In order to improve the accuracy and reliability of the photovoltaic (PV) model, this paper explores a novel nature-inspired metaheuristic algorithm, i.e., the nutcracker optimizer algorithm (NOA), for the parameter extraction of a PV model, such as a single diode model (SDM), double diode model (DDM), and triple diode model (TDM) of PV components. The Aleo Solar S79Y300 monocrystalline silicon solar panel was tested at 1000 W/m² solar irradiance and 25 °C temperature, and the results of the proposed NOA algorithm were compared with three popular algorithms, i.e., particle swarm optimization (PSO), firework algorithm (FWA), and whale optimization algorithm (WOA), in terms of algorithm accuracy and running time, and non-parametric tests were performed. The results show that the NOA can improve the efficiency of PV parameter extraction, and its performance is the best among the tested algorithms. It has the best root mean square error (RMSE) values in the SDM, being 7.92587 × 10⁻⁵ and 6.02460 × 10⁻⁵ in the DDM and 6.23617 × 10⁻⁵ in the TDM, and the shortest average execution time according to the overall ranking, making it well suited for extracting PV model parameters.

In this paper, we proposed a novel bonding technology to fabricate a microfluidic device based on Poly(methyl methacrylate) (PMMA). The method, which used chloroform and ethanol as miscible bonding solvent, can complete complex structures rapid assembly (10 min) at 40°C. A bonding strength of 267.5 N/cm² can be achieved, while the micro channel deformation was less than 7.26%. Then we utilized this method to produce a three layers micro mixer, which included a T-shaped inlet channel and six H-shaped mixing units. Numerical simulation indicated that, the well mixing length of the mixer was only about 6 mm when Re = 10. Finally, fluorescence microscopy was used to verify mixer performance. The method provided the potential for mass production of multilayer rigid polymer microfluidic devices.

Polymer microchannels can be commonly processed using many non-lithographic methods for reducing the manufacturing cost and steps. In this research, an inexpensive and high-precision thermal engraving technology is developed and achieved to machine polymer microchannels ranging from tens to hundreds of micrometers. This paper presents the design of a thermal engraving device, the processing method and the experimental procedure. Thermal engraving microscribers can fabricate microchannels with a width less than 100 μm. Furthermore, the effects of velocity and temperature on the roughness of polymethyl methacrylate (PMMA) microchannels are also discussed. Finally, a smooth microchannel with these parameters optimally coordinated is achieved. Meanwhile, the contact angle (CA) and the electro-osmotic flow (EOF) of microchannels fabricated by this technology are also measured. The experimental results show that this method of fabrication has the advantages of low cost, high efficiency and small polymer microchannel size compared with several non-lithographic methods. This method of fabrication would be attractive for labs lacking extremely clean rooms and expensive photolithography apparatuses.

We proposed a thermal engraving technology based on heat transfer theory and polymer rheology in microfluidic field. Then, we established a 3D model of the thermal engraving process based on polymethyl methacrylate (PMMA) material. We could employ the model to analyze the influence of temperature and speed on microchannel processing through the finite element simulation. Thus, we gained the optimal processing parameters. The orthogonal experiments were carried out within the parameter ranges obtained by the simulation results. Finally, we fabricated the smooth microchannel, the average roughness of which was 0.3 μm, by using the optimal parameters. Furthermore, we examined the surface morphology and wettability. Our work provides a convenient technological support for a fast, low-cost, and large-scale manufacturing method of microfluidic chips.