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In this thesis, we contribute to the understanding of electronic and optical properties of 2-dimensional materials, with a strong focus on graphene-based nanostructures \cite{graphene_book}. The thesis is structured into eight chapters, starting with an introduction and ending with a conclusion. In chapter 2, we present the methods used throughout this thesis. We start by introducing the tight-binding model to understand the single-particle properties of graphene, bilayer graphene, and graphene quantum dots. We then introduce configuration interaction, the Hubbard model, the Bethe-Salpeter equation, and Hartree-Fock as tools for tackling the interacting problem and correlated electron systems. We also discuss numerical methods, including techniques for addressing the numerical complications that arise when working with the many-body problem such as the calculation of Coulomb matrix elements. In chapter 3, we present a new approach to the energy spectra of $p_z$ electrons in small hexagonal graphene quantum dots. This approach is analytical, and allows us to predict the dependence of the energy gap on size and edge type. In chapter 4, we describe a proposal of a quantum simulator of an extended bipartite highly tunable Hubbard model with broken sublattice symmetry inspired by graphene. We predict the electronic and magnetic properties of a small simulator. The proposed simulator, allows us to study the ground state of the Hubbard Hamiltonian for a broad range of regimes accessible due to the high tunability of the simulator. In chapter 5, we study the electronic properties of quasi 2-dimensional quantum dots made of topological insulators using HgTe. We show that in a square HgTe quantum dot one set of material parameters defines the topologically nontrivial case, in which topologically protected edge states are found, and another set of parameters defines a topologically trivial regime corresponding to a trivial insulator without edge states. In chapter 6, we examine excitons in AB-stacked gated bilayer graphene (BLG) quantum dots (QDs). We confine both electrons and holes using gates and demonstrate that excitons can exist in the BLG QD. We predict absorption to occur in the terahertz regime and find that low-energy excitons are dark. In chapter 7, we determine the many-body states of massive Dirac Fermions confined in a bilayer graphene lateral gated quantum dot. Tuning the strength of Coulomb interactions versus the single-particle level spacing we predict the existence of spontaneously spin and valley symmetry-broken states of interacting massive Dirac Fermions.

Atomically thin 2D materials have gained the interest of the scientific community in the past decade due to their exotic electronic and optoelectronic properties, thus emerging as potential candidates for the next generation of nano-devices. Quantum confinement in one of the dimensions is the primary reason for these exotic properties. However, it has been seen that these properties are widely inconsistent, and they are controlled by variety of factors such as material synthesis, device fabrication, testing environment, etc. Due to low dimensional nature of these materials, defects are inevitable. These defects typically originate from either the presence of bulk impurities or interface between sample and substrate. These defects manifest as mid-gap states in semiconductor channel and act as trapping centers for charge carriers, thus often referred to as trap states. The presence of trap states is not necessarily a detrimental thing. In this dissertation, I will focus on the role these trap states play in the emergence of a few electronic and optoelectronic properties.High responsivity (R) in photodetectors based on 2D materials is mainly associated with a presence of photogating effect in which trap states dynamics plays a crucial role. Photogating also results in fractional power (γ) dependence of the photocurrent (Iph) on an effective illumination intensity (Peff). Chapter 2 presents photoconductivity studies of few layers of rhenium diselenide (ReSe2) based field-effect transistors (FETs) over a wide range of applied gate voltages (-48 V ≤ Vg ≤ 60 V) and temperature (20 K ≤ T ≤ 300 K). A very high responsivities ≈ 16500 A/W and external quantum efficiency (EQE) ~ 106 % (at 140 K, Vg = 60 V and Peff = 0.2 nW) was obtained. Investigating R and γ at various gate voltages and over a wide range of temperatures leads to a strong correlation between R and γ. Such correlations indicate the importance of trap states and photogating in governing high responsivities in these materials. It is expected that thicker samples will aid in photoconduction by effectively increasing photon absorption. In chapter 3, a layer dependent study of optoelectronic properties of indium selenide (InSe) based FETs shows that responsivity decreases for thicker InSe devices. In these devices, photogating remains constant (similar γ) and responsivity depends predominately upon field-effect mobility (μFE). Interlayer resistance regulates the mobility and (consequentially) responsivity. Thus, mobility dominates the responsivity and trap states play second fiddle. The presence of metal−insulator transition (MIT) in two-dimensional (2D) systems leads to tunable material properties by regulating parameters such as charge carrier density. Chapter 4 shows our observation on MIT in the 2D copper indium selenide (CuIn7Se11) flakes by electrostatic doping via the SiO2 back gate. A temperature and gate voltage dependence of conductivity (σ) of CuIn7Se11 FET shows clear evidence of the metallic and insulating phase. Evidence of 2D variable-range hopping (VRH) and percolation critical conductivity confirms the presence of charge density inhomogeneity originating from trap states. The low effective mass and high dielectric of copper indium selenide systems result in a lower critical charge carrier density required for percolation-driven MIT, attended by conventional SiO2 dielectric gate. Even though findings reported in this dissertation are performed on specific materials, fundamental understandings can be easily extrapolated to other 2D systems. Understanding the role of trap states will provide valuable insights for the design and development of high-performance devices using 2D materials.

