We demonstrate the impact of SiO2 layer on thermal conductivity of Si nanowire by nonequilibrium molecular dynamics simulation. Our results indicate that the presence of the oxide layer is influential to the significant decrease in the thermal conductivity. By analyzing the vibrational density of states, we show the reduction of the thermal conductivity stems from the attenuation of the low-frequency phonon modes. This work suggests that the disorders near the SiO2/Si surface is crucial to characterize the thermal properties of practical SiNW.

In the recent submicron technologies, the pattern formation on photomasks is increasing in its difficulty owing to the complexity of optical proximity effect correction (OPC) and resolution enhancement techniques (RET). The detection and repair of critical patterns after OPC or RET have become essential procedures for photomask preparation, and design rule check (DRC) or lithography simulation tools have often been used to verify these patterns. However, the detection and repair of critical patterns have been becoming an excessive burden in the development of lithography processes and mask data processing. In this paper, we describe how to detect and repair these OPC critical patterns in lithography using the OPC-DFM rule, which can be derived from the OPC extraction test element group (TEG) effectively and easily. This technology enables the removal of OPC critical patterns before photomask preparation.

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In this study, we investigated the dependence of critical dimension (CD) bias on pattern dimension (width, space and pitch) in detail and quantitatively in gate etch process. The mechanism of CD bias dependence was estimated from the characteristic of each etching step. Based on the etching mechanism, the numerical model was generated by using linear combination of functions of pattern dimension which have strong correlation to CD bias dependence. For the purpose of improving the pattern-to-pattern gate CD variation, the correction of line width of mask was carried out to compensate CD bias dependence by using this model. This model accurately predicted CD bias dependence, and pattern-to-pattern CD variation was improved in gate etch process successfully.

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