Optimal Structural Parameters Research Articles

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.

Multidisciplinary design and optimization of journal bearing for high-power wind turbine speed increaser

With the increasing power of wind turbine generators (WTG), the failure rate of rolling bearings in wind turbines due to insufficient bearing capacity increases with the increase of bearing size. To overcome these challenges, this paper proposes a design optimization method for the rectangular groove elliptical sliding bearing (RGEB) of the WTG output shaft. This method can maximize the radial bearing capacity under the premise of ensuring that the oil film pressure is large, the end leakage and the temperature rise are small. The multidisciplinary design and modeling of RGEB are carried out according to the structure and working conditions of WTG. Based on computational fluid dynamics (CFD), the influence of the number of rectangular dynamic pressure grooves on the bearing performance is analyzed. The kriging model, BP neural network model, and SSA-BP model are constructed for each performance index of RGEB, to establish a high-precision combined surrogate model based on global error criterion. After establishing the optimization equation, the PSO and SQP combined optimization algorithm is used to optimize the optimal structural parameters. The results show that the bearing capacity of the optimized RGEB is 95.9% higher than that of the ordinary elliptical bearing (EB) without increasing the size and quality of the bearing. In addition, the combined surrogate model can effectively replace the expensive finite element model to deal with the WTG sliding-bearing optimization problem.

Online sorting of surface defective walnuts based on deep learning

To address concerns regarding walnut shell damage and inadequate sorting precision during the mechanized sorting of walnuts, a walnut automatic sorting machine was designed based on deep learning and experimental research. Initially, the rationality of the design was verified through experiment. Then, three deep learning semantic segmentation algorithms, namely PSPnet, U-net, and Deeplabv3+, were selected to train walnut detection models. Results indicated that the U-net algorithm proved to be the most effective, achieving a Mean Intersection over Union of 96.71% and a Mean Pixel Accuracy value of 98.52%. Finally, performance tests were conducted on the prototype machine, yielding results with an average sorting efficiency of 51.70 kg/h, an average loss rate of 6.50%, and an average accuracy of sorting walnuts of 92.98%. The findings can provide insights for future structural improvements and operational parameter optimization of walnut automatic sorting machines.

Structural form and parameter optimization of manipulator grasping fragile workpieces to improve the impact characteristics based on the signal-to-noise ratio

The contact impact stress (CIS) between a manipulator finger and a fragile workpiece has a significant effect on clamping stability. The CIS is affected by various factors, for example, the structural form and parameters of the manipulator finger. In this paper, an optimization method combining Taguchi’s method with signal-to-noise ratio (SNR) theory is proposed to reduce the CIS by optimizing the structural form and parameters of the fingers of an internally supported manipulator. The process consists of three stages. In the first stage, finite element models are built using SolidWorks, HyperMesh, and LS-DYNA software to simulate the CIS of the manipulator when gripping fragile workpieces. In the second stage, the SNR theory is applied to evaluate the effect of CIS and its fluctuations on CIS by treating the CIS and its fluctuations as signals, and changes in the structural forms and parameters of the fingers as noise. In the third stage, the optimal combination corresponding to the maximum SNR is obtained, and the degree of influence and significance level of each factor on the impact force was obtained by calculating the SNR response and variance. The simulation results indicate that the optimized structural parameters reduce the CIS by 26.85% compared to the original design. The experimental results verify the correctness of the simulation results and the effectiveness of the proposed method in reducing CIS.

Straw movement and flow field in a crushing device based on CFD-DEM coupling with flexible hollow straw model

To accurately predict and evaluate the performance of the crushing device of no-till planter, it is strongly necessary to establish an accurate interaction model of the straw-crushing device coupling system. The traditional model has low prediction accuracy and cannot simulate the fracture characteristics of the straw during the operation of the crushing device due to the straw being usually regarded as a rigid body or a combination of rigid ball joints. In this paper, a breakable and flexible hollow straw model is first proposed and a CFD-DEM coupling model of the straw group-crushing device considering the effect of gas-solid two phase is also established. Afterwards, the corresponding verification experiments are conducted and the effect of working and structural parameters on the straw-throwing weight and crushing length is also analysed. It is demonstrated that the relative error between the simulation results and the experimental results for the straw crushing length is 7.7%, and the relative error for the straw-throwing weight is 7.1%, thereby verifying the correctness of the CFD-DEM model. Finally, the response surface method is also used to determine the optimal working and structural parameters of the crushing device and corresponding field tests verification is also conducted. Results indicate that the optimal parameter combination is as: the rotational speed of the crushing spindle is 2400 rpm, the inlet clearance is 30 mm and the starting point angle is 45°. Moreover, the crushing length after optimisation is 6.6% smaller than before optimisation, and the straw-throwing weight is increased by 11.5%.

