Hasil untuk "Mechanical engineering and machinery"

Dazhong Wu, Connor Jennings, J. Terpenny et al.

A. Devi, Tanmoy Chakraborty

In real‐world processes, such as heat transfer, fluid flow, and chemical reactions, irreversibility occurs frequently, which induces an augment in entropy. The optimization of the entropy generation in a mechanical system is one of the fundamental areas of research to channel the energy of the system for utilization. This research exhibits an entropy generation in a nanofluid flow drenched in a fluid‐saturated non‐Darcy porous medium toward a stagnation point. The flow line also experiences the existence of nonuniform heat generation/absorption following the first‐order chemical reaction, which enhances the applicability of this model in different domains of science and engineering. A special form of the Lie group approach is applied to revert the governing partial differential system into its self‐similar ordinary differential form. The solutions of the transformed nonlinear ODEs are acquired analytically through the DTM ‐Padé as well as numerically by the Runge–Kutta–Fehlberg (RKF‐45) method coupled with the shooting process. The fallouts are vividly sketched graphically. One of the upshots reveals that the escalation of space and temperature‐reliant heat absorption parameters can optimize the thermal irreversibility of the system and so as the total entropy generation. Meanwhile, by incrementing the Darcy parameter from 0 to 0.8, the wall shear stress decays by 23.7%, whereas with the same hike in the Forchheimer resistance factor, declines the rate of heat and mass transfer approximately by 2.6% and 3.6%, respectively. Another upshot reveals that with the escalation of the space‐dependent heat source parameter from 0.1 to 0.5, the Nusselt number significantly decreased by 23.9%. Meanwhile boosting the temperature‐reliant heat sink parameter from ‐0.1 to ‐0.5 causes an inclination in the rate of heat transportation by 10.5%. Moreover, it is found that mass transport irreversibility can be controlled by enhancing the constructive chemical reaction rate. We hope that this study will be beneficial for many engineering and industrial processes, particularly in geothermal energy extraction, nuclear waste disposal management, groundwater filtration machinery and food processing equipment.

Xianhe Zhang, Zhenrong Yang, Hongyun Wang et al.

High entropy alloys exhibit superior mechanical properties, especially wear resistance, making them crucial for wear-resistant and surface protection applications, necessitating in-depth research into their wear resistance and coating materials. This study utilizes molecular dynamics methods to perform a comprehensive investigation and meticulous analysis of the wear resistance of FeNiCrCoAl high entropy alloys, with the goal of providing crucial theoretical support for their practical applications. The FeNiCrCoAl high entropy alloy was applied as a coating onto an Al substrate, serving as the subject of friction simulations. By regulating the indentation depth of abrasive particles and coating thickness, we systematically examined how these factors affect the friction properties of the material. The findings reveal that when the depth of abrasive pressing is less than the coating thickness, the friction coefficient rises with increasing pressing depth; conversely, when the pressing depth exceeds the coating thickness, the friction coefficient decreases. As the coating thickness increases, the material generates a reduced proportion of disordered lattice structures during friction, accompanied by an increase in dislocation line density. This suggests a reduced wear from abrasive particles, indicating that thicker coatings enhance the material’s wear resistance.

Chunge Wang, Yuanyuan Huang, Zixia Zhao et al.

A novel stretchable flexible electrode capable of simultaneously detecting isotropic three-directional strain and normal pressure has been developed. Inspired by the recursive symmetry of the Peano-Gosper fractal, the electrode integrates liquid metal (EGaIn) microchannels within a PDMS matrix to achieve uniform strain distribution and mechanically robust conductive pathways under large deformation. Within a strain range of 0–60%, the electrode exhibits highly consistent three-directional responses, with resistance variation across axes kept below 4% and a gauge factor (<i>GF</i>) standard deviation of only 0.0252. The device demonstrates low hysteresis (minimum DH = 0.94%), good cyclic durability, and reliable electromechanical stability. For normal pressure sensing (0–20 kPa), it provides a linear response (<i>R</i>² ≈ 0.99) with a moderate sensitivity of 0.198 kPa⁻¹. Wearable tests on the wrist, finger, and fingertip confirm the electrode’s reliable operation in multidimensional mechanical monitoring. This integrated fractal–liquid metal design offers a promising route for multifunctional sensing in applications such as soft robotics, human–machine interaction, and wearable electronics.