Yes / MXenes (viz., transition metal carbides, carbonitrides, and nitrides) have emerged as a new subclass of 2D materials. Due to their outstanding physicochemical and biological properties, MXenes have gained much attention in the biomedical field in recent years, including drug delivery systems, regenerative medicine, and biosensing. Additionally, the incorporation of MXenes into hydrogels has garnered significant interest in biomedical engineering as an electroactive and mechanical nanoreinforcer capable of converting nonconductive scaffolds into excellent conductors of electricity with an impressive effect on mechanical properties for the engineering of electroactive organs and tissues such as cardiac, skeletal muscle, and nerve. However, many questions and problems remain unresolved that need to be answered to usher these 2D materials toward their true destiny. Thus, this review paper aims to provide an overview of the design and applications of MXene-integrated composites for biomedical applications, including cardiac tissue engineering, wound healing, infection therapy, cancer therapy, and biosensors. Moreover, the current challenges and limitations of utilizing MXenes in vivo are highlighted and discussed, followed by its prospects as a guideline toward possible various futuristic biomedical applications. This review article will inspire researchers, who search for properties, opportunities, and challenges of using this 2D nanomaterial in biomedical applications. / Open Access Funding provided by Istituto Italiano di Tecnologia within the CRUI-CARE Agreement.

yes / 2D materials such as graphene, LAPONITE® clays or molybdenum disulfide nanosheets are of extremely high interest to the materials community as a result of their high surface area and controllable surface properties. While several methods to access 2D inorganic materials are known, the investigation of 2D organic nanomaterials is less well developed on account of the lack of ready synthetic accessibility. Crystallization-driven self-assembly (CDSA) has become a powerful method to access a wide range of complex but precisely-defined nanostructures. The preparation of 2D structures, however, particularly those aimed towards biomedical applications, is limited, with few offering biocompatible and biodegradable characteristics as well as control over self-assembly in two dimensions. Herein, in contrast to conventional self-assembly rules, we show that the solubility of polylactide (PLLA)-based amphiphiles in alcohols results in unprecedented shape selectivity based on unimer solubility. We use log Poct analysis to drive solvent selection for the formation of large uniform 2D diamond-shaped platelets, up to several microns in size, using long, soluble coronal blocks. By contrast, less soluble PLLA-containing block copolymers yield cylindrical micelles and mixed morphologies. The methods developed in this work provide a simple and consistently reproducible protocol for the preparation of well-defined 2D organic nanomaterials, whose size and morphology are expected to facilitate potential applications in drug delivery, tissue engineering and in nanocomposites. / University of Warwick, Materials GRP, EPSRC, The Royal Society, ERC

Atomically thin two-dimensional (2D) materials come in all necessary flavors to make semiconductor devices: conductors, semiconductors, and insulators. Graphene, transition metal dichalcogenides (TMDCs), and hexagonal boron nitride (hBN) are the quintessential building blocks. The van der Waals nature of the bonds in 2D films allows the ability to stack materials to achieve novel properties because of their exceptional mechanical, electronic, and optical properties and interactions, which enables various applications of 2D materials in transistors, biosensors, light-emitting devices, and photodetectors. Spectroscopic measurements such as Raman and photoluminescence (PL) reveal a wealth of information since 2D materials are affected by their environment and other local perturbations, e.g., strain and charge doping. My research focused on developing efficient and noninvasive optical methods to evaluate and characterize the properties of 2D materials. In particular, we investigated strain-tunable properties, the effects and signature of charge doping, and the environmental screening properties of graphene and TMDCs. Identifying the charge density and impurities in graphene is vital for graphene-based applications, which require high-quality graphene. I developed an effective optical method to determine the doping level and the local charge density variations in graphene before any fabrication process. This method differentiates charge density variations in graphene via the Raman 2D peak asymmetry that manifests at low charge 1-25 × 1010 cm-2. We explore the effect of charge inhomogeneity, "charge puddles", within the laser spot using simulated Raman 2D spectra, revealing a different signature for large or small charge puddles. Our work provides a simple and noninvasive optical method for estimating the doping level, local charge density variation, and transport properties of graphene, with up to two orders of magnitude higher precision than previously reported optical methods. Strain is another crucial factor that significantly impacts the properties of 2D materials. We studied the charge distribution and radiative efficiency of excitonic complexes in strained monolayer TMDCs, especially WSe2. Straining and electrostatic gating are combined to investigate the dynamics of quasi-particles in WSe2. We found that negative trions accumulate while positive trion emission is near zero, indicating that both conduction and valence bands are bent downwards in the strained area. Finite element analysis of strain distribution and density functional theory calculations of band structures of WSe2 support the experimental results. Hence, localized strain allows locally separating electrons and holes in WSe2 and manipulating light-matter interaction for applications in novel strained-engineered optoelectronics. I applied machine learning and deep learning techniques to improve the efficiency and accuracy of data processing and analysis since traditional methods require domain expertise and have the potential to introduce artifacts. I categorized the wealth of information and data by applying machine learning to spectroscopic information to separate different influences, e.g., strain, charge doping, and dielectric environment. We developed deep learning models to classify graphene Raman spectra according to different charge densities and dielectric environments. To improve the accuracy and generalization of all models, we use data augmentation through additive noise and peak shifting. Using a convolutional neural net (CNN) model, we demonstrated the spectra classification with 99% accuracy. Our approach has the potential for fast and reliable estimation of graphene doping levels and dielectric environments. The proposed model paves the way for achieving efficient analytical tools to evaluate the properties of graphene. / 2022-11-23T00:00:00Z