Solar Cell Manufacturing Process Research Articles

A Horizontal Double‐Sided Copper Metallization Technology Designed for Solar Cell Mass‐Production

ABSTRACTIn the international photovoltaic market, the “carbon footprint” label has received great attention, and low‐carbon footprint products are widely popular. Compared with metallic silver, copper has the characteristics of low carbon emissions and low cost, which can effectively reduce the carbon footprint. Based on this, this article reports a horizontal double‐sided copper metallization technology. This technology can not only metalize the front and back sides of various types of silicon solar cells at the same time but also has fast speed, good uniformity, and simple process, making it suitable for the industrial mass production of solar cells. This article describes the structure and manufacturing process of TOPCon solar cells patterned with an ultrashort pulse laser and metalized using this novel horizontal double‐sided copper metallization technology. In this batch, average efficiency reached above 26%.

Ultrathin Self-Assembled Monolayer for Effective Silicon Solar Cell Passivation.

Passivation technology is crucial for reducing interface defects and impacting the performance of crystalline silicon (c-Si) solar cells. Concurrently, maintaining a thin passivation layer is essential for ensuring efficient carrier transport. With an ultrathin passivated contact structure, both Silicon Heterojunction (SHJ) cells and Tunnel Oxide Passivated Contact (TOPCon) solar cells achieve an efficiency surpassing 26%. To reduce production costs and simplify solar cell manufacturing processes, the rapid development of organic material passivation technology has emerged. However, its widespread industrial production is hindered by environmental safety concerns, such as strong acid corrosion and biological and ecological safety issues. Here, we discovered a low-cost self-assembled monolayer (SAM) hole-selective transport material known as 2PACz ([2-(9H-carbazol-9-yl) ethyl] phosphonic acid) with phosphate groups to form c-Si solar cells for the first time. The ultrathin film of 2PACz with phosphate groups can establish strong and stable P-O-Si bonds on the silicon surface. Meanwhile, like 2PACz, a uniform ultrathin film with a carbazole function group can offer electron-localizing and thus hole-selective properties, which provides ideas for studying dopant-free silicon solar cells. As a result of such interfacial passivation engineering, it plays an important role in repairing porous structures, such as pyramid-textured silicon surfaces, and cutting losses during the commercialization of c-Si solar cells. Crucially, this advancement offers insights for the development of new high-efficiency ultrathin film passivation methods in the postsilicon era.

Research on multi-defects classification detection method for solar cells based on deep learning.

Solar cells are playing a significant role in aerospace equipment. In view of the surface defect characteristics in the manufacturing process of solar cells, the common surface defects are divided into three categories, which include difficult-detecting defects (mismatch), general defects (bubble, glass-crack and cell-crack) and easy-detecting defects (glass-upside-down). Corresponding to different types of defects, the deep learning model with different optimization methods and a classification detection method based on multi-models fusion are proposed in the paper. In the proposed model, in order to solve the mismatch problem between the default anchor boxes size of YOLOv5s model and the extreme scale of the battery mismatch defect label boxes, the K-means algorithm was adopted to re-cluster the dedicated anchor boxes for the mismatch defect label boxes. In order to improve the comprehensive detection accuracy of YOLOv5s model for the general defects, the YOLOv5s model was also improved by the methods of image preprocessing, anchor box improving and detection head replacing. In order to ensure the recognition accuracy and improve the detection speed for easy-detecting defects, the lightweight classification network MobileNetV2 was also used to classify the cells with glass-upside-down defects. The experimental results show that the proposed optimization model and classification detection method can significantly improve the defect detection precision. Respectively, the detection precision for mismatch, bubble, glass-crack and cell-crack defects are up to 95.64%, 91.8%, 93.1% and 98.0%. By using lightweight model to train the glass-upside-down defect dataset, the average classification accuracy reaches 100% and the detection speed reaches 13.29 frames per second. The comparison experiments show that the proposed model has a great improvement in detection accuracy compared with the original model, and the defect detection speed of lightweight classification network is improved more obviously, which confirms the effectiveness of the proposed optimization model and the multi-defect classification detection method for solar cells defect detection.

