Variation Of Structural Parameters Research Articles

External electric field induced emission behavior for ESIPT-based 2-(benzo[d]thiazol-2-yl)-4-(pyren-1-yl)phenol towards near-infrared region

Organic light-emitting diodes (OLEDs) for low energy transfer and double emission, but the current methods for regulating ESIPT processes are mostly solvent and substituent effects. Here, utilizing the density theory functional (DFT) and time-dependent density functional theory (TD-DFT) methods, the ESIPT process controlled by an external electric field (EEF) is proposed, and the changes in photophysical properties of 2-(benzo[d]thiazol-2-yl)-4-(pyren-1-yl)phenol (PyHBT) are investigated. Structural parameter variations and IR vibrational spectra measure the prerequisite for the ESIPT process, namely, intramolecular hydrogen bond (IHB) strength, and the scanned potential energy curves (PECs) demonstrate that the ESIPT process of PyHBT is harder to execute as the positive EEF increases, and the opposite is true for the negative EEF. The absorption and fluorescence spectra show shifts under the distinct EEFs, and even the emission wavelength reaches the short-wave near-infrared (SW-NIR) region (780–1100 nm), such as 815.2 nm for a positive EEF of + 30 × 10-4 a.u. in the keto form. Additionally, the fluorescence intensity of PyHBT is strongly influenced by the positive EEF, especially in the enol form, and the investigation of the mechanism by hole-electron analysis demonstrates that under the positive EEF, the twisted intramolecular charge transfer (TICT) process is induced, which triggers the weakening of the fluorescence intensity. In summary, our work not only complements the theoretical approach to modulate the ESIPT process, but also reveals that the photophysical properties of materials affected by the external electric field are even expected to reach the NIR region.

Investigation on enhanced band-gap properties of 2D hierarchical phononic crystals

Phononic crystals have garnered considerable attention in recent years for their unique band-gap properties, which can effectively manipulate the propagation of acoustic and elastic waves. This research focuses on exploring richer band gaps and utilizing band gap characteristics to achieve structural vibration reduction. In this study, a novel two-dimensional (2D) hierarchical phononic crystal with rich periodicities is proposed, which possesses enhanced band-gap properties. The research method used for the proposed structure is numerical simulation using the finite element method (FEM). By applying Bloch’s theorem, FEM is a more convenient tool for calculating the band gap of structures. Based on the numerical results, it can be concluded that the band gaps of the proposed 2D hierarchical phononic crystal can be classified not just into full and directional band gaps, but also into more fascinating categories based on the vibration patterns of macro and micro unit cells, which are referred to as Type I, Type II and Type III band gaps. Furthermore, the impact of structural parameter variations on the band gap is also studied, and results indicate that appropriate adjustments to the structural parameters (such as the number of unit cell n, the angle θ and the length l1) can lead to low-frequency shift and bandwidth increase in certain band gaps. A prototype of the hierarchical phononic crystal is manufactured using the 3D printing technique. Vibration tests are conducted and the simulation and experimental results are compared to verify the vibration reduction performance of the 2D hierarchical phononic crystal. The important contribution of this study is to reveal an interesting band gap generation characteristic of 2D hierarchical phononic crystals, which is beneficial for promoting understanding of the band gap mechanism in periodic structures. The enhanced band-gap properties in hierarchical periodic structures provide more potentialities and possibilities for practical vibration and noise reduction applications.

