Organic transistors-based devices for biological applications

Abstract

Organic transistors-based devices have critical impact in the next-generation smart sensors, implantable biomimetic apparatuses and brain inspired bioelectronics. With innovative fabrication, optimization and integration methods, this thesis aims to broaden the biological applications of organic transistors from novel diagnostic devices for monitoring individual’s daily health conditions, intelligent surgical tools for clinical treatment and finally to neuromorphic circuit with artificial synapse to mimic functions of human brain. Firstly, organic electrochemical transistors (OECTs)-based enzymatic sensors for glucose and lactate detection is reported with detection limit down to 10-7 M and 10-6 M respectively. Platinum nanoparticles, core component in these sensors, is successfully deposited by a two-step dip coating method without involving electrical bias. After integrating sensors with microfluidic channel, not only fast detection (1 minute) and low analyte consumption (30 μL) are realized, simultaneously detection of glucose and lactate is also achieved. A noninvasively detection of glucose in human saliva is demonstrated on our glucose sensor, which successfully distinguish diabetic patients with healthy individual. Besides laboratory test, we intend to transfer our technology into a real product. A prototype of portable glucose sensor for point-of-care test (POCT) has been successfully fabricated and can interact with smartphone through Bluetooth. Owning to its multifunctionality, high sensitivity, portability together with non-invasive property, this glucose sensor shows great potential in healthcare monitoring and POCT applications. In addition to basic metabolite sensing, a C-reactive protein (CRP, inflammation biomarker) sensor is demonstrated based on an organic field effect transistor (OFET) with extended sensing gate. The ultra-thin device (630 nm in thickness) with novel capsule-like CYTOP encapsulation layer possesses both extreme bending stability with 1.5 μm bending radius and superior sterilization compatibility to withstand 100 °C- saturated steam or boiling water. This CRP sensor can detect CRP antigen down to 1 μg/mL and is able to be transferred on a ventricular catheter to distinguish different inflammation states of the patients. The proposed device with superb flexibility, sterilization compatibility and high sensitivity can be an important milestone for next- generation smart surgical tools for clinical usage. Finally, a neuromorphic circuit for simulating associative learning is realized with the help of a non-volatile OECT as artificial synapse. The non-volatile OECT with poly(3,4-ethylenedioxythiophene):Tosylate (PEDOT:Tos)/ Polytetrahydrofuran (PTHF) composite active channel shows stable memory window and enduring state retention time longer than 200 minutes. The memory property as a function of PTHF ratio inside channel is investigated in-depth. Based on this non-volatile OECT, different synaptic functions from short-term plasticity (STP) like paired-pulse facilitation (PPF) and post-tetanic potentiation (PTP) to long-term plasticity (LTP) like short term memory (STM) to long term memory (LTM) transition are demonstrated. In addition, by integrating a pressure sensor, a photoresistor, a volatile and a non-volatile OECT, a neuromorphic circuit for simulating associative learning was achieved. The circuit can emulate the association between two physical input signals (pressure and light), which is the first time ever reported to the best of our knowledge. This proposed neuromorphic circuit with unique associative learning behavior can be utilized in human-machine interface applications.