A deep investigation into the structure of carbon dots

Since their discovery, carbon dots (CDs) have been a promising nanomaterial in a variety of fields including nanomedicine. Despite their potential in this area, there are many obstacles to overcome for CDs to be approved for biomedical use. One major hindrance to CDs’ approval is related to their poorly defined structure. Herein a structural study of CDs is presented in order to rectify this shortcoming. The properties of three CDs which have significant promise in biomedical applications, black CDs (B-CDs), carbon nitride dots (CNDs), and yellow CDs (Y-CDs), are compared in order to develop a coherent structural model for each nanosystem. Absorption coefficients were measured for each system and this data gave insight on the level of disorder in each system. Furthermore, extensive structural characterization has been performed in order to derive structural information for each system. This data showed that B-CDs and CNDs are functionalized to a greater degree and are also more disordered and amorphous than Y-CDs. These techniques were used to develop a structural model consistent with the obtained data and what is known for carbonic nanostructures. These models can be used to analyze CD emission properties and to better understand the structure-property relationship in CDs

Development of sample preparation and chromatographic mass spectrometric techniques for determination of selected organic pollutants in wastewater

Abstract : In the recent past, there has been a great concern on the ever-increasing emergence of organic contaminants in the various environmental compartments, that pose great health concerns to humans and aquatic life. These organic pollutants have been ubiquitous in the environment for decades, however, they were not identifiable until the emergence of new and advanced analytical technologies. Therefore, the main objective of this study was to develop robust and efficient analytical and modelling techniques, for the extraction and analysis of selected multiclass organic contaminants from wastewater samples. This is because their analytical determination is very challenging due to their occurrence in trace levels (ng L-1 to μg L-1) in the environment. The analytical techniques comprise of optimization of both the sample preparation procedures and instrumental analysis for detection and quantification. Solid phase extraction (SPE), dispersive liquid-liquid microextraction (DLLME) and ultrasonic-assisted magnetic solid phase dispersive extraction (UA-MSPDE) were the selected sample preparation techniques used for the extraction and preconcentration of methylparaben, ethylparaben, propylparaben, ethoprofos, parathion methyl, azinphos methyl and chlorpyrifos in water samples. This was followed by instrumental analysis for their detection and quantification using liquid chromatography tandem mass spectrometry (LC-MS/MS). The developed analytical techniques were applied in real environmental samples obtained from different water treatment stages of a local wastewater treatment plant in Gauteng province, South Africa. Experimental factors that had an influence on the analytical response in terms on highest percentage recoveries were optimized using both univariate (one factor a time) and multivariate approach for all the experiments in this study. Multivariate optimization was accomplished using Statistica and Minitab software. The performance characteristics of the LC-MS/MS facilitated the determination of these organic contaminants at trace levels. Multiple reaction monitoring mode (MRM) was used for specific and sensitive targeted analysis, where the quadrupole analyzers were set at multiple ion frequencies for the specific analytes under investigation together with their product fragment ions. MRM is ideally suitable for trace level analysis of complex mixtures. Oasis HLB cartridges were found to be suitable for extraction of parabens giving satisfactory results. Vortex assisted dispersive liquid-liquid microextraction (VA-DLLME) was used for the extraction and enrichment of organophosphorus pesticides in wastewater samples. Selection of the appropriate organic solvent (extractant and disperser solvents) used for this method was of utmost importance and was performed using univariate optimization. v The results revealed chloroform to be the most suitable extractant solvent while acetone was the optimum disperser solvent. This was followed by the chemometric optimization of the independent variables that significantly affect the outcome of the analytical response. The organophosphorus compounds that were extracted in wastewater samples using this technique with satisfactory results were ethoprofos, parathion methyl and azinphos methyl. Also, a novel method was developed for the extraction and preconcentration of multiclass organic compounds (parabens and organophosphorus pesticides) using synthesized pristine carbon nanodots (CNDs) applied as SPE adsorbent. A comparison between the synthesized CNDs and commercial based SPE sorbent was analyzed. Two-level factorial design and response surface methodology based on central composite design were used for multivariate optimization of the experimental variables. Furthermore, the CNDs were also functionalized with magnetite. The magnetic CNDs were applied for the development of magnetic solid phase dispersive extraction method with ultrasonic dispersion for the simultaneous extraction of chlorpyrifos and triclosan in environmental water samples. This method offered a very rapid and simple extraction and preconcentration of these organic contaminants with satisfactory results.Ph.D. (Chemistry

Fragmentation of explosively metastable glass [post-print]

