Search

Virtual metrology (VM) is widely used for yield management and control in semiconductor manufacturing owing to its high real-time inspection, low cost, and convenient maintenance. However, the multimodal characteristics of batch processes are ignored in the existing yield VM models. The adaptive multimodal division and modal sample imbalance have also not been considered. Therefore, a data-driven adaptive VM model based on the Gath–Geva fuzzy clustering (GGFC) and multitask learning deep belief network (MLDBN) is proposed to solve the problems above. First, the GGFC model is designed to realize the feature extraction of the batch direction and the modal division of the time and variable directions. Second, the partition coefficient and classification entropy indexes are designed to determine the modal categories automatically and establish the SMOTE model to deal with the imbalance of multimodal samples. Third, the local features of multimodal are extracted by the designed MLDBN models. After that, the batch direction features and the multi-features extracted from multimodal are used as the improved MLDBN parameters to realize the fusion prediction. Finally, experiments are carried out by the accurate industrial data from a multibatch wafer fabrication process. The efforts show that the proposed VM model presents better performances in the result of different indicators and has higher accuracy and robustness than the traditional models. [ABSTRACT FROM AUTHOR]

Gyrotron, as a most likely practical high-power terahertz (THz) radiation source, has been widely applied to THz dynamic nuclear polarization-enhanced nuclear magnetic resonance (DNP-NMR) spectroscopy. In this article, an iris cavity with high-quality factor is theoretically designed for a frequency-tunable THz gyrotron, which could be tuned at three frequency regimes: 140, 250, and 263 GHz, respectively. Based on the self-developed nonlinear code, the beam wave interactions in the designed cavity are studied in detail when the corresponding high-order axial modes (HOAMs) are TE−6.1.q, TE0.4.q', and TE8.2.q. By tuning the applied magnetic field under the condition that the beam voltage U0 is 20 kV and beam current I0 is 0.10 A, the output power and frequency tuning ranges could achieve 0.75 kW and 1.15 GHz, 0.63 kW and 3.10 GHz, and 0.59 kW and 2.54 GHz. Meanwhile the calculation results are compared with the 3-D particle software CST, which have confirmed that the frequency and power tuning ranges of TE−6.1.q, TE0.4.q', and TE8.2.q'' could reach 0.46 kW and 1.07 GHz, 0.37 kW and 2.24 GHz, and 0.34 kW and 1.96 GHz. These results could be beneficial for the development of frequency-tunable gyrotron toward some up-and-coming novel THz applications. [ABSTRACT FROM AUTHOR]