Optimizations of structure stiffnesses and sensitivities of Y-type six-axis force/torque sensor

PurposeThe six-axis force/torque sensor based on a Y-type structure has the advantages of simple structure, small space volume, low cost and wide application prospects. To meet the overall structural stiffness requirements and sensor performance requirements in robot engineering applications, this paper aims to propose a Y-type six-axis force/torque sensor.Design/methodology/approachThe performance indicators such as each component sensitivities and stiffnesses of the sensor were selected as optimization objectives. The multiobjective optimization equations were established. A multiple quadratic response surface in ANSYS Workbench was modeled by using the central composite design experimental method. The optimal manufacturing structural parameters were obtained by using multiobjective genetic algorithm.FindingsThe sensor was optimized and the simulation results show that the overload resistance of the sensor is 200%F.S., and the axial stiffness, radial stiffness, bending stiffness and torsional stiffness are 14.981 kN/mm, 16.855 kN/mm, 2.0939 kN m/rad and 6.4432 kN m/rad, respectively, which meet the design requirements, and the sensitivities of each component of the optimized sensor have been well increased to be 2.969, 2.762, 4.010, 2.762, 2.653 and 2.760 times as those of the sensor with initial structural parameters. The sensor prototype with optimized parameters was produced. According to the calibration experiment of the sensor, the maximum Class I and II errors and measurement uncertainty of each force/torque component of the sensor are 1.835%F.S., 1.018%F.S. and 1.606%F.S., respectively. All of them are below the required 2%F.S.Originality/valueHence, the conclusion can be drawn that the sensor has excellent comprehensive performance and meets the expected practical engineering requirements.

Seed Trajectory Control and Experimental Validation of the Limited Gear-Shaped Side Space of a High-Speed Cotton Precision Dibbler

In this paper, a cotton precision seed-taking dibbler device was designed to address the problems of congestion and leakage of the hole-type dibbler during high-speed operation (more than 4 km/h). Firstly, the motion trajectory of the seed in the limited gear-shaped space was analyzed and a motion model was established to analyze the relationship between the motion trajectory and seed-filling performance. Secondly, a central combination test with four factors and five levels was implemented using the discrete element software EDEM2018, which simulated the seed-filling performance of the seed-holding space with different structural dimensions. The optimal parameters impacting the seed-filling behavior of the designed dibbler were derived via response surface optimization and multiple regression analyses. Under optimal conditions, three bench tests were repeatedly conducted, and the average qualified index was 93.67%, the leakage index Y3 was 2.67%, and the multiple index Y2 was 3.66%, which was close to the simulation results. Finally, for the speed adaptability test of the seed-holding space with optimal structural parameters, the qualified index was more than 90% when the rotating speed ranged from 1.0 to 2.0 r/s (the speed of the corresponding dibbler was 5.4 km/h to 7.2 km/h), indicating that the dibbler could meet the requirements of high-speed operation and had good speed adaptability. The results can not only provide a reference for the development of precision hole-type dibblers but also have theoretical significance for the quantitative separation of the individual from the population of irregularly rotating agricultural materials and ore materials such as cotton seeds.

基于EDEM的滩涂养殖双螺旋推进器仿真分析与试验

Aiming at the problems of coastal ecological damage and low yield of mudflat aquaculture caused by the invasion of M. alterniflora, in order to improve the operational efficiency of mudflat wet and soft ground, and to promote the ecological balance and the development of coastal agriculture, a walking device with twin spiral propellers for muddy wet and soft ground was designed. Using EDEM simulation software to simulate and analyze, the discrete element model of muddy soil particles is established to analyze the interaction mechanism with the spiral propeller and the operation propulsion effect, and it is concluded that the spiral propeller will not produce congestion phenomenon during the operation; data are collected through several simulation tests, and the optimal parameter design of the spiral propeller structure is derived from the response surface analysis, and the spiral propeller is designed to operate at a speed of 2.416 mph in the simulation with the optimal parameter of structural design. The field test shows that the optimal height of the spiral blades is 50 mm, the total length of the drum is 2,970 mm, the helix angle of lift is 30 °, the pitch is 453 mm, and the propelling speed is 2.36 m/s. The data collected through several simulation tests are used to find the optimal parameter design of the spiral propeller structure, and the simulation speed of the spiral propeller in the optimal structural design parameter is 2.416 m/s.

