AIMC Topic: Solar Energy

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Doping-Induced Charge Localization Suppresses Electron-Hole Recombination in Copper Zinc Tin Sulfide: Quantum Dynamics Combined with Deep Neural Networks Analysis.

The journal of physical chemistry letters Jan 8, 2021
Nonradiative electron-hole recombination constitutes a major route for charge and energy losses in copper zinc tin sulfide (CZTS) solar cells. Using a combination of nonadiabatic (NA) molecular dynamics and deep neural networks (DNN), we demonstrated...
Copper Quantum Theory Neural Networks, Computer Zinc Solar Energy Tin Compounds Electrons Sulfides
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Self-assembled Janus plasmene nanosheets as flexible 2D photocatalysts.

Materials horizons Nov 16, 2020
A leaf is a free-standing photocatalytic system that can effectively harvest solar energy and convert CO and HO into carbohydrates in a continuous manner without the need for regeneration or tedious product extraction steps. Despite encouraging advan...
Catalysis Nanoparticles Hydrophobic and Hydrophilic Interactions Nanostructures Solar Energy
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Micro-cracks detection of solar cells surface via combining short-term and long-term deep features.

Neural networks : the official journal of the International Neural Network Society Apr 18, 2020
The machine vision based methods for micro-cracks detection of solar cells surface have become one of the main research directions with its efficiency and convenience. The existed methods are roughly classified into two categories: current viewing in...
Machine Learning Humans Neural Networks, Computer Time Factors Deep Learning Solar Energy
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Convolutional Neural Networks for the Design and Analysis of Non-Fullerene Acceptors.

Journal of chemical information and modeling Nov 21, 2019
Convolutional neural network (CNN) is employed to construct generative and prediction models for the design and analysis of non-fullerene acceptors (NFAs) in organic solar cells. It is demonstrated that the dilated causal CNN can be trained as a good...
Organic Chemicals Solar Energy Neural Networks, Computer Drug Design Thermodynamics Electric Power Supplies
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Integrated support vector regression and an improved particle swarm optimization-based model for solar radiation prediction.

PloS one May 31, 2019
Solar energy is a major type of renewable energy, and its estimation is important for decision-makers. This study introduces a new prediction model for solar radiation based on support vector regression (SVR) and the improved particle swarm optimizat...
Humidity Sunlight Turkey Solar Energy Forecasting Wind Support Vector Machine Regression Analysis Humans Algorithms
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Predicting the Health Status of an Unmanned Aerial Vehicles Data-Link System Based on a Bayesian Network.

Sensors (Basel, Switzerland) Nov 13, 2018
Unmanned aerial vehicles (UAVs) require data-link system to link ground data terminals to the real-time controls of each UAV. Consequently, the ability to predict the health status of a UAV data-link system is vital for safe and efficient operations....
Aircraft Solar Energy Health Status Robotics Humans Bayes Theorem Remote Sensing Technology
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Hybrid PSO-FLC for dynamic global peak extraction of the partially shaded photovoltaic system.

PloS one Nov 2, 2018
Particle Swarm Optimization (PSO) is widely used in maximum power point tracking (MPPT) of photovoltaic (PV) energy systems. Nevertheless, this technique suffers from two main problems in the case of partial shading conditions (PSCs). The first probl...
Models, Theoretical Fuzzy Logic Solar Energy Computer Simulation Time Factors Algorithms
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PV Analyzer: A Decision Support System for Photovoltaic Solar Cells Libraries.

Molecular informatics Jul 18, 2018
This work describes the integration of several data mining and machine learning tools for researching Photovoltaic (PV) solar cells libraries into a unified workflow embedded within a GUI-supported Decision Support System (DSS), named PV Analyzer. Th...
Machine Learning Software Quantitative Structure-Activity Relationship Solar Energy
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A neural network based computational model to predict the output power of different types of photovoltaic cells.

PloS one Sep 12, 2017
In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The...
Power Plants Silicon Crystallization Neural Networks, Computer Solar Energy
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Short-term prediction of solar energy in Saudi Arabia using automated-design fuzzy logic systems.

PloS one Aug 14, 2017
Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy sources have a drawback related to the difficulty in predicting their availability in the near future. Thi...
Algorithms Models, Theoretical Solar Energy Fuzzy Logic Computer Simulation Saudi Arabia
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