Development of Sn-doped ZnO based ecofriendly piezoelectric nanogenerator for energy harvesting application.

In this work, we have a demonstrated zinc oxide (ZnO) polymer-based ecofriendly piezoelectric nanogenerator (PENG) on a paper substrate for an energy harvesting application. The ZnO thin film is developed on the paper substrate, where different doping concentrations of Sn have been investigated systematically to validate the effect of doping towards enhancing the device performance. The piezoelectric potential of the fabricated device is evaluated by applying three different loads (4 N, 8 N, 22 N), where the source of the corresponding mechanical loads is based on the object of a musical drum stick. The results suggest that the pristine ZnO PENG device can generate a maximum output voltage and current of 2.15 V and 17 nA respectively. Moreover, the ZnO PENG device doped with 2.5% Sn achieved an even higher voltage (4.15 V) and current (36 nA) compared to pristine ZnO devices. In addition, the hydrothermal growth technique used to develop Sn-doped ZnO has the benefits of high scalability and low cost. Hence, the Sn-doped PENG device is a suitable candidate for energy harvesting applications operating in both uniform and non-uniform loading conditions.

Multi-Response Optimization of WEDM Process Parameters for Machining of Superelastic Nitinol Shape-Memory Alloy Using a Heat-Transfer Search Algorithm.

Nitinol, a shape-memory alloy (SMA), is gaining popularity for use in various applications. Machining of these SMAs poses a challenge during conventional machining. Henceforth, in the current study, the wire-electric discharge process has been attempted to machine nickel-titanium (Ni55.8Ti) super-elastic SMA. Furthermore, to render the process viable for industry, a systematic approach comprising response surface methodology (RSM) and a heat-transfer search (HTS) algorithm has been strategized for optimization of process parameters. Pulse-on time, pulse-off time and current were considered as input process parameters, whereas material removal rate (MRR), surface roughness, and micro-hardness were considered as output responses. Residual plots were generated to check the robustness of analysis of variance (ANOVA) results and generated mathematical models. A multi-objective HTS algorithm was executed for generating 2-D and 3-D Pareto optimal points indicating the non-dominant feasible solutions. The proposed combined approach proved to be highly effective in predicting and optimizing the wire electrical discharge machining (WEDM) process parameters. Validation trials were carried out and the error between measured and predicted values was negligible. To ensure the existence of a shape-memory effect even after machining, a differential scanning calorimetry (DSC) test was carried out. The optimized parameters were found to machine the alloy appropriately with the intact shape memory effect.