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Purpose: In this study, the artificial intelligence techniques namely Artificial Neural Network, Random Forest, and Support Vector Machine are employed for PM 2.5 modelling. The study is carried out in Rohtak city of India during paddy stubble burning months i.e., October and November. The different models are compared to check their respective efficacies and also sensitivity analysis is performed...
Low temperature (< 160 °C epi temperature) Ge based punch through selector has been demonstrated with good Ion/Ioff and matched with TCAD results. High Jon verifies the high dopant activation at low temperature. Benchmarking with the available selector technologies, Jon/Joff >104 with voltage designability makes Ge based selector an attractive option for RRAM.
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