Automated Scanning Dielectric Microscopy Toolbox for Operando Nanoscale Electrical Characterization of Electrolyte‐Gated Organic Transistors

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Abstract
Electrolyte‐gated organic transistors (EGOTs) leveraging organic semiconductors' electronic and ionic transport characteristics are the key enablers for many biosensing and bioelectronic applications that can selectively sense, record, and monitor different biological and biochemical processes at the nanoscale and translate them into macroscopic electrical signals. Understanding such transduction mechanisms requires multiscale characterization tools to comprehensively probe local electrical properties and link them with device behavior across various bias points. Here, an automated scanning dielectric microscopy toolbox is demonstrated that performs operando in‐liquid scanning dielectric microscopy measurements on functional EGOTs and carries out extensive data analysis to unravel the evolution of local electrical properties in minute detail. This paper emphasizes critical experimental considerations permitting standardized, accurate, and reproducible data acquisition. The developed approach is validated with EGOTs based on blends of organic small molecule semiconductor and insulating polymer that work as accumulation‐mode field‐effect transistors. Furthermore, the degradation of local electrical characteristics at high gate voltages is probed, which is apparently driven by the destruction of local crystalline order due to undesirable electrochemical swelling of the organic semiconducting material near the source electrode edge. The developed approach paves the way for systematic probing of EGOT‐based technologies for targeted optimization and fundamental understanding.
Funding Information
  • Generalitat de Catalunya (2021‐SGR‐00443)
  • Ministerio de Ciencia e Innovación (PID2022‐142297NB‐I00, PID2022‐141393OB‐I00, FUNFUTURECEX2019‐000917‐S)
  • HORIZON EUROPE European Innovation Council (101046719)
  • H2020 Marie Skłodowska-Curie Actions (813863)
  • Agencia Estatal de Investigación (PID2019‐110210GB‐I00)

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