pH sensing technology is pivotal for monitoring aquatic ecosystems and diagnosing human health conditions. Indium–gallium–zinc oxide electrolyte-gated thin-film transistors (IGZO EGTFTs) are highly regarded as ion-sensing devices due to the pH-dependent surface chemistry of their sensing membranes. However, applying EGTFT-based pH sensors in complex biofluids containing diverse charged species poses challenges due to ion interference and inherently low sensitivity constrained by the Nernst limit. Here, we propose a dual-biased (DB) EGTFT pH sensing platform, acquiring back-gate-assisted sensitivity enhancement and recyclable redox-coupled protonation at the semiconductor-biofluid interface. A solution-processed amorphous IGZO film, used as the proton-sensitive membrane, ensures scalable uniformity across a 6-inch wafer. These devices demonstrate exceptional pH resistivity over several hours when submerged in solutions with pH levels of 4 and 8. In-depth electrochemical investigations reveal that back-gate bias significantly enhances sensitivity beyond the Nernst limit, reaching 85 mV/pH. This improvement is due to additional charge accumulation in the channel, which expands the sensing window. As a proof of concept, we observe consistent variations in threshold voltage during repeated pH cycles, not only in standard solutions but also in physiological electrolytes such as phosphate-buffered saline (PBS) and artificial urine, confirming the potential for reliable operation in complex biological environments.
This work was also supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Education (MOE) (Grant Nos. RS-2023-00245734 and RS-2023-00220077). This research was also supported by the NRF funded by Ministry of Science and ICT (MSIT), under the ITRC (Information Technology Research Center) support program (Grant No. IITP-2023-2020-0-01461) supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation). This research was supported by Bio-convergence Technology Education Program through the Korea Institute for Advancement Technology (KIAT) funded by the Ministry of Trade, Industry and Energy (MOTIE) (Grant No. P0017805). This work was supported by the Technology Innovation Program (Grant No. RS-2022-00154781) funded by the MOTIE, Korea. This work was supported by the NRF funded by the MSIT (Grant No. RS-2023-00213089). The following are results of a study on the \"Leaders in Industry-university Cooperation 3.0\" Project, supported by the NRF funded by the MOE (Grant No. 1345370640). This work was also supported by the National Research Council of Science & Technology (NST) grant funded by the MSIT (Grant No. CRC23021-000). This research was supported by 2024 Regional Industry-linked University Open-Lab Development Support Program through the Commercialization Promotion Agency for R&D Outcomes (COMPA) funded by MSIT (Grant No. 1711199984). This work was supported by the Korea Basic Science Institute (National Research Facilities and Equipment Center) grant funded by the MSIT (No. RS-2024-00403163). This research was supported by Basic Science Research Program through the NRF of Korea funded by the MOE (Grant No. 2021R1A6A1A10044950).