Research Status of Deep-Sea Polymetallic Nodule Collection Technology

The bottom of the ocean is rich in mineral resources, and deep-sea mining has been a research hotspot in recent years. As a key part of deep-sea mining operation, polymetallic nodule collection technology has been researched in many countries around the world. The distribution of deep-sea polymetallic nodule mining areas and the characteristics of nodules are summarized, which provides a reference for the study of collection technology and the optimization of pick-up device structure. In order to further establish a deep-sea mining collection technology system, the current development status of polymetallic nodule mechanical, mechanical–hydraulic composite and hydraulic collection technologies are summarized, and the analysis shows that hydraulic collection technology has a more promising commercialization prospect. For the hydraulic collection technology, the research progress of suck-up-based collection technology, Coandă-effect-based collection technology, double-row hydraulic collection sluicing technology and other collection technologies are summarized from three aspects: collecting principle, device structure parameter optimization, and sea trial situation, and the key technical problems of hydraulic ore collection are put forward. Through the comparative analysis of the pick-up efficiency, energy consumption, environmental disturbance and other performances of different devices, it is found that the Coandă-effect-based hydraulic collection technology has better comprehensive performance. A structural design evaluation indicator for the collection head of hydraulic collection technology is proposed, and the prospect of further research on hydraulic collection technology is put forward.

Erosion Wear Analysis on Valve Cage of Cage-Typed Sleeve Control Valve for Coal Liquefaction

Abstract Cage-typed sleeve control valve (CSCV) is the key basic equipment in direct coal liquefaction projects. The working condition of CSCV has the characteristics of high-pressure difference, high velocity, and high solid content. There is a general issue of liquid–solid two-phase erosion wear in CSCV, which can easily lead to the failure of the internal structure in the valve cage. Therefore, it is necessary to study erosion wear characteristics of internal structures in the valve cage. Considering the real conditions of erosion wear in the valve cage, a simplified T-shaped flow path is designed, and the precision of both the liquid–solid two-phase flow model and the erosion prediction model is validated. The flow characteristics and erosion wear characteristics in the T-shaped flow path under different working conditions are studied. Based on the simulation results of different structural parameters and boundary conditions, the erosion wear of the T-shaped flow path is predicted and calculated by the response surface method. Subsequently, the prediction formula for the maximum erosion rate is derived. The formula enables the swift determination of optimal structural parameters for the flow path, aiming to mitigate damage to the valve caused by erosion wear. This work can quickly predict the erosion wear rate of the key areas in the valve cage, which can provide a certain reference value for the life prediction and structural optimization of CSCV, and it can also benefit the safety and maintenance of the coal liquefaction system.

Magnetic focusing sensor and its characterizations of defect non-destructive testing for ferromagnetic steel plate

The fast development in precision manufacturing and product quality inspection of ferromagnetic material desperately demands that the defect determining the performance, service life and reliability of the mechanical part should be accurately sensed, detected and evaluated. However, conventional defect detection methods and related magnetic induction sensors are usually characterized with low accuracy in small defect detection, which makes the non-destructive testing (NDT) for ferromagnetic material full of challenges. Thus, a new magnetic focusing sensor is proposed and designed for the precision defect detection of ferromagnetic steel plate here. First, the theoretical principle analysis of the magnetic focusing sensor is introduced, and the preliminary finite element modeling (FEM) is conducted to demonstrate the feasibility of the magnetic focusing sensor in tiny defect inspection. Then, both the static and coupling dynamic characterizations of the magnetic focusing sensor are investigated using the FEM method. The optimal structural parameters of the magnetic focusing (MF) sensor in static conditions are summarized. Furthermore, the effects of the dynamic movement of the MF sensor on the multi-physical fields of the magnetization field, electric field, electromagnetic attraction force field and thermal field are all revealed. Finally, experiments regarding the performance evaluation and comparison between the MF sensor and other two magnetic flux leakage (MFL) sensors are conducted, and the prominent capabilities of accurate and precise defect detection for the MF sensor is demonstrated through the defect detection with different sizes. The effectiveness and feasibility of the MF sensor in detecting tiny defects on ferromagnetic object, as well as its great potential for practical application is therefore validated. Additionally, the main conclusions, advantages of the MF sensor are summarized and the future work is discussed.

