Coupled System Research Articles

A self-driven solar coupling system with activated carbon felt cathode for resourcefully purifying uranium and organic contaminated water

With the continuous development of nuclear energy, it becomes increasingly important to recover uranium from the radioactive wastewater, in which various organics may combine with uranyl ions (UO22+) to form refractory complexes. Developing highly active cathode materials for uranium reduction is essential to improve the performance of self-driven solar coupling system (SSCS) in treating complex radioactive wastewater. In this study, an activated carbon felt (ACF) cathode is prepared by anodizing carbon felt (CF) in NaOH solution to adjust the surface morphology and functional groups. The ACF is then used in a SSCS combined with a TiO2 nanorods array (TNA) photoanode for the efficient recovery of uranium and the rapid degradation of organic pollutants with simultaneous electricity generation. Compared to CF, the functionalized ACF with oxygen-containing functional groups, provides sufficient sites for UO22+ adsorption and facilitates the charge separation. The SSCS with the ACF cathode exhibits removal ratios of approximately 99.9 % for tetracycline hydrochloride (TCH) and UO22+, with removal rates of ∼ 0.025 and ∼ 0.154 min−1, respectively. In contrast, the SSCS with the CF cathode achieves removal rates of ∼ 0.006 and ∼ 0.026 min−1. Additionally, a maximum power density of 0.94 mW·cm−2 with a fill factor of 23.36 % is achieved. After 20 cycles, the system maintains removal ratios of 99.1 % for TCH and 98.2 % and UO22+. Intensive investigation also reveals that the system functions robustly in treating complex wastewater with a complicated condition of pH, co-exited ions, and various pollutant concentrations. Furthermore, efficient removal of organics and uranium is also achieved from polluted seawater or under real sunlight illumination. This paper presents a simple method to prepare low-cost, highly active and stable cathodes for uranium reduction in an easy-to-operated, energy-saving and economical solar-driven system.

Capacity matching and optimization of solar-ground source heat pump coupling systems

Capacity matching and optimization of solar-ground source heat pump coupling systems

Soundbox-based sound insulation measurement of composite panels with viscoelastic damping

Sound transmission loss (STL), an essential index for assessing the sound insulation performance of composite laminated structures, typically relies on experimental methods to measure. The soundbox method (SBM), a straightforward technique for measuring the STL, is sensitive to microphones’ positions. Within the framework of the Chebyshev-Ritz method, a semi-analytical vibro-acoustic model extended to composite laminated panels with viscoelastic damping (VED) is proposed for the first time. Based on the developed simplified layer-wise theory, the panel is modeled using three layers: the top face layer, the VED layer, and the bottom face layer. A closed cavity is added to the model as the soundbox enclosure used in actual measurements. By employing the Hamilton's principle, the governing equation for the coupling system is derived, and the vibration and internal acoustic responses of the coupling system are calculated. A discretization strategy is introduced to address the frequency-dependent properties of the VED layer, avoiding the need to reconstruct the stiffness matrix at each frequency. To obtain the STL of the panel, sound pressures at external measurement points are calculated based on the Rayleigh integral. The proposed model is validated against numerical results from finite element analyses. The influences of the microphone position inside and outside the cavity on the measured STL are studied. Furthermore, parametric studies over the microphones' positions are performed to enhance the SBM-based evaluation of the composite panel's sound insulation performance. The optimal locations for two internal microphones and one external microphone are recommended. Finally, experimental studies are carried out to guide the implementation of the SBM.

Particle trajectories in the KP-II equation

In the current work, we consider particle trajectories beneath traveling soliton solutions described by the Kadomtsev–Petiviashvili-II (KP-II) equation, which is a model for small-amplitude water waves in shallow water. The KP-II equation has a large number of exact solutions describing crossing line solitons. Here, we describe the particle drift induced by the single line soliton and various two- and three-soliton solutions on a two-dimensional horizontal domain.First, the derivation of the KP-II equation is used to exhibit expressions for the three components of the fluid velocity vector induced by a surface wave profile given by the KP-II equation. These velocity components can be used to specify a coupled system of ordinary differential equations (ODEs) which describe the motion of a fluid particle. Given an initial position inside the fluid for a specific particle, as well as continuously providing time-dependent values for the surface deflection, the ODE system can be solved numerically to find the particle path induced by the passage of a wave. A special numerical integration grid tracking the particle is used to handle integral terms occurring in the fluid velocity expressions.

