First-principles Study of Structural and Optical Properties of Novel Materials

Novel materials, including two-dimensional (2D) materials, ferroelectric materials, as well as hybrid perovskites materials, have attracted tremendous attention in recent years because of their unique structural symmetries and electronic structures. Among them, 2D materials, such as graphene, black phosphorene, and transition metal dichalcogenides (TMDs), etc., have great potentials for nanoelectronics and optical applications. Particularly, these 2D materials can sustain much larger strain than their bulk counterparts, making strain a unique and efficient tool to tune a wide range of properties of 2D structures. In the first part of this thesis, we explore how strain tunes quasiparticle energy and excitonic effects of typical 2D materials, including black phosphorus and monolayer 2H-phase TMDs, i.e., MoS2, MoSe2, WS2, and WSe2. Beyond the widely studied uniaxial and biaxial strain, we expand the research to arbitrarily axial strains and find complicated variations of quasiparticle band gaps, band-edge energies, direct-indirect gap transitions, and exciton energies. These results provide a complete picture for straining engineering of electronic structures and optical spectra of 2D TMDs. The second part of this thesis focuses on the electronic polarization of non-centrosymmetric layered van der Waals (vdW) metal chalcogen-diphosphates MCDs, especially on CuInP2Se6. We employ first-principles modern-polarization theory to study the electrical polarization ordering and build an electrostatic-energy model to explore the effects of boundary conditions. We find the existence of intrinsic off-plane polarization of CuInP2Se6, with an antiferroelectric (AFE) ground state for monolayer and ferroelectric state (FE) ground state for bulk under the open-circuit boundary condition. However, for close-circuit boundary condition, we find that the ground state is always FE through bulk to monolayer. We also apply Monte Carlo simulations to obtain the FE Curie temperature and electric hysteresis. This study gives hope to overcoming the depolarization effect and realizing ultra-thin FE transistors and memories based on vdW materials. In the last part, we focus on nonlinear optical properties of a novel family of materials, organic-inorganic hybrid perovskites materials. We have developed a high-efficient, large-scale parallel simulation tool (NLOPACK), making it possible to explore the nonlinear optical properties of a family of organic-inorganic hybrid halide perovskites, CH3NH3MX3 (M= Ge, Sn, Pb; X=Cl, Br, I), which contains a large number of atoms and cannot be handled by traditional simulation packages. We employ this code and find significant second harmonic generation (SHG) and linear electro-optic (LEO) effect in the cubic phase of CH3NH3SnI3, in which those effects are comparable with those widely used organic/inorganic nonlinear optical materials. The reason for these enhanced nonlinear optical properties in hybrid perovskites is explained as well. This work will motivate experimental efforts to fabricate hybrid perovskites for low-cost, nonlinear-optical device implementations

Preliminary study on a predacious natural enemy, Broad vein-longitudinal striped ladybug Brumoides lineatus (Weise)

Originating text in Chinese.Citation: Weng, Wenshen, Huang, Yuqing. (1988). Preliminary study on a predacious natural enemy, Broad vein-longitudinal striped ladybug Brumoides lineatus (Weise). Entomological Knowledge, 25, 105-108

Development of electronic nose for detection of micro-mechanical damages in strawberries

A self-developed portable electronic nose and its classification model were designed to detect and differentiate minor mechanical damage to strawberries. The electronic nose utilises four metal oxide sensors and four electrochemical sensors specifically calibrated for strawberry detection. The selected strawberries were subjected to simulated damage using an H2Q-C air bath oscillator at varying speeds and then stored at 4°C to mimic real-life mechanical damage scenarios. Multiple feature extraction methods have been proposed and combined with Principal Component Analysis (PCA) dimensionality reduction for comparative modelling. Following validation with various models such as SVM, KNN, LDA, naive Bayes, and subspace ensemble, the Grid Search-optimised SVM (GS-SVM) method achieved the highest classification accuracy of 0.84 for assessing the degree of strawberry damage. Additionally, the Feature Extraction ensemble classifier achieved the highest classification accuracy (0.89 in determining the time interval of strawberry damage). This experiment demonstrated the feasibility of the self-developed electronic nose for detecting minor mechanical damage in strawberries