Guest Editors
Dr. Pattabhi Ramaiah Budarapu, School of Mechanical Sciences, Indian Institute of Technology Bhubaneswar, India.
Prof. Timon Rabczuk, Institute for Structural Mechanics, Bauhaus University Weimar, Germany.
Summary
Recently, a rapid expansion and dramatic transformation in green energy has been witnessed due to the advances in digitization, artificial intelligence, and machine learning based technologies. Therefore, demand for the advanced energy storage materials and the associated smart technologies has significantly increased. As a result, the major research focus is on the development of efficient technologies involving both computational as well as experimental studies for better understanding of green energy materials.
Recently, batteries have emerged as the best option for energy storage in several applications, for instance electric vehicles. The driving range, charge time, battery lifespan and cost are the key parameters of the electric vehicle customers. The effectiveness of batteries significantly influences the performance of electric vehicles. Therefore, techniques for the design and development of efficient materials, as well as techniques to accurately predict their performance and life are required to be developed.
On the other hand, harnessing solar energy using photovoltaic solar cells is a prospective green energy generation technique. The performance and durability of solar cells depend on several factors, such as manufacturing and installation, operating conditions, presence of defects, to name a few. Therefore, health monitoring of solar cells at regular intervals is important to avoid the drop in their performance. Furthermore, design and development of material technologies for enhanced efficiency of solar cells is required.
The range of applications of energy storage is wide; from nano devices, electronic gadgets, electric vehicles to industries. The main focus of this special issue is on artificial intelligence for advances in material technologies for green energy. The topics are not restricted; however, some are listed below.
Design and development of efficient green energy materials
Materials design for nano energy applications
Prediction of performance parameters of energy storage materials
Computational characterization and materials design for green energy applications
Analysis of multiscale multifield problems in energy applications
Data-driven and machine learning based approaches for energy materials
Time Series and forecasting techniques for the analysis of energy materials
Machine learning based interatomic potentials
Density functional theory based design of energy materials
Batteries and Solar cells
Design and development of energy sources for electric vehicles and industries
Investigation of degradation and mitigation techniques for energy materials
Stochastic and uncertainty analysis of energy materials
Keywords
Energy materials;
Green energy;
Nano energy;
Batteries and Solar cells;
Multiscale multifield problems in energy;
Date driven and machine learning approaches for energy;
Time Series and forecasting techniques;
Performance analysis;
Stochastic and uncertainty analysis.
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