Study on updating finite element model of steel truss structure based on knowledge-enhanced deep reinforcement learning

Accurate assessment of the damage to a structure is the key to structural health monitoring. Among them, one effective means to assess the real-time status of the structure is by establishing a finite element model (FEM) of the structure and updating it synchronously. Previous research mainly updates the FEM of the structure with a certain moment in time without considering the continuous changes of structural parameters over a longer time. In this paper, we propose a FEM updating method for steel truss structure based on knowledge-enhanced deep reinforcement learning, which introduces long short-term memory (LSTM) network based on a deep deterministic policy gradient (DDPG) algorithm and constructs a knowledge-enhanced noise function (NF) module based on parametric analysis. The NF-LSTM-DDPG algorithm can fit a continuous variation of structural parameters. The ablation experiments revealed that the LSTM network and the NF module facilitate the exploration and learning ability of the DDPG algorithm. The NF-LSTM-DDPG algorithm is used in an actual steel truss structure case, and the variation rules of the elastic modulus and support deviations obtained from the solution are consistent with the actual situation. The average relative error of the 34 strain measurement points after updating is 14.147 %, and the relative error is higher than 20 % in only 13 days out of 187 days of continuous monitoring. Five days were selected for the comparative study, and the experimental results show that the relative error of the NF-LSTM-DDPG algorithm is 13.206 %, which is higher than that of the particle swarm optimization algorithm and the simulated annealing algorithm. The change of elastic modulus updated based on the NF-LSTM-DDPG algorithm is more reasonable than other algorithms.

Syntheses and Patterns of Changes in Structural Parameters of the New Quaternary Tellurides EuRECuTe3 (RE = Ho, Tm, and Sc): Experiment and Theory.

The layered orthorhombic quaternary tellurides EuRECuTe3 (RE = Ho, Tm, Sc) with Cmcm symmetry were first synthesized. Single crystals of the compounds up to 500 μm in size were obtained by the halide-flux method at 1120 K from elements taken in a ratio of Eu/RE/Cu/Te = 1:1:1:3. In the series of compounds, the changes in lattice parameters were in the ranges a = 4.3129(3)-4.2341(3) Å, b = 14.3150(9)-14.1562(9) Å, c = 11.2312(7)-10.8698(7) Å, V = 693.40(8)-651.52(7) Å3. In the structures, the cations Eu2+, RE3+ (RE = Ho, Tm, Sc), and Cu+ occupied independent crystallographic positions. The structures were built with distorted copper tetrahedra forming infinite chains [CuTe4]7- and octahedra [RETe6]9- forming two-dimensional layers along the a-axis. These coordination polyhedra formed parallel two-dimensional layers CuRETe32-∞2. Between the layers, along the a-axis, chains of europium trigonal prisms [EuTe6]10- were located. Regularities in the variation of structural parameters and the degree of distortion of coordination polyhedra depending on the ionic radius of the rare-earth metal in the compounds EuRECuCh3 (RE = Ho, Er, Tm, Lu, Sc; Ch = S, Se, Te) were established. It is shown that with a decrease in the ionic radius ri(RE3+) in the compounds EuRECuTe3, the unit-cell volume, bond length d(RE-Te), distortion degree [CuTe4]7-, and crystallographic compression of layers [RECuTe3]2- decreased. The distortion degree of tetrahedral polyhedra [CuCh4]7-, as well as the structural parameters in europium rare-earth copper tellurides EuRECuTe3, were higher than in isostructural quaternary chalcogenides. Ab initio calculations of the crystalline structure, phonon spectrum, and elastic properties of compounds EuRECuTe3 (RE = Ho, Tm, and Sc) ere conducted. The types and wave numbers of fundamental modes were determined, and the involvement of ions in IR and Raman modes was assessed. The calculated data of the crystal structure correlated well with the experimental results.

Investigation of geometrical hopper and initial packing state on the inter-phase momentum transfer with granular flow in vertical packed bed

Abstract For the specific application of vertical packed bed design, the main task is to optimize and improve the granular flow pattern, since a worse granular flow pattern is detrimental to the performance of heat transfer and flow in vertical packed bed. To improve the uniformity of granular flow profiles, an application of the discrete element method is used to investigate the granular flow pattern in a vertically packed bed under the condition of different tapered hopper angles and initial packing states. The uniformity of granular dramatically decreases with an increase in the fluctuation of granular velocity distribution. The variation of structural parameters has a positive influence on enhancing the stability of the granular layer. Coefficient of variation and relative fluctuation kinetic energy are introduced as criteria to describe the stability of the granular layer. This study numerically reveals the evolution of initial packing states has a slight influence on improving the stability of granular flow.