3D printing and solar cell fabrication methods: A review of challenges, opportunities, and future prospects

In the solar cell industry, three-dimensional (3D) printing technology is currently being tested in an effort to address the various problems related to the fabrication of solar cells. 3D printing has the ability to achieve coating uniformity across large areas, excellent material utilization with little waste, and the flexibility to incorporate roll-to-roll (R2R) and sheet-to-sheet (S2S) systems. The main aim of this review is to highlight the key gaps in current solar cell manufacturing processes and to point out the use of 3D printing technology as an alternative in solar cell fabrication. The present paper provides a comprehensive review of solar cell fabrication methods, with a focus on 3D printing technology applications in solar cell fabrication. Drawbacks with the conventional solar cell manufacturing systems, solar cell development challenges, and future prospects are also highlighted. The paper concludes that 3D printing technology can be a viable candidate to fabricate solution-processable solar cells over a wide area with excellent material utilization and good flexibility. The study might lead to more research and investigations into 3D printing technologies' applications in the solar cell industry.

Modeling and experimental investigation of monocrystalline silicon wafer cut by diamond wire saw

Diamond wire sawing is one of the key technologies in solar cell manufacturing process and semiconductor chip manufacturing process. The thinned of silicon wafer has become a development trend of semiconductor industry, and the reduction of silicon wafer thickness can improve the material utilization and reduce the manufacturing cost. Therefore, the minimum thickness analytical model of diamond wire saw cutting monocrystalline silicon wafer is proposed in this paper to study the processing mechanism of minimum thickness of monocrystalline silicon wafer. Firstly, based on the Kirchhoff’s thin plate theory, the theoretical equation of the maximum internal stress of single silicon wafer and the sawing thickness of the silicon wafer is derived from the sawing force model. Combined with the Mohr’s strength theory, the analytical model of minimum sawing thickness of monocrystalline silicon wafer is established. Then, the analytical model is verified by the finite element simulation. The average error between the simulation results and the calculation results of the analytical model about the minimum sawing thickness of silicon wafer is 9%. Finally, the monocrystalline silicon sawing verification experiments are conducted under some groups of processing conditions. The experimental results show that the minimum sawing thickness of the silicon wafer decreases with the increasing axial speed of the wire saw, increases with the increase of the feed rate of the wire saw, and decreases first and then increases with workpiece speed becoming large. The average error of the experimental results and the calculation results of the analytical model of the wafer minimum sawing thickness is 7.4%, which verifies corrections of the analytical model.

Thin Films Characterization and Study of N749-Black Dye for Photovoltaic Applications

This paper reports on the fabrication and photovoltaic characteristics of a heterojunction solar cell based on an organic small molecular semiconductor, N-749 black dye (N749-BD). To investigate the photovoltaic characteristics of N749-BD, an ITO/PEDOT:PSS/N749-BD/Ag device is prepared by spin casting a 100 ± 5-nm thin film of N749-BD on the poly(3,4, ethylene dioxythiophene):polystyrene sulfonate (PEDOT:PSS) film, which acts as buffer/hole transport layer (HTL) and indium tin oxide (ITO) is employed as a transparent conducting substrate. Under standard testing conditions (STC), i.e., 25 °C, 1.5 AM global and 100 mW/cm2 irradiation, the photovoltaic parameters of the device, such as fill factor (FF) and power conversion efficiency (PCE), are found to be 0.65 and 3.8% ± 0.5%, respectively. Current-voltage (I–V) characteristics of the device are also studied in dark conditions to measure reverse saturation current (I0), series resistance at the interface, rectification ratio (RR), barrier height (ϕb) and ideality factor (n). Optical bandgaps (Eg) of N749-BD thin film are found by applying Tauc’s plot on its ultraviolet-visible (UV-Vis) spectrum, which are measured to be 1.68, 2.67, 3.52 and 4.16 eV. External quantum efficiency (EQE) measurements of the fabricated device are studied, which demonstrate large value of EQE ≈ 12.89%, with peak intensity at 626 nm. Bond dynamics and compositional analysis of N749-BD is carried out via Fourier transformed infrared (FTIR) spectroscopy. Morphology of the thin film of N749-BD on quartz glass are investigated via scanning electron microscopy (SEM) with in-situ energy dispersive X-ray (EDX) spectroscopy which exhibits random distribution of N749-BD grains across the surface with nearly uniform grain sizes and shapes. The larger values of FF, PCE and EQE of ITO/PEDOT:PSS/N749-BD/Ag device suggests the potential of N749-BD to be utilized in low cost, simple manufacturing process and high performance of solar cells.

