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Technical category
    • Application of inorganic nanofiber technology to promote the development of biotechnology

      Smart machinerynovel materials FutureTech Application of inorganic nanofiber technology to promote the development of biotechnology

      Inorganic porous nanofibers with surfaceinterface defects are prepared through humidity-controlled electrospinninghigh-temperature annealing technology. Under the irradiation of light sources of different wavelengths (380~780 nm), the bound electrons stored in the valence band can be excited to the conduction band to form free electrons on the surface of the material, generating different intensities of microcurrents, light sensitivitymicrocurrent changes. Because the "inorganic nanofiber" technology has high uniquenesshigh product compatibility, it can be applied to a wide range of markets.
    • (test)Application of inorganic nanofiber technology to promote the development of biotechnology

      Smart machinerynovel materials FutureTech (test)Application of inorganic nanofiber technology to promote the development of biotechnology

      Inorganic porous nanofibers with surfaceinterface defects are prepared through humidity-controlled electrospinninghigh-temperature annealing technology. Under the irradiation of light sources of different wavelengths (380~780 nm), the bound electrons stored in the valence band can be excited to the conduction band to form free electrons on the surface of the material, generating different intensities of microcurrents, light sensitivitymicrocurrent changes. Because the "inorganic nanofiber" technology has high uniquenesshigh product compatibility, it can be applied to a wide range of markets.
    • 基於深度學習的光刻電路失真預測,光罩修正及新穎布局圖樣偵測的設計自動化技術

      FutureTech 基於深度學習的光刻電路失真預測,光罩修正及新穎布局圖樣偵測的設計自動化技術

      The DNN models of this technology include a LithoNet, an OPCNet,a layout novelty detection network. LithoNet is a learning-based pre-simulation model for layout-to-SEM contour prediction,OPCnet is a dual network of LithoNet for photomask optimization. Integrated with a well-trained LithoNet, our layout novelty detection network, consisting of a self-attention guided LithoNetan autoencoder, can check if there are layout patterns easily resulting in local distortions in contours of metal lines based on multi-modal (global-local) feature fusion.