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Solar Markets in the 21st Century
Published in Anco S. Blazev, Solar Technologies for the 21st Century, 2021
Manufacturers typically use some variation of the so-called Czochralski process, in which a seed crystal is introduced to a silicon melt and slowly withdrawn to generate a long mass of monocrystalline silicon.
First-Generation Solar Cells
Published in Denise Wilson, Wearable Solar Cell Systems, 2019
Of all the downsides of monocrystalline silicon for use in wearable solar cell systems, the most important is likely to be the cost. Monocrystalline silicon is the most expensive among silicon solar cells, at about 75 cents per Watt (of power production capacity) for stationary modules (Energy Informative 2013).
A Novel Internet of Things Access Architecture of Energy-Efficient Solar Battery Charging System for Mobile Phones
Published in Lavanya Sharma, Pradeep K Garg, From Visual Surveillance to Internet of Things, 2019
Monocrystalline silicon cells (single crystalline cells) are used for charging the equipment through solar cells. They are made from pure silicon. They are proven to be most efficient in terms of performance and space as compared to all other solar cells. Their silicon-ingots shape helps to optimizing the performance. The greatest productivity that can be reproduced in the lab with a monocrystalline silicon cell is 25%.
Micro electrical discharge milling of a monocrystalline silicon complex micro-cavity
Published in Materials and Manufacturing Processes, 2022
Sirui Gong, Han Wang, Chuan Tian, Zhenlong Wang, Yukui Wang
The removal of monocrystalline silicon is mainly divided into thermal erosion and thermal stress removal. According to SEM images, in this case, the electrical erosion of monocrystalline silicon is still mainly manifested as thermal erosion. There are irregular droplet solidification products and a lot of cracks on the surface, and the denatured layer is densely covered with holes and cavities. Spark discharge generates a lot of heat instantly, and the temperature of the workpiece material in the processing area climbed sharply. After the end of spark discharge, the workpiece is cooled rapidly under the action of working fluid. Especially in narrow pulse width discharge, this sudden hot and cold causes a temperature gradient and thermal stress. Microcracks occur when the thermal stress exceeds the tensile strength of the workpiece material. As a hard and brittle material, monocrystalline silicon has low tensile strength and fracture toughness, so it is more prone to microcracks. The main characteristic of thermal stress erosion is the fractures and ejection at the edge of discharge pits. The SEM image shows that there is no fracture notch and broken particles with the current processing parameters. Therefore, the removal of monocrystalline silicon is mainly by thermal erosion in the circumstances.
Supervised subgraph augmented non-negative matrix factorization for interpretable manufacturing time series data analytics
Published in IISE Transactions, 2020
Hongyue Sun, Ran Jin, Yuan Luo
Crystal growth data set. A CZ crystal growth process is widely used for growing monocrystalline silicon ingots (Sun et al., 2016). In this study, time series measurements for 45 ingots (samples) are obtained, a relatively small data set is available since each ingot is expensive and time-consuming to grow. We evaluate the methods by a training data set of 27 samples (17 normal and 10 defective, which account for 60% of the total samples), and a testing data set of 18 samples (11 normal and seven defective, which account for 40% of the total samples) through random partition. The process variables under study include heater power (Power), SP temperature value (SP), pull speed (Pull), and furnace pressure (Pressure), which are selected based on the process control loop, and measured one sample per minute. The variables are the same as in Sun et al. (2016) to ensure fair comparison. To characterize the differences in normal and defective samples, we generate a normal reference curve for each process variable based on the average of normal samples in the training data set. The time series are subtracted by the reference curves, resulting in the difference (from normal reference) curves. Based on engineering knowledge, there is typically a 2- to 3-hour delay in the defect detection. Therefore, a 3-hour window (i.e., 180 measurement points) of the difference curve prior to defect detection is extracted in defective samples. A 3-hour window of the difference curves prior to the mean of defect detection time is extracted in normal samples to match defective samples.
Methods of extracting silica and silicon from agricultural waste ashes and application of the produced silicon in solar cells: a mini-review
Published in International Journal of Sustainable Engineering, 2021
Fortunate Farirai, Maxwell Ozonoh, Thomas Chinedu Aniokete, Orevaoghene Eterigho-Ikelegbe, Mathew Mupa, Benson Zeyi, Michael Olawale Daramola
The most common solar cell technologies are monocrystalline, polycrystalline and amorphous. Monocrystalline silicon cells are produced from pure silicon (single crystal) wafers. The wafer substrates are cut from column ingots grown by the Czochralski (CZ) process (Goetzberger, Hebling, and Schock 2003; Miles 2006). Single-crystal solar cells are cut from pieces of unbroken silicon crystals. The crystals are shaped as cylinders and sliced into circular disks. These slices can be cut into other shapes such as rectangular or square to optimise the space to be occupied by cells on the module.