Optimization of the deformation transfer mechanism: analysis of spring hanging point and structural parameters

Abstract This paper thoroughly investigates the impact of the spring hanging point’s positioning and structural parameters on the multi-mode robot’s performance within the deformable transfer domain mechanism. The spring hanging point is a pivotal design element, significantly influencing the robot’s extensive deformation, efficiency, and adaptability. Operating as a cross-domain entity between land and air, the robot effectuates the transition between ground and aerial domains via the deformation trans-domain mechanism, executing a spectrum of intricate tasks. The precise placement of the spring hanging point and variations in structural parameters directly shape the robot’s performance metrics, encompassing deformation speed, stability, and energy utilization. Through elucidating fundamental principles, deliberating spring hanging point location choices, suggesting optimization methodologies, scrutinizing structural parameter impact on performance, and validating via dynamic modeling, this paper offers theoretical underpinnings for deforming domain mechanism design and enhancement, thereby elevating the robot’s overall efficacy.

Deep learning-based prediction of plant height and crown area of vegetable crops using LiDAR point cloud

Remote sensing has been increasingly used in precision agriculture. Buoyed by the developments in the miniaturization of sensors and platforms, contemporary remote sensing offers data at resolutions finer enough to respond to within-farm variations. LiDAR point cloud, offers features amenable to modelling structural parameters of crops. Early prediction of crop growth parameters helps farmers and other stakeholders dynamically manage farming activities. The objective of this work is the development and application of a deep learning framework to predict plant-level crop height and crown area at different growth stages for vegetable crops. LiDAR point clouds were acquired using a terrestrial laser scanner on five dates during the growth cycles of tomato, eggplant and cabbage on the experimental research farms of the University of Agricultural Sciences, Bengaluru, India. We implemented a hybrid deep learning framework combining distinct features of long-term short memory (LSTM) and Gated Recurrent Unit (GRU) for the predictions of plant height and crown area. The predictions are validated with reference ground truth measurements. These predictions were validated against ground truth measurements. The findings demonstrate that plant-level structural parameters can be predicted well ahead of crop growth stages with around 80% accuracy. Notably, the LSTM and the GRU models exhibited limitations in capturing variations in structural parameters. Conversely, the hybrid model offered significantly improved predictions, particularly for crown area, with error rates for height prediction ranging from 5 to 12%, with deviations exhibiting a more balanced distribution between overestimation and underestimation This approach effectively captured the inherent temporal growth pattern of the crops, highlighting the potential of deep learning for precision agriculture applications. However, the prediction quality is relatively low at the advanced growth stage, closer to the harvest. In contrast, the prediction quality is stable across the three different crops. The results indicate the presence of a robust relationship between the features of the LiDAR point cloud and the auto-feature map of the deep learning methods adapted for plant-level crop structural characterization. This approach effectively captured the inherent temporal growth pattern of the crops, highlighting the potential of deep learning for precision agriculture applications.

Spatial and temporal variations of fish assembly with environmental parameters from two major rivers in Dinajpur district of Bangladesh

The study examined habitat and seasonal variations of fin fish structure and ecological parameters in the Atrai and Dhepa Rivers, Dinajpur, Bangladesh. The researchers collected data from four sampling stations, revealing 15532 individuals from 44 genera and 59 species. Pethia ticto, Chanda nama, Cirrhinus reba, Puntius sophore, and Salmophasia bacaila were recorded as dominated fishes (>4.95%). The fish population was highest in autumn at Mohonpur (MP), while lowest in the monsoon at Karnai Bazar (KB). There were no significant variations across stations for rainfall, dissolved oxygen, pH, transparency, air and water temperatures, and pH. However, significant differences were observed among seasons based on all factors. The study also revealed differences in dominance, Margalef, Shannon, and evenness diversity indices spatiotemporally, except for evenness diversity indices among seasons. The findings could be useful for conservation studies in the future, especially after establishing and managing restricted areas like fish sanctuaries in both rivers. Bangladesh J. Sci. Ind. Res. 59(2), 55-66, 2024