Huibin Wang, Changfeng Yan, Yaofeng Liu et al.

As the main part of industrial rotating machinery, rolling bearings play an important role in improving the efficiency of mechanical equipment. Due to the influence of the complicated working environment, the single fault is easy to develop into the compound fault. The accurate identification of compound faults can effectively assess the severity of bearing damage, and can provide references for the continued use or replacement of bearings by technicians. The compound faults of rolling bearings are characterized by coupling, concealment, and complex resonance. For the diagnosis of compound faults, the “blind” methods that select the single optimal demodulation frequency band for analysis and identification sometimes cannot completely extract multiple fault components, and some “target” methods cannot effectively extract fault features because they do not consider the influence of random slip of bearing. In order to solve this problem, the LFIgram method is proposed by constructing the log envelope autocorrelation slice bispectrum (LEAB) and LEAB feature index (LFI). The frequency band of the original signal is divided by the maximal overlap discrete wavelet packet transform (MODWPT), and the LFI index is used to quantitatively describe the fault signals of different frequency bands. According to the different fault characteristic frequencies (FCFs), the resonant frequency band of the maximum LFI value is selected, the resonance band signal is analyzed by LEAB, and the fault type is identified according to the fault characteristic frequency in the LEAB. The simulated and experimental vibration signals of rolling bearings with compound faults are used to verify the feasibility of the proposed method. The results show that the proposed LFIgram can improve the accuracy of compound faults identification and would be applied in engineering practice to a certain extent.

Saravana Kumar Krishnamoorthy, Narottam Das, Prasad Gudimetla et al.

In electrical engineering, Brushless Direct Current (BLDC) motors are frequently used in mechanical applications because of their effectiveness, strong torque, and small design. Nevertheless, reaching peak performance and making accurate adjustments to parameters can be difficult when using a simple, customized Proportional Integral Derivative (PID) controller. In the past, speed control typically included adjusting crucial factors like voltage, and current. However, manual speed regulation has drawbacks, including being time-consuming, susceptible to human error, and lacking scalability. Different traditional models have tried to enhance speed control efficiency with Artificial Intelligence (AI) but face challenges in improving Rise Time, Settling Time, Maximum Overshoot, and overall efficiency. A proposed approach to address this problem involves the implementation of a developed model using the Enhanced Whale Optimization Algorithm- Tuned PID (EWOA-TPID) Controller. This system utilizes the benefits of the Whale Optimization Algorithm (WOA) to increase convergence speed, enhance exploitation and exploration abilities, and accurate speed control by efficiently tuning the parameters of PID to decrease the steady state error and overshoot. The key performance metrics which comprise Rise Time, Settling Time, and Maximum Overshoot are utilized to assess the efficacy of this approach. Moreover, the presented system is compared with conventional models to showcase the improved effectiveness of the respective model. This innovative approach intends to contribute significantly to studies in areas like robotics, automation, electric vehicles, industrial machinery, and other systems that use BLDC motors for speed regulation.

Seon-Woo Lee, A. B. Kareem, J. Hur

Speed reducers (SR) and electric motors are crucial in modern manufacturing, especially within adhesive coating equipment. The electric motor mainly transforms electrical power into mechanical force to propel most machinery. Conversely, speed reducers are vital elements that control the speed and torque of rotating machinery, ensuring optimal performance and efficiency. Interestingly, variations in chamber temperatures of adhesive coating machines and the use of specific adhesives can lead to defects in chains and jigs, causing possible breakdowns in the speed reducer and its surrounding components. This study introduces novel deep-learning autoencoder models to enhance production efficiency by presenting a comparative assessment for anomaly detection that would enable precise and predictive insights by modeling complex temporal relationships in the vibration data. The data acquisition framework facilitated adherence to data governance principles by maintaining data quality and consistency, data storage and processing operations, and aligning with data management standards. The study here would capture the attention of practitioners involved in data-centric processes, industrial engineering, and advanced manufacturing techniques.

Yazhou Zhang, Huansheng Wu, Linpeng Liu et al.

