Low frequency noise in flexible transistors

Low frequency noise analysis in novel transistors

Low frequency noise (LFN) including 1/f noise (or flicker noise) in transistors plays a critical role in determining the performance of transistors used as sensors or in RF circuits. As various novel transistors in different physical dimensions (1D, 2D nanostructures) with new materials (organic film, inorganic nanomaterials) proposed for numerous applications (e.g. various types of sensors, disposable RFID tags etc.), understanding the fundamental physics of LFN in those novel transistors is of a paramount importance. Pin pointing the origin of the LFN will give a solution to improve the noise performance. Unfortunately, significantly less efforts are being made on the LFN in the novel transistors in our community due to in my opinion underestimation of the importance. 

With this motivation in mind, I have worked on investigating the origin of low frequency noise in various novel transistors (organic thin-film transistors, 2D layered transistors). Using the knowledge I earned, I also studied how the LFN affects the performance of transistors in modern sensor applications such as neural recording in brain-machine interfaces

This work experimentally studies the origin of 1/f noise in organic TFTs. With varying grain size, gate field effect and semiconductor film thickness, I observed that the exponent values – which is closely related to the distribution of trap densities of different energy level – were significantly different in each case. All data indicate that deep traps near channel surface were dominant sources of the 1/f noise under ‘carrier number fluctuation’ theory. (Link)

Under switching gate bias (i.e. switching between accumulation/depletion mode), capture/emission of the carriers by/from traps within the semiconductor is the dominant mechanism of the 1/f noise in organic TFTs. This was the first experimental report in organic TFTs. This is especially important in analog and mixed signal applications.(Link)

In this work, we studied the flicker noise characteristics of multilayered MoS2 transistor using measurement and analysis methodology I used for organic transistors. From the experimental results, we learned that deep traps existing in the device affect the 1/f noise especially at lower gate bias conditions, which can be explained with carrier number fluctuation model. (Link)

As a more practical study, I investigated how important is to understand low frequency noise of novel transistors in sensor applications. I found that the LFN becomes a dominant factor in nanowire transistors used for extracellular neural recording, determining signal-to-noise ratio. It was particularly interesting to see how sometime observed random telegraph noise signal shows up as recording artifact. I believe this effort would help us to build more solid design guideline for the next generation active neural recording system using novel technologies. (Link)

Related Publications & Presentations

    1. Hongki Kang, and Vivek Subramanian, “Measurement and analysis of 1/f noise under switched bias in organic thin film transistors,” APPLIED PHYSICS LETTERS, 104, 023301, 2014. (Link)
    2. Hongki Kang, Lakshmi Jagannathan, and Vivek Subramanian, “Measurement, analysis, and modeling of 1/f noise in pentacene TFTs," APPLIED PHYSICS LETTERS, 99, 062106, 2011. (Link)
    3. Hyuk-Jun Kwon, Hongki Kang, Jaewon Jang, Sunkook Kim, and Costas P. Grigoropoulos, “Flicker noise analysis of 2D multi-layer MoS2 transistors," APPLIED PHYSICS LETTERS, 104, 083110, 2014. (Link) – Equal contribution with H.-J. Kwon
    4. Hongki Kang, Jee-Yeon Kim, Yang-Kyu Choi, and Yoonkey Nam, “Feasibility Study of Extended-gate Type Silicon Nanowire Field-Effect Transistor for Neural Recording,” SENSORS, 17(4), 705, 2017. (Link)
    5. PhD dissertation: Gravure-printed Highly-scaled Organic Thin-film Transistors for Low-cost and Large-area Electronics
    6. Hongki Kang, Jee-Yeon Kim, Yang-Kyu Choi, and Yoonkey Nam, “A Feasibility Study of Tri-Gate Silicon Nanowire Field-Effect Transistor for Neural Signal,” IEEE EMBC 2016, Orlando, US, August 2016.
    7. Hongki Kang, Jee-Yeon Kim, Yang-Kyu Choi, and Yoonkey Nam, “In-depth characterization of silicon nanowire field-effect transistor (SiNW-FET) for neural recording and direct performance comparison with passive MEA,” MEA Meeting 2016, Reutlingen, Germany, June 2016.
    8. Hongki Kang, Lakshmi Jagannathan, and Vivek Subramanian, “Measurement, analysis, and modeling of 1/f noise in pentacene TFTs," LOPE-C, Messe Frankfurt, Germany, June 2011.