Special Issue on Nanoelectronic Devices and Circuits for Next Generation Sensing and Information Processing
IEEE Transaction on Nanotechnology (TNANO) seeks original research manuscripts for a Special Issue on Nanoelectronic Devices and Circuits for Next Generation Sensing and Information Processing.
The next generation paradigm of information processing may involve a network of interconnected physical objects such as computers, mobile phones, sensors, actuators, wearable devices, vehicles, homes, buildings, and even energy systems, in which continuous sensing and computing takes place. In such a computing paradigm the vision is to connect a large amount of objects, allow them to collect and exchange data through network connectivity, and consequently utilize the enormous data for analytics and operation. Such as infrastructure provides increasingly smart, reliable and secure services among different things for different users. It has been extensively applied to diverse application domains, such as environmental monitoring, security surveillance, smart power grids, energy-efficient buildings, and interconnected vehicles.
To enable next generation sensing, control, and computing, in reality, advanced nanoelectronic devices and circuits must be developed and co-optimized across multiple hierarchical levels in order to sense, process and transmit data, while satisfying the demanding performance requirements for high speed, low power, flexible reconfigurability, high reliability etc. In addition, with the increasing complexity and data volume of sensing and computing, novel designs must be explored to improve design efficiency, enhance reliability and reduce time-to-market. For these reasons, there is an immediate need to re-think the conventional design strategies for implementing the next-generation sensing, control, and computing paradigm.
This special issue focuses on novel device technology and circuit designs to implement smart, efficient, reliable and secure sensing, control, and computing paradigm. The topics of interest include, but are not limited to the following:
- Nanoelectronic devices with ultra-high energy efficiency
- Energy-efficient analog front end and wireless communication circuits using nanoelectronic devices
- Emerging device and memory technology for information processing and storage
- Emerging device, including but not limited to GFET, TFET, Graphene nanoribbon tunnel FET, fordigital, analog, and RF circuit design
- Emerging memory, including but not limited to phase change memory, magnetic device, resistive memory, for digital, analog, and RF circuit design
- Nano-sensors for data sensing in Internet of Things
- Nano-CMOS and Post-CMOS based circuits for big data processing
- Nanoelectronic technology based sensors and controller for Cyber-Physical Systems
- Security and reliability solutions for nanoelectronic devices and circuits
- Nanoelectronic devices and circuits for secure sensing
- Novel devices and circuits for non-conventional computing
- Neuromorphic circuits and architectures
- Nano-CMOS and Post-CMOS based sensors and circuits for smart grid
- Case studies for sensors and circuits designed using nanoelectronic technology
All manuscripts must be submitted online using the IEEE TNANO manuscript template and Information for Authors, via the IEEE Manuscript Central found at https://mc.manuscriptcentral.com/tnano. On submission, authors must select the “Special Issue” manuscript type instead of “Regular Paper.” Manuscripts must focus on nanotechnology as reflected by technical content and references.
Special Issue Timeline:
The following is the tentative timeline for the special issue:
- Submission Deadline: 1 October 2016
- Author Notification: 1 December 2016
- Revised Manuscript Due: 15 January 2017
- Notification of Acceptance: 15 February 2017
- Final Manuscript Due: 15 April 2017
- Tentative Publication Date: Late 2017
Please address all other correspondence regarding this Special Issue to the Guest Editors using the following email-ID: email@example.com or NANO-SM-SI@unt.edu
Saraju P. Mohanty, Professor, Computer Science and Engineering, University of North Texas
Xin Li, Associate Professor, Electrical and Computer Engineering, Carnegie Mellon University,
Hai (Helen) Li, Associate Professor, Electrical and Computer Engineering, University of Pittsburgh,
Yao (Kevin) Cao, Professor Electrical, Computer and Energy Engineering, Arizona State University,
See Call for Papers here.