Life cycle assessment of organic solar cells and perovskite solar cells with graphene transparent electrodes

Indium Tin Oxide as the transparent electrode in solar cells has shown a bottleneck due to the use of scarce mental. The graphene transparent electrode (GTE) opens a sustainable route for third-generation solar cells. This work investigates the environmental performance of flexible organic solar cells and perovskite solar cells with GTEs by life cycle assessment. The manufacturing process of solar cells is developed including detailed production procedures of GTEs. The comprehensive life cycle inventories (LCIs) are provided for two kinds of solar cells. According to LCIs, life cycle impact assessment is carried on to unmask various impact categories in their full life cycles. Sensitivity analyses using the Monte Carlo method are conducted to quantify the uncertainty of final environmental impacts. The results prove that perovskite solar cells with GTEs have the shortest Energy Payback Time. A longer lifespan of both solar cells should be pursued to meet the requirement of sustainable manufacture.

Fluoride pollutants removal from industrial wastewater

BackgroundThe main object of the present study is the industrial wastewater effluent treatment resulting from a solar cell manufacturing process, which is a Joint Egyptian Chinese Renewable Energy laboratory, in Sohag Governorate. Fluoric and hydrochloric acids are the main pollutants causing a pH of 1 to 3. The effluent is neutralized by the addition of both potassium hydroxide and calcium hydroxide to permit the precipitation of the resulting sparingly soluble calcium fluoride. The chlorides are partially precipitated as calcium chloride, and the further addition of hydrated aluminum sulfate is used to precipitate the remaining extra chloride as an insoluble complex to reach the allowable chloride concentration in the treated effluent. Set of experiments at bench and pilot scales were run to achieve the optimum conditions for defluorination and dichlorination taking into consideration not exceeding the allowable ranges of pollutants as soluble salts in the final effluent.ResultsExperimental results showed that the performance of a pilot scale was satisfactory in fluorides, chlorides, and dissolved solids by 97.64, 78.85, and 79.4% removal, respectively. Based on these results a full-scale industrial treatment unit was designed for construction and operation as a treatment unit for industrial wastewater contaminated with fluorides as main pollutant.ConclusionsThe recommended treatment procedure succeeded in the removal of fluorides and chlorides as main contaminants in the effluent which permit the use of treated water in the irrigation of non-edible plants, according to Egyptian Code No. (501/2015).

A Study on the Detection of Defects in Solar Cells and Modules in EL Images based on Artificial Intelligence

Currently, investment is being made in renewable energy for the transition to a low-carbon economy and society, and interest in solar energy is also increasing. In addition to the technological development of solar cells and photovoltaic (PV) modules, research in the field of convergence with artificial intelligence technology is being actively conducted. Defects occurring in the manufacturing process of solar cells and modules can be detected through electroluminescence (EL) measurements. In this study, we propose an artificial intelligence technology that can automatically detect defects in cells and modules in real time using EL image data of solar cells and modules in the manufacturing process. For EL defect detection, we propose an algorithm with high suitability in terms of speed and accuracy by applying deep learning-based object detection models and comparing and evaluating detection performance. In the case of the YOLO (you only look once) algorithm, which belongs to a one-step detector, it learns In the case of the YOLO (you only look once) algorithm, which belongs to a one-step detector, it learns through an optimization process to find information about the defect and the location information of the corresponding failure in the form of a bounding box, and then detects the failure based on this information. The introduction of a deep learning-based defect detection model in the manufacturing process is expected to reduce the time required for defect detection by solar cell and PV module manufacturers and contribute to productivity improvement.

