Machine Learning Assisted Device Modeling: A Survey

This survey based on the various device modelling characteristics assists with various machine learning algorithms. Device modelling is a crucial task in the field of electronics and it helps to predict the behaviour of devices under various conditions. Traditional methods for device modelling are often limited in their accuracy and require extensive manual effort. However, the device's original characteristics generated with TCAD(Training Computer Aided Design) simulation can be predicted with Machine learning algorithms. This survey investigates the various machine-learning algorithm that assists with various device modelling characteristics and analyses the simulation results with which device structure provides better performance. To analyse the challenges faced when using machine learning for device modellings, such as data availability and quality, model interpretability, and computational complexity. Finally, the future directions and potential applications of machine learning in device modelling, with various machine learning algorithms. This survey provides a comprehensive overview of the current state-of-the-art in machine learning-assisted device modelling and highlights the potential of this technology for advancing the field of electronics.