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John O | April 2019

Scientists create an organic transistor that works with both low and high currents

By Josh Perry, Editor


Physicists at the Ludwig Maximilian University (LMU) of Munich, Germany developed a fabrication technique for tiny organic transistors with a structure that allows them to work with low or high currents, according to a report from the university.


LMU scientists developed an organic transistor from low and high currents.
(Christoph Hohmann, Nanosystems Initiative Munich)


“By carefully tailoring a small set of parameters during the production process,” the article explained, “they have been able to design nanoscale devices for high or low current densities. The primary innovation lies in the use of an atypical geometry, which also facilitates assembly of the nanoscopic transistors.”


Researchers believe that these new transistors could be used in OLED and sensors where low voltages are required. They are particularly interested in using the transistors in memristors that model the behavior of neurons when processing electrical signals. A patent application was also filed for the device so it can be developed for industrial applications.


The research was recently published in Nature Nanotechnology. The abstract stated:


“Until now, organic semiconductors have failed to achieve high performance in highly integrated, sub-100 nm transistors. Consequently, single-crystalline materials such as single-walled carbon nanotubes, MoS2 or inorganic semiconductors are the materials of choice at the nanoscale.


“Here we show, using a vertical field-effect transistor design with a channel length of only 40 nm and a footprint of 2 × 80 × 80 nm2, that high electrical performance with organic polymers can be realized when using electrolyte gating. Our organic transistors combine high on-state current densities of above 3 MA cm−2, on/off current modulation ratios of up to 108 and large transconductances of up to 5,000 S m−1.


“Given the high on-state currents at such large on/off ratios, our novel structures also show promise for use in artificial neural networks, where they could operate as memristive devices with sub-100 fJ energy usage.”

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