Research on the ignition mechanism and structural optimization of turbulent jet pre-chamber in GDI engines

Turbulent jet ignition has been widely studied, but it is mainly focused on gas engines, the igniting mechanisms of pre-chamber (PC) on GDI engines and the contributions of heat and radicals of the jet in inhomogeneous charge still remain to be clarified. Thus, 3-D simulations with comprehensive spray mixing process were performed under variable structural parameters. The decoupling results of thermal and chemical effects show that the influence of jet temperature on the heat release rate (HRR) inside main chamber (MC) is greater than that of free radicals. The mechanism of hot jet ignition containing free radicals in MC is flame propagation without ignition delay. However, compared to jet temperature, the free radicals in the jet have less effects on HRR in MC after the ignition. The nozzle diameter significantly affects fuel entry into the PC, influencing the pressure difference between PC and MC, and thus the jet velocity and duration. The optimal diameter in this study is 1.0 mm, and the jet duration is prolonged for too small or too large diameters. The nozzle angle is constrained by combustion chamber geometry, with the optimal angle being 140° to avoid jet impingement on cylinder head or piston.

Damage detection and model updating of offshore jacket platforms using a direct sensitivity relation based on structural response

One of the challenges of the finite element model updating using time domain data is the lack of a direct relationship between changes in structural parameters and structural responses. Computational techniques, such as the Finite Difference Method (FDM) and Direct Differentiation Method (DDM), are used to calculate the sensitivity of the structural response to variations of structural parameters in the time domain. The use of these methods is time-consuming for large and complex structure. In the present study, an exact sensitivity equation is presented that establishes a direct and linear relationship between changes of structural parameters and structural response variations. The proposed closed form equations, have high computational efficiency in calculating the sensitivity of time domain responses. The measured responses directly contribute to the calculation of the sensitivity matrix, so the finite element model updating procedure is improved in terms of accuracy and reliability. The proposed method updates the finite element model even using a single excitation frequency that distinguishes the presented sensitivity relationship from frequency response-based methods which use wide ranges of excitation frequencies for model updating. To evaluate the effectiveness of the proposed method, different damage scenarios with different intensities have been simulated on two offshore jacket platform models. The performance of the proposed method in identifying the location and severity of induced damages in the presence of measurement and modeling errors confirms the effectiveness of the proposed method.

Synthesis, Crystal Structure, and Optical and Magnetic Properties of the New Quaternary Erbium Telluride EuErCuTe3: Experiment and Calculation.

This paper reports for the first time on a new layered magnetic heterometallic erbium telluride EuErCuTe3. Single crystals of the compound were obtained from the elements at 1120 K using CsI as a flux. The crystal structure of EuErCuTe3 was solved in the space group Cmcm (a = 4.3086(3) Å, b = 14.3093(9) Å, and c = 11.1957(7) Å) with the KZrCuS3 structure type. In the orthorhombic structure of erbium telluride, distorted octahedra ([ErTe6]9-) form two-dimensional layers (Er(Te1)2/2e(Te2)4/2k-)∞2, while distorted tetrahedra ([CuTe4]7-) form one-dimensionally connected substructures (Cu(Te1)2/2e(Te2)2/1t5-∞1) along the [100] direction. The distorted octahedra and tetrahedra form parallel two-dimensional layers (CuErTe32-∞2) between which Eu2+ ions are located in a trigonal-prismatic coordination environment (EuTe610-). The trigonal prisms are connected by faces, forming chains (Eu(Te1)2/2(Te2)4/22-∞1) along the [100] direction. Regularities in the variations in structural parameters were established in the series of erbium chalcogenides (EuErCuCh3 with Ch = S, Se, and Te) and tellurides (EuLnCuTe3 with Ln = Gd, Er, and Lu). Ab-initio calculations of the crystal structure, phonon spectrum, and elastic properties of the compound EuErCuTe3 were performed. The types and wavenumbers of fundamental modes were determined, and the involvement of ions in the IR and Raman modes was assessed. The experimental Raman spectra were interpreted. The telluride EuErCuTe3 at temperatures below 4.2 K was ferrimagnetic, as were the sulfide and selenide derivatives (EuErCuCh3 with Ch = S and Se). Its experimental magnetic characteristics were close to the calculated ones. The decrease in the magnetic phase transition temperature in the series of the erbium chalcogenides was discovered.

