Structural Parameters Research Articles

Effect of anterior segment structure on vault and position after implantable collamer lens implantation.

To evaluate the effect of anterior-segment structure on vault and position after implantable collamer lens (ICL) implantation using ultrasound biomicroscopy. The retrospective case-control study included insufficient vault eyes (<250 μm), ideal vault eyes (250-750 μm), and excessive vault eyes (>750 μm). The preoperative biometric parameters of the anterior-segment structure and basic data between the three groups were analyzed using one-way analysis of variance. There were significant differences (P < 0.05) between the three groups in maximum ciliary body thickness (CBTmax), iris-zonule distance (IZD), and trabecular-ciliary angle (TCA). The vault gradually decreased as CBTmax decreased and TCA increased. In the pairwise comparison, the CBTmax comparison between the insufficient vault (<250 μm) group and the excessive vault (>750 μm) group was statistically significant (P = 0.024, 95% CI: -0.17-0.017 μm); the TCA comparison between the insufficient vault (<250 μm) group and the excessive vault (>750 μm) group was statistically significant (P = 0.005, 95% CI: 1.78°-12.15°); The IZD comparison between the insufficient vault (<250 μm) group and the excessive vault (>750 μm) group was statistically significant (P = 0.037, 95% CI: 0.0027-0.1119 μm). The analysis of 284 ICL haptics locations showed that there were 16.67%, 32.69%, and 70.83% haptics located in the ciliary sulcus in three groups, respectively. The vault and ICL haptics position are related to anterior-segment structure. A thinner and posteriorly positioned ciliary body would increase the risk of low vault and fewer ICL haptics located in the ciliary sulcus after ICL implantation. This provides guidance for the selection of the ICL size and placement position before surgery.

Improving the Estimation of Structural Parameters of a Mixed Conifer–Broadleaf Forest Using Structural, Textural, and Spectral Metrics Derived from Unmanned Aerial Vehicle Red Green Blue (RGB) Imagery

Improving the Estimation of Structural Parameters of a Mixed Conifer–Broadleaf Forest Using Structural, Textural, and Spectral Metrics Derived from Unmanned Aerial Vehicle Red Green Blue (RGB) Imagery

Effect of calcination temperature on structure evolution of hematite nanoparticles

The objective of this study is to investigate the transition structure of iron oxide, specifically the change from magnetite to hematite, as well as the influence of calcination temperature on the structural growth of hematite nanoparticles. The magnetite was extracted from the native iron sand in Indonesia using the coprecipitation procedure. To generate hematite, magnetite was calcined at various temperatures (350, 500, 650, and 800 °C). The structural changes resulting from the effect of calcination temperature were investigated by combining a number of characterisation methods. The crystal structure was examined using synchrotron x-ray diffraction (SRD) and the local structure was examined using x-ray absorption spectroscopy (XAS). Crystallite size was calculated using the Debye-Schrerrer equation at the most dominant SRD peak. Surface morphology was investigated using scanning electron microscopy (SEM). SRD data revealed that the sample calcined at 350 °C displayed both the Fe3O4 and α-Fe2O3 phases, while higher temperatures revealed the single-phase α-Fe2O3. Furthermore, an increase in calcination temperature was shown to be associated with an increase in crystallinity and crystallite size. For the samples H350 and H800, the crystallinity increased from 95.56 to 98.17%. In the magnetite, H350, H500, H650, and H800 samples, the crystallite size increased from 9.57 to 29.55, 16.40, 28,48, 29.26, and 29.55 nm. Higher calcination temperatures, on the other hand, increase the interatomic distance while decreasing the Debye–Waller factor, according to XAS fitting data. It can be inferred that around 500 °C, the transition from Fe3O4 to single-phase α-Fe2O3 was observed. While a greater calcination temperature of at least 800 °C would alter the structural parameters, it would not affect the phase.