Study on the subsurface damage depth of monocrystalline silicon in ultrasonic vibration assisted diamond wire sawing

Diamond wire sawing is one of the key technologies in solar cell manufacturing process and semiconductor chip manufacturing process. The subsurface damage depth (SSD) affects the quality of machined surface in diamond wire sawing, which must be evaluated. In this paper, a mathematical model of the SSD in monocrystalline silicon wafers induced by ultrasonic vibration assisted diamond wire sawing (UAWS) was proposed. In this model, the input is the depth and deflection angle of the median crack, the depth and length of the lateral crack, and ultrasonic vibration, and the output is the residual SSD on the chip. According to the model, the variation of SSD with position angle of diamond abrasives under ultrasonic vibration was analyzed on the cross section of wire saw, and the influence of shielding effect about median crack on SSD under ultrasonic vibration was analyzed later. Then, a finite element model (FEM) of diamond wire sawing monocrystalline silicon was established by ABAQUS,and the SSD under different slicing parameters was simulated. Finally, the interface bonding method was used to measure the SSD of monocrystalline silicon wafer. The experimental results showed that the SSD increases with the increase of the wire saw feed rate, and decreases with the increase of the wire saw speed and the workpiece rotation speed. The SSD in wafer sliced by UAWS is 18.95% on average lower than that in wafer sliced by conventional wire sawing (CWS). The maximum error between theoretical of mathematical model and experimental values is 15.9%, which verifies the validity of the mathematical model.

Performance-Enhancing Approaches for PEDOT:PSS-Si Hybrid Solar Cells.

The emerging energy crisis has focused significant worldwide attention on solar cells. Although crystalline silicon solar cells are currently widely used, their high cost limits the development of solar power generation. Consequently, hybrid solar cells are becoming increasingly important, especially organic-Si hybrid solar cells (HSCs). Organic-Si HSCs combine a mature technology and high efficiency with the low-temperature manufacturing process and tunable optoelectronic properties of organic solar cells. The organic material can be P3HT, carbon nanotubes, graphene, and PEDOT:PSS. Here we review the performance of PEDOT:PSS/Si HSCs and methods for improving their efficiency, such as PEDOT:PSS modification, optimization of the trapping effect, passivation of the silicon surface, addition of an interface layer, improvement of a back contact, and optimization of the metal top electrode. This Review should help fill the gap in this area and provide perspectives for the future development of the PEDOT:PSS/Si HSCs.

Effect of the Heat Treatment on the Microstructure and Morphology of Cigs Thin Films Prepared by RF Magnetron Sputtering at Room Temperature

This work investigates the microstructural and morphological changes on CIGS thin films submitted to a post-deposition heat treatment. The CIGS 1000 nm-thick films were deposited at room temperature by RF magnetron sputtering onto glass substrates covered with molybdenum films. After deposition, the samples were submitted to a heat treatment, with temperatures ranging from 450 to 575 oC. The treatment was also carried out under a selenium atmosphere (selenization), from 400 to 500 oC. Morphological analyzes showed that the as-deposited film was uniform and amorphous. When the treatment was carried out without selenization, the crystallization occurred at or above 450 oC, and the grains remained nanosized. However, high temperatures led to the formation of discontinuities on the film surface and the formation of extra phases, as confirmed by X-ray diffraction data. The crystallization of the films treated under selenium atmosphere took place at lower temperatures. However, above 450 °C the film surface was discontinuous, with a lot of holes, whose amount increased with the temperature, showing that the selenization process was very aggressive. X-ray diffraction analyses showed that the extra phases were eliminated during selenization and the films had a preferential orientation along [112] direction. The results indicate that in the manufacturing process of solar cells, CIGS films deposited at room temperature should be submitted to a heat treatment carried out at 450 °C (without selenization) or 400 °C (with selenization).

The Use of Lasers at Various Stages of the Manufacturing Process of Solar Cells Based on Crystalline Silicon

The purpose of this chapter of the book is to present knowledge on the use of laser technology in silicon photovoltaic cell manufacturing processes. Particular consideration was given to the technique of using a disk laser to cut the edges of silicon wafers together with the recognition of the flow of laser micromachining on the quality of cut edges to obtain their minimal deformation. The second topic described is the method of producing point contacts employing laser radiation between a layer of vaporised aluminium and crystalline silicon using the Nd:YAG laser. The results illustrating the impact of the structure and parameters of point contact for a given laser radiation energy on basic electrical parameters for complete, prototype solar cells are included. The chapter in the book provides an overview of the literature on the above topics and presents selected results of experimental works carried out by the authors. The motive for its publication is the need to present selected results of own research carried out in the Welding Department cooperating for many years with the Institute of Engineering and Biomedical Materials (IMIiB) of the Silesian University of Technology and the Institute of Metallurgy and Materials Engineering (IMIM) of the Polish Academy of Sciences in Cracow.

