首页|Reports from Southwest Minzu University Advance Knowledge in Machine Learning (P rediction of Jte Breakdown Performance In Sic Pin Diode Radiation Detectors Usin g Tcad Augmented Machine Learning)
Reports from Southwest Minzu University Advance Knowledge in Machine Learning (P rediction of Jte Breakdown Performance In Sic Pin Diode Radiation Detectors Usin g Tcad Augmented Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news originating from Chengdu, People's Repu blic of China, by NewsRx correspondents, research stated, "The design of Junctio n Termination Extension (JTE) is an important step for meeting the reliability r equirement of SiC PiN diode radiation detectors. For early evaluation, Technolog y Computer Aided Design (TCAD) software is often used to simulate the electronic property of detectors with different JTE parameters." Financial supporters for this research include Southwest Minzu University Resear ch Startup Funds, China, Fundamental Research Funds for the Central Universities -Southwest Minzu University, China, State Key Laboratory of Nuclear Physics and Technology -Peking University, China. Our news journalists obtained a quote from the research from Southwest Minzu Uni versity, "But it is time consuming, which need 1 h or even longer for one case. Here, a TCAD augmented Machine Learning (ML) method based on the fully connected Neural Network (NN) algorithm is proposed to predict the breakdown performance quickly with different parameters of Spatial Modulation (SM) JTE. Utilized simil ar to 5000 datum generated by TCAD simulation, the ML model could be established and achieve good prediction of breakdown voltage and location within a few seco nds. As a semi-supervised learning model, its prediction accuracy of breakdown l ocation is higher than 89.4 % and the determination coefficient R- 2 of breakdown voltage could be up to 0.97 compared with TCAD simulations. Moreo ver, this model could give the relationship curve of breakdown voltages and dopi ng concentration, which is useful to choose an ideal structure with a wide impla ntation dose window."
ChengduPeople's Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningSouthwest Minzu University
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