Enhancing mid-infrared surface phonon polariton modes: optimization of structural parameters in Nb-doped SrTiO3 with hole array structures for advanced infrared sensors

This study utilized the finite difference time domain method to investigate the mid infrared surface phonon polaritons and localized surface phonon resonances in undoped and niobium (Nb)-doped SrTiO3 (STO) with planar and holes array structures. Research has shown that Nb-doped STO operates in the Reststrahlen band of 8.06–18.48 µm, providing a wider spectral response than undoped STO (12.58–18.26 µm) and effectively covering the atmospheric window of long wave infrared. This indicates that the increase in virtual permittivity has the least impact on spectral broadening, indicating that the new infrared sensor technology has broad prospects. The optimization of structural parameters, including the period, filling factor, and depth of STO holes array, as well as the response to changes in incident light angle, is crucial for guiding the design of high-performance optoelectronic devices. In addition, this study explored the excitation of four resonant modes within a holes array and analyzed their relationship with array parameters to enhance the design of optoelectronic applications.

Frequency-extended inverse design of transmission-type linear-to-circular polarization control metasurface based on deep learning

Due to the parameter range limitations of the training dataset, traditional inverse prediction network models can only predict structure parameters of the metasurface within a limited frequency range. When the given design targets exceed the prediction range of network models, the predicted results will not match the actual results. This paper proposes a frequency-extended inverse design method (FEIDM) based on deep learning to address the problem. The method can automatically collect the required data and train the network model based on the center working frequency of the design targets, thereby achieving accurate prediction of metasurface structural parameters and effectively reducing labor and computational costs. Taking the transmission-type linear-to-circular polarization control metasurface as an example, the unit cell of the metasurface is first established in the paper. The structural parameters and corresponding electromagnetic parameters are collected without changing the unit size of the metasurface, and an initial inverse prediction network model (IIPNM) is constructed. The research results indicate that its predictable center working frequency range is 3–5.5 GHz. Using the design concept proposed in this paper, a program is constructed, it can automatically achieve data collection, target extraction, network model training, and prediction. Four given design targets are predicted. Among them, the center working frequencies of the three design targets are outside the initial predictable range. The predicted results meet the requirements of the given target, verifying the effectiveness of the proposed scheme. Finally, a set of parameters is selected to fabricate, and the experimental results are consistent with the simulation results. The research results can provide a reference for the efficient prediction of metasurface structural parameters over a wide frequency band.

Design of Isoindigo-Based Small-Molecule Donors for Bulk Heterojunction Organic Solar Cell Applications in Combination with Nonfullerene Acceptors.

The development of small-molecule organic solar cells with the required efficiency depends on the information obtained from molecular-level studies. In this context, 39 small-molecule donors featuring isoindigo as an acceptor moiety have been meticulously crafted for potential applications in bulk heterojunction organic solar cells. These molecules follow the D2-A-D1-A-D2 and D2-A-π-D1-π-A-D2 framework. Similar molecules considered in the previous experimental study (molecules R1 ((3E,3″E)-6,6″-(benzo[1,2-b:4,5-b']dithiophene-2,6-diyl)bis(1,1'-dimethyl-[3,3'-biindolinylidene]-2,2'-dione)) and R2 ((3E,3″E)-6,6″-(4,8-dimethoxybenzo[1,2-b:4,5-b']dithiophene-2,6-diyl)bis(1,1'-dimethyl-[3,3'-biindolinylidene]-2,2'-dione))) have been chosen as reference molecules. Molecules with and without π-spacers have been considered to understand the impact of the length of the π-spacer on intramolecular charge-transfer transitions and absorption properties. A detailed investigation is carried out to establish the relationship between the structure and photovoltaic parameters using density functional theory and time-dependent density functional theory methods. The newly developed molecules exhibit better electronic, excited-state, and charge transport properties than the reference molecules. Additionally, model donor-acceptor interfaces are constructed by integrating the designed donor molecules with fullerene/nonfullerene acceptors. The electronic and excited-state properties of these interfaces are rigorously evaluated. Results elucidate that the donor comprising of isoindigo-bithiophene-pyrroloindacenodithiophene (IIG-T2-PIDT) emerges as a promising candidate for bulk heterojunction solar cells based on nonfullerene acceptors. This research provides systematic design strategies for the development of small-molecule donors for organic solar cells.