Vibration sensors are widely applied in the detection of faults and analysis of operational states in engineering machinery and equipment. However, commercial vibration sensors with a feature of high hardness hinder their usage in some practical applications where the measured objects have irregular surfaces that are difficult to install. Moreover, as the operating environments of machinery become increasingly complex, there is a growing demand for sensors capable of working in wet and humid conditions. Here, we present a flexible, superhydrophobic vibration sensor with parallel microcracks. The sensor is fabricated using a femtosecond laser direct writing ablation strategy to create the parallel cracks on a PDMS film, followed by spray-coating with a conductive ink composed of MWCNTs, CB, and PDMS. The results demonstrate that the developed flexible sensor exhibits a high-frequency response of up to 2000 Hz, a high acceleration response of up to 100 m/s2, a water contact angle as high as 159.61°, and a linearity of 0.9812 between the voltage signal and acceleration. The results indicate that the sensor can be employed for underwater vibration, sound recognition, and vibration monitoring in fields such as shield cutters, holding significant potential for mechanical equipment vibration monitoring and speech-based human–machine interaction.

Yue Yu, Xinxing Liu, Sam Zhang et al.

Wide-bandgap (WB) mixed-halide perovskite solar cells (PSCs) play a crucial role in perovskite-based tandem solar cells (TSCs), enabling them to exceed the Shockley–Queisser limits of single-junction solar cells. Nonetheless, the lack of stability in WB perovskite films due to photoinduced phase segregation undermines the stability of WB PSCs and their TSCs, thus impeding the commercialization of perovskite-based TSCs. Many efforts have been made to suppress photoinduced phase segregation in WB perovskite films and significant progresses have been obtained. In this review, we elaborate the mechanisms behind photoinduced phase segregation and its impact on the photovoltaic performance and stability of devices. The importance role of advanced characterization techniques in confirming the photoinduced phase segregation are comprehensively summarized. Beyond that, the effective strategies to alleviate photoinduced phase segregation in WB mixed halide PSCs are systematically assessed. Finally, the prospects for developing highly efficient and stable WB PSCs in tandem application are also presented.

A. MOISE, A. IACOB, A. CANĂ et al.

This work highlights the fact that construction works, which often involves deep excavation and work in areas with unstable ground, poses significant risks to workers. The proper use of shore supports is an essential measure to protect workers and prevent accidents. Supports are not an option, but a necessity imposed by occupational health and safety legislation and regulations. Their correct implementation reflects a culture of prevention and respect for worker safety, being essential to the success of construction projects.

Alireza Azarhooshang, Alireza Rezazadeh

Abstract Virtual power plants (VPP) with resources and storages are able to control the active power of the network. They are also connected to the network through an inverter, which is capable of controlling reactive power. Therefore, it is expected that the optimal use of inverter‐based VPP can play an effective role in improving the economic and technical status of the distribution network. So, the operation of a smart distribution system is presented in this paper by considering inverter‐based VPPs constrained to the operator's measures. The weighted sum of expected energy loss (EEL) and voltage security index (VSI) is minimized while considering AC optimal power flow equations, restrictions of network's security, and operating model of the inverter‐based VPPs. Uncertainties with an origin of the amount of demand, renewable energy, and parameters of mobile energy storage are also discussed. The uncertainties are modelled using a stochastic optimization approach relying on the unscented transformation (UT). Evaluating inverter‐based VPP performance, providing models of flexible resources such as responsive loads and mobile storages, checking network voltage security status, and modelling uncertainties using the UT method are among the innovations of this study. According to the results, it is demonstrated that the technical situation of the distribution system is improved with the help of optimal management of the VPP. With energy management of the inverter‐based VPP, the suggested design has succeeded to enhance the operating status (voltage security) of the system by approximately 33–73% (12%) in comparison to power flow studies.

Yong YANG, Jiajia CHEN, Songyan LIU et al.

