Leveraging both faces of polar semiconductor wafers for functional devices

Autor: van Deurzen, Len, Kim, Eungkyun, Pieczulewski, Naomi, Zhang, Zexuan, Feduniewicz-Zmuda, Anna, Chlipala, Mikolaj, Siekacz, Marcin, Muller, David, Xing, Huili Grace, Jena, Debdeep, Turski, Henryk

Unlike non-polar semiconductors such as silicon, the broken inversion symmetry of the wide bandgap semiconductor gallium nitride leads to a large electronic polarization along a unique crystal axis. This makes the two surfaces of the semiconductor wa

Externí odkaz: http://arxiv.org/abs/2404.03733

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Multi-step ART1 algorithm for recognition of defect patterns on semiconductor wafers.

Autor: Choi, Gyunghyun¹ (AUTHOR), Kim, Sung-Hee¹ (AUTHOR), Ha, Chunghun² (AUTHOR), Bae, SukJoo¹ (AUTHOR) sjbae@hanyang.ac.kr

Publikováno v: International Journal of Production Research. Jun2012, Vol. 50 Issue 12, p3274-3287. 14p. 4 Illustrations, 1 Diagram, 6 Charts, 1 Graph.

Publisher Correction: Using both faces of polar semiconductor wafers for functional devices.

Autor: van Deurzen L; School of Applied and Engineering Physics, Cornell University, Ithaca, NY, USA. lhv9@cornell.edu., Kim E; Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA., Pieczulewski N; Department of Materials Science and Engineering, Cornell University, Ithaca, NY, USA., Zhang Z; Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA., Feduniewicz-Zmuda A; Institute of High Pressure Physics 'Unipress', Polish Academy of Sciences, Warsaw, Poland., Chlipala M; Institute of High Pressure Physics 'Unipress', Polish Academy of Sciences, Warsaw, Poland., Siekacz M; Institute of High Pressure Physics 'Unipress', Polish Academy of Sciences, Warsaw, Poland., Muller D; School of Applied and Engineering Physics, Cornell University, Ithaca, NY, USA., Xing HG; Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA.; Department of Materials Science and Engineering, Cornell University, Ithaca, NY, USA.; Kavli Institute at Cornell for Nanoscale Science, Cornell University, Ithaca, NY, USA., Jena D; School of Applied and Engineering Physics, Cornell University, Ithaca, NY, USA.; Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA.; Department of Materials Science and Engineering, Cornell University, Ithaca, NY, USA.; Kavli Institute at Cornell for Nanoscale Science, Cornell University, Ithaca, NY, USA., Turski H; Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA.; Institute of High Pressure Physics 'Unipress', Polish Academy of Sciences, Warsaw, Poland.

Publikováno v: Nature [Nature] 2024 Nov; Vol. 635 (8037), pp. E3.

Defect detection and classification on semiconductor wafers using two-stage geometric transformation-based data augmentation and SqueezeNet lightweight convolutional neural network

Autor: López de la Rosa, Francisco, Gómez-Sirvent, José L., Morales, Rafael, Sánchez-Reolid, Roberto, Fernández-Caballero, Antonio

Publikováno v: In Computers & Industrial Engineering September 2023 183