Ultrahigh-[formula omitted] Fano resonance in a cavity-waveguide coupled system based on second-order topological photonic crystals with elliptical holes

We present a novel configuration of second-order topological photonic crystal (SOTPC) comprising interconnected dielectric material with elliptical air holes. Based on this SOTPC design, we construct a topological corner state (TCS) cavity and a topological edge state (TES) waveguide. Through the coupling of the TCS cavity with the TES waveguide, we establish a topological cavity-waveguide coupled system (TCWCS) that exhibits an ultrasharp asymmetric topological Fano resonance. Numerical simulations demonstrate that the proposed TCWCS achieves an exceptionally high quality factor exceeding 108, surpassing previously reported results by several orders of magnitude. Moreover, the refractive index sensing application implemented with TCWCS shows a sensitivity of 278 nm/RIU and a figure of merit surpassing 107 1/RIU. Notably, our simulations reveal that the lineshape and quality factor of the Fano resonance, as well as the index sensing performance in the TCWCS, are highly robust against structural defects. The demonstrated capabilities of the TCWCS open up avenues for further exploration and development in the field of topological photonics based on our proposed SOTPC.

Excellent Hole Mobility and Out-of-Plane Piezoelectricity in X-Penta-Graphene (X = Si or Ge) with Poisson's Ratio Inversion.

Recently, the application of two-dimensional (2D) piezoelectric materials has been seriously hindered because most of them possess only in-plane piezoelectricity but lack out-of-plane piezoelectricity. In this work, using first-principles calculation, by atomic substitution of penta-graphene (PG) with tiny out-of-plane piezoelectricity, we design and predict stable 2D X-PG (X = Si or Ge) semiconductors with excellent in-plane and out-of-plane piezoelectricity and extremely high in-plane hole mobility. Among them, Ge-PG exhibits better performance in all aspects with an in-plane strain piezoelectric coefficient d11 = 8.43 pm/V, an out-of-plane strain piezoelectric coefficient d33 = -3.63 pm/V, and in-plane hole mobility μh = 57.33 × 103 cm2 V-1 s-1. By doping Si and Ge atoms, the negative Poisson's ratio of PG approaches zero and reaches a positive value, which is due to the gradual weakening of the structure's mechanical strength. The bandgaps of Si-PG (0.78 eV) and Ge-PG (0.89 eV) are much smaller than that of PG (2.20 eV), by 2.82 and 2.47 times, respectively. This indicates that the substitution of X atoms can regulate the bandgap of PG. Importantly, the physical mechanism of the out-of-plane piezoelectricity of these monolayers is revealed. The super-dipole-moment effect proposed in the previous work is proved to exist in PG and X-PG, i.e., it is proved that their out-of-plane piezoelectric stress coefficient e33 increases with the super-dipole-moment. The e33-induced polarization direction is also consistent with the super-dipole-moment direction. X-PG is predicted to have prominent potential for nanodevices applied as electromechanical coupling systems: wearable, ultra-thin devices; high-speed electronic transmission devices; and so on.

Coupled piecewise tri-stable stochastic resonance system driven by dual inputs and joint EMD/VMD analysis