The Fastest Capillary Flow in Root-like Networks under Gravity.

Capillary flow has garnered significant attention due to its unique dynamic characteristics that require no external force. Creating a quantitative analytical model to evaluate capillary flow behaviors in root-like networks is essential for enhancing fluid control properties in functional textiles. In this study, we explore the capillary dynamics within root-like networks under the influence of gravity and derive the most rapid capillary flow via structural optimization. The flow time in a capillary is dominated by the capillary pressure, viscous pressure loss, and gravity, each of which exhibits diverse sensitivities to the structures of root-like networks. We scrutinize various structural parameters to understand their impact on capillary flow in root-like networks. Subsequently, optimal structural parameters (namely, the mother tube diameter and diameter ratio) are identified to minimize capillary flow time. Moreover, we discovered that the correlation between flow time and distance for capillary flow in root-like networks does not obey the classical Lucas-Washburn equation. These results affirm that root-like networks can enhance capillary flow, providing critical insights for numerous capillary-flow-dependent engineering applications.

Research on the Grinding Process of Superhard Particles in the Fluidized Bed Opposed Jet Mill Based on the CFD-DEM Methodology

The process of superhard particle breakage in the grinding zone of the fluidized bed opposed jet mill is investigated using the CFD-DEM (computational fluid dynamics-discrete element method) coupling method with the Tavares UFRJ Breakage Model in the present study. The effects of structural and operational parameters, such as target plate structure, nozzle position, air inlet velocity, and feed rate, on the equipment stress distribution, airflow velocity, pressure field, particle velocity, and cumulative particle size distribution are thoroughly studied to determine the optimal structural and operational parameters. Experimental validation is conducted, including scanning electron microscope (SEM) observation of particle morphology and analysis of particle size distribution of ground product particles. The simulation results indicate that the wear rate of the structure without a target plate is lower than that of the structure with a target plate in the grinding central zone. Therefore, the structure without a target plate is chosen for further investigation. The cumulative particle size distribution after grinding is influenced by nozzle position, air inlet velocity, and feed rate. The particle D50 is positively correlated with nozzle spacing and feed rate, while it is negatively correlated with air inlet velocity. The optimal grinding effect is achieved when the distance between the nozzle and the center of the grinding zone ranges from 52.5 mm to 72.55 mm, the air inlet velocity is 950 m/s, and the feed rate is 10.5 g/s. Through experimental investigation, it has been observed that when the feed rate is 10 g/s, the particle size distribution becomes more uniform. Furthermore, consistent trends in the cumulative particle size distribution in the experiment and simulation results can be found, which validates the present numerical model. It was observed that particles at low feed rates retain certain angular edges, while particle roundness increases at high feed rates.

Deep Reinforcement Learning Lane-Changing Decision Algorithm for Intelligent Vehicles Combining LSTM Trajectory Prediction

Intelligent decisions for autonomous lane-changing in vehicles have consistently been a focal point of research in the industry. Traditional lane-changing algorithms, which rely on predefined rules, are ill-suited for the complexities and variabilities of real-world road conditions. In this study, we propose an algorithm that leverages the deep deterministic policy gradient (DDPG) reinforcement learning, integrated with a long short-term memory (LSTM) trajectory prediction model, termed as LSTM-DDPG. In the proposed LSTM-DDPG model, the LSTM state module transforms the observed values from the observation module into a state representation, which then serves as a direct input to the DDPG actor network. Meanwhile, the LSTM prediction module translates the historical trajectory coordinates of nearby vehicles into a word-embedding vector via a fully connected layer, thus providing predicted trajectory information for surrounding vehicles. This integrated LSTM approach considers the potential influence of nearby vehicles on the lane-changing decisions of the subject vehicle. Furthermore, our study emphasizes the safety, efficiency, and comfort of the lane-changing process. Accordingly, we designed a reward and penalty function for the LSTM-DDPG algorithm and determined the optimal network structure parameters. The algorithm was then tested on a simulation platform built with MATLAB/Simulink. Our findings indicate that the LSTM-DDPG model offers a more realistic representation of traffic scenarios involving vehicle interactions. When compared to the traditional DDPG algorithm, the LSTM-DDPG achieved a 7.4% increase in average single-step rewards after normalization, underscoring its superior performance in enhancing lane-changing safety and efficiency. This research provides new ideas for advanced lane-changing decisions in autonomous vehicles.