Coupling Gold Nanospheres into Nanochain Constructs for High-Contrast, Longitudinal Photoacoustic Imaging.

Structural parameters play a crucial role in determining the electromagnetic and thermal responses of gold nanoconstructs (GNCs) at near-infrared (NIR) wavelengths. Therefore, developing GNCs for reliable, high-contrast photoacoustic imaging has been focused on adjusting structural parameters to achieve robust NIR light absorption with photostability. In this study, we introduce an efficient photoacoustic imaging contrast agent: gold sphere chains (GSCs) consisting of plasmonically coupled gold nanospheres. The chain geometry results in enhanced photoacoustic signal generation originating from outstanding photothermal characteristics compared to traditional gold contrast agents, such as gold nanorods. Furthermore, the GSCs produce consistent photoacoustic signals at laser fluences within the limits set by the American National Standards Institute. The exceptional photoacoustic response of GSCs allows for high-contrast photoacoustic imaging over multiple imaging sessions. Finally, we demonstrate the utility of our GSCs for molecular photoacoustic cancer imaging, both in vitro and in vivo, through the integration of a tumor-targeting moiety.

Ultra-high sensitive dual-parameter sensor based on double-hole fiber for simultaneous detection of magnetic field and temperature

An ultra-high sensitive dual-parameter sensor based on double-hole fiber (DHF) is proposed for simultaneous detection of magnetic fields and temperatures. The sensor utilizes the DHF containing a Ge-doped core with two large air holes symmetrically arranged at its two sides. To enhance the sensitivity to both a magnetic field and temperature, Al wires with different diameters are embedded on the inner walls of the air holes in the DHF, creating a magnetic field sensing channel filled with magnetic fluid and a temperature sensing channel filled with thermo-sensitive liquid. Structural parameters and metal materials of the sensor are optimized by using the finite element method. Numerical results demonstrate that this DHF-based dual-parameter sensor can detect magnetic fields ranging from 40 Oe to 130 Oe and temperatures ranging from 24.3 °C to 49.3 °C simultaneously. The maximum magnetic field sensitivity reaches up to 64000 pm/mT, while the maximum temperature sensitivity is approximately 44.6 nm/°C, both exceeding current reports by more than one order of magnitude for simultaneous detection of magnetic field and temperature. With its high sensitivity, low fabrication difficulty, and simple structure, this DHF-based dual-parameter sensor has potential applications in the fields of material characterization analysis, geological environmental monitoring, and aeronautical engineering.

Dynamics of the nonlinear optical second, and third harmonic generation in GaAs/Ga0.7Al0.3As quantum well due to hydrostatic pressure and temperature

Abstract We studied the effects of hydrostatic pressure and temperature on the second and third harmonic generation (SHG and THG) of nonlinear optics semi-parabolic GaAs/Al0.3Ga0.7As quantum well. By solving the Schrödinger equation numerically, we can determine the system's subband energy levels and propagation wave functions, and then calculate its optical gain. The numerical simulation results show that both temperature and hydrostatic pressure can effectively improve the nonlinear optical performance of the system. As an interesting observation, we studied the mechanism of the two in this process. These findings highlight a feasible method to adjust the nonlinear optical performance of GaAs/Al0.3Ga0.7As quantum system through the subtle interaction between hydrostatic pressure, temperature and structural parameters.&amp;#xD;

Dynamic characteristics of terahertz hot-electron graphene FET bolometers: Effect of electron cooling in channel and at side contacts

We analyze the operation of the hot-electron FET bolometers with the graphene channels (GCs) and the gate barrier layers. Such bolometers use the thermionic emission of the hot electrons heated by incident-modulated THz radiation. The hot electrons transfer from the GC into the metal gate. As the THz detectors, these bolometers can operate at room temperature. We show that the response and ultimate modulation frequency of the GC-FET bolometers are determined by the efficiency of the hot-electron energy transfer to the lattice and the GC side contacts due to the 2DEG lateral thermal conductance. The dependences of these mechanisms on the band structure and geometrical parameters open the way for the GC-FET bolometers optimization, in particular, for the enhancement of the maximum modulation frequency.