An unusual form of glass with bulbous head and thin tail, known as Rupert\u27s drops, can withstand high impact or pressure applied to the head, but explodes instantly into small particles when the tail is broken. The mechanism is not well understood. To examine this, we performed macro- and microstatistical analyses of a sample of 500 g of fragments of exploded Rupert\u27s drops to determine the mass and particle distributions and associated fractal dimensions. To our knowledge, this is the first such statistical study of the fragmentation of a metastable material with large internal energy. The resulting fractal dimensionD = 1.06 ± 0.09, derived from the scaling region of the mass and particle distribution functions approximated by power laws, differs from fractal dimensions (usually ≥2) previously reported for many brittle materials. The observed distribution functions place constraints on proposed mechanisms for the explosive disintegration of the drops and presumably other physical systems characterized by high compressive stress at the surface and tensile stress within the core

Hyperelastic and elastic-plastic approaches for modelling uniaxial tensile performance of woven fabrics / Yahya, M.F. and Chen, X.

This article presents thefindings ofexperimental andfinite element simulation warp direction uniaxial tensile testing ofplain 1/1, 2/2 twill and 8 ends satin woven fabrics with respect to a wovenfabric model developed in IGES using UniverFilter. Woven fabrics have been specifically configured as a balanced weave thereby allowing systematic investigation of the effect of uniaxial tensile stress on the weave. Static automatic incrementation of large representative volume elements has enabled characterisation ofthe response oftwo-dimensional woven fabrics under uniaxial tensile stress with respect to hyperelastic and elastic-plastic material properties. Plain 1/1 and 8 ends satin woven fabrics were well-described by the hyperelastic model and the elastic-plastic model predicted extended strain percentages. The modelling indicates that satin woven fabric possesses the lowest strain distribution and compression stress in the unloaded weft direction compared to plain and twill woven fabrics

Design of a reusable kinetic energy absorber for an astronaut safety tether to be used during extravehicular activities on the Space Station

The goal of this project is to design a reusable safety device for a waist tether which will absorb the kinetic energy of an astronaut drifting away from the Space Station. The safety device must limit the tension of the tether line in order to prevent damage to the astronaut's space suit or to the structure of the spacecraft. The tether currently used on shuttle missions must be replaced after the safety feature has been developed. A reusable tether for the Space Station would eliminate the need for replacement tethers, conserving space and mass. This report presents background information, scope and limitations, methods of research and development, alternative designs, a final design solution and its evaluation, and recommendations for further work

A study of nuclear plant heat rate optimization using nonlinear artificial intelligence and linear statistical analysis models

The emphasis of this dissertation is on developing methods by which a combination of multivariate analysis techniques (MAT) and artificial intelligence (Al) procedures can be adapted to on-line, real time monitoring systems for improving nuclear plant thermal efficiency. Present-day first principle models involve performing a heat balance of plant systems and the reactor coolant system. Typical variables involved in the plant data acquisition system usually number one-to-two thousand. The goal of the current work is twofold. First, simulate the heat rate with MAT and Al computer models. The second objective is to selectively reduce the number of predictors to only the most important variables, induce small perturbations around normal operating levels, and evaluate changes in the magnitude of plant efficiency. It is anticipated that making small changes will improve the thermal efficiency of the plant and lead to supplementary cost savings. Conclusions of this report are several. A sensitivity analysis showed the reduction of input variables by dimensionality reduction, i.e., principal component analysis or factor analysis, removes valuable information. Predictors can simply be eliminated from the input space, but dimensionality reduction of the input matrix is not an alternative option. However, perturbation modeling does require data to be standardized and collinear variables removed. Filtering of input data is not recommended except to remove outliers. It\u27s ascertained that perturbation or sensitivity analysis differs from prediction modeling in that two additional requirements are necessary besides the criterion prediction. One is the magnitude of the criterion result given an input perturbation, and second, is the directionality of the model. Directionality is defined as the positive or negative movement of the heat rate (criterion) given a predetermined increase/decrease in predictor value, or input perturbation. While the criterion prediction is still important, it is directionality that determines whether a model is capturing proper changes in system process information. Final results showed that although the secondary-side of a nuclear plant might meet thermodynamic conditions for a steady-flow system, temporal information is needed by the model in order to capture system process information. Modeling of the data is governed by quasi-static range theory, which states data must be closely spaced (in time) and prior temporal information is necessary. The conclusion reached is the perturbation model of a nuclear plant is a time-dependent, dynamic system; all indications as of date show it is also nonlinear. Hence a time-dependent nonlinear modeling method, such as a neural network with time delayed inputs, is needed for sensitivity modeling