Minimum entropy principle-based solar cell operation without a pn-junction and a thin CdS layer to extract the holes from the emitter

2016 ◽  
Vol 120 (16) ◽  
pp. 165701
Author(s):  
Karl W. Böer
Keyword(s):  
Solar Cell ◽  
Minimum Entropy ◽  
Pn Junction ◽  
Entropy Principle

scholarly journals Neuro-Fuzzy Transformation with Minimize Entropy Principle to Create New Features for Particulate Matter Prediction

2021 ◽  
Vol 11 (14) ◽  
pp. 6590
Author(s):  
Krittakom Srijiranon ◽  
Narissara Eiamkanitchat
Keyword(s):  
Particulate Matter ◽  
Fuzzy Model ◽  
Original Data ◽  
Northern Region ◽  
National Standard ◽  
Minimum Entropy ◽  
Fuzzy Transformation ◽  
Neuro Fuzzy ◽  
Proposed Model ◽  
Entropy Principle

Air pollution is a major global issue. In Thailand, this issue continues to increase every year, similar to other countries, especially during the dry season in the northern region. In this period, particulate matter with aerodynamic diameters smaller than 10 and 2.5 micrometers, known as PM10 and PM2.5, are important pollutants, most of which exceed the national standard levels, the so-called Thailand air quality index (T-AQI). Therefore, this study created a prediction model to classify T-AQI calculated from both types of PM. The neuro-fuzzy model with a minimum entropy principle model is proposed to transform the original data into new informative features. The processes in this model are able to discover appropriate separation points of the trapezoidal membership function by applying the minimum entropy principle. The membership value of the fuzzy section is then passed to the neural section to create a new data feature, the PM level, for each hour of the day. Finally, as an analytical process to obtain new knowledge, predictive models are created using new data features for better classification results. Various experiments were utilized to find an appropriate structure with high prediction accuracy. The results of the proposed model were favorable for predicting both types of PM up to three hours in advance. The proposed model can help people who are planning short-term outdoor activities.

pn Junction depth impact on short circuit current of solar cell

Solar Energy ◽  
2009 ◽  
Vol 83 (9) ◽  
pp. 1629-1633 ◽  
Author(s):  
F. Jahanshah ◽  
K. Sopian ◽  
Y. Othman ◽  
H.R. Fallah
Keyword(s):  
Solar Cell ◽  
Short Circuit ◽  
Short Circuit Current ◽  
Junction Depth ◽  
Pn Junction

Grain Boundary Shunt Currents Across a pn Junction

1981 ◽  
Vol 5 ◽  
Author(s):  
S. Roy Morrison
Keyword(s):  
Solar Cell ◽  
Grain Boundary ◽  
Grain Boundaries ◽  
Pn Junction

ABSTRACTThe effect on the diode characteristics when a conducting grain boundary intersects a pn junction is analyzed. The possibilities of conducting grain boundaries are related to the levels associated with precipitates at the grain boundary. The effect of the grain boundary on the diode characteristics is found particularly degrading when donor impurities precipitate in the n region while simultaneously acceptor impurities precipitate in the p region. Both solar cell characteristics and the dark diode characteristics are analyzed.

A New Knowledge Discovery Model for Extracting Diagnosis Rules of Manufacturing Process

2006 ◽  
Vol 505-507 ◽  
pp. 889-894
Author(s):  
Ying Chieh Tsai ◽  
Ching Hsue Cheng ◽  
Jing Rong Chang
Keyword(s):  
Knowledge Discovery ◽  
Manufacturing Process ◽  
Conveyor Belt ◽  
Membership Functions ◽  
Minimum Entropy ◽  
Manufacturing Line ◽  
Proposed Model ◽  
New Knowledge ◽  
Entropy Principle ◽  
Correlation Based Feature Selection

The knowledge obtained from the experience of monitoring manufacturing process is critical to guarantee good products produced at the end of manufacturing line. Recently, many methods have been developed for the described purpose above. In this paper, a new knowledge discovery model based on soft computing is proposed. The proposed model contains a new algorithm Modified Correlation-based Feature Selection (MCFS), a new algorithm Modified Minimum Entropy Principle Algorithm (MMEPA), and Variable Precision Rough Set Model (VP-model). After conducting a real case of monitoring the process of manufacturing industrial conveyor belt, some advantages of the proposed model are that (1) MCFS can quickly identifying and screening irrelevant, redundant, and noisy features for data reduction; (2) MMEPA can objectively construct membership functions of fuzzy sets for fuzzifing the reduced dataset; (3) VP-model can extract causal relationship rules for controlling product quality; (4) Extracted rules by the proposed knowledge discovery model are easily understood and interpretable.

Investigation of Rbx(MA)1−xPbI3(x = 0, 0.1, 0.3, 0.5, 0.75, 1) perovskites as a potential source of P- and N-type materials for PN-junction solar cell

2019 ◽  
Vol 125 (4) ◽  
Author(s):  
Abida Saleem ◽  
Muhammad Imran ◽  
Muhammad Arshad ◽  
Afzal H. Kamboh ◽  
Nawazish A. Khan ◽  
...  
Keyword(s):  
Solar Cell ◽  
Junction Solar Cell ◽  
Potential Source ◽  
Pn Junction

Optimization of the InGaP Top ${\it pn}$ Junction for a New Triple Tandem Solar Cell Design

2017 ◽  
Author(s):  
Victor de Rezende Cunha ◽  
Rudy Kawabata ◽  
Luciana Dornelas ◽  
Mauricio Pires ◽  
Patricia de Souza
Keyword(s):  
Solar Cell ◽  
Cell Design ◽  
Tandem Solar Cell ◽  
Pn Junction

scholarly journals An Entropic Scheme for an Angular Moment Model for the Classical Fokker-Planck-Landau Equation of Electrons

2014 ◽  
Vol 15 (2) ◽  
pp. 422-450 ◽  
Author(s):  
Jessy Mallet ◽  
Stéphane Brull ◽  
Bruno Dubroca
Keyword(s):  
Discrete Model ◽  
Landau Equation ◽  
Numerical Test ◽  
Test Cases ◽  
Minimum Entropy ◽  
Fundamental Properties ◽  
Direct Numerical Solution ◽  
Entropy Principle ◽  
The Moment ◽  
Fokker Planck

AbstractIn plasma physics domain, the electron transport is described with the Fokker-Planck-Landau equation. The direct numerical solution of the kinetic equation is usually intractable due to the large number of independent variables. That is why we propose in this paper a new model whose derivation is based on an angular closure in the phase space and retains only the energy of particles as kinetic dimension. To find a solution compatible with physics conditions, the closure of the moment system is obtained under a minimum entropy principle. This model is proved to satisfy the fundamental properties like a H theorem. Moreover an entropic discretization in the velocity variable is proposed on the semi-discrete model. Finally, we validate on numerical test cases the fundamental properties of the full discrete model.

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