Chapter 1
Introduction

Since the beginning of mass production of silicon (Si) metal-oxide-semiconductor field-effect transistors (MOSFETs), the dimensions of these devices have been continuously scaling according to Moore’s Law. Hence, already in the nineties the typical channel lengths reached sub-100nm range, which opened a new era of nanoscale MOSFETs. Their integration into the digital and analog circuits allowed for a significant miniaturization of the final products of the modern microelectronics industry. However, the probability of functional failure of these devices is larger, since scaling has made the impact of single defects on the channel electrostatics more crucial. Therefore, investigation of device reliability has become essential. The main ingredients of any reliability study of modern nanoscale MOSFETs are experimental characterization and modeling of charging/discharging of individual defects, both of which typically lead to a drift in the device characteristics. However, investigation of reliability is not possible without accounting for device-to-device variability, which is also very important in scaled devices. In this context, the first part of this work deals with modeling of the impact of the position of single defects on the reliability of nanoscale MOSFETs in the presence of randomly distributed discrete dopants, which are considered one of the main sources of variability. Comparison of the simulation results with the experimental data will allow for the derivation of a technique suitable for the evaluation of the lateral positions of these single defects.

Although the International Technology Roadmap for Semiconductors (ITRS)[84] requires further scaling of modern MOSFETs down to 5nm channel lengths, simultaneous achievement of high transistor performance targets with these devices is extremely complicated. Therefore, in the meantime the device research community has a clear understanding that scaling of conventional Si MOSFETs according to Moore’s Law is close to its end. Extension of these limits requires switching of attention to principally new transistor technologies, which could fulfill the requirements on miniaturization and high device performance simultaneously. A very interesting approach is the implementation of new two-dimensional (2D) semiconductors as channel materials for next-generation transistors. This idea has been intensively developed since 2004, when the electric field effect in high-mobility graphene was discovered by K. Novoselov and A. Geim[133]. The first practical step in this direction was taken in 2007, when the group of M. Lemme reported the first graphene field-effect device[108]. This triggered the introduction of numerous next-generation 2D FETs. However, although within the next few years a number of other successful attempts at fabricating graphene FETs were undertaken, it has been clear since the beginning that graphene devices are only suitable for integration into analog circuits. The reason for this is the lack of a bandgap in graphene, which does not allow for the high on/off ratio necessary for digital circuits to be reached. Hence, research attention has shifted to other 2D semiconductors with sizable bandgap allowing for the limitations of graphene to be overcome. The most widely used is molybdenum disulphide (MoS2), which was shown to be suitable for use as a channel material in 2011, when the first MoS2 FET was reported by A. Kis and colleagues[141]. Subsequent studies have shown that graphene FETs can be outperformed by MoS2 devices with respect to transconductance and on current value, despite significantly smaller mobility. However, the level of fabrication technology of next-generation 2D FETs is obviously below the standards for Si technologies. Hence, contrary to modern nanoscale Si MOSFETs, the typical channel length of both graphene and MoS2 FETs are in the micrometer range. While the characterization of reliability of these devices is extremely important, the impact of single defects on their performance is not yet the most crucial issue (as it was for Si technologies in the seventies and eighties). Therefore, the building of methodology for a reliability study for these new devices has to be started from scratch, while also dealing with the issues of Si MOSFETs that have been known for decades. Thus, in the second part of this work a detailed analysis of the reliability of both graphene and MoS2 FETs will be performed. A majority of attention will be paid to experimental analysis of the impact of bias-temperature instabilities (BTI) and hot-carrier degradation (HCD) on the performance of next-generation 2D FETs. However, the experimental results will be supported by simulations.

The period of time in which this dissertation has been written falls exactly within the overlap between the era of ultra-scaled Si MOSFETs and the era of next-generation 2D FETs. While characterization of reliability is of key importance for both types of devices, in the former case one has to deal with the impact of single defects, while in the latter continuously distributed multiple defects are in the meantime more crucial. Therefore, both these questions will be touched upon in the course of this work.

The structure of this dissertation is organized as follows. The first three chapters contain a description of the theoretical background and an overview of previous research. Inclusion of such information is necessary to understand the results obtained by the author. Namely, Chapter 2 presents a brief description of the main approaches used for the simulation of the charged carrier transport through the channel of modern nanoscale Si MOSFETs in the presence of individual defects and randomly distributed discrete dopants. Basic information about the Boltzman transport equation (BTE), drift diffusion (DD) and density gradient (DG) models will be provided. In addition, the main principles of the time-dependent defect spectroscopy (TDDS), which is now used as the main experimental technique to characterize single defects in nanoscale MOSFETs, will be discussed. Chapter 3 provides an overview of the main reliability issues in modern Si MOSFETs, followed by a description of the analytical models used for their modeling. Most essential in the context of this work are the universal relaxation model, the capture/emission time (CET) map model, and the four-state non-radiative multiphonon (NMP) model, all of which are discussed in detail. The main idea is that although the described models have been previously developed for Si MOSFETs, they will be useful for understanding of BTI and HCD in next-generation 2D technologies. In Chapter 4 a brief review of 2D materials (graphene, MoS2, hexagonal boron nitride [hBN] and others) and their properties will be provided. This will be accompanied by an overview of previous research on graphene and MoS2 FETs and their reliability. The next three chapters describe the results obtained within this work. Chapter 5 is devoted to characterization and modeling of single defects in modern nanoscale Si MOSFETs. The simulation results obtained for similar devices with a single trap and a number of configurations of randomly distributed discrete dopants are discussed. Based on comparison of these results with experimental data obtained using TDDS, a technique allowing for the evaluation of the lateral trap position with a high accuracy is derived. Chapter 6 includes a detailed analysis of BTI and HCD in graphene FETs. The experimentally measured stress/recovery data for both issues are shown to agree with universal relaxation and CET map models developed for Si technologies. Moreover, a detailed classification of HCD mechanisms in graphene FETs is provided, in particular with the help of the adjusted DD model. The results on hysteresis stability and BTI analysis in MoS2 FETs with SiO2 and hBN insulators can be found in Chapter 7. While BTI results are accompanied by modeling using the universal relaxation model, it is also shown that the reliability characteristics of MoS2 FETs can be reproduced using our simulator Minimos-NT employing the four-state NMP model. Finally, the main results are summarized.