In this study, Atomic Layer Deposition (ALD) equipment was used to deposit Al₂O₃ film on a p-type silicon wafer, trimethylaluminum (TMA) and H₂O were used as precursor materials, and then the post-annealing process was conducted under atmospheric pressure. The Al₂O₃ films annealed at different temperatures between 200–500 °C were compared to ascertain the effect of passivation films and to confirm the changes in film structure and thickness before and after annealing through TEM images. Furthermore, the negative fixed charge and interface defect density were analyzed using the C-V measurement method. Photo-induced carrier generation was used to measure the effective minority carrier lifetime, the implied open-circuit voltage, and the effective surface recombination velocity of the film. The carrier lifetime was found to be the longest (2181.7 μs) for Al₂O₃/Si post-annealed at 400 °C. Finally, with the use of VHF (40.68 MHz) plasma-enhanced chemical vapor deposition (PECVD) equipment, a silicon nitride (SiN_x) film was plated as an anti-reflection layer over the front side of the wafer and as a capping layer on the back to realize a passivated emitter and rear contact (PERC) solar cell with optimal efficiency up to 21.54%.

In this study, a self-developed atmospheric pressure atomic layer deposition (APALD) system is used to deposit Al₂O₃ passivation film, along with the use of precursor combinations of Al(CH₃)₃/H₂O to improve its passivation characteristics through a short-time microwave post-annealing process. Comparing the unannealed and microwave-annealed samples whose temperature is controlled at 200–500 °C, APALD non-vacuum deposited film can be realized with a higher film deposition rate, which is beneficial for increasing the production throughput while at the same time reducing the operating cost of vacuum equipment at hand. Since the microwave has a greater penetration depth during the process, the resultant thermal energy provided can be spread out evenly to the entire wafer, thereby achieving the effect of rapid annealing. The film thickness is subsequently analyzed by TEM, whereas the chemical composition is verified by EDS and XPS. The negative fixed charge and interface trap density are analyzed by the C-V measurement method. Finally, the three major indicators of τ_eff, SRV, and IVoc are analyzed by QSSPC to duly verify the excellent passivation performance.

Based on the standard back-propagation neural network, the paper proposes a method combining principal component analysis, variational mode decomposition, improved error back-propagation neural network and multi-task learning to predict the medium and short term power load of the power grid. Firstly, the principal component analysis method is used to extract the characteristics of the influencing factors of the power load, effectively reducing the dimensions of the data samples, eliminating the redundancy and linear information of the data, and retaining the main components as the input data of the model. Then, a combined prediction model based on the combination of variational modal decomposition (VMD), short-term and short-term memory network (LSTM) and multi-task learning (MTL) is proposed. VMD is used to decompose the original load sample set into several different eigenmode functions (IMF) and a residual component to reduce the nonstationarity and complexity of the load data sample set. LSTM model is used to predict the decomposed multi-modal components separately, and MTL is used to establish a shared learning layer to speed up the operation efficiency, and the prediction results of different components are superimposed to obtain the final load prediction value. Finally, through simulation experiments, the prediction results of PCA-VMD-LSTM-MTL, BP model, ELM model and LSTM show that the prediction effect of PCA-VMD-LSTM-MTL model is better than the other three prediction models, and it shows good performance in short-term power load forecasting.

This study mainly constructs a finite element analysis model. The temperature, energy partition and changes of FC300 gray cast iron workpiece during dry grinding are investigated. Thermal load and mechanical deformation of workpiece during grinding can leave residual stress on the surface, which has a considerable impact on the fatigue properties of the workpiece. In the experimental part, different grinding wheel speeds (1200, 900, 600, 400 rpm), workpiece speeds (1000, 3000, 5000, 10000 mm/min), and grinding depths (10, 20 mm/min) were measured μm) Changes in residual stress under conditions. A moving heat source model and a multi abrasive model are established to simplify the condition of the grinding wheel contacting the workpiece. The comparison of material residual forces measured by X-ray diffraction measurements shows that the finite element analysis model proposed in this paper has good reliability. Finally, this model is used to analyze the effects of grinding wheel speed, workpiece speed, and grinding depth on the residual stress on the workpiece surface, and to understand the possible causes of residual stress during grinding.

This study explores the deposition of indium tungsten oxide (IWO) thin films on glass substrates using sputtering techniques, with the aim of developing photodetectors sensitive to both ultraviolet (UV) and visible light spectra. The films were designed in a metal-semiconductor-metal configuration to enhance electrical conductivity, which is critical for efficient photodetection. This structure achieved a dark-to-light current ratio of 6.23 × 10² and a responsivity of 0.48 A W⁻¹ at a reverse bias of 2 V. Furthermore, when configured as UV photodetectors, the IWO films demonstrated significant improvement, achieving a dark-to-light current ratio of 1.32 × 10⁴ under the same bias conditions. The photodetectors exhibited a detectivity (D*) of 2.18 × 10¹⁰ cm·Hz^0.5·W⁻¹ and a noise equivalent power (NEP) of 6.88 × 10⁻¹⁰ W. These findings highlight the potential of IWO to improve photodetector performance across different light spectra, reinforcing its viability for cost-effective integration into advanced optoelectronic devices.