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Amir Reza Ansari Dezfoli

1 paper indexed

openalexZenodo (CERN European Organization for Nuclear Research)

Feature Importance and Growth Rate Prediction in SiC PVT Processes through Advanced Machine Learning Models

Amir Reza Ansari Dezfoli

Silicon carbide is a key wide-bandgap semiconductor material for next-generation power electronics, yet the Physical Vapor Transport (PVT) method used for bulk crystal growth remains constrained by complex thermal-chemical interactions and low growth rates. This study develops a…

Also available via: European Organization for Nuclear Research

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