Structural stability and optoelectronic properties of tetragonal MAPbI3 under strain

In recent years, organic–inorganic hybrid perovskites have attracted wide attention due to their excellent optoelectronic properties in the application of optoelectronic devices. In the manufacturing process of perovskite solar cells, perovskite films inevitably have residual stress caused by non-stoichiometry components and the external load. However, their effects on the structural stability and photovoltaic performance of perovskite solar cells are still not clear. In this work, we investigated the effects of external strain on the structural stability and optoelectronic properties of tetragonal MAPbI3 by using the first-principles calculations. We found that the migration barrier of I− ion increases in the presence of compressive strain and decreases with tensile strain, indicating that the compressive strain can enhance the structural stability of halide perovskites. In addition, the light absorption and electronic properties of MAPbI3 under compressive strain are also improved. The variations of the band gap under triaxial and biaxial strains are consistent within a certain range of strain, resulting from the fact that the band edge positions are mainly influenced by the Pb–I bond in the equatorial plane. Our results provide useful guidance for realizing the commercial applications of MAPbI3-based perovskite solar cells.

Improved stability and efficiency of CdSe/Sb2Se3 thin-film solar cells

Quasi-one-dimensional van der Waals Sb2Se3 compound is a promising absorber material with desired optical properties and has theoretical potential to achieve high power conversion efficiency (PCE) of ∼30%. Here, we report a new window layer, i.e., sputtered CdSe, which can enhance the Sb2Se3 device stability during light soaking and improve the photocurrent collection. Compared to the widely used CdS window layer, CdSe can suppress the interfacial diffusion between the window layer and the Sb2Se3 film, thereby reducing interfacial recombination sites. The dominant degradation mechanism in the CdS/Sb2Se3 devices is found to be the S diffusion instead of the Cd diffusion, as CdSe/Sb2Se3 devices did not show degradation during the 85 °C 120 h 1-Sun light soaking with similar Cd diffusion. Meanwhile, the enhanced photocurrent and reduced series resistivity in the CdSe/Sb2Se3 solar cells lead to an improved PCE of 4.5% with a glass/FTO/CdSe/Sb2Se3/graphite cell architecture. The obtained results suggest that CdSe can be employed as a window layer in the thin-film solar cells made of stable and efficient Sb2Se3-like quasi-one-dimensional van der Waals materials, providing a cost-effective way to integrate into the traditional thin-film solar cell manufacturing process.

Development of Novel Solar Cell Micro Crack Detection Technique

This paper presents the development of a solar cell inspection manufacturing execution system (MES). The main objective of the MES is to detect micro cracks in the manufacturing process of solar cells. Hence, to accept or reject a solar cell during the assembling unit. The proposed MES consists of three stages, at first stage, the inspection system will be placed on the manufacturing process of the solar cell. After the solar cell has been manufactured, it will pass under an in-line electroluminescent (EL) system. At this stage, an OR operation between a healthy/no-crack and the inspected solar cell image will be obtained. This OR operation will generate a better calibration for the cracks in the photovoltaic solar cell image. The final calibrated image presents a high quality, and low noise structure, thus easier to identify the micro cracks size, location, and orientation. The last stage evaluates the calibrated image using the plot profile which is well known as the distance in pixels versus the gray level of the image. The plot profile will indicate whether to accept or reject the solar cell, 10% confidence interval for the gray level was used to identify the upper and lower detection limits.

