Publication
ACS Nano
Paper

Silicon Nanowire Field Effect Transistor Sensors with Minimal Sensor-to-Sensor Variations and Enhanced Sensing Characteristics

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Abstract

Silicon nanowire field effect transistor (FET) sensors have demonstrated their ability for rapid and label-free detection of proteins, nucleotide sequences, and viruses at ultralow concentrations with the potential to be a transformative diagnostic technology. Their nanoscale size gives them their ultralow detection ability but also makes their fabrication challenging with large sensor-to-sensor variations, thus limiting their commercial applications. In this work, a combined approach of nanofabrication, device simulation, materials, and electrical characterization is applied toward identifying and improving fabrication steps that induce sensor-to-sensor variations. An enhanced complementary metal-oxide-semiconductor-compatible process for fabricating silicon nanowire FET sensors on 8 in. silicon-on-insulator wafers is demonstrated. The fabricated nanowire (30 nm width) FETs with solution gates have a Nernst limit subthreshold swing (SS) of 60 ± 1 mV/decade with ∼1.7% variations, whereas literature values for SS are ≥80 mV/decade with larger (>10 times) variations. Also, their threshold voltage variations are significantly (∼3 times) reduced, compared to literature values. Furthermore, these improved FETs have significantly reduced drain current hysteresis (∼0.6 mV) and enhanced on-current to off-current ratios (∼106). These improvements resulted in nanowire FET sensors with the lowest (∼3%) reported sensor-to-sensor variations, compared to literature studies. Also, these improved nanowire sensors have the highest reported sensitivity and enhanced signal-to-noise ratio with the lowest reported defect density of 2.1 × 1018 eV-1 cm-3, in comparison to literature data. In summary, this work brings the nanowire sensor technology a step closer to commercial products for early diagnosis and monitoring of diseases.

Date

22 Jun 2018

Publication

ACS Nano

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