A novel piecewise tri-stable stochastic resonance (NPTSR) system is proposed to address the issue of output saturation caused by high-order terms limitation in this paper. Building upon this, the exploration is extended to a coupled piecewise tri-stable stochastic resonance system driven by dual inputs (DCPTSR). First, we uncover the influence of dual input interaction on output quality, finding that when the fRequencies of the two input signals are consistent, varying the amplitude of the driving signal can effectively enhance the output performance of the target signal. Secondly, by utilizing the adiabatic approximation theory, the steady-state probability density (SPD) and signal-to-noise ratio (SNR) of the DCPTSR system are derived, which allows us to analyze the effects of various parameters on both SPD and SNR. Next, three combined denoising systems, namely EMD-DCPTSR, VMD-DCPTSR, and SDCPTSR, are constructed by utilizing empirical mode decomposition (EMD), variational mode decomposition (VMD), and the stochastic resonance (SR). Through numerical simulations, we demonstrate that the combined denoising system outperforms the stand-alone SR system, and we analyze the stochastic resonance phenomenon of the DCPTSR system using the spectral amplification (SA) coefficient as an evaluation index. Finally, to assess practical applicability, these systems are deployed for bearing fault detection. The experimental results exhibit notable signal-to-noise gain improvements for the DCPTSR system compared to standalone SR systems by 0.7699 ∼ 9.4541 dB. The EMD-DCPTSR system shows signal-to-noise gain improvements of 0.3245 ∼ 1.1709 dB compared to the VMD-DCPTSR and SDCPTSR systems. Moreover, all three combined denoising systems outperform the standalone SR system in terms of signal processing capabilities. In conclusion, this paper extensively investigates the interaction between the two input signals in a dual-input system and studies the output performance of using EMD, VMD, and SR as preprocessing methods for the SR system. Through numerical simulations and practical engineering applications, we highlight the substantial advantages of combined denoising systems. These findings offer essential theoretical insights and promising prospects for engineering applications.

Chaotic Behavior and Heat Transfer Analysis of Pulsating Flows with Different Frequencies

Due to the rapid development of electronic devices, the improvement of air–cooling methods for thermal management is urgent. In the present work, a promising way of coupling pulsating flow and vortex generators is proposed to eliminate the impacts of severe local high-temperature regions behind the vortex generators. Different from the traditional qualitative analysis, chaos is introduced to identify the quantitative impacts of the nonlinear dynamics of the coupling system. Particularly, the flow field was examined using the line stretching and the Poincaré map, and the chaotic characteristics of high-frequency pulsating flow were investigated. The results show that high-frequency pulsating flow enhances heat transfer mainly by promoting chaotic mixing. The chaotic fluid repeatedly stretches and folds, which increases the line stretching. Thus, the line stretching distribution can represent the heat transfer. Compared to the steady flow case, at Reynolds number of 1024 and pulsation frequency of 250 Hz, pulsating flow improves the Nusselt number by 5.82% and reduces friction factor by 2.62%, resulting in an improvement of thermal performance factor by 6.76%.

Synthesis and characterization of Zn-In-S composites for photocatalytic benzyl alcohol oxidation and nitrobenzene reduction

Photocatalytic transformation of organics is a promising alternative to conventional synthetic methodologies. ZnIn2S4 is active in photocatalytic redox reactions, but its performance is hindered by fast charge carrier recombination, and optimizing its properties through synthesis or modification is complicated. Herein, Zn-In-S based composites were prepared via a facile solvothermal method by varying the ratio of sulfide precursor (TAA) with a fixed Zn/ In molar ratio of 1: 2. The phase composition of the obtained materials depends on the amount of TAA. At lower ratios, composites consisting of crystalline In(OH)3 and unknown ZnxInySz phase were formed. Pure-phase ZnIn2S4 was obtained when the feed molar ratio of zinc and TAA was 1: 6 or higher. The photocatalytic oxidation of benzyl alcohol (BA) and reduction of nitrobenzene (NB) in a coupled system were applied to evaluate the activity of Zn-In-S-based composites. Under visible light irradiation, the ZnxInySz/ In(OH)3 composite (ZIS14) synthesized with a molar ratio of Zn to TAA of 1: 4 exhibited boosted and optimal performance compared to the bare ZnIn2S4 and other samples. After 5 hours of irradiation, the BA conversion and benzaldehyde (BAD) yield were 57 % and 55 %, respectively, and the NB conversion and aniline (AN) yield were 70 % and 35 %, individually, outperforming previous studies under similar experimental conditions. This work not only elucidates the photoredox process of BA and NB in one system, but also has significant implications for understanding the complex hydro/solvothermal processes involved in the fabrication of multicomponent sulfides.

