Extremely-Low-Power Devices and Their Applications
A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "A:Physics".
Deadline for manuscript submissions: closed (30 April 2020) | Viewed by 42070
Special Issue Editor
Special Issue Information
Dear Colleagues,
Over the past 60 years, the size reduction of electron devices has increased the density and speed of semiconductor chips exponentially. However, as the end of Moore’s law approaches, power-consumption issues are becoming more critical in terms of energy efficiency, reliability, density and even performance. For example, it is expected that the ICT industry will use 20% of all electricity and emit up to 5.5% of the world’s carbon emissions by 2025. Thus, extremely-low-power electronic systems are indispensable to the future of the ICT industry and various pioneering ideas have been proposed, including sharp-switching devices, M/NEMS devices, extremely-low-power memory/sensors, reconfigurable computing devices, neuromorphic devices and so forth. This Special Issue on extremely-low-power devices and their applications will cover the timely topics of pioneering semiconductors, M/NEMS and sensor devices for dramatic power saving and boosting energy efficiency.
Potential topics include, but are not necessarily limited to:
- Sharp-switching devices (e.g. tunnel FETs, negative capacitance FETs, impact-ionization MOS, latch-mode SOI MOSFETs, etc.)
- Micro-/nano-electromechanical devices including relays, memory cells and sensors
- Extremely-low-power memory
- Extremely-low-power sensors
- Reconfigurable computing devices
- Neuromorphic devices
- Applications of extremely-low-power devices
Prof. Dr. Woo Young Choi
Guest Editor
Manuscript Submission Information
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Keywords
- Sharp-switching devices (e.g. tunnel FETs, negative capacitance FETs, impact-ionization MOS, latch-mode SOI MOSFETs, etc.)
- Micro-/nano-electromechanical devices including relays, memory cells and sensors
- Extremely-low-power memory
- Extremely-low-power sensors
- Reconfigurable computing devices
- Neuromorphic devices
- Applications of extremely-low-power devices
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