Grey modeling study on mechanical properties and pore structure of concrete with different basalt fiber contents based on NMR

This paper investigates the correlation between strength and pore characteristics of basalt fiber-reinforced concrete (BFRC) with different fiber contents and establishes a link between meso- and macro-properties. The research focuses on BFRC with differing fiber contents, analyzing compressive strength, flexural strength, and splitting tensile strength across eight admixture levels (ranging from 0 % to 0.35 %). Using the nuclear magnetic resonance (NMR) technique, T2 spectra of BFRC with varying fiber contents are obtained, deriving curves of the pore distribution. Additionally, considering the parameters of different pore size proportions, the paper delves into analyzing the impact of pore structure on BFRC's distinct mechanical properties using grey correlation. Utilizing the optimal pore structure parameters derived from GCA to forecast different strengths, this study establishes GM(1,3) prediction models for three strengths, respectively. The results showed that basalt fibers can enhance concrete strength. And, 0.25 % basalt fibers optimize concrete's the inner structure of BFRC by decreasing harmful pores. The comprehensive correlation between pore parameters and BFRC strength ranges significantly indicating a notable relationship between strength and pore alterations. The compressive strength was most related to the total porosity and the proportion of non-harmful pores, and the splitting tensile and flexural strengths were related to the fractal dimension and porosity of the harmful pores as well as to the total and non-harmful porosity, respectively. A BFRC strength prediction model formula was developed based on the most relevant pore structure parameters derived from GCA. This calculation formula showcases a high accuracy in predicting BFRC strength, establishing a mesoscopic-to-macroscopic quantitative relationship that effectively informs the production and application of BFRC.

Density Functional, Dielectric Studies and Anticancer Activity of (2e)-1-(3-Bromothiophen-2-yl)-3-(2, 3, 5-Trimethoxyphenyl) Prop-2-en-1-One

In this work, the optimized structure parameters, and vibrational wavenumbers of (2E)-1-(3-Bromothiophen-2-yl)-3-(2, 3, 5-trimethoxyphenyl) prop-2-en-1-one (BTTP) molecule have been predicted by Density Functional Theory (DFT) method with B3LYP/6–311++G (d,p) basis set. The calculated vibrational wavenumbers have been compared with observed FT-IR (4000 − 400 cm−1) and FT-Raman (3500 − 100 cm−1) wavenumbers. The difference between the observed and the scaled wavenumber values of most of the fundamentals is very small. Using the aid of VEDA 4 software, the vibrational assignments were made using potential energy distributions. The calculated HOMO, LUMO energies and energy differences demonstrate that charge transfers take place within the molecule. The stability of the molecule arising from hyperconjugative interactions, and charge delocalization have been analyzed using natural bond orbitals (NBO) analysis. The results provide that charge in electron density (ED) in the bonding, and antibonding orbital and second order delocalization energies E(2) confirms the occurrence of intramolecular charge transfer (ICT) within the molecule. Thermodynamic parameters such as entropy (S), enthalpy changes (ΔH) and heat capacity at constant pressure (Cp) are calculated in the temperature range from 100 to 700 K. The first hyperpolarizability (β), dipole moment (μ), and polarizability (α) values are being used to confirm the nonlinear optical behavior of the molecule. In addition, the dielectric properties explain the interactions between the sample and solvent at high frequencies. Finally, the compound is taken for the docking studies and molecular docking was performed against the potential target protein tankyrase and the results are compared with the drug Warfarin. The anticancer activity of BTTP confirms that it can be treated as antineoplastic against the two tested cell lines.

