Novel machine learning-based prediction approach for nanoindentation load-deformation in a thin film: Applications to electronic industries

被引：0

作者：

Laxmikant Vajire, Sujal ^{[1
]}

Prashant Singh, Abhishek ^{[1
,2
]}

Kumar Saini, Dinesh ^{[3
]}

Kumar Mukhopadhyay, Anoop ^{[4
]}

Singh, Kulwant ^{[5
,6
]}

Mishra, Dhaneshwar ^{[1
,7
]}

机构：

[1] Department of Mechanical Engineering, School of Automobile, Mechatronics, Mechanical Engineering, Manipal University Jaipur, Dahmikalan 303007, Rajasthan, Jaipur, India

[2] ARK Infosolutions Pvt. Ltd, Uttar Pradesh, Noida, India

[3] Department of Computer and Communication Engineering, School of Computers, Information Technology, Manipal University Jaipur, Dahmikalan 303007, Rajasthan, Jaipur, India

[4] Department of Physics, School of Basic Sciences and Research, Sharda University, Uttar Pradesh, Greater Noida,201310, India

[5] Department of Electronics and Communication Engineering, School of Electrical, Electronics, Communication Engineering, Manipal University Jaipur, Dahmikalan 303007, Rajasthan, Jaipur, India

[6] FlexMEMS Research Centre (FMRC), Manipal University Jaipur, Dahmikalan 303007, Rajasthan, Jaipur, India

[7] Multiscale Simulation Research Center (MSRC), Manipal University Jaipur, Dahmikalan 303007, Rajasthan, Jaipur, India

来源：

Computers and Industrial Engineering | 2022年 / 174卷

关键词：

Aluminum nitride - Deformation - E-learning - Gallium nitride - III-V semiconductors - Lattice mismatch - Light emitting diodes - Nanoindentation - Sapphire - Semiconductor quantum wells - Substrates;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

引用

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