The Manufacturing Science and Technology Group (MSTG) sessions bring together invited speakers to highlight the challenges and opportunities for successful manufacturing of next generation materials, devices and technologies. Our sessions are meant to generate synergy among scientists and engineers working across the spectrum of these technologies, including basic research, discovery, metrology, characterization, processing, and development, and deployment. We seek to encourage everyone to keep these manufacturing challenges in mind as they move technologies forward. This year we are highlighting the areas of machine learning for process control and for materials discovery, as well as characterization, and contributions to the Symposium theme of “Imperfectly Perfect Materials.
MS1+HI: Machine Learning for Microelectronics Manufacturing Process Control
- Peter Barar, Synopsys
- Adnan Chowdhury, NXP Semiconductors
- Jeff David, PDF Solutions, “Progressing Process Control with Data-Centric AI”
- Jun Shinagawa, Tokyo Electron America, “Paths Toward Autonomous Plasma Process Tool Operation by Pairing of Plasma and Machine Learning Technologies”
MS2+AP+AS+TF: Advanced Characterization and Metrology for 3D
- Bryan Barnes, NIST, “Semiconductor Metrology for Dimensional and Materials Scaling”
- Cornel Bozdog, Nearfield Instruments, “New in-Line Metrology for Advanced Semiconductor Nodes”
- Taeyong Jo, Samsung
- Sergei Kalinin, Oak Ridge National Laboratory, “Automated Experiment in Electron Microscopy: From Physics Discovery Towards Creating Structures with Designed Properties”
- Subra Sankaranarayanan, Argonne National Laboratory, “Towards a Digital Twin for Spatiotemporal Experiments”
MS3+HI: Machine Learning for Materials’ Discovery
- Daniel Du, Exxon Mobil
- Aarti Singh, Carnegie Mellon University, “Deep Optimization for Material Discovery”
- Brian Valentine, DOE, “Recent Advances in Semiconductor Material Design and Discovery”
MS4: Manufacturing Science and Technology Poster Session