Researchers Design Transistor and Logic Circuits Without Any Semiconductors----Chinese Academy of Sciences

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Researchers Design Transistor and Logic Circuits Without Any Semiconductors

Feb 23, 2021

A team led by Prof. YAN Yong from the National Center for Nanoscience and Technology (NCNST) of the Chinese Academy of Sciences (CAS), collaborating with Profs. LI Tiehu from Northwestern Polytechnical University and Bartosz Grzybowski from Ulsan University of Science and Technology (UNIST), reported a transistor and logic circuits created exclusively from thin films of metal nanoparticles. This finding was recently published in Nature Electronics.

The capability of electrically modulating the charge carrier concentration and/or the conductivity of the semiconductor materials is the essential characteristic for their wide applications in electronic devices. This tunable conductivity feature is, however, challenging to achieve for metallic materials in which metals screen the electric field and therefore, their electrical resistance is insensitive to applied field.

In this work, the researchers showed that the conductivity of a metal nanoparticle thin layer can be electrically modulated by creating dynamic counterion gradients around the charged nanoparticles. This characteristic enabled them to build transistors via an unconventional five-electrode configuration.

The proof-of-the-concept devices can achieve an on/off ratio up to approximately 400, can perform ‘NOT’ logic and simple computations (e.g. half-adder), consists of non-toxic nanoparticles casted from alcohol solutions, and is mechanically flexible for circuit integrations. In addition, because the ionic nanoparticles are hydrated and screened by counterions, they can withstand electrostatic discharges.

Besides, the researchers proposed the possibility to integrate multi-properties of metal nanoparticles achieved by modifying nanocores with chemically/biologically functionalized self-assembled monolayers (SAMs). One can envision that such combinations would generate more complex platforms that can carry out sensing functions and perform logic operations, displaying self-learning memory and processing capabilities.