Integrated study of the structural and magnetic characteristics of Nd(Mn, Cr)0.5O3: exploring perovskite material

In this work, a perovskite material, Nd(Mn,Cr)0.5O3, is synthesized by a sol–gel chemical route method, and the structural and magnetic properties of the prepared samples were studied for a range of annealing temperatures. The variation of structural parameters against annealing temperatures is analyzed via Rietveld refinement, and it exhibits orthorhombic cubic geometry with non-monotonically increasing lattice parameters. lattice strain is due to canting in the Cr3+ and Mn3+ ions and the presence of strain is also confirmed by the shifting of XRD peaks towards a higher 2θ angle. The obtained Goldschmidt tolerance factor is 0.87, which confirms the stability of the perovskite structure. The magnetic properties of the prepared samples show the ferromagnetic transition temperature ranging from 86.5 K to 82.2 K due to super-exchange interaction between Cr3+ and Mn3+ ions via oxygen ions. The stability in crystal structure, lower value of strain, and ferromagnetic nature at low temperature for the samples annealed up to1000 °C may make this material applicable for magnetic data storage.

Configurable dual-topological-interface-states induced reflection in hybrid multilayers consisting of a Ge2Sb2Te5 film

Active control of induced reflection is crucial for many potential applications ranging from slowing light to biosensing devices. However, most previous approaches require patterned nanostructures to achieve controllable induced reflection, which hinders their further applications due to complicated architectures. Herein, we propose a lithography-free multilayered structure to achieve the induced reflection through the coupling of dual-topological-interface-states. The multilayers consist of two one-dimensional (1D) photonic crystals (PCs) and an Ag film separated by a Spacer, topological edge state (TES) and topological Tamm state (TTS) can be excited simultaneously and their coupling induces the reflection window. The coupled-oscillator model is proposed to mimic the coupling between the TES and TTS, and the analytical results are in good agreement with finite element method (FEM). In addition, the TES-TTS induced reflection is robust to the variation of structural parameters. By integrating an ultra-thin phase-change film of Ge2Sb2Te5 (GST) into the multilayers, the induced reflection can be switched through the phase transition of the GST film. The multipole decomposition reveals that the vanished reflection window is arising from the disappearance of TTS associated with the toroidal dipole (TD) mode.

Leading-edge tubercles as an alternative to increasing a Francis turbine torque generation

Hydroelectricity accounts for 63.8% of Brazilian electricity, but several of the country’s power plants require modernization. For this, the insertion of leading-edge tubercles is an alternative since this device improves wind and tidal turbines. Surprisingly, no study explored the device’s potential for hydraulic turbine improvement. To address this gap, numerical simulations were conducted in Ansys CFX to assess the tubercles’ effects on the performance of Francis turbines. For this, the current study validated the simulations and tested the impacts of the tubercle structural parameters variation over the benchmarking turbine Francis-99 and applied the device in a non-modernized runner blade to evaluate its effects on equipment performance. The parameters test revealed that variations in tubercle amplitude and waviness ratio improved the torque generation up to 0.34% despite elevating the net head up to 0.43%. In the non-modernized blade, the device increased the torque generation and net head up to 1.77% and 4.13%, respectively, proving that the tubercles are an alternative for hydraulic turbine improvement. Also, the flow field analysis exhibits that the device creates vortices that influence the blade pressure side, delaying boundary layer detachment, agreeing with other results in the literature.

