UCLA researchers devise scalable method for fabricating high-quality graphene transistors

UCLA researchers have developed a successful, scalable method for fabricating self-aligned graphene transistors with transferred gate stacks.

By performing the conventional lithography, deposition and etching steps on a sacrificial substrate before integrating with large-area graphene through a physical transferring process, the new approach addresses and overcomes the challenges of conventional fabrication. With a damage-free transfer process and a self-aligned device structure, this method has enabled self-aligned graphene transistors with the highest cutoff frequency to date — greater than 400 GHz.

Self-aligned graphene transistor

PNAS – High-frequency self-aligned graphene transistors with transferred gate stacks

Graphene has attracted enormous attention for radio-frequency transistor applications because of its exceptional high carrier mobility, high carrier saturation velocity, and large critical current density. Herein we report a new approach for the scalable fabrication of high-performance graphene transistors with transferred gate stacks. Specifically, arrays of gate stacks are first patterned on a sacrificial substrate, and then transferred onto arbitrary substrates with graphene on top. A self-aligned process, enabled by the unique structure of the transferred gate stacks, is then used to position precisely the source and drain electrodes with minimized access resistance or parasitic capacitance. This process has therefore enabled scalable fabrication of self-aligned graphene transistors with unprecedented performance including a record-high cutoff frequency up to 427 GHz. Our study defines a unique pathway to large-scale fabrication of high-performance graphene transistors, and holds significant potential for future application of graphene-based devices in ultra–high-frequency circuits.

Last year, UCLA researchers had a scalable method to make graphene transistors with speeds up to 50 Ghz. The new transistors are over 8 times faster.

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