An Assessment of Convergence of Climate Reanalyses from Two Coupled Data Assimilation Systems with Identical High-Efficiency Filtering

Abstract Coupled data assimilation (CDA) uses coupled model dynamics and physics to extract observational information from measured data in multiple Earth system domains to reconstruct historical states of the Earth system, forming a reanalysis of climate variability. Due to imperfect numerical schemes in modeling dynamics and physics, models are usually biased from the real world. Such model bias is a critical obstacle in the reconstruction of historical variability by combining model and observations and, to some degree, causes divergence of CDA results because of individual model behavior in each system. Here, based on a multitime-scale high-efficiency filtering algorithm which includes a deep-ocean bias relaxing scheme, we first develop a high-efficiency online CDA system with the Community Earth System Model (CESM-MSHea-CDA). Then, together with the other previously established CDA system within the Coupled Model, version 2.1 (CM2-MSHea-CDA), that is developed by the Geophysical Fluid Dynamics Laboratory, we conduct climate reanalysis for the past 4 decades (1978–2018). Evaluations show that due to improved representation for multiscale background statistics and effective deep-ocean model bias relaxing, both CDA systems produce convergent estimation of variability for major climate signals such as variability of basin-scale ocean heat content, El Niño–Southern Oscillation (ENSO), and Pacific decadal oscillation (PDO). Particularly, both CDA systems generate similar time mean of global and Atlantic meridional overturning circulations that converge to the geostrophic velocity estimate from climatological temperature and salinity data. The CDA-estimated mass transport at typical measurement sections is mostly consistent with the observations. Significance Statement A coupled climate model simulates the interactions of the atmosphere, ocean, sea ice, and land processes and derives change and variations of the climate system by combining these components. Due to imperfect numerical schemes, a model usually has systematic biases to the real world. Coupled data assimilation (CDA) combines coupled model dynamics and physics with atmospheric and oceanic observations to reconstruct the historical states of Earth’s climate system, forming the analysis of climate change and variability. However, because of the existence of model errors and individual data assimilation algorithm behaviors, currently, the ocean variability of reanalysis produced by different numerical systems is basically divergent. Here, we first apply an identical coupled data assimilation algorithm and effective model error relaxing scheme to two widely used IPCC coupled models to establish two CDA systems. Then, we use both CDA systems to assimilate historical atmospheric and oceanic observations to form two sets of climate reanalyses for the past 4 decades. We found, by some degree, that the results of these multimodel coupled climate reanalyses converged to what historical states ought to be in observational estimation. These convergent climate reanalyses are expected to significantly increase our understanding of CDA and climate assessment.

A novel optimization framework using frequency-based substructuring for estimation of linear bolted joint stiffness and damping

Estimating the stiffness and damping coming from a joint is a major challenge. This work proposes a novel framework to estimate the unknown parameters using frequency-based substructuring and a maximum a posteriori optimization approach. The idea is to minimize the discrepancy between the measured responses of an assembled system and the responses obtained by coupling the measured responses of the individual substructures with a joint model. The system’s dynamics are assumed to be linear. However, the FRFs of the coupled system (which drive the objective function) change nonlinearly with the linear joint parameters, making it a nonlinear optimization problem. Therefore, the joint parameters are estimated iteratively using the Gauss minimization method, a well-established linearization scheme. The framework is numerically validated on simple mdof systems, and the method’s effectiveness is tested by adding noise to the generated data. To demonstrate the framework’s applicability on real structures, joint stiffness and damping of a known benchmark structure are estimated based on real measurements. Two different underlying joint models are applied. The first assumes just flexibility at the connection. The second assumes the joint is a separate substructure. The algorithm can find realistic stiffness parameters and a range for the damping parameters providing a good compromise between the measurements in both cases.

