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Based on the principles of biomimicry, evolutionary algorithms (EAs) have been widely applied across diverse domains to tackle practical challenges. However, the inherent limitations of these algorithms call for further refinement to strike a delicate balance between global exploration and local exploitation. Thus, this paper introduces a novel multi-strategy enhanced hybrid algorithm called MHWACO, which integrates a Whale Optimization Algorithm (WOA) and Ant Colony Optimization (ACO). Initially, MHWACO employs Gaussian perturbation optimization for individual initialization. Subsequently, individuals selectively undertake either localized exploration based on the refined WOA or global prospecting anchored in the Golden Sine Algorithm (Golden-SA), determined by transition probabilities. Inspired by the collaborative behavior of ant colonies, a Flight Ant (FA) strategy is proposed to guide unoptimized individuals toward potential global optimal solutions. Finally, the Gaussian scatter search (GSS) strategy is activated during low population activity, striking a balance between global exploration and local exploitation capabilities. Moreover, the efficacy of Support Vector Regression (SVR) and random forest (RF) as regression models heavily depends on parameter selection. In response, we have devised the MHWACO-SVM and MHWACO-RF models to refine the selection of parameters, applying them to various real-world problems such as stock prediction, housing estimation, disease forecasting, fire prediction, and air quality monitoring. Experimental comparisons against 9 newly proposed intelligent optimization algorithms and 9 enhanced algorithms across 34 benchmark test functions and the CEC2022 benchmark suite, highlight the notable superiority and efficacy of MSWOA in addressing global optimization problems. Finally, the proposed MHWACO-SVM and MHWACO-RF models outperform other regression models across key metrics such as the Mean Bias Error (MBE), Coefficient of Determination (R2), Mean Absolute Error (MAE), Explained Variance Score (EVS), and Median Absolute Error (MEAE).

Abstract Based on the coupling effects of contact electrification and electrostatic induction, a triboelectric nanogenerator (TENG) can convert mechanical energy into electric power, which is at the cutting edge of alternative energy technology. Although a considerable number of TENGs with different configurations have been designed, some of them however, which only depend on the electrostatic induction effect have not received enough attention. Here, a non‐contact TENG model consists of copper rings and charged dielectric sphere is presented, which is aimed at exploring the working process of TENGs caused by electrostatic induction. Two classical models, including vertical and horizontal double copper rings models are also proposed. Relevant advanced and accurate models of TENGs have been established through the finite element method. We anticipate that the constructed model and theoretical analysis are helpful for the design of non‐contact model TENGs with complicated geometric construction, and expand their applications in various fields.

Particle Swarm Optimization (PSO) is facing more challenges in solving high-dimensional global optimization problems. In order to overcome this difficulty, this paper proposes a novel PSO variant of the hybrid Sine Cosine Algorithm (SCA) strategy, named Velocity Four Sine Cosine Particle Swarm Optimization (VFSCPSO). The introduction of the SCA strategy in the velocity formulation ensures that the global optimal solution is found accurately. It increases the flexibility of PSO. A series of experiments are conducted on the CEC2005 test suite with compositional algorithms, algorithmic variants, and good intelligent algorithms. The experimental results show that the algorithm effectively improves the overall performance of compositional algorithms; the Friedman test proves that the algorithm has good competitiveness. The algorithm also performs better in PID parameter tuning. Therefore, the VFSCPSO is able to solve the high-dimensional global optimization problems in a better way.

Recently, the nanogenerators which can convert the mechanical energy into electricity by using piezoelectric one-dimensional nanomaterials have exhibited great potential in microscale power supply and sensor systems. In this paper, we provided a comprehensive review of the research progress in the last eight years concerning the piezoelectric nanogenerators with different structures. The fundamental piezoelectric theory and typical piezoelectric materials are firstly reviewed. After that, the working mechanism, modeling, and structure design of piezoelectric nanogenerators were discussed. Then the recent progress of nanogenerators was reviewed in the structure point of views. Finally, we also discussed the potential application and future development of the piezoelectric nanogenerators.

This paper reports the noncontact manipulation of free-falling cylindrical streams of liquid metals into unique shapes, such as levitated loops and squares. Such cylindrical streams form in aqueous media by electrochemically lowering the interfacial tension. The electrochemical reactions require an electrical current that flows through the streams, making them susceptible to the Lorentz force. Consequently, varying the position and shape of a magnetic field relative to the stream controls these forces. Moreover, the movement of the metal stream relative to the magnetic field induces significant forces arising from Lenz's law that cause the manipulated streams to levitate in unique shapes. The ability to control streams of liquid metals in a noncontact manner will enable strategies for shaping electronically conductive fluids for advanced manufacturing and dynamic electronic structures. [ABSTRACT FROM AUTHOR]

Orthorhombic (K,Na)NbO3 (KNN) nanorod arrays with the [110]-orientation were grown on SrTiO3 substrates by the hydrothermal method. The nanorods exhibited greatly enhanced piezoelectric performance, with the d33 piezoelectric coefficient increasing from 140 pm/V to 360 pm/V, after annealing in oxygen at temperatures ranging from 500 °C to 800 °C. The high temperature annealing process was accompanied by severe volatilization of K, which modified the K/Na ratio closer to 1:1. Thus, orthorhombic-tetragonal (O-T) phase boundaries appeared, which improved the piezoelectric property. Moreover, surface oxygen vacancies were passivated in the high-temperature oxygen atmosphere, which would reduce the charge density in the nanorods and contribute to the enhanced piezoelectricity. Therefore, excellent piezoelectricity in the KNN nanorod arrays was driven by the combination of the O-T phase boundaries and the oxygen vacancy passivation. This work demonstrates that KNN has great potential in piezoelectric materials area. [ABSTRACT FROM AUTHOR]

The development of self-powered vibration sensors using polymeric piezoelectric nanomaterials has attracted great attention owing to their outstanding flexibility and energy harvesting behaviours. In this study, ultra-long poly (vinylidene fluoride) (PVDF) nanofibres with optimised β-phase content were synthesised through electrospinning method with different DC voltages. The increase in the β-phase content of the PVDF nanofibres greatly enhanced their piezoelectric response with nearly tripled output voltage and current under the same strain condition. Moreover, the output voltage exhibited linear correlations with both the amplitude and frequency of the strain. Under a fixed frequency of 1.54 Hz, the output voltage exhibited a linear correlation to the strain amplitude with strain sensitivity up to 0.92 V rad−1 and 0.61 V mm−1. The frequency-dependent strain sensing behaviour also confirmed the necessity for frequency calibration to the measured results of vibration. Accordingly, the sensor can be used for self-powered monitoring of the vibration state of a metal foil and measuring the intrinsic resonance frequency of the objects without any powering source. [ABSTRACT FROM AUTHOR]