Objectives: With the development of modern processing technology, heat accumulation has become an urgent processing problem that needs to be solved. A heat pipe is a heat exchange element that efficiently transfers heat through the gas-liquid phase change of the working fluid inside the pipe. Gravity heat pipe have advantages such as simple structure, stable operation, and low cost, and are widely used in various heat exchange scenarios in industrial production. They have played a significant role in energy conservation, the development and utilization of new energy, and in strengthening heat exchange during processing. This article prensents experimental research on diamond nanofluids, exploring the influence of different parameters on the heat transfer performance of diamond nanofluid gravity heat pipes, laying a foundation for the research and application of heat pipe technology in heat dissipation during machining processes such as drilling, milling, and grinding. Methods: The evaporation section is heated using a DC power supply and thermal resistance wire. K-type thermocouples and temperature acquisition cards are used to record the temperature of the evaporation and condensation sections of the gravity heat pipe. The influence of heating power, filling rate, nanofluid concentration, and nanoparticle size on the heat transfer performance of the gravity heat pipe is analyzed using thermal resistance R as an indicator. Results: The heat transfer performance of gravity heat pipes is investigated under a power range of 3-18 W, while maintaining a filling rate of 20% and a nanoparticle concentration of 1%. The results show that as the heating power increases, the temperatures of the evaporation and the condensation sections gradually increase, while the rise time gradually shortenes. The temperature difference between the evaporation and condensation sections shows a decreasing trend. When the heating power increases for the same concentration and filling rate of nanoparticles, the total thermal resistance shows a decreasing trend, but the magnitude of the decrease continues to decrease. Keeping the concentration of nanoparticles at 2% and the heating power at 6 W, the heat transfer performance of gravity heat pipes is investigated under conditions of filling rates of 8%, 14%, 20%, and 26%. The results show that the overall temperature of the 20 nm diamond nanofluid is higher than those of other filling rates at a 20% filling rate, while the overall temperature at a 26% filling rate is lower than at other filling rates. The overall temperature at a 26% filling rate is higher than at other filling rates. With the same mass fraction and heating power, as the filling rate increases, the total thermal resistance shows a trend of first decreasing and then increasing, with the minimum value of the total thermal resistance appearing at a filling rate of 14%. By maintaining a filling rate of 26% and a heating power of 12 W, the heat transfer performance of gravity heat pipes under 0.5%, 1.0%, 1.5%, and 2.0% mass fraction conditions is investigated. The results show that the overall temperature of 20 nm diamond nanofluid heat pipes is the highest at a 1% mass fraction, while the overall temperature is lower at a 2.0% mass fraction. The hot-end temperature of 50 nm diamond nanofluid heat pipes is the highest at a 1.5% mass fraction, and the cold-end temperature is the lowest. At a mass fraction of 2.0%, there is a situation where the hot-end temperature is lower and the cold-end temperature is higher. With the same filling rate and heating power, as the mass fraction increases, the total thermal resistance first increases and then decreases. At a mass fraction of 2.0%, the minimum total thermal resistance will appears. In addition, for diamond nanofluids with different particle sizes, there is a trend of heat transfer capacity decreasing first and then improving with increasing mass fraction. Maintaining a filling rate of 14% and a mass fraction of 2.0%, the heat transfer performance of gravity heat pipes with particle sizes of 20 nm and 50 nm was investigated. The total thermal resistance of 50 nm diamond nanofluid gravity heat pipes was always lower than that of 20 nm diamond nanofluid gravity heat pipes. However, as the heating power increases, the advantage of 50 nm diamond nanofluid gravity heat pipes tends to weaken. Maintaining a liquid filling rate of 14% and a mass fraction of 2.0%, the heat transfer performance of gravity heat pipes with and without a liquid absorbing core was investigated. The total thermal resistance of gravity heat pipes with suction cores is lower than that of heat pipes without suction cores, but as the heating power increases, the advantage tends to weaken. Conclusions: When the mass fraction is 2.0%, gravity heat pipes have the best heat transfer performance, with a total thermal resistance increase of approximately 28.4%-64.7% compared to the maximum value. When the filling rate is 14%, the heat transfer performance is the best, and the total thermal resistance decreases by about 6.1%-8.5% compared to the maximum value. When using diamond nanofluids with a particle size of 50 nm, the overall heat transfer performance of gravity heat pipes is better than that of 20 nm. When the heating power of the power supply increases, the heat exchange performance also improves. When using a gravity heat pipe with a liquid absorbing core, its overall heat transfer performance is better than that of a gravity heat pipe without a liquid absorbing core.

Umme Kawsar Alam, Kassidy Shedd, Joshua Kirkland et al.