Study on Vibration and Noise of Railway Steel–Concrete Composite Box Girder Bridge Considering Vehicle–Bridge Coupling Effect

A steel–concrete composite beam bridge fully exploits the mechanical advantages of the concrete structure and steel structure, and has the advantages of a fast construction speed and large stiffness. It is of certain research value to explore the application of this bridge type in the field of railway bridges. However, with the rapid development of domestic high-speed railway construction, the problem of vibration and noise radiation of high-speed railway bridges caused by train loads is becoming more and more serious. A steel–concrete composite beam bridge combines the tensile characteristics of steel and the compressive characteristics of concrete perfectly. At the same time, it also has the characteristics of a steel bridge and concrete bridge in terms of vibration and noise radiation. This feature makes the study of the vibration and noise of the bridge type more complicated. Therefore, in this paper, the characteristics of vibration and noise radiation of a high-speed railway steel–concrete composite box girder bridge are studied in detail from two aspects: the theoretical basis and a numerical simulation. The main results obtained are as follows: Relying on the idea of vehicle–rail–bridge coupling dynamics, a structural dynamics analysis model of a steel–concrete combined girder bridge for a high-speed railroad was established, and numerical program simulation of the vibration of the vehicle–rail–bridge coupling system was carried out based on the parametric design language of ANSYS 18.0 and the language of MATLAB R2021a, and the structural vibration results were analyzed in both the time domain and frequency domain. By using different time-step loading for the vehicle–rail–bridge coupling vibration analysis, the computational efficiency can be effectively improved under the condition of guaranteeing the accuracy of the result analysis within 100 Hz. Based on the power flow equilibrium equation, a statistical energy method of calculating the high-frequency noise radiation is theoretically derived. Based on the theoretical basis of the statistical energy method, the high-frequency noise in the structure is numerically simulated in the VAONE 2021 software, and the average contribution of the concrete roof plate to the three acoustic field points constructed in this paper is as high as 50%, which is of great significance in the study of noise reduction in steel–concrete composite girders.

Analysis on dual Fano resonance in a coupled-resonator waveguide

Dual Fano resonance was demonstrated in a compact coupling system without additional large footprint tunable devices consisting of a grating-coupled waveguide and a micro-racetrack resonator on thin film lithium niobate. A multimode interference model was proposed for the dual Fano resonance system. The inverse design method was used to realize model fitting, validate our model, and analyze our model. Based on the parameters obtained by the inverse design, we further analyzed the influence of different parameters. Our research also shows that through the interaction of two Fano resonance modes, tunable line shape and enhanced extinction ratio can be realized in the transmission spectrum, which has potential applications in optical sensing.

Enhancing linezolid activity in the treatment of oral biofilms using novel chitosan microneedles with iontophoretic control

This study aimed to prepare and assess active microneedle (MN) patches based on a novel biomaterial and their effective coupled (physical and electrical) transdermal delivery of a model drug (Linezoid). Modified MN patches (e.g. fabricated from Linezoid, boronated chitosan, polyvinyl alcohol and D-sorbitol) were engineered using a vacuum micromoulding method. Physicochemical, FTIR (Fourier transform infrared), in-silico, structural and thermal analysis of prepared formulations were conducted to ascertain MN quality, composition and integrity. In-vitro mechanical tests, membrane toxicity, drug release, antibiofilm, ex-vivo mucoadhesion, insertion and in-vivo antibiofilm studies were performed to further validate viability of the coupled system. Optimized MN patch formulation (CSHP3 - comprising of 3 % w/v boronated chitosan, 3.5 % w/v PVA and 10 % w/w D-sorbitol) exhibited sharp-tipped, equi-distant and uniform-surfaced micron-scaled projections with conforming physicochemical features. FTIR analysis confirmed modification (i.e., boronation) of chitosan and compatibility as well as interaction between CSHP3 constituents. In-silico analysis indicated non-covalent interactions between all formulation constituents. Moreover, boronated chitosan-mucin glycoprotein complex showed a stronger bonding (∼1.86 times higher CScore) as compared to linezolid-mucin counterpart. Thermal analysis indicated amorphous nature of CSHP3. A ∼ 1.42 times higher tensile strength was displayed by CSHP3 as compared to control (i.e., pure chitosan, polyvinyl alcohol and D-sorbitol-based MN patch). Membrane toxicity study indicated non-toxic and physiological compatible nature of CSHP3. Within 90 min, 91.99 ± 2.3 % linezolid was released from CSHP3. During release study on agarose gel, CSHP3-iontophoresis treatment resulted in a ∼ 1.78 and ∼ 1.20 times higher methylene blue-covered area and optical density, respectively, within 60 min as compared to CSHP3 treatment alone. Staphylococcus aureus biofilms treated with CSHP3 exhibited 65 ± 4.2 % reduction in their mass. CSHP3 MN patches remained adhered to the rabbit oral mucosa for 6 ± 0.15 h. Mucosa treated with CSHP3 and CSHP3-iontophoresis combination showed a generation of pathways in the epithelium layers without any damage to the underlying lamina propria. Eradication of Staphylococcus aureus from oral mucosal wounds and complete tissue regeneration was recorded following 7-day treatment using CSHP3-iontophoresis coupled approach.

