The 10 most-cited articles in Applied Mechanics and Materials, 2022

Neurotransmitters are synapses transmitting messengers that are vital towards human wellness. Any abnormality in their behaviour can lead to huge psychological ailments such as Parkinson's, Alzheimer's, and Schizophrenia. During diagnosing and assessing mental diseases, it is critical to discover distinct measures of different neurotransmitters present. A combination of nanomaterials, proteins, and polymers are employed to create suitable detecting and sensing component systems. Electrochemical detection has been widely employed for in-vivo detection, with FSCV emerging as the most promising technology to date due to advantages such as high sensitivities, simple device structure, and facile downsizing. Excessive background noise and signal, restricted target selectivity, declination with time, and the device fouling are all issues that in-vivo electrochemical neurotransmitter indications encounter. Nanomaterials have sparked a tremendous focus in recent years owing to their diverse properties. CPEs are amongst the safest and most ecologically beneficial electrodes with a vast scope…

Rare-earth-based nanocomposites are currently attracting extensive research interest in biology, medicine, physics, chemistry and material science owing to their optical, electrical and electronic properties, their stability and novel applications. Rare-earth based nanomaterials, especially rare earth oxides (Yttrium oxide, Gadolinium oxide, lanthanum oxide, cerium dioxide, etc.) have fascinated people's devotion owing to their good environmentally friendly and redox properties characteristics. Rare-earth based nanomaterials with exceptional electrochemical properties can be attained by simple, low-cost, environmentally friendly approaches such as hydrothermal/solvothermal method, electrodeposition method, atomic layer deposition method, etc. The electrochemical and microstructures properties of the samples were characterized by X-ray diffraction, scanning electron microscopy, galvanostatic charge/discharge cycling, potentiostatic electrochemical impedance spectroscopy and cyclic voltammetry, in this review, we present a wide-ranging explanation of synthesis methods, morphology and…

This paper provides the modeling and control of stator active and reactive power for doubly fed induction generator (DFIG) under wind turbine systems using a direct power control (DPC) is applied to the grid side converter (GSC), also the rotor side converter (RSC) of the DFIG is controlling with the field control (FOC) to realize the decoupling control of the active and reactive power. For tuning the PI controllers is a tedious work and it is difficult to tune the PI gains optimally due to the nonlinearity and the high complexity of the system. This paper presents an approach to use the particle swarm optimization algorithm to design the optimal PI controllers for the rotor side converter (RSC) of the DFIG. Based on the simulation results, the PSO-PI provides lower value for the criteria and better response compared with the PI conventional.

Pollution by textile dyes on waterbodies is an issue for both human health and the environment. To remove/degrade dyes, many approaches (coagulation, membrane separation, and adsorption) have been investigated. However, the use of semiconductor-assisted materials in conjunction with sustainable solar energy has emerged as a possible solution to the problem. Although single component photocatalysts have been tested, composites of semiconductor materials are being employed owing to their low efficiency and stability due to the high recombination rate electron-hole pair and inefficient visible light absorption. By combining two or more semiconductor components, semiconductor heterojunction systems are created. Overall stability is increased by the synergistic impact of their features, such as adsorption and better charge carrier movement. This paper discusses current advances in advanced nanocomposite materials utilized as photocatalysts, as well as the utilization of heterojunctions, crystallinity, and doping to improve photocatalytic characteristics. The conclusion includes a…

One of the most often credited materials for opening up new possibilities in the creation of next-generation biosensors is graphene oxide (GO). GO has good water dispersibility, biocompatibility, and high affinity for specific biomolecules due to the coexistence of hydrophobic domains from pristine graphite structure and hydrophilic oxygen containing functional groups, as well as properties of graphene itself that are partly dependent on preparation methods. The high signal output and a strong potential for rapid industrial growth rate, graphene-based materials, such as graphene oxide (GO), are receiving substantial interest in bio sensing applications. Some of graphene's most enticing qualities are its superior conductivity and mechanical capabilities (such as toughness and elasticity), as well as its high reactivity to chemical compounds. The existence of waves on the surface (natural or created) is another property/variable that has immense potential if properly utilized. Single cell detection can be performed by optical biosensors based on graphene. The present state of…