A novel stability analysis method of single-layer ribbed reticulated shells with roof plates

The steel dome of liquefied natural gas (LNG) storage tanks comprises a curved roof plate welded onto a single-layer ribbed reticulated shell (SLRR shell). However, the roof plate may cause diaphragm effects, which may resulting in instability of the steel dome at a relatively low load level. In this paper, an innovative equivalent single-layer ribbed reticulated shell (ESLRR shell) was proposed to investigate the impact of the diaphragm effect. Specifically, the roof plate and H-shaped radial beam were equated as radial irregular beams based on the principle of plate-shell composite action. Next, we performed a systematic analysis of the instability mechanisms in the ESLRR shell, revealing the interaction between the beam buckling and the overall structural instability. Finally, through parametric study, we explored the effects of roof plate thickness and rise-to-span ratio on the ESLRR shell, and obtained the optimal structural parameters. The results show that the proposed method effectively solves the challenges associated with the presence of roof plates in LNG storage tanks steel dome stability analysis; Under the combination of weak boundary stiffness and high bending moment, radial irregular beams are more prone to buckling; Increasing roof plate thickness or rise-to-span ratio can reinforce the stability of the ESLRR shell. Overall, this research work provides theoretical guidance for the future design and optimization of LNG storage tank domes.

Optimization of vertical gradient Pb-Sn hybrid perovskite solar cells using SCAPS (Solar Cell Capacitance Simulator)

Lead-tin hybrid perovskite solar cells emerge as a promising alternative to traditional lead-based cells, addressing environmental and stability concerns, however their efficiency lags. During the fabrication of lead-tin mixed perovskites, the Pb/Sn ratio varies across the film due to different solubilities under various processing conditions. To tackle this issue, we propose a novel perovskite absorber with a vertical gradient in the lead-tin ratio. Our study employs SCAPS-1D simulations to investigate the performance of ITO/HTL/gradient perovskite/ETL/Ag cell structures with different transport layer materials. We systematically analyze the impact of doping levels, defect density states, and interfacial defects in the absorber layer on device efficiency. Through optimization of the device structural parameters, reflecting real experimental conditions, we achieved an energy conversion efficiency of 24.84%. This efficiency is comparable to that of lead-based perovskite solar cells. Interestingly, simulations suggest that omitting the electron transport layer still yields an efficiency above 23.5%, potentially simplifying the fabrication process. This finding indicates that vertically graded Pb-Sn hybrid perovskite solar cells hold great promise for high-efficiency solar cell applications.

Design and Optimization of MEMS Resonant Pressure Sensors with Wide Range and High Sensitivity Based on BP and NSGA-II.

With the continuous progress of aerospace, military technology, and marine development, the MEMS resonance pressure sensor puts forward the requirements of not only a wide range but also high sensitivity. However, traditional resonators are hardly compatible with both. In response, we propose a new sensor structure. By arranging the resonant beam and the sensitive diaphragm vertically in space, the new structure improves the rigidity of the diaphragm without changing the thickness of the diaphragm and achieves the purpose of increasing the range without affecting the sensitivity. To find the optimal structural parameters for the sensor sensitivity and range, and to prevent the effects of modal disturbances, we propose a multi-objective optimization design scheme based on the BP and NSGA-II algorithms. The optimization of the structure parameters not only improved the sensitivity but also increased the interference frequency to solve the issue of mode interference. The optimized structure achieves a sensitivity and range of 4.23 Hz/kPa and 1-10 MPa, respectively. Its linear influence factor is 38.07, significantly higher than that of most resonant pressure sensors. The structural and algorithmic optimizations proposed in this paper provide a new method for designing resonant pressure sensors compatible with a wide range and high sensitivity.

Computational study of stability, photovoltaic, and thermoelectric properties of new inorganic lead-free halide perovskites

Abstract Due to their rich and extraordinary properties, halide perovskites have gained attention over time for their applications in thermoelectric and solar cells. Here, several physical properties (stability, photovoltaic, and thermoelectric) of inorganic halide perovskites XZnI3 (X = Na, K, Rb, Cs) are predicted using the density functional theory (DFT) within the Wien2k code. The optimization of structural parameters has been calculated using PBE-GGA approach. The tolerance factor, Born criteria, phonon dispersion, and negative formation energy show the formation and stability of these studied materials in the ideal cubic structure. Additionally, the modified Becke-Johnson method is applied for optoelectronic and transport properties. All compounds exhibit the nature of indirect band gap semiconductors with better absorption in the visible and ultraviolet regions 10^{5} \textrm {cm}^{-1})$ ?> . The transport properties present high electrical conductivity, large Seebeck coefficient, and good (PF, ZT) factors for all these materials. Finally, all these properties of inorganic halide perovskites open up new possibilities for efficient applications in thermoelectric and solar cells.