Electrochemical Capacitance Traces with Interlayer Spacing in Two‐dimensional Conductive Metal–Organic Frameworks

AbstractElectrically conductive metal–organic frameworks (MOFs) are promising candidates for electrochemical capacitors (EC) for fast energy storage due to their high specific surface areas and potential for redox activity. To maximize energy density, traditional inorganic pseudocapacitors have utilized faradaic processes in addition to double‐layer capacitance. Although conductive MOFs are usually comprised of redox active ligands which allow faradaic reactions upon electrochemical polarization, systematic studies providing deeper understanding of the charge storage processes and structure‐function relationships have been scarce. Here, we investigate the charge storage mechanisms of a series of triazatruxene‐based 2D layered conductive MOFs with variable alkyl functional groups, Ni3(HIR3‐TAT)2 (TAT=triazatruxene; R=H, Et, n‐Bu, n‐Pent). Functionalization of the triazatruxene core allows for systematic variation of structural parameters while maintaining in‐plane conjugation between ligands and metals. Specifically, R groups modulate interlayer spacing, which in turn shifts the charge storage mechanism from double‐layer capacitance towards pseudocapacitance, leading to an increase in molar specific capacitance from Ni3(HIH3‐TAT)2 to Ni3(HIBu3‐TAT)2. Partial exfoliation of Ni3(HIBu3‐TAT)2 renders redox active ligand moieties more accessible, and thus increases the dominance of faradaic processes. Our strategy of controlling charge storage mechanism through tuning the accessibility of redox‐active sites may motivate further design and engineering of electrode materials for EC.

Electrochemical Capacitance Traces with Interlayer Spacing in Two-dimensional Conductive Metal-Organic Frameworks.

Electrically conductive metal-organic frameworks (MOFs) are promising candidates for electrochemical capacitors (EC) for fast energy storage due to their high specific surface areas and potential for redox activity. To maximize energy density, traditional inorganic pseudocapacitors have utilized faradaic processes in addition to double-layer capacitance. Although conductive MOFs are usually comprised of redox active ligands which allow faradaic reactions upon electrochemical polarization, systematic studies providing deeper understanding of the charge storage processes and structure-function relationships have been scarce. Here, we investigate the charge storage mechanisms of a series of triazatruxene-based 2D layered conductive MOFs with variable alkyl functional groups, Ni3(HIR3-TAT)2 (TAT=triazatruxene; R=H, Et, n-Bu, n-Pent). Functionalization of the triazatruxene core allows for systematic variation of structural parameters while maintaining in-plane conjugation between ligands and metals. Specifically, R groups modulate interlayer spacing, which in turn shifts the charge storage mechanism from double-layer capacitance towards pseudocapacitance, leading to an increase in molar specific capacitance from Ni3(HIH3-TAT)2 to Ni3(HIBu3-TAT)2. Partial exfoliation of Ni3(HIBu3-TAT)2 renders redox active ligand moieties more accessible, and thus increases the dominance of faradaic processes. Our strategy of controlling charge storage mechanism through tuning the accessibility of redox-active sites may motivate further design and engineering of electrode materials for EC.