In this paper, we present a modeling of the photovoltaic array in order to tracking the maximum power point (MPPT) using a soft computing approach based on artificial neural network, The maximum power point tracking MPPT play a crucial role in photovoltaic systems for their ability to maximize the power output under varying conditions; The photovoltaic array modeled and implemented in matlab simulink environnement using the conventional perturb and observe algorithm for multiple ranges under varying temperatures and irradiances levels, a feed forward neural network collect the training data from the photovoltaic array simulink model, after the training process check, the neural network model tested with new temperatures and irradiance data to predict the maximum power point of the photovoltaic array, The developed neural network model shown an interesting results compared to simulink model based on classic perturb and observe algorithm.

A warehouse management system (WMS) is a software application that helps control and manage the day-to-day operations in a warehouse. WMS software guides inventory receiving and put-away, optimizes picking and shipping of orders. This research has the objective to design a warehouse management information system in Hypertext Preprocessor language (PHP). The development methodology used is Rapid Application Development (RAD) with an object-oriented approach while the tool used in design is Unified Modeling Language (UML). Problems in the distributor of plumbing products are the increasingly large amount of stored information resulting in storing information in Excel files that no longer meet the requirements of retrieving and synthesizing information, as well as the storage of goods in the warehouse is disorganized leading to the increasing order processing time, which is one of the reasons of the increase in order delay rate. The solution of this problem focuses on implementing a management information system which helps to store and retrieve goods information (quantity,…

This paper presents the research on the process of designing and optimizing the powertrain of electric vehicles, such as the general arrangement of electric vehicles, the design of electric motors, transmission systems, battery systems, as well as selecting the appropriate layout design. In addition, the article analyzes the computational models of electric drive systems, energy systems and calculates the performance of these systems in accordance with actual use. Finally, design and simulation calculations of the powertrain and energy of electric vehicles are performed using Simcenter Amesim software. Keywords: Electric vehicle, battery, electric motor, Simcenter Amesim

Abstract. Triboelectric nanogenerators (TENG) have made significant progress as a sustainable energy harvesting technique due to their ease of assembly, high power density, good stability and cost-efficiency. This study develops the magnetic structured triboelectric nanogenerators (MS-TENG) for energy harvesting with different loading frequency. The MS-TENG use magnetic force in the sliding mode to provide the repulsive force. The dielectric and electrode components, in particular, are appropriately connected to the circuit, which is attached to the digital oscilloscope for voltage performance. The copper capsules in mode two were the most effective design for the MS-TENG. The highest load-circuit voltage of 4.0 V is obtained for the copper (Cu) MS-TENG in mode 2 (dielectric capsule designed in mode 2 is first coated with a layer of Cu or Al and then covered with Kapton). A peak power in this design is 3.4 µW. The suggested MS-TENG offers a practical way to gather electrical energy via the triboelectric effect, which are suitable for multifunctional applications.

Energy harvesting has been at the forefront of research due to the significant interest in green energy sources, especially for powering remote sensors in structural health monitoring of coastal and offshore facilities. This work reports the magnet-actuated piezoelectric harvesters (M-APH) that use magnetic coupling to actuate piezoelectric film-embedded silicon rubber strips for energy harvesting from fluids. The piezo-silicon strips are deflected by the tip-magnets in the actuation system, such that the M-APH can effectively be triggered to generate electrical energy from vibration. The M-APH prototypes are printed using 3D printing technology, and the experiments are conducted to determine the output electrical voltage using a rectifier. Strip properties are varied to study the geometric influence (i.e., thickness and shape) on the energy performance. The electrical performance was evaluated for each curved piezoelectric strip and straight strips according to the piezoelectric material used. The reported M-APH can be applied to various fluids for energy harvesting.