Introduction: Effective control of rehabilitation robots requires considering the distributed and multi-contact point physical human–robot interaction and users’ biomechanical variation. This paper presents a quasi-static model for the motion of a soft robotic exo-digit while physically interacting with an anthropomorphic finger model for physical therapy.Methods: Quasi-static analytical models were developed for modeling the motion of the soft robot, the anthropomorphic finger, and their coupled physical interaction. An intertwining of kinematics and quasi-static motion was studied to model the distributed (multiple contact points) interaction between the robot and a human finger model. The anthropomorphic finger was modeled as an articulated multi-rigid body structure with multi-contact point interaction. The soft robot was modeled as an articulated hybrid soft-and-rigid model with a constant bending curvature and a constant length for each soft segment. A hyperelastic constitute model based on Yeoh’s 3rdorder material model was used for modeling the soft elastomer. The developed models were experimentally evaluated for 1) free motion of individual soft actuators and 2) constrained motion of the soft robotic exo-digit and anthropomorphic finger model.Results and Discussion: Simulation and experimental results were compared for performance evaluations. The theoretical and experimental results were in agreement for free motion, and the deviation from the constrained motion was in the range of the experimental errors. The outcomes also provided an insight into the importance of considering lengthening for the soft actuators.

Matthew Fowler, Eben Lenfest, Anthony Viselli et al.

Experimental results from the Floating Offshore-wind and Controls Advanced Laboratory (FOCAL) experimental program, which tested a performance-matched model of the IEA Wind 15 MW Reference Turbine on a 1:70 scale floating semisubmersible platform, are compared with OpenFAST simulations. Four experimental campaigns were performed, and data from the fourth campaign, which focused on wind and wave testing of the scaled floating wind turbine system, are considered. Simulations of wave-only, wind-only, and wind/wave environments are performed in OpenFAST, and results for key metrics are compared with the experiment. Performance of the real-time Reference OpenSource COntroller (ROSCO) in above-rated wind conditions, including the effects of the floating feedback loop, are investigated. Results show good agreement in mean values for key metrics, and hydrodynamic effects are matched well. Differences in the surge resonant behavior of the platform are identified and discussed. The effect of the controller and floating feedback loop is evident in both the experiment and OpenFAST, showing significant reduction in platform pitch response and tower base bending load near the platform pitch natural frequency.

Andrew Kirby, François‐Xavier Briol, Thomas D. Dunstan et al.

Abstract Turbine wake and local blockage effects are known to alter wind farm power production in two different ways: (1) by changing the wind speed locally in front of each turbine and (2) by changing the overall flow resistance in the farm and thus the so‐called farm blockage effect. To better predict these effects with low computational costs, we develop data‐driven emulators of the ‘local’ or ‘internal’ turbine thrust coefficient CT∗ as a function of turbine layout. We train the model using a multi‐fidelity Gaussian process (GP) regression with a combination of low (engineering wake model) and high‐fidelity (large eddy simulations) simulations of farms with different layouts and wind directions. A large set of low‐fidelity data speeds up the learning process and the high‐fidelity data ensures a high accuracy. The trained multi‐fidelity GP model is shown to give more accurate predictions of CT∗ compared to a standard (single‐fidelity) GP regression applied only to a limited set of high‐fidelity data. We also use the multi‐fidelity GP model of CT∗ with the two‐scale momentum theory (Nishino & Dunstan 2020, J. Fluid Mech. 894, A2) to demonstrate that the model can be used to give fast and accurate predictions of large wind farm performance under various mesoscale atmospheric conditions. This new approach could be beneficial for improving annual energy production (AEP) calculations and farm optimization in the future.

Siena C. Senatore, Kota Z. Takahashi, Philippe Malcolm

Introduction: Human-in-the-loop optimization algorithms have proven useful in optimizing complex interactive problems, such as the interaction between humans and robotic exoskeletons. Specifically, this methodology has been proven valid for reducing metabolic cost while wearing robotic exoskeletons. However, many prostheses and orthoses still consist of passive elements that require manual adjustments of settings.Methods: In the present study, we investigated if human-in-the-loop algorithms could guide faster manual adjustments in a procedure similar to fitting a prosthesis. Eight healthy participants wore a prosthesis simulator and walked on a treadmill at 0.8 ms−1 under 16 combinations of shoe heel height and pylon height. A human-in-the-loop optimization algorithm was used to find an optimal combination for reducing the loading rate on the limb contralateral to the prosthesis simulator. To evaluate the performance of the optimization algorithm, we used a convergence criterium. We evaluated the accuracy by comparing it against the optimum from a full sweep of all combinations.Results: In five out of the eight participants, the human-in-the-loop optimization reduced the time taken to find an optimal combination; however, in three participants, the human-in-the-loop optimization either converged by the last iteration or did not converge.Discussion: Findings from this study show that the human-in-the-loop methodology could be helpful in tasks that require manually adjusting an assistive device, such as optimizing an unpowered prosthesis. However, further research is needed to achieve robust performance and evaluate applicability in persons with amputation wearing an actual prosthesis.

