Non-classical logic inverter coupling a ZnO nanowire-based Schottky barrier transistor and adjacent Schottky diode

Literature Information

Publication Date 2014-05-30
DOI 10.1039/C4CP01266F
Impact Factor 3.676
Authors

Seyed Hossein Hosseini Shokouh, Syed Raza Ali Raza, Hee Sung Lee, Seongil Im


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Abstract

On a single ZnO nanowire (NW), we fabricated an inverter-type device comprising a Schottky diode (SD) and field-effect transistor (FET), aiming at 1-dimensional (1D) electronic circuits with low power consumption. The SD and adjacent FET worked respectively as the load and driver, so that voltage signals could be easily extracted as the output. In addition, NW FET with a transparent conducting oxide as top gate turned out to be very photosensitive, although ZnO NW SD was blind to visible light. Based on this, we could achieve an array of photo-inverter cells on one NW. Our non-classical inverter is regarded as quite practical for both logic and photo-sensing due to its performance as well as simple device configuration.

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Contents list

Front/Back Matter

DOI: 10.1039/C7CP90024D

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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