Application of Instrumented Indentation Procedure in Assessing the Low-Cycle Fatigue Properties of Selected Heat-Treated Steels

The paper presents an analysis of the low-cycle fatigue (LCF) properties of C45, X20Cr13, and 34CrNiMo6 steels subjected to various heat treatment processes. Strain-controlled LCF tests were carried out with a total cyclic strain amplitude equal to 0.5, 1 and 1.5%. Fatigue life, cyclic stress-strain behavior and hardness were analyzed. Qualitative and quantitative relationships between material LCF properties resulting from the heat treatment processes, were related to the indentation force P*, which was derived experimentally by applying an instrumented indentation procedure with the use of the Vickers indenter. The proposed parameter P* and its changes ΔP* seem to be promising for the identification of the structural stress parameter σ* that is necessary for deriving values of the fatigue strength coefficients σf’ corresponding to different tempering temperatures. The common feature of all steels analyzed in this paper is that the elastic parts of the strain-life characteristics remain parallel after being subjected to different tempering temperatures.

A Remaining Useful Life Prediction Method of Mechanical Equipment Based on Particle Swarm Optimization-Convolutional Neural Network-Bidirectional Long Short-Term Memory

In industry, forecast prediction and health management (PHM) is used to improve system reliability and efficiency. In PHM, remaining useful life (RUL) prediction plays a key role in preventing machine failures and reducing operating costs, especially for reliability requirements such as critical components in aviation as well as for costly equipment. With the development of deep learning techniques, many RUL prediction methods employ convolutional neural network (CNN) and long short-term memory (LSTM) networks and demonstrate superior performance. In this paper, a novel two-stream network based on a bidirectional long short-term memory neural network (BiLSTM) is proposed to establish a two-stage residual life prediction model for mechanical devices using CNN as the feature extractor and BiLSTM as the timing processor, and finally, a particle swarm optimization (PSO) algorithm is used to adjust and optimize the network structural parameters for the initial data. Under the condition of lack of professional knowledge, the adaptive extraction of the features of the data accumulated by the enterprise and the effective processing of a large amount of timing data are achieved. Comparing the prediction results with other models through examples, it shows that the model established in this paper significantly improves the accuracy and efficiency of equipment remaining life prediction.

Spectrum feature extraction method combining Allan variance, VMD, and PSD

Spectrum feature extraction plays a crucial role in identifying seismic events and calculating structural response parameters. However, the criteria for identifying effective modal components in Variational Mode Decomposition (VMD) are not well-defined, resulting in inaccurate spectrum feature extraction. To address this issue, we propose a novel spectrum feature extraction method that combines Allan variance, VMD, and power spectral density (PSD). Firstly, VMD is applied to filter noise components from triaxial accelerometer observations and add effective signals. Secondly, PSD is utilized to extract three groups of seismic frequencies (tri-axial accelerometers). Finally, the Allan method is introduced to identify the group of accelerometer observations with the highest reliability as the vibration frequency caused by the seismic excitation. We validate the effectiveness of our method by analyzing a Mw 2.6 micro-seismic event that occurred in Huairou, Beijing in 2022. The result shows that our proposed method accurately extracts spectrum features of the Great Wall. Specifically, the seismic excitation vibration frequencies at four monitoring stations were found to be 26.95 Hz, 12.89 Hz, 12.89 Hz, and 12.5 Hz. These findings underscore our method's utility in evaluating the Great Wall's structural response to seismic loading, which has significant implications for the conservation and protection of heritage structures.