Structural and microstructural studies on SiC-SiO2 ceramic composites

In this study, SiC ceramic substrates were prepared with 99.5% silicon carbide powders which were came from waste silicon mud during the manufacturing process of solar cells. It is found that a SiO2 layer with 50 nm in thickness is present on the SiC surface by TEM analysis. The relative density of the SiC samples is too low after sintering to 1550 °C, which is only 60% of the relative density. It will cause a poor mechanical strength at lower relative density of samples. To improve the density of SiC samples, an amorphous SiO2 was introduced as a sintering aid. Different amounts of amorphous SiO2 from 1 wt% to 5 wt% were then added into SiC powders and made into discs. We call this modified-SiC. These samples were sintered at high temperatures from 1350 °C to 1500 °C. The SiO2 addition and sintering temperature effects on the density, phase evolution, microstructure and mechanical properties of modified-SiC were investigated. A Y-ZrO2 layer was then coated onto the SiC disc. Sintering temperature can be efficiently decreased and the mismatch between ZrO2 coatings and SiC disc can be reduced when SiO2 is added into SiC. It is found that SiC powders with 3 wt% SiO2 addition shows the most optimum outcome with higher density and stronger mechanical properties.

A Condition Change Detection Method for Solar Conversion Efficiency in Solar Cell Manufacturing Processes

A solar cell manufacturing process typically has multiple, serial fabrication stages. In general, there are limited quality inspection and control points along the multiple fabrication stages, resulting in inconsistent product quality at the final stage. The existing studies on solar cell manufacturing focus on offline quality monitoring after completion of all manufacturing stages. Thus, an effective in-process method of detecting changes in key stages in terms of product quality is necessary to mitigate the effect of the quality fluctuation. This paper proposes an in-process method of detecting the process changes in terms of product quality by studying multichannel sensing signals collected in the epitaxy stage. This stage is an important stage of material layer formation and considerably influences the solar conversion efficiency of the final product. Interpretable geometric features are obtained by considering the process knowledge for each channel of sensing data. A decision-level data fusion method is further proposed to integrate the changes detected from each sensing signal. The proposed method is demonstrated via a real case from solar cell manufacturing processes.

Factor Optimization in the Manufacturing Process of Dye-Sensitized Solar Cells Based on Naturally Extracted Dye from a Maqui and Blackberry Mixture (Aristotelia Chilensis and Rubus Glaucus)

Optical and electrical properties of mini modules of dye-sensitized solar cells (DSSCs) using anthocyanin-enriched extracts from maqui (Aristotelia Chilensis) and blackberry (Rubus Glaucus) have been investigated. Anthocyanins pigments are a group of purple, red, blue and violet water-soluble polyphenolic components widely distributed in berry fruits, and maqui and blackberry are particularly rich sources. The main objective of this study was to analyze the factors involved in the performance of a DSSC. For this purpose, the experimental design considered the variation in the anthocyanin concentration, impregnation time and extract type through the Taguchi methodology with an orthogonal array L4(23) methodology that contributed to reduce cost, time and to obtain reliable statistical results. Then, the effect of these factors was identified by ANOVA, determining the incidence on the efficiency of the DSSC. As a result of the experimental program, the effect on efficiency by anthocyanin concentration was 43.90%, impregnation time 4.55% and extract type 51.22%. The variable extract type contributed the most to the performance, followed by anthocyanin concentration. However, the impregnation time had no effect on the efficiency of the DSSC with a maqui (Aristotelia Chilensis) and blackberry (Rubus glaucus) mixture. With this research, it is possible to identify the influence of different manufacturing factors that affect the efficiency of the DSSC with natural dyes, such as maqui and blackberry mixtures. Through this research, it is established that the incorporation of maqui to the mixture enhances the efficiency of the DSSCs. Maqui as a dye improves the optical absorption properties of the material by increasing the peak of absorption range. This study promotes new research in DSSC with mixtures of natural dyes.

Optimizing the Organic Solar Cell Manufacturing Process by Means of AFM Measurements and Neural Networks

In this paper we devise a neural-network-based model to improve the production workflow of organic solar cells (OSCs). The investigated neural model is used to reckon the relation between the OSC’s generated power and several device’s properties such as the geometrical parameters and the active layers thicknesses. Such measurements were collected during an experimental campaign conducted on 80 devices. The collected data suggest that the maximum generated power depends on the active layer thickness. The mathematical model of such a relation has been determined by using a feedforward neural network (FFNN) architecture as a universal function approximator. The performed simulations show good agreement between simulated and experimental data with an overall error of about 9%. The obtained results demonstrate that the use of a neural model can be useful to improve the OSC manufacturing processes.