Foreword Special Issue on “New Simulation Methodologies for Next-Generation TCAD Tools”

IEEE Transactions on Electron Devices, vol. 68, pp. 5346–5349

Abstract

Technology computer-aided design (TCAD) is an integral part of the development process of semiconductor technologies and devices, a field which has become increasingly complex and heterogeneous. Processing of integrated circuits requires nowadays over 400 process steps, and the resulting devices often have an intricate 3-D structure and contain various specifically designed materials. The full device behavior can only be understood by considering effects on all length scales from atomistic (material properties, interfaces, defects, and so on), to nanometric (quantum confinement, non-bulk properties, tunneling, ballistic transport, and so on), to full-chip dimensions (strain, heat transport, and so on), and time scales from femtoseconds (scattering, ferroelectric switching time, and so on) to seconds (trapping times, degradation, and so on). Voltages, currents, and charges have been scaled to such low levels that statistical effects and process variations have a strong impact. Devices based on new materials (e.g., 2-D crystals) and physical principles (ferroelectrics, magnetic materials, qubits, and so on) challenge standard TCAD approaches. While the simulation methods developed by the physics community can describe the basic device behavior, they often lack important simulation capabilities like, for example, transient simulations or integration with other TCAD tools, and are often too slow for daily use. Due to the complexity of semiconductor technology, it becomes more and more difficult to assess the impact of a change in processing or device structure on circuit performance by looking at a single aspect of an isolated device under idealized conditions. Instead, a TCAD tool chain is required which can handle realistic device structures embedded in a chip environment. New methodologies are required for all aspects of TCAD to ensure an efficient tool chain covering from atomistic effects to circuit behavior based on flexible simulation models that can handle new materials, device principles, and the ensuing large-scale simulations and that make use of artificial intelligence for well-chosen (sub)routines to decrease the overall simulation time. This Special Issue features six invited and 18 regular papers that address these problems.

Authors 8

1. Christoph Jungemann Aachen Faculty of Electrical Engineering and Information Technology

   RWTH Aachen University

   Affiliation as printed

   Faculty of Electrical Engineering and Information Technology, RWTH Aachen University, Aachen, Germany

2. Fabrizio Bonani

   Politecnico di Torino

   Affiliation as printed

   Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy

3. Elena Gnani

   University of Bologna

   Affiliation as printed

   University of Bologna, Bologna, Italy

4. Sung‐Min Hong

   Gwangju Institute of Science and Technology

   Affiliation as printed

   Gwangju Institute of Science and Technology, Gwangju, Republic of Korea

5. Seonghoon Jin

   Samsung Semiconductor (United States)

   Affiliation as printed

   Samsung, San Jose, CA, USA

6. Xiaoyan Liu

   Peking University

   Affiliation as printed

   School of Electronics Engineering and Computer Science, Peking University, Beijing, China

7. Victor Moroz

   Synopsys (United States)

   Affiliation as printed

   Synopsys, Mountain View, CA, USA

8. Anne S. Verhulst

   IMEC

   Affiliation as printed

   imec, Leuven, Belgium