Optimal Structural Parameters Research Articles

Design and Optimization of External Rotor Consequent Pole Permanent Magnet Motor with Low Iron Loss and Low Torque Ripple

To reduce the iron loss and torque ripple of an external rotor consequent pole (ERCP) motor used in an electric vehicle air-conditioning compressor, the magnetic pole structure of the motor was improved, and an unequal piecewise consequent pole (CP) structure was designed. The performance of the motor is optimized by reducing the harmonic content in the air gap flux density and reducing the iron saturation degree of the motor. The designed CP structure can significantly reduce the iron loss and torque ripple of the motor. Based on the Taguchi method, the optimal size parameters of the unequal piecewise CP structure are determined, and the final optimization design scheme is obtained. The results of finite element simulation and high-precision iron loss model show the following: compared with the original motor, the iron loss and torque ripple of the motor with the final optimized design scheme are significantly reduced.

In Situ Generated CO Enables High-Current CO2 Reduction to Methanol in a Molecular Catalyst Layer.

Molecular catalysts such as cobalt phthalocyanine (CoPc) exhibit remarkable electrochemical activity in methanol production from CO2 or CO, but fast conversion with a high current density is still yet to be realized. While adopting flow cells with gas diffusion electrodes is a common approach to enhanced reaction rates, the current scientific and engineering knowledge primarily centers on metal particle-based catalysts like Cu. This focus overlooks the emerging heterogenized molecular catalysts with distinct physical and chemical properties. In this work, we observe that the partial current density of CO reduction to methanol catalyzed by tetraamine-substituted CoPc (CoPc-NH2) supported on carbon nanotubes (CNTs) remains below 30 mA cm-2, even with systematic optimization of structural and operational parameters of the flow cell. A comparative analysis with a Cu metal catalyst reveals that the porous and electrolyte-philic nature of CoPc-NH2/CNT leaves a large fraction of active sites deprived of CO under reaction conditions. To address this microenvironmental challenge, we directly use CO2 as the reactant, leveraging its faster diffusion rate in water compared to CO. Effective CO2 reduction generates CO in situ to feed the catalytic sites, achieving an unprecedently high partial current density for methanol of 129 mA cm-2. This research underscores the necessity for new insights and approaches in the development of molecular catalyst-based electrodes.

Design and Optimization of Heat Dissipation for a High-Voltage Control Box in Energy Storage Systems

Abstract To address the issue of excessive temperature rises within the field of electronic device cooling, this study adopts a multi-parameter optimization method. The primary objective is to explore and realize the design optimization of the shell structure of the high-voltage control box, aiming to effectively mitigate the temperature rise in internal components and enhance their thermal management efficacy without altering the fan performance, environmental conditions, or spatial layout. Initially, the study employs computational fluid dynamics methods to investigate the heat dissipation characteristics of the high-voltage control box, subsequently verifying the simulation parameters' accuracy through temperature rise tests. Building upon this foundation, the article conducts a thorough analysis of how the position and shape of the box's openings impact the device's temperature rise. The findings suggest that configuring circular openings on the front and rear sides can optimize the heat dissipation effect. Moreover, the SHERPA algorithm was employed to refine the size and distribution of the openings on the outer shell of the high-voltage control box through multi-parameter optimization, yielding locally optimal structural parameters. Post-optimization, the temperature measurement points within the high-voltage control box exhibited a maximum reduction in temperature rise of 27.16%. The pivotal contribution of this methodology is the application of a data-driven decision-making process for the enhancement of conventional heat dissipation designs. This research offers invaluable practical insights and novel perspectives on the optimization of thermal management designs for box-type electronic devices, significantly advancing the field of thermal management technology in electronic devices.

Carbon emission reduction in public buildings of extreme cold regions: A study on enclosure structure and HVAC system parameter optimization

AbstractThe implementation of strategies aimed at curtailing energy consumption and carbon emissions in buildings is of paramount importance. Priority should be accorded to the reduction of embodied carbon emissions from construction materials and operational carbon emissions during the usage phase. A public building situated in an extremely cold region is chosen as the subject of this study. An initial investigation is conducted into the impact of various enclosure structure materials on embodied carbon. The impact of different heating, ventilation and air conditioning (HVAC) systems on the total carbon emissions of public buildings are studied as well. The findings indicate that the amalgamation of W3 + R + G4 + H4 culminates in the least total carbon emissions. Upon establishing the foundational scheme for the public building, an optimization (nondominated sorting genetic algorithm II [NSGA II] and Criteria Importance Through Intercrieria Correlation [CRITIC]) of the enclosure structure parameters is initiated to examine the optimal parameters of the public building's enclosure structure. The findings reveal that a decrease in the heat transfer coefficient could trigger an increase in total carbon emissions. This is attributed to the fact that the carbon emissions embodied in the production process of these materials could potentially outweigh the reduction observed in operational carbon emissions. Further adjustments were also made to the parameters of the HVAC system in the buildings. The findings indicate that within the context of public buildings, given the presence of optimal parameters and an HVAC system that utilizes solar energy for both heating and cooling in the American Society of Heating, Refrigerating and Air‐Conditioning Engineers, Inc. 6 A climatic zone, the efficiency of the cooling system can exert a significant influence on the operations carbon emissions reduction.

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.

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

Purpose The 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/approach The 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. Findings The 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/value Hence, the conclusion can be drawn that the sensor has excellent comprehensive performance and meets the expected practical engineering requirements.

A spin-polarized DFT analysis of the physical attributes of vacancy ordered Rb2TcCl6 double perovskite for optoelectronic and spintronics

Due to their versatile properties, vacancy-ordered double perovskites offer a wide range of potential uses due to their versatile properties. We have thoroughly examined the physical characteristics of vacancy-ordered Rb2TcCl6 in its cubic phase by employing the spin-polarized computations. The ground state energy and optimum structural parameters are obtained in order to assess the structural stability, which is further validated using the tolerance factor and formation energy values. The ductile character of Rb2TcCl6 is revealed by a comprehensive evaluation of mechanical properties. Vickers hardness factor suggests that Rb2TcCl6 can withstand against pressure-induced disturbance more strongly. A direct bandgap for spin-up is measured up to 2.33 eV, while for spin-dn it is 2.02 eV. According to the magnetic moments of 2.69 μB, Rb2TcCl6 is an attractive material for spintronic devices. A number of optical parameters are determined. For optoelectronic applications, Rb2TcCl6 is an excellent choice due to its strong polarization in the visible and ultraviolet regions, as shown by its optical characteristics.

Optimal Design of Light Microclimate and Planting Strategy for Chinese Solar Greenhouses Using 3D Light Environment Simulations

Light has a significant impact on crop production. The objective of this study was to explore the optimal lighting structure parameters and the corresponding planting strategy of Chinese solar greenhouses (CSG). Taking CSG-grown melons as the experimental subject, we have developed a detailed 3D model capable of calculating the light interception at a single organ level, e.g., for individual leaves. The quantitative research was carried out after verifying the proposed model using field data. The results indicated that the reasonable ridge height for the most common 9 m span CSG was 4.9 m, and the horizontal projection on rear roof was 1.6 m in Shenyang area. In comparison with the experimental greenhouse, the optimized greenhouse improved crop light interception by 0.5 % and increased the average air temperature by 9.3 % during winter. The suitable planting strategy was E-W row orientation, with a ridge spacing of 1.2 m, a row spacing of 0.4 m, and a plant spacing of 0.38 m. Compared with the N-S row orientation, the crop light interception increased by 7.1 % and 10.8 % in the two growing seasons, respectively. The model described herein can serve as a foundation for the production of CSG.

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.