Nanocellulose as building block for novel materials

This thesis describes the fabrication of novel green materials using nanocellulose as the building block. Bacterial cellulose (BC) was used as the nanocellulose predominantly in this work. BC is highly crystalline pure cellulose with an inherent fibre diameter in the nano-scale. A single BC nanofibre was found to possess a Young’s modulus of 114 GPa. All these properties are highly favourable for using BC as a nanofiller/reinforcement in green nanocomposite materials. In this work, the surface of BC was rendered hydrophobic by grafting organic acids with various aliphatic chain lengths. These surface-modified BC was used as nanofiller for poly(L-lactide) (PLLA). Direct wetting measurements showed that the BC nanofibre-PLLA interface was improved due to the hydrophobisation of BC with organic acids. This led to the production of BC reinforced PLLA nanocomposites with improved tensile properties. Nanocellulose can also be obtained by grinding of wood pulp, producing nanofibrillated cellulose (NFC). The surface and bulk properties of one type of NFC and BC were compared in this work. Furthermore, the reinforcing ability of NFC and BC was also studied and it was observed that there is no significant difference in the mechanical performance of NFC or BC reinforced nanocomposites. A novel method based on slurry dipping to coat sisal fibres with BC was developed to modify the surface of natural fibres. This method can produce either (i) a densely BC coating layer or (ii) “hairy” BC coated sisal fibres. Randomly oriented short BC coated sisal fibre reinforced hierarchical composites were manufactured. It was found that hierarchical (nano)composites containing BC coated sisal fibres and BC dispersed in the matrix were required to produce composites with improved mechanical properties. This slurry dipping method was also extended to produce robust short sisal fibre preforms. By infusing this preform with a bio-based thermosetting resin followed by curing, green composites with significantly improved mechanical properties were produced. BC was also used as stabiliser and nano-filler for the production of macroporous polymers made by frothing of acrylated epoxidised soybean oil followed by microwave curing

Mass dimension one fermions from flag dipole spinors

According to the Lounesto classification, there are six classes of spinors. The Dirac and Weyl spinors belong to the first three and the sixth classes respectively. The remaining fourth and fifth classes are known as the flag dipole and flag pole spinors respectively. In this letter, a mass dimension one fermionic field with flag dipole spinors as expansion coefficients is constructed. These spinors are shown to be related to Elko (flag pole spinors) by a matrix transformation. It shows that the flag dipole spinors are generalizations of Elko. To construct a Lorentz-covariant quantum field, an infinitesimal deformation is applied to the spinor dual. Subsequently, we show that the fermionic fields constructed from Elko and flag dipole spinors are physically equivalent.Comment: 10 page

Reverse Engineering Environment for Teaching Secure Coding in Java

Few toolsets for program analysis and Java learning system provide an integrated console, debugger, and reverse engineered visualizer. We present an interactive debugging environment for Java which helps students to understand the secure coding by detecting and visualizing the data flow anomaly. Previous research shows that the earlier students learn secure coding concepts, even at the same time as they first learn to write code, the better they will continue using secure coding practices. This paper proposes web-based Java programming environment for teaching secure coding practices which provides the essential and fundamental skills in secure coding. Also, this tool helps students to understand the data anomaly and security leak with detecting vulnerabilities in given code.Cockrell School of Engineerin

Bounds on Quantum Multiple-Parameter Estimation with Gaussian State

We investigate the quantum Cramer-Rao bounds on the joint multiple-parameter estimation with the Gaussian state as a probe. We derive the explicit right logarithmic derivative and symmetric logarithmic derivative operators in such a situation. We compute the corresponding quantum Fisher information matrices, and find that they can be fully expressed in terms of the mean displacement and covariance matrix of the Gaussian state. Finally, we give some examples to show the utility of our analytical results.Comment: 7 pages, 5 figure