Mechanism of Silver Nanoparticles Deposition by Electrolysis and Electroless Methods on a Graphite Substrate

This study shows a silver electrodeposition model (EDM) on a graphite ‎substrate. The electrolyte was a 0.01 M solution of pure silver and chromium nitrate using an ‎electrolyzing cell. EDC with current density up to 20 mA/cm2 and 15 mV and pulse current were studied. Results revealed that silver deposited at a ‎rate of 0.515 mg/cm2/min with 12 mA /cm2 that decreases to 0.21 and 0.16 mg/cm2.min ‎with the decrease of current density to 6 and 5 mA/cm2 respectively. The model postulates that ‎silver ions (a) were first hydrated before diffusing (b) from the solution bulk to ‎the cathode vicinity, the next step (c) involved the chemical adsorption of these ions on certain ‎accessible sites of the graphite substrate (anode), the discharged entities (d) adhere to the graphite ‎surface by Van der Vales force. Silver ions are deposited because the ‎discharge potential of silver is low (0.38 mV) as compared to other metal ions like chromium (0.82 mV). Pulse ‎current controls silver deposition due to flexibility in controlling steps (a) - (c) of the ‎deposition mechanisms.

Investigations on the properties of composite coatings electro co-deposited on AZ80 Mg alloy using triangular waveform pulse current

In this research, boron carbide (B4C) and titanium carbide (TiC) nanoparticles were deposited along with Nickel on AZ80 magnesium alloy substrates. Triangular waveform pulse current was used for depositing the coatings on the substrate. The objective of this research is to investigate the microstructural evolution of the coatings in response to the current density, duty cycle and the concentration of reinforcements in the bath. The influence of process parameters were also assessed in terms of the microhardness and specific wear rate. To enhance the surface properties of AZ80 magnesium alloy, a three component layer was successfully applied via electro co-deposition technique for the first time. The magnesium alloy substrates were cleaned and pretreated as per ASTM B480−88. The pretreated samples were coated at three levels of current density viz. 1.5 A/dm2, 2 A/dm2 and 2.5 A/dm2, and the duty cycle was varied between 30%, 40% and 50%. The concentrations of reinforcements in the bath were kept at 0 g/L, 0.5 g/L and 1 g/L. The samples were coated according to Taguchi L9 orthogonal array with two replications. The microstructural studies conducted using scanning electron microscope (SEM) revealed the defects, grain refinement and homogeneous distribution of reinforcements in the Ni matrix. The deposition and orientation of reinforcements in preferred planes were investigated with XRD. Vickers microhardness tests conducted as per ASTM E384-17 revealed that the sample coated with 2.5 A/dm2current density, 30 % duty cycle, 1 g/L B4C and 0.5 g/L TiC produced the coatings with the highest hardness of 412.56 Hv. The results of the pin on disc wear tests conducted according to ASTM G99 were in agreement with the hardness results and the corresponding microstructure. The sample with the maximum microhardness exhibited the minimum specific wear rate of 2.1 E-08 mm3/Nm. The ability of triangular pulse current waveform to deposit hybrid composite coatings on AZ80 magnesium alloy and enhance its surface properties has been confirmed by the results of this research.

New EDM Generator Used for the Machining of 1.2363 and 1.2343ESR Steels

The basic building block of any electric discharge machine is a generator, which ensures the operation of material separation itself. Not only the erosion rate and electricity consumption but also the quality of the machined surfaces depend on the design of the generator. These key factors for efficient machining have been investigated using a new energy-saving and powerful generator developed for the electric discharge machine (EDM) while machining 1.2363 and 1.2343ESR steels. In order to monitor and model the responses in the form of eroding rate and surface quality, a two-level half-factor experiment was performed with one replication at the corner points and two replications at the central points, for a total of 80 rounds. Both graphite and copper electrodes of sizes 10x10 mm and 100x100 mm were used for eroding and the influence of parameter settings: Open-voltage, Pulse current, Pulse on-time and Pulse off-time was monitored. It was found out that the shape of the electrode and Pulse current have the most significant effect on the erosion rate. The parameters Pulse current, Pulse on-time and their mutual interaction have the most significant effect on the surface topography. Statistically significant factors influencing the occurrence of defects turned out to be Pulse current, Pulse on-time and Material of workpiece, where it can be seen that the material 1.2343ESR is significantly less prone to the formation of surface defects.