Deformation of Existing Shield Tunnel Adjacent to Deep Excavations: Simulation and Monitoring Analysis

Deep excavations near subway tunnels can induce deformation, necessitating a comprehensive investigation into causal factors and mitigation strategies. Field measurements were conducted to assess both vertical and horizontal displacements of existing tunnels near a deep excavation in Shenzhen. Utilizing a validated three-dimensional finite element model that considers structure−strata interactions, this study analyzes tunnel displacements, ground movements, diaphragm wall impacts and the sensitivity of enclosure structure parameters. The results indicate that tunnel deformation correlates with enclosure structure deformation, particularly near the center of the pit. Moreover, shallow soil excavation significantly affects the vertical displacement of shallow-buried tunnels. However, the design parameters of the existing enclosure structures inadequately limit tunnel displacement. Therefore, it is crucial to intensify vertical displacement monitoring in shallow tunnels during early excavation stages and to enhance horizontal displacement monitoring during later phases. Implementing measures such as optimizing central support design or retaining soil at the pit bottom helps control maximum horizontal displacement. While support stiffness plays a greater role than retaining wall thickness, its impact on deep excavation projects is limited.

Multiscale study of reactive transport and multiphase heat transfer processes in catalyst layers of proton exchange membrane fuel cells

Improving the performance of proton exchange membrane fuel cells (PEMFCs) requires deep understanding of the reactive transport processes inside the catalyst layers (CLs). In this study, a particle-overlapping model is developed for accurately describing the hierarchical structures and oxygen reactive transport processes in CLs. The analytical solutions derived from this model indicate that carbon particle overlap increases ionomer thickness, reduces specific surface areas of ionomer and carbon, and further intensifies the local oxygen transport resistance (Rother). The relationship between Rother and roughness factor predicted by the model in the range of 800-1600 s m-1 agrees well with the experiments. Then, a multiscale model is developed by coupling the particle-overlapping model with cell-scale models, which is validated by comparing with the polarization curves and local current density distribution obtained in experiments. The relative error of local current density distribution is below 15% in the ohmic polarization region. Finally, the multiscale model is employed to explore effects of CL structural parameters including Pt loading, I/C, ionomer coverage and carbon particle radius on the cell performance as well as the phase-change-induced (PCI) flow and capillary-driven (CD) flow in CL. The result demonstrates that the CL structural parameters have significant effects on the cell performance as well as the PCI and CD flows. Optimizing the CL structure can increase the current density and further enhance the heat-pipe effect within the CL, leading to overall higher PCI and CD rates. The maximum increase of PCI and CD rates can exceed 145%. Besides, the enhanced heat-pipe effect causes the reverse flow regions of PCI and CD near the CL/PEM interface, which can occupy about 30% of the CL. The multiscale model significantly contributes to a deep understanding of reactive transport and multiphase heat transfer processes inside PEMFCs.

Natural Characteristics of a Marine Two-Stage Tandem Hybrid Planetary System

This study focuses on a marine two-stage tandem hybrid planetary system. Natural frequencies and vibration modes are determined using a translational–torsional coupled dynamic model. Based on the motion characteristics of the transmission system, free vibration is categorized into three typical modes. The parameter sensitivity of natural frequencies is computed, and the effects of structural parameters such as unequally spaced planet, mesh stiffness, planet mass and rotational inertia on the natural frequencies are analyzed. Utilizing the coupling factor, the mode transition criterion for the natural frequencies response to parameters is formulated. The results demonstrate that the vibration modes of the two-stage tandem hybrid planetary system can be classified as the fixed-axis train vibration mode, the differential train vibration mode, and the coupled vibration mode. Unequally spaced planet primarily disrupts vibration modes without significantly affecting natural frequencies. In contrast, the effects of mesh stiffness, planet mass and rotational inertia on the modes are opposite to those of unequally spaced planets. The validity of the parameter sensitivity and mode transition criterion is substantiated through illustrative examples.

Orthogonal effect of exchange and correlation parameters in density functional theory to compute geometric and spectroscopic quantities.