Post-earthquake damage probability assessment of high-speed railway simply supported bridge based on traffic capacity

Railway transportation is an important channel for emergency rescue and disaster relief. Traditionally, the method of evaluating the damage degree of bridges under different seismic intensities from the perspective of structural damage cannot be directly used to judge the traffic capacity of trains on bridges after earthquakes. It is impossible to guarantee the running safety and affect the transportation of materials after the earthquake. Because the damage state of track structure directly affects the running safety of trains, this study combines the relationship between the damage of track structure and the deformation of bridge structure after earthquake, and puts forward the transverse relative displacement of girder end (TRDGE) as the damage index of train running function of railway bridge after earthquake. Then, the OpenSees-TRBF (Train-Railway-Bridge-Foundation Coupled System Dynamic Analysis Platform) co-simulation method is used to carry out the train-track-bridge coupling dynamic calculation under different seismic damage states, and the running safety analysis database under different TRDGEs is established. Then, the Particle Swarm Optimization (PSO) algorithm is used to classify the bridge damage index of traffic capacity through different target safety speeds. Based on the probabilistic seismic demand model, the exceedance probability curve of traffic capacity damage under different seismic intensities is established. Finally, based on the curve, the running safety risk domain of trains on the bridge under different seismic intensities is obtained with a confidence level of 95 %. This study proposes a post-earthquake damage assessment method for railway bridges based on the assurance of running safety probabilities, evaluating the damage degree of the bridge with the residual traffic capacity of the bridge after the earthquake. This study can be applied to assess earthquake damage on existing railway bridges and provide references for the safe speed of trains on the bridge after an earthquake.

A hybrid reanalysis-forecast meteorological forcing data for advancing climate adaptation in agriculture

Climate variability in the growing season is well suited for testing adaptation measures. Adaptation to adverse events, such as heatwaves and droughts, increases the capacity of players in agri-food systems, not only producers but also transporters and food manufacturers, to prepare for production disruptions due to seasonal extremes and climate change. Climate impact models (e.g., crop models) can be used to develop adaptation responses. To run these models, historical records and climate forecasts need to be combined as a single daily time series. We introduce the daily 0.5° global hybrid reanalysis-forecast meteorological forcing dataset from 2010 to 2021. The dataset consists of the Japanese 55-yr Reanalysis (JRA55) and the Japan Meteorological Agency/Meteorological Research Institute Coupled Prediction System version 2 (JMA/MRI-CPS2) 5-member ensemble forecast. Both are bias-corrected using the Delta method and integrated with a baseline climatology derived from the Environmental Research and Technology Development Fund’s Strategic Research 14 Meteorological Forcing Dataset (S14FD). The dataset is called JCDS (JRA55-CPS2-Delta-S14FD) and offers a framework for monitoring and forecasting applications towards adaptation.