Research on restoration method of nuclear pulse current signal of semiconductor detector based on artificial neural networks

The charge pulse generated by semiconductor detector caused by nuclear event carries nuclide and nuclear reaction information, but the amplified charge pulse amplitude is obviously weak and the noise is so large. Aiming at the difficulty of obtaining the charge signal pulse generated by the detector, a method for recovering the nuclear pulse current signal of semiconductor detector is proposed. Pulse recovery is divided into two parts: pulse shape recovery and pulse amplitude recovery. Point at the pulse shape, a shape recognition network of nuclear pulse current signal based on deep learning is proposed. For pulse amplitude,it can be obtained by Mexican straw hat wavelet forming algorithm. This algorithm can eliminate the baseline fluctuation caused by pulse stacking. The proposed shape recognition network of nuclear pulse current signal is composed of classifier and regressor. The classifier is used to judge whether the data contains a complete rising edge. The data containing the complete rising edge is sent to the regressor for prediction, so as to obtain the parameters related to the current pulse shape. The precision, recall and F-Measure of the classifier in classifying the test set are 98.88%, 98.05% and 98.33%, respectively. The average absolute error of the regressor in predicting the parameters related to the current pulse shape is about 9 ns. The experimental results show that the proposed method can recover the shape and amplitude of the current signal.

A pulse current generator for dense plasma focus

A pulse current generator applied in a type of high-yield intense pulsed neutron source, the Dense Plasma Focus (DPF), is designed and developed in this paper. There are three key components in this generator. Each group of capacitors and switches is integrative to meet the DPF's requirements of low circuit inductance. A coaxial multi-channel switch is developed to solve the problems of the switch inductance, the jitter and the electrode erosion. A kind of sectorial plate transmission line is adopted to transfer the high pulse current from the capacitors to the DPF. The following technical parameters of the generator were achieved on dummy load: output current amplitude of ∼560 kA when primary capacitors are charged with 22 kV.

Electrical Double Layer Mechanism Analysis of PEM Water Electrolysis for Frequency Limitation of Pulsed Currents

This paper proposes a method for improving hydrogen generation using pulse current in a proton exchange membrane-type electrolyzer (PEMEL). Traditional methods of electrolysis using direct current are known as the simplest approach to produce hydrogen. However, it is highly dependent on environmental variables, such as the temperature and catalyst used, to enhance the rate of electrolysis. Therefore, we propose electrolysis using a pulse current that can apply several dependent variables rather than environmental variables. The proposed method overcomes the difficulties in selecting the frequency of the pulse current by deriving factors affecting hydrogen generation while changing the concentration generated by the cell interface during the pulsed water-electrolysis process. The correlation between the electrolyzer load and the frequency characteristics was analyzed, and the limit value of the applicable frequency of the pulse current was derived through electrical modeling. In addition, the operating characteristics of PEMEL could be predicted, and the PEMEL using the proposed pulse current was verified through experiments.

Statistical Feature Extraction Combined with Generalized Discriminant Component Analysis Driven SVM for Fault Diagnosis of HVDC GIS

Accurately identifying the types of insulation defects inside a gas-insulated switchgear (GIS) is of great significance for guiding maintenance work as well as ensuring the safe and stable operation of GIS. By building a set of 220 kV high-voltage direct current (HVDC) GIS experiment platforms and manufacturing four different types of insulation defects (including multiple sizes and positions), 180,828 pulse current signals under multiple voltage levels are successfully measured. Then, the apparent discharge quantity and the discharge time, two inherent physical quantities unaffected by the experimental platform and measurement system, are obtained after the pulse current signal is denoised, according to which 70 statistical features are extracted. In this paper, a pattern recognition method based on generalized discriminant component analysis driven support vector machine (SVM) is detailed and the corresponding selection criterion of involved parameters is established. The results show that the newly proposed pattern recognition method greatly improves the recognition accuracy of fault diagnosis in comparison with 36 kinds of state-of-the-art dimensionality reduction algorithms and 44 kinds of state-of-the-art classifiers. This newly proposed method not only solves the difficulty that phase-resolved partial discharge (PRPD) cannot be applied under DC condition but also immensely facilitates the fault diagnosis of HVDC GIS.