The influence of the composition of the functional used for density functional theory computations on one structural parameter (a dihedral angle) and a spectroscopic parameter (absorption wavelength) is assessed in this study on the basis of two molecules (flavonols). In this kind of molecules, these two parameters should be correlated according to the nature of the electronic transition involved. However, it is shown herein that by varying the proportion of true exchange and correlation while building a functional, it is possible to obtain independently a large range of values for these parameters without any relation with the underlying real values. Therefore, it is concluded that the choice of a functional after a benchmark, especially using user-defined functionals, should be carried out with great care to avoid such effects.

Multi-functional metasurface: ultra-wideband/multi-band absorption switching by adjusting guided-mode resonance and local surface plasmon resonance effects

This study introduces an innovative dual-tunable absorption film with the capability to switch between ultra-wideband and narrowband absorption. By manipulating the temperature, the film can achieve multi-band absorption within the 30–45 THz range or ultra-wideband absorption spanning 30–130 THz, with an absorption rate exceeding 0.9. Furthermore, the structural parameters of the absorption film are optimized using the particle swarm optimization (PSO) algorithm to ensure the optimal absorption response. The absorption response of the film is primarily attributed to the coupling of guided-mode resonance and local surface plasmon resonance effects. The film’s symmetric structure enables polarization incoherence and allows for tuning through various means such as doping/voltage, temperature and structural parameters. In the case of a multi-band absorption response, the film exhibits good sensitivity to refractive index changes in multiple absorption modes. Additionally, the absorption spectrum of the film remains effective even at large incidence angles, making it highly promising for applications in fields such as biosensing and infrared stealth.

Effect of Structural Parameters on Output Characteristics of a Novel Self-Supplied Aviation Intelligent Pump

The aviation intelligent pump system is an effective solution to aircraft hydraulic systems’ inefficient power consumption and temperature increase. A self-supplied aviation intelligent pump (SAIP) has a high power-to-weight ratio and compact structure, making it the optimal choice for an intelligent pump. To analyze the output characteristics of a novel aviation intelligent pump, it is crucial to establish an accurate mathematical model that describes its dynamic characteristics. This can be achieved by analyzing the working principle and exploring the influence of critical parameters. The paper introduces the composition and working principle of a self-supplied electro-hydraulic servo variable displacement pump. It then establishes a mathematical model of the whole pump, with a detailed analysis and modeling of the critical variable mechanism and the swash plate assembly’s load moment. A simulation model was created to examine the impact of crucial structural parameters, such as the offset spring’s stiffness and control piston’s diameter, on the output characteristics of the intelligent pump. An experimental platform was also constructed, and the experimental results confirm the accuracy of the SAIP model presented in this paper. The investigation of the output characteristics fully reveals the dynamic performance of the SAIP. This provides the basis for the subsequent design of high-performance flow and pressure control strategies and aids in researching intelligent aircraft hydraulic systems.

Impact location of metal structures based on time–frequency image features and deep residual network

Impact location detection plays an important role in the structural health monitoring of metal materials. However, the methods of metal material impact location detection based on physical analysis are often limited by the extraction accuracy of some parameters such as material and structure parameters and time difference calculation. Therefore, this paper develops a deep residual network method for impact location detection, time–frequency characteristic deep residual network (TF-DRN). This method takes the four-channel short-time Fourier transform time–frequency graph as input, uses the unique residual network architecture to automatically extract the advanced features, and then uses the global average pooling layer and the full connection layer to establish the mapping between the advanced features and the impact location, so as to detect the impact location. By introducing regularization and batch normalization, the problems of gradient disappearance and gradient explosion are alleviated, and the generalization and efficiency of impact location detection are further improved. The experimental results show that on an 800 mm × 800 mm × 2.5 mm aluminum plate, the average error of the validation set and the test set are 0.85 cm and 1.33 cm respectively, and the performance of the method is significantly better than that of CNN, ResNet18 and ResNet33 networks.