Self-Assembled Monolayers (SAMs) in Organic Field-Effect Transistors

Organic printed electronics is attracting an ever-growing interest in the last decades because of its impressive breakthroughs concerning the chemical design of π-conjugated materials and their processing. This has an impact on novel applications, such as flexible-large-area displays, low- cost printable circuits, plastic solar cells and lab-on-a-chip devices. The organic field-effect transistor (OFET) relies on a thin film of organic semiconductor that bridges source and drain electrodes. Since its first discovery in the 80s, intensive research activities were deployed in order to control the chemico-physical properties of these electronic devices and consequently their charge. Self-assembled monolayers (SAMs) are a versatile tool for tuning the properties of metallic, semi-conducting, and insulating surfaces. Within this context, OFETs represent reliable instruments for measuring the electrical properties of the SAMs in a Metal/SAM/OS junction. Our experimental approach, named Charge Injection Organic-Gauge (CIOG), uses OTFT in a charge-injection controlled regime. The CIOG sensitivity has been extensively demonstrated on different homologous self-assembling molecules that differ in either chain length or in anchor/terminal group. One of the latest applications of organic electronics is the so-called “bio-electronics” that makes use of electronic devices to encompass interests of the medical science, such as biosensors, biotransducers etc… As a result, thee second part of this thesis deals with the realization of an electronic transducer based on an Organic Field-Effect Transistor operating in aqueous media. Here, the conventional bottom gate/bottom contact configuration is replaced by top gate architecture with the electrolyte that ensures electrical contact between the top gold electrode and the semiconductor layer. This configuration is named Electrolyte-Gated Field-Effect Transistor (EGOFET). The functionalization of the top electrode is the sensing core of the device allowing the detection of dopamine as well as of protein biomarkers with ultra-low sensitivity.

Physical modeling and numerical simulations of degradation mechanisms in devices and insulators for power applications

In this thesis, a TCAD approach for the investigation of charge transport in amorphous silicon dioxide is presented for the first time. The proposed approach is used to investigate high-voltage silicon oxide thick TEOS capacitors embedded in the back-end inter-level dielectric layers for galvanic insulation applications. In the first part of this thesis, a detailed review of the main physical and chemical properties of silicon dioxide and the main physical models for the description of charge transport in insulators are presented. In the second part, the characterization of high-voltage MIM structures at different high-field stress conditions up to the breakdown is presented. The main physical mechanisms responsible of the observed results are then discussed in details. The third part is dedicated to the implementation of a TCAD approach capable of describing charge transport in silicon dioxide layers in order to gain insight into the microscopic physical mechanisms responsible of the leakage current in MIM structures. In particular, I investigated and modeled the role of charge injection at contacts and charge build-up due to trapping and de-trapping mechanisms in the oxide layer to the purpose of understanding its behavior under DC and AC stress conditions. In addition, oxide breakdown due to impact-ionization of carriers has been taken into account in order to have a complete representation of the oxide behavior at very high fields. Numerical simulations have been compared against experiments to quantitatively validate the proposed approach. In the last part of the thesis, the proposed approach has been applied to simulate the breakdown in realistic structures under different stress conditions. The TCAD tool has been used to carry out a detailed analysis of the most relevant physical quantities, in order to gain a detailed understanding on the main mechanisms responsible for breakdown and guide design optimization.