controlled bio-nanofluid microdevices.
We calculate the magnetic dipole moments of doubly strange hidden-charm pentaquark states with spin-parity assignments JP=12− and JP=32− using QCD light-cone sum rules—presenting the first systematic QCD light-cone sum rule investigation of the electromagnetic multipole structure in the S=−2 sector. To assess the model dependence of the predictions, we employ a set of independent interpolating currents constructed in diquark-diquark-antiquark form, which probe different assumptions about the internal color-spin correlations. For the spin-32 states, we also compute the electric quadrupole and magnetic octupole moments as complementary observables. The magnetic dipole moments exhibit a considerable spread across different currents: they range from −2.15μN to 5.74 μN for spin-12 pentaquarks and from −4.25μN to −0.43μN for their spin-32 counterparts. This variation reflects the sensitivity of magnetic moments to the detailed internal wave function. A quark-level decomposition reveals that the charm quark provides the dominant contribution in most configurations, while strange quarks play a decisive role only in currents that favor axial-vector diquark structures. For the spin-32 states, the electric quadrupole moments lie between −2.01×10−2 fm2 and 5.55×10−2 fm2, and the magnetic octupole moments are typically an order of magnitude smaller. The significant current dependence of the magnetic dipole moments provides a quantitative measure of the theoretical uncertainty arising from the choice of interpolating operator. The pronounced isospin sensitivity of Jμ3(x) across all three multipole moments is shown to arise from its axial-vector diquark structure, which isolates the light quark from spin averaging and allows the charge asymmetry eu/ed=−2 to propagate directly into the electromagnetic moments; the ratio μu/μd=−2.00 confirms this mechanism exactly. Our predictions offer concrete benchmarks for future experimental measurements and lattice QCD calculations, and they may help discriminate among competing structural models for doubly strange hidden-charm pentaquarks.
Porosity strongly influences the electromechanical properties of Barium Titanate (BaTiO3, BTO) ceramics. Although porosity is generally associated with performance degradation, controlled nanoscale porosity can be exploited to tailor or even enhance specific functional properties. However, establishing a quantitative relationship between pore architecture and the macroscopic electromechanical response remains challenging. In this work, we developed a multiscale computational framework that combines molecular dynamics (MD) simulations with Mori–Tanaka (MT) micromechanical homogenization to directly link pore architecture to macroscopic electromechanical properties. First, MD simulations were performed to determine the effective elastic, piezoelectric, and dielectric tensors of nanoporous BTO with varying pore configurations and porosity levels. These atomistically derived properties were subsequently incorporated into the MT homogenization model to predict the macroscopic electromechanical behaviour. The results show that increasing porosity systematically reduces elastic stiffness. However, the dielectric and piezoelectric responses exhibit a non-monotonic dependence on pore architecture. A more uniform distribution of smaller nanopores not only mitigates stiffness degradation by more than a factor of three but also enhances the dielectric and piezoelectric responses. In particular, the piezoelectric stress coefficient e33 can be increased by up to 24% at 5% porosity, while the average relative dielectric permittivity εavgr can be increased by up to 31% at 10% porosity compared with dense BTO. Overall, the proposed multiscale framework provides a systematic route for establishing quantitative structure–property relationships in nanoporous BTO, thereby guiding the design of porous piezoelectric materials for sensing, actuation, and energy-harvesting applications.
Parametric modulation provides a powerful approach for coherently coupling detuned harmonic modes in quantum information platforms. Here, we demonstrate an on-chip superconducting multimode resonator in which strong parametric modulation induces a large and tunable normal-mode splitting, enabling controllable mode-mode coupling. When a short microwave pulse is applied under strong modulation such that its spectral bandwidth covers the two dressed-mode absorption peaks, the emitted microwave components associated with the two dressed modes interfere, giving rise to a clear time-domain beating signal. By switching off the parametric modulation before the beating signal is released, we achieve controllable time-domain beating dynamics. The observed behavior is analogous to dressed-mode dynamics associated with Autler-Townes splitting. These results highlight parametric normal-mode splitting as an effective tool for time-domain control of microwave dynamics and as a building block for future quantum information applications in superconducting circuits.
