|
|
|
The SISC is a workshop-style conference that provides a forum for device engineers, solid state physicists, and materials scientists to discuss topics of common interest, formally through invited and contributed presentations, and informally during poster and rump sessions.
The SISC is sponsored by the IEEE Electron Device Society and is held right after IEDM.
This year, SISC will be held as a fully in-person event.
The program includes talks and poster presentations (theory and experiment) on the role of materials, interfaces, and defects on performance and reliability of:
- Logic Devices for future technology nodes (Nanosheet, CFET, VFET, etc.),
- Steep Sub-Threshold slope logic devices (Tunnel FETs, etc.),
- Insulators on High-Mobility substrates (SiGe, Ge, etc.),
- Low Dimensional materials and devices,
- Non-Volatile Memory for AI / In-Memory / Neuromorphic Compute (ReRAM, PCM, ECRAM, etc.),
- Ferroelectric devices (FeFET, FeRAM, etc.),
- Amorphous Oxide Semiconductor channel transistors (IGZO, etc.),
- Monolithic and/or Heterogeneous ICs (BEOL, interconnects, packaging, etc.),
- Wide Bandgap semiconductor power devices (SiC, GaN, β-Ga2O3, etc.),
- Materials and devices for Qubits in Quantum Computing and Cryogenic Electronics,
including machine learning / materials discovery techniques developed and used for their study.
2024 Confirmed Technical Invited Talks
The technical program will be complemented by Invited Presentations from both industry and academia.
- Dr. Sandy Liao, TSMC, Taiwan
CFET Technology for Future Logic Scaling
- Prof. Saptarshi Das, Penn State U., USA
Monolithic 3D Integration of Functionally Diverse 2D Devices
- Dr. Kwangmin Park, Samsung, S. Korea
Pioneering Innovation for Next Generation 3D Memory Era
- Prof. Sumeet Gupta, Purdue U., USA
Variability in Hafnia-based Ferroelectrics: A Phase-Field Simulation based Perspective
- Dr. Chris Neumann , Intel, USA
Hafnia-Based FeRAM for High-Density, High-Speed Embedded Memory
- Dr. Adrian Chasin, imec, Belgium
IGZO Thin-Film Transistor Reliability: the Last Standing Roadblock for Memory Applications
- Prof. Siddharth Rajan, The Ohio State U., USA
Device Engineering for High-Performance Gallium Oxide Electronics
- Dr. Ruqiang Bao, IBM, USA
Gate Stack Innovations for Gate-All-Around (GAA) Device Architecture to Continue Transistor Scaling
Invited Honorary Lecture
- Prof. Andre Stesmans, KU Leuven, Belgium
Electron Spin Resonance as Powerful Spectroscopy for Assessment of Point Defects in
Semiconductor/Insulator Structures: Some Historical Reflections on Interfaces
Wednesday Evening Tutorial
The Wed Tutorial will shed light on a single topic in depth, particularly benefiting students and newcomers to the field.
- Prof. Shinichi Takagi, U. Tokyo, Japan
Hafnia-Based Ferroelectric FETs and Capacitors for Low-Power Memory and AI Applications: Physical Understanding of Device Operation and Reliability
Since the discovery of ferroelectricity in HfO2-based dielectric films in 2011, ferroelectric devices using HfO2-based thin films as dielectrics have attracted strong interest. Thus, active research and developments on Si-friendly HfO2-based ferroelectric FeRAMs and FeFETs have been conducted for memory and logic applications with extremely low power consumption. Furthermore, these HfO2-based ferroelectric devices are also promising as hardware for realizing AI applications with high energy efficiency, because of the versatile properties such as analog memory characteristics and coexistence of memory and logic functions.
This tutorial will introduce the recent development of FeRAMs and FeFETs for memory and AI applications with an emphasis on the physical understanding of electric characteristics and reliability. For metal/ferroelectric/metal (MFM) capacitors, I will provide the critical issues for FeRAM applications, such as ferroelectric film thickness scaling, operation voltage and reliability including oxide breakdown, wakeup and fatigue. Also, for metal/ferroelectric/semiconductor (MFIS) gate stacks, I will discuss the complicated interaction and coupling between polarization charges, trapped charges and inversion-layer charges, which are of the paramount importance in quantitative understanding of the FeFET operation and the reliability. Based on this knowledge, the memory characteristics and the reliability of FeFETs will be examined from the viewpoint of the ferroelectric film thickness scaling.
The tutorial will also explore the AI applications using the HfO2-based ferroelectric devices. Various examples of the ferroelectric devices for application to AI computation systems will be introduced. Among them, this presentation will shed light more on physical reservoir computing using FeFETs, which is one of the unique AI computation applications that take advantage of the ferroelectric device properties. Physical reservoir computing, represented by hardware with input-history-dependent and nonlinear dynamics, has recently attracted significant attention as a method to realize real-time AI processing with high energy efficiency at the edge. The principle, the basic AI characteristics and applications to speech recognition of FeFET reservoir computing will be explained.
A Best Student Presentation Award will be given in memory of E. H. Nicollian, who made many important contributions to the field and had a strong presence within the SISC.
A Best Poster Award will be given in memory of T. P. Ma.
You can also download the Call in the PDF format. Please help us promote SISC among your colleagues and collaborators by forwarding the Call to them and by posting a hard copy at your affiliation.
For questions about the SISC focus, abstract submission, and related issues, please contact the Technical Program Chair.
|
