A non-linear complex system governed by multi-spatial and multi-temporal physics scales cannot be fully understood with a single diagnostic, as each provides only a partial view and much information is lost during dat...
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A non-linear complex system governed by multi-spatial and multi-temporal physics scales cannot be fully understood with a single diagnostic, as each provides only a partial view and much information is lost during data extraction. Combining multiple diagnostics may lead to incomplete projections of the system’s physics. By identifying hidden inter-correlations between diagnostics, we can leverage mutual support to fill in these gaps, but uncovering these inter-correlations analytically is too complex. We introduce a groundbreaking machine learning methodology to address this issue. Unlike traditional methods, our multimodal approach does not rely on the target diagnostic’s direct measurements to generate its super-resolution version. Instead, it utilizes other available diagnostics to produce super-resolution data, capturing detailed structural evolution and responses to perturbations that were previously unobservable. This capability not only enhances the resolution of a diagnostic for deeper insights but also reconstructs the target diagnostic, providing a valuable tool for mitigating diagnostic failure. This methodology addresses a critical problem in fusion plasmas: the Edge Localized Mode (ELM), a plasma instability that can cause significant erosion of plasma-facing materials. One method to stabilize ELM is using resonant magnetic perturbation to trigger magnetic islands. However, low spatial and temporal resolution of measurements limits the analysis of these magnetic islands due to their small size, rapid dynamics, and complex interactions within the plasma. With super-resolution diagnostics, we can experimentally verify theoretical models of magnetic islands for the first time, providing unprecedented insights into their role in ELM stabilization. This advancement aids in developing effective ELM suppression strategies for future fusion reactors like ITER and has broader applications, potentially revolutionizing diagnostics in fields such as astronomy, astr
Efficient forward models that accurately model layered biological tissue such as the brain are vital for real-time clinical analysis. We present a robust numerical layered diffusion-based model and compare it to Monte...
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Layered models can better quantify flow changes between superficial and deeper biological tissues. We discuss their ability for real-time quantitation (0.1-5 Hz) and performance against homogeneous models in both the ...
The outstanding thermoelectric performance of GeTe has attracted significant attention in the research community in recent years. However, many of the underlying physical mechanisms that contribute to GeTe's excep...
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During epithelial wound healing, cell morphology near the healed wound and the healing rate vary strongly among different developmental stages even for a single species like Drosophila. We develop deformable particle ...
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During epithelial wound healing, cell morphology near the healed wound and the healing rate vary strongly among different developmental stages even for a single species like Drosophila. We develop deformable particle (DP) model simulations to understand how variations in cell mechanics give rise to distinct wound closure phenotypes in the Drosophila embryonic ectoderm and larval wing disc epithelium. We find that plastic deformation of the cell membrane can generate large changes in cell shape consistent with wound closure in the embryonic ectoderm. Our results show that the embryonic ectoderm is best described by cell membranes with an elasto-plastic response, whereas the larval wing disc is best described by cell membranes with an exclusively elastic response. By varying the mechanical response of cell membranes in DP simulations, we recapitulate the wound closure behavior of both the embryonic ectoderm and the larval wing disc.
Z-scheme heterojunction catalysts have received great attention due to their efficient ability to separate electrons and ***,using the first-principles calculations,we designed a series of promising two-dimensional(2D...
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Z-scheme heterojunction catalysts have received great attention due to their efficient ability to separate electrons and ***,using the first-principles calculations,we designed a series of promising two-dimensional(2D)/2D Z-scheme systems with interlayer inequivalent,including MoSi_(2)N_(4)/MoSi_(2)N_(4),WSi_(2)N_(4)/WSi_(2)N_(4) and MoSi_(2)N_(4)/WSi_(2)N_(4).Molecular dynamics simulation and phonon dispersion show that they have sufficient environmental *** inequivalent structure between the layers caused the directional formation of built-in potentials,driving the transfer of net charge between layers,which greatly enhanced their catalytic *** smaller band gap and enhanced light absorption performance further revealed their perfect catalytic ***,all they met the redox potential requirements of water splitting in a range of pH 0-7,demonstrate they are very remarkable photocatalysts for H_(2)*** interestingly,they also have good sliding ferroelectricity,and the opposite built-in potential can be obtained by sliding between layers,which is very promising for future *** works may provide new insights into energy conversion devices.
The superposition of atomic vibrations and flexoelectronic effect gives rise to a cross correlation between free charge carriers and temporal magnetic moment of phonons in conducting heterostructures under an applied ...
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The superposition of atomic vibrations and flexoelectronic effect gives rise to a cross correlation between free charge carriers and temporal magnetic moment of phonons in conducting heterostructures under an applied strain gradient. The resulting dynamical coupling is expected to give rise to quasiparticle excitations called magnetoelectronic electromagnons that carry electronic charge and temporal magnetic moment. Here, we report experimental evidence of magnetoelectronic electromagnons in the freestanding degenerately doped p-Si based heterostructure thin film samples. These quasiparticle excitations give rise to long-distance (>100 μm) spin transport, demonstrated using spatially modulated transverse magnetothermoelectric and nonlocal resistance measurements. The magnetoelectronic electromagnons are nonreciprocal and give rise to large magnetochiral anisotropy (0.352A−1T−1) that diminishes at lower temperatures. The superposition of nonreciprocal magnetoelectronic electromagnons gives rise to longitudinal and transverse modulations in charge carrier density, spin density, and magnetic moment, demonstrated using the Hall effect and edge dependent magnetoresistance measurements, which can also be called inhomogeneous magnetoelectronic multiferroic effect. These quasiparticle excitations are analogous to photons where time dependent polarization and temporal magnetic moment replace electric and magnetic field, respectively, and most likely topological because they manifest topological Nernst effect. Hence, the magnetoelectronic electromagnon can potentially give rise to quantum interference and entanglement effects in conducting solid state systems at room temperature in addition to efficient spin transport.
This paper introduces an approach for vibration-based damage detection based on matrix updating aided by the Whale Optimization Algorithm (WOA). The methodology uses the Data-driven Stochastic Subspace Identification ...
This paper introduces an approach for vibration-based damage detection based on matrix updating aided by the Whale Optimization Algorithm (WOA). The methodology uses the Data-driven Stochastic Subspace Identification (SSI-DATA) technique to determine the modal parameters, which are compared with those obtained from both healthy and damaged conditions of the structure. The methodology’s efficacy is assessed through three distinct steps: numerical simulations, experimental data, and real-world data from a bridge. Initially, numerical analyses are conducted on a cantilever beam, a 10-bar truss, and a Warren truss subjected to environmental vibrations with varying damage cases and noise levels. Subsequently, experimental validations are performed on a test system and in the Z24 Bridge. Results from the computational simulations demonstrate the method’s promise to identify, locate, and quantify single and multiple damage cases, even amidst signal noise, variations in the first vibration mode as minimal as 0.015%, and complex structures with 54 elements. Moreover, the matrix updating method utilizing WOA showcased superior accuracy compared to existing techniques in the literature. In addition, the Z24 Bridge example validated the capability of the presented damage detection method to localize structural damage solely based on natural frequencies.
We induce virtual critical coupling in an overcoupled photonic microresonator using complex-frequency pulses. We observe efficient cavity storage as an incident pulse of time constant 138 ps suppresses the resonant tr...
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We report a new type of extreme event - extreme irregular mixed-mode oscillatory burst - appearing in an asymmetric double-welled, driven Helmholtz-Duffing oscillator. The interplay of cubic and quadratic nonlineariti...
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