Characteristics analysis and structure optimization of a hybrid micro-jet impingement/micro-channel heat sink

To solve the heat dissipation problem of high-power electronics, a novel hybrid micro-jet impingement/micro-channel heat sink is proposed in this work. Different from the continuous and straight rectangular micro-channel, the inclined and interrupted channel walls (fins) are adopted to enhance the fluid disturbance inside the heat sink. To obtain the thermal–hydraulic performance of the hybrid heat sink, an overall 3D modeling and numerical simulations are conducted instead of local cell numerical simulation. In addition, to further improve the heat transfer and flow resistance performance, the effects of variation of structural parameters on heat transfer and flow resistance properties are investigated, including the fin inclination angle, fin length and fin height. The results of structural parametric analysis reveal that there are interactions between different structural parameters, but with different levels of significance for different evaluation indicators. Then, to obtain the optimal combinations of structural parameters for different applications, the multi-objective genetic algorithm coupled with artificial neural network (ANN) is utilized to search for the optimal value of each structural parameter. The heat transfer thermal resistance, pressure drop and mean absolute temperature deviation of the heated surface are utilized as the optimization objectives to evaluate the cooling and resistance characteristics. The optimization results obtained by three-objective optimization and two-objective optimization are analyzed and compared. Finally, seven optimal compromise solutions are selected from the Pareto front by using TOPSIS algorithm with different weight factor matrices. For the optimal compromise solutions, the maximum relative errors between the predicted values of the ANN and numerical simulation values are only 3%, which further demonstrates the accuracy of the artificial neural network model and the effectiveness of using multi-objective optimization to guide heat sink design.

Widely tunable single-mode interband cascade lasers based on V-coupled cavities and dependence on design parameters

We report an investigation of V-coupled cavity interband cascade (IC) lasers (ICLs) emitting in the 3-μm wavelength range, employing various waveguide structures and coupler sizes. Type-II ICL devices with double-ridge waveguides exhibited wide tuning ranges exceeding 153 nm. Type-I ICL devices with deep-etched waveguides achieved single-mode emission with wavelength tunable over 100 nm at relatively high temperatures up to 250 K. All devices exhibited a side-mode suppression ratio higher than 30 dB. By comparing the performance of all devices with different sizes and configurations, a good tolerance against the structural parameter variations of the V-coupled cavity laser (VCCL) design is demonstrated, validating the advantages of the VCCL to achieve single-mode emission with wide tunability.

Detection of liquid chemical analytes using a novel PCF-SPR sensor based on the wavelength sensitivity measurement method

This paper proposes a novel, highly sensitive, dual-coated PCF-SPR sensor for harmful chemical detection. The sensor’s performance is investigated based on the measurement of the wavelength sensitivity method. Silver (Ag) is a plasmonic material, and Ta2O5 is used as an overlayer to enhance its performance. The impact of Ta2O5 thickness and structural parameter variation on sensor performance is also measured. The proposed plasmonic sensor measured the maximum wavelength sensitivity of 23000 nm/RIU. This investigation undoubtedly provides a new approach to designing a PCF-SPR sensor that tunes the range of chemical refractive indices by changing Ta2O5 thickness. Besides, the simplicity, flexibility, and fabrication-friendly design make it applicable for chemical analyte sensing.

Investigation of pressure impact on physical characteristics of FeSe chalcogenide superconductor: Insights from first principles calculation

Understanding the high-pressure physical characteristics of iron selenium (FeSe) superconductors is crucial to comprehending their superconducting abilities. First-principles Density Functional Theory has been computed in the present calculations to analyze the pressure impact on structural, mechanical, electronic and superconducting characteristics along with the Debye and melting temperatures of tetragonal FeSe. The analysis of mechanical characteristics suggests that this compound remains mechanically stable up to a pressure of 20 GPa. The applied hydrostatic pressure is observed to have a significant impact on the elastic moduli and the anisotropic behaviour of FeSe at all pressure conditions. Similarly, the first indication of ductility is observed approximately at 8 GPa and then it increases as pressure rises. At 0 GPa, the optimized structural values are seen to line up with the available data. The variation of structural parameters and electronic factors of FeSe with applied pressure is also mentioned here. Moreover, the assessment of the compound’s electronic characteristics provides strong evidence for its metallic nature and the rise in a number of states at the Fermi energy level with applied pressure may be the cause for the increase in the superconducting critical temperature of FeSe with pressure.