Accelerating Deep Neural Networks with Analog Memory Devices
Katherine Spoon, Stefano Ambrogio, et al.
IMW 2020
This review examines the advantages of two-dimensional (2D) and thin film materials in the development of chemical sensor systems. More specifically, this paper focuses on the use of graphene, transition metal dichalcogenides (TMDs), and thin film metal-oxide semiconductors (MOX) in gas- and liquid-phase chemical sensing applications. Key features in terms of material properties, device characteristics, as well as scalability for system development are examined. Key challenges associated with various sensing approaches (e.g. optical, electrochemical, FET/chemiresistive) are presented along with recent advances. Lastly, common methods for preprocessing and pattern recognition are summarized while highlighting the development of olfaction-inspired sensor systems to motivate the use of machine learning for data analysis.
Katherine Spoon, Stefano Ambrogio, et al.
IMW 2020
An Chen, Stefano Ambrogio, et al.
EDTM 2020
Manuel Le Gallo, S.R. Nandakumar, et al.
Neuromorph. Comput. Eng.
Eiji Nakamura, Keiji Matsumoto, et al.
ECTC 2019