Irreversibility analysis of Eyring Powell nanofluid flow in curved porous channel

AbstractThe aim of this study is to minimize entropy in the MHD Eyring‐Powell fluid through a semi‐porous curved channel. The flow phenomena are examined under the consideration of joule heating, viscous heating, thermophoresis, and Brownian motion. The motivation of this research is to minimize entropy production in curved porous channel because thermal systems become more efficient as a result of decreased energy consumption, operational expenses, and experimental costs. This approach is useful in designing industrial equipment that requires efficient thermal management, such as fuel cells, chemical processing, and advanced refrigeration systems. The coupled boundary layer equations of the problem are highly nonlinear PDEs, which are transformed into systems of coupled ODEs by using similarity variables. The solution of a coupled system of ODEs is obtained numerically via Bvp4c. The effect of several physical parameters for entropy analysis, Bejan number, concentration, and velocity/temperature are illustrated and analyzed using graphs. Furthermore, the computational outcomes of physical quantities, for example, heat and mass transfer rate are also presented. Results indicated that the increasing value of the Reynolds number increases the entropy generation rate, while the reverse tendency is noticed for the Eyring‐Powell parameter. The rising values of the Brownian parameter increase the Bejan number after its decrease, while reverse behavior is observed for the thermophoresis parameter.

Model order reduction of thermal-dynamic coupled flexible multibody system with multiple varying parameters

Spacecrafts usually suffer from the thermal shock during operation, leading to large control error or even failure. At the same time, spacecrafts are often rigid-flexible coupled multibody systems with large degrees of freedom and multiple varying parameters. The real-time control and condition monitoring require effective order reduction methods. In this investigation, the displacement and temperature fields are discretized by the Absolute Node Coordinate Formulation (ANCF) to achieve unified description. The coupled thermal-dynamic reduced-order model (ROM) is established based on the Proper Orthogonal Decomposition (POD) method. For the purpose of further increase efficiency, a linearization method is introduced so that the calculation times of the elastic force can be significantly reduced. In order to predict the response of the thermal-dynamic coupled system with multiple varying parameters, the interpolation on Grassmann manifold is introduced to maintain the orthogonality of the basis. As verification and validation, three numerical examples are presented to show the feasibility and efficacy of the proposed method.

Unveiling the Influence of Line Shape of Surface Plasmon Resonances on Exciton–Plasmon Strong Coupling

AbstractStrong coupling between surface plasmon resonance (SPR) modes and excitons holds great potential for many chemical and physical applications. However, a clear understanding on how far‐field spectral characteristics of SPR (linewidths and intensity) affect the coupling strength remains unclear because these parameters are difficult to be individually tuned. These spectral characteristics are associated with the damping rate and field enhancement that depend on the morphology of the plasmonic nanostructure. In this work, the influence of the SPR line shape on exciton‐plasmon coupling is systematically investigated by delicately tuning the linewidths and resonance intensities of the plasmonic arrays. It is found that the SPR modes with narrow linewidths or large intensity are favorable for the exciton–plasmon system to achieve strong coupling. The obtained clear relationships between the SPR line shape and coupling strength provide guidance for the design and optimization of exciton‐plasmon coupling systems, favoring the highly efficient manipulation of exciton polaritons and enabling specific applications driven by strong coupling.

Mathematical analysis and asymptotic predictions of chemical-driven swimming living organisms in weighted networks

This paper derives well-posedness and asymptotic results that provide qualitative information about the behavior, mechanism and strategies used by living organisms to navigate their biological networks. Chemical driven swimming is a captivating phenomenon that is observed in various living organisms like bacteria and protozoa but the problem in weighted networks is more complex, since the equations of parabolic-parabolic Keller-Segel model coupled with incompressible Navier-Stokes equations must be reformulated in a discrete setting. The starting point is to transpose the coupled system from the Euclidean case to the connected networks with certain network-theoretic simplified approaches, which yields fruitful key results. These results not only enable the construction of global solutions but also serve as a foundation for determining information about the stability and large time behavior of the system. Then, decay rates are well established to predict important features, such as how quickly weak solutions at a given point decrease over time due to dissipative processes. Additionally, the L1- convergence of cell densities towards the self-similar Gaussian solution of the heat equation is well proved by time dependent scaling, which shows that the solution maintains its shape and only scales in time and space as time evolves. Finally, this paper includes many numerical tests through a recent robust numerical scheme to illustrate the theoretical results and to develop computational control and prediction of living organisms' trajectories around central nodes in networked flows.