E. Bottani, B. Bottari, D. Milanese et al.

One of the main issues addressed by the recent COVID-19 pandemic which affected the whole world is the availability of Personal Protective Equipment (PPE) (e.g., face masks, white coats, or disposable gloves). This issue impacts on sustainability from different perspectives, such as more generated waste or environmental pollution, both for manufacturing and disposal, or more inequalities deriving from who can afford and access PPE and who cannot, since many shortages were recorded during the pandemic as well as fluctuating unit prices. Moreover, quite often PPE intended for single use are improperly used more times, thus generating a biological risk of infection. In an attempt to propose an innovative solution to face this problem, in this paper the re-design of an oven originally intended for food purposes is presented, with the aim of operating a thermal sanitization of PPE. The machinery and its components are detailed, together with physical and microbiological tests performed on non-woven PPE to assess the effect of treatment on mechanical properties and viral load. The pilot machinery turned out to be effective in destroying a bovine coronavirus at 95 °C and thus reducing contaminating risk in one hour without compromising the main properties of PPE, opening perspectives for the commercialization of the solution in the near future.

P. Barati, M. Saghafian

In a bifurcation including a mother artery and two daughter arteries, the energy drop is minimum, if, the cube of the radius of the mother artery equals the sum of the cube of the radii of daughter arteries. This is the expression of Murray’s law (or cubic law) assuming the flow is steady. In this paper, an extension of Murray’s law is investigated using the minimum energy hypothesis, totally analytical for pulsating flow. In addition to the two terms that Murray considered in his calculations, there is additional energy to move fluid toward and back in the pulsating flow. This additional energy is calculated and added to two other parts of energy in Murray’s analysis, and then optimized. The relationships for diameters and the angle between daughter arteries are extended. The effect of frequency and Womersley number have appeared as coefficients in the relations. According to the results, the most difference between Murray’s law for both diameters and the angle between daughter arteries, and the relationship derived in the present paper, occurs in Womersley number between 2 and 5. For a special case which in the daughter arteries have the same diameter, the power of diameters varies up from 3 to 3.2. Also, for this special case, there is maximum 6 degrees difference with Murray’s law for the angle between daughter arteries. In short, the obtained relations, assuming pulsating flow, do not yield very different results from Murray's law assuming steady flow.

Ying Zhan, Austin Fergusson, Lacey R. McNally et al.

Bacteria‐mediated drug delivery systems comprising nanotherapeutics conjugated onto bacteria synergistically augment the efficacy of both therapeutic modalities in cancer therapy. Nanocarriers preserve therapeutics’ bioavailability and reduce systemic toxicity, while bacteria selectively colonize the cancerous tissue, impart intrinsic and immune‐mediated antitumor effects, and propel nanotherapeutics interstitially. The optimal bacteria–nanoparticle (NP) conjugates will carry the maximal NP load with minimal motility speed hindrance for effective interstitial distribution. Furthermore, a well‐defined and repeatable NP attachment density distribution is crucial to determining these biohybrid systems’ efficacious dosage and robust performance. Herein, our nanoscale bacteria‐enabled autonomous delivery system (NanoBEADS) platform is utilized to investigate the effects of assembly process parameters of mixing method, volume, and duration on NP attachment density and repeatability. The effect of linkage chemistry and NP size on NP attachment density, viability, growth rate, and motility of NanoBEADS is also evaluated. It is shown that the linkage chemistry impacts NP attachment density while the self‐assembly process parameters affect the repeatability and, to a lesser extent, attachment density. Lastly, the attachment density affects NanoBEADS’ growth rate and motility in an NP size‐dependent manner. These findings will contribute to the development of scalable and repeatable bacteria–NP biohybrids for applications in drug delivery and beyond. An interactive preprint version of the article can be found here: https://www.authorea.com/doi/full/10.22541/au.163100509.93917936.

X. Wei, Lei Wang, Xiangdong Ni et al.