Fabrication and Manufacturing Process of Solar Cell: Part II

Green Energy ◽  
2020 ◽  
pp. 39-65
Author(s):  
Prabhansu ◽  
Nayan Kumar
Keyword(s):  
Solar Cell ◽  
Manufacturing Process

scholarly journals Pengaruh Variasi Jarak Sumber Cahaya Terhadap Kinerja Dye Sensitized Solar Cell (DSSC) Menggunakan Ekstrak Antosianin Bunga Rossela

2020 ◽  
Vol 1 (2) ◽  
pp. 22-23
Author(s):  
Rafika Andari
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
Light Source ◽  
Manufacturing Process ◽  
Low Cost ◽  
Dye Sensitized Solar Cell ◽  
Light Sources ◽  
Halogen Lamp ◽  
Cell Efficiency ◽  
Dye Sensitized

Abstrak Objektif. Penggunaan sel surya silikon saat ini masih tergolong mahal serta juga menggunakan bahan kimia yang berbahaya pada proses pembuatannya. Oleh karena itu perlu dikembangkan sel surya alternatif yang berbahan dasar murah dan ramah lingkungan, seperti DSSC (Dye Sensitized Solar Cell). Penggunaan DSSC sangat bagus dikembangkan dikarenakan proses pembuatan yang sederhana, biaya murah serta berbahan dasar organik.. Berdasarkan hal tersebut, perlu adanya pengembangan DSSC menggunakan dye dari ekstrak antosianin dari bahan alam yang banyak terdapat dilingkungan.  Material and Metode. Penelitian ini bertujuan mengetahui karakteristik DSSC menggunakan ekstrak bunga rosella dengan variasi jarak sumber cahaya terhadap DSSC. Karakteristik yang diukur adalah nilai arus dan tegangan serta efisiensi sel.  Sebagai sumber cahaya digunakan adalah lampu halogen 150 watt. Sumber cahaya diletakkan pada jarak 10 cm, 20 cm dan 30 cm. Hasil. Karakterisasi nilai tegangan dan arus DSSC menggunakan cahaya lampu halogen dengan jarak 10 cm terhadap DSSC lebih besar dibandingkan dengan jarak 20 cm dan 30 cm. Hasil pengujian menunjukkan bahwa efisiensi sel yang berjarak 10 cm terhadap DSSC merupakan hasil terbaik arus maksimal (Imax) 0,08 mA, tegangan maksimal (Vmax) 121,7 mV. Kesimpulan. Kinerja dari DSSC dipengaruhi oleh jarak sumber cahaya yang digunakan terhadap sel. Perbedaan nilai efisiensi ini disebabkan oleh besar intensitas cahaya terhadap sel, semakin dekat jarak sumber cahaya semakin besar intensitas cahaya sehingga menghasilkan nilai efisiensi yang besar. Abstrack Objective. The use of silicon solar cells is still relatively expensive and also uses harmful chemicals in the manufacturing process. Therefore it is necessary to develop alternative solar cells that are based on inexpensive and environmentally friendly, such as DSSC (Dye-Sensitized Solar Cell). The use of DSSC is very well prepared because of the simple manufacturing process, low cost, and organic-based. Based on this, the development of DSSC requires the use of dye from anthocyanin extracts from natural materials that are widely available in the environment. Materials and Methods. This study aims to determine the characteristics of DSSC using rosella flower extracts with variations in the distance of the light source to DSSC. The trademarks measured are current and voltage values ​​and cell efficiency. As the light source used is a 150-watt halogen lamp. Light sources are placed at a distance of 10 cm, 20 cm, and 30 cm. Results. Characterization of DSSC voltage and current values ​​using a halogen lamp with a distance of 10 cm to DSSC is more significant than a length of 20 cm and 30 cm. The test results show that the efficiency of cells within 10 cm of DSSC is the best result of maximum current (Imax) of 0.08 mA, maximum voltage (Vmax) of 121.7 mV. Conclusion. The performance of DSSC is influenced by the distance of the light source used against the cell. This difference in efficiency value is caused by the higher intensity of the light to the battery, the closer the distance of the light source, the higher the depth of the sun to produce an immense efficiency value.

Application of Heuristic Genetic Algorithm for Parameters Optimization of a Solar Cell Manufacturing Process

2013 ◽  
Vol 711 ◽  
pp. 758-762
Author(s):  
Tung Hsu Hou ◽  
Cecilia Lin ◽  
Keng Yu Lin
Keyword(s):  
Genetic Algorithms ◽  
Solar Cell ◽  
Manufacturing Process ◽  
Alternative Energy ◽  
Rapid Development ◽  
Back Propagation ◽  
Parameters Optimization ◽  
Multi Objective ◽  
Cell Manufacturing ◽  
Order Preference

The more rapid development of economy, the more resources demand. The developments of solar and other alternative energy are particularly urgent and important. Diffusion manufacturing processes is core process of a solar cell manufacturing process. The physical and chemical reactions with the corresponding product characteristics are non-linear. The processes cannot be amended effectively depend on engineers experiences. In order to find the optimal process parameters for the silicon solar cell diffusion process, this research proposed an approach which combines several methods: Revised Multi-objective genetic algorithms (RMOGA) and Adaptive Multi-objective genetic algorithms (AMOGA) that integrates back-propagation neural networks (BPN), technique for order preference by similarity to ideal solution (TOPSIS), and genetic algorithms (GA) with the concept of elite sets and local search. The result of this study shows that AMOGA has the best performance to enhance the breadth and depth of the MOGA search, and also quickly convergent to the high quality and quantity optimal solutions. That provides decision-makers more diverse choices.

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

Energies ◽  
2018 ◽  
Vol 11 (5) ◽  
pp. 1221 ◽  
Author(s):  
Giacomo Capizzi ◽  
Grazia Lo Sciuto ◽  
Christian Napoli ◽  
Rafi Shikler ◽  
Marcin Woźniak
Keyword(s):  
Neural Networks ◽  
Solar Cell ◽  
Manufacturing Process ◽  
Organic Solar Cell ◽  
Cell Manufacturing

Identifying groups of airborne particles by ordination

1994 ◽  
Vol 52 ◽  
pp. 856-857
Author(s):  
M. Shlepr ◽  
C. M. Vicroy
Keyword(s):  
Elemental Analysis ◽  
Energy Dispersive Spectroscopy ◽  
Manufacturing Process ◽  
Spatial Representation ◽  
Airborne Particles ◽  
Common Source ◽  
Data Set ◽  
Microelectronics Industry ◽  
Induced Changes ◽  
Source Materials

The microelectronics industry is heavily tasked with minimizing contaminates at all steps of the manufacturing process. Particles are generated by physical and/or chemical fragmentation from a mothersource. The tools and macrovolumes of chemicals used for processing, the environment surrounding the process, and the circuits themselves are all potential particle sources. A first step in eliminating these contaminants is to identify their source. Elemental analysis of the particles often proves useful toward this goal, and energy dispersive spectroscopy (EDS) is a commonly used technique. However, the large variety of source materials and process induced changes in the particles often make it difficult to discern if the particles are from a common source.Ordination is commonly used in ecology to understand community relationships. This technique usespair-wise measures of similarity. Separation of the data set is based on discrimination functions. Theend product is a spatial representation of the data with the distance between points equaling the degree of dissimilarity.

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