High efficiency quantum dot-sensitised solar cells by material science and device architecture

This thesis studied cadmium sulfide and cadmium selenide quantum dots and their performance as light absorbers in quantum dot-sensitised solar cells. This research has made contributions to the understanding of size dependent photodegradation, passivation and particle growth mechanism of cadmium sulfide quantum dots using SILAR method and the role of ZnSe shell coatings on solar cell performance improvement.

Factors influencing robustness and effectiveness of conditional random fields in active learning frameworks

Active learning approaches reduce the annotation cost required by traditional supervised approaches to reach the same effectiveness by actively selecting informative instances during the learning phase. However, effectiveness and robustness of the learnt models are influenced by a number of factors. In this paper we investigate the factors that affect the effectiveness, more specifically in terms of stability and robustness, of active learning models built using conditional random fields (CRFs) for information extraction applications. Stability, defined as a small variation of performance when small variation of the training data or a small variation of the parameters occur, is a major issue for machine learning models, but even more so in the active learning framework which aims to minimise the amount of training data required. The factors we investigate are a) the choice of incremental vs. standard active learning, b) the feature set used as a representation of the text (i.e., morphological features, syntactic features, or semantic features) and c) Gaussian prior variance as one of the important CRFs parameters. Our empirical findings show that incremental learning and the Gaussian prior variance lead to more stable and robust models across iterations. Our study also demonstrates that orthographical, morphological and contextual features as a group of basic features play an important role in learning effective models across all iterations.

Hydraulic conductivity fields: Gaussian or not?

Hydraulic conductivity (K) fields are used to parameterize groundwater flow and transport models. Numerical simulations require a detailed representation of the K field, synthesized to interpolate between available data. Several recent studies introduced high-resolution K data (HRK) at the Macro Dispersion Experiment (MADE) site, and used ground-penetrating radar (GPR) to delineate the main structural features of the aquifer. This paper describes a statistical analysis of these data, and the implications for K field modeling in alluvial aquifers. Two striking observations have emerged from this analysis. The first is that a simple fractional difference filter can have a profound effect on data histograms, organizing non-Gaussian ln K data into a coherent distribution. The second is that using GPR facies allows us to reproduce the significantly non-Gaussian shape seen in real HRK data profiles, using a simulated Gaussian ln K field in each facies. This illuminates a current controversy in the literature, between those who favor Gaussian ln K models, and those who observe non-Gaussian ln K fields. Both camps are correct, but at different scales.

Dual compressible hybrid quantum secret sharing schemes based on extended unitary operations

A crucial issue with hybrid quantum secret sharing schemes is the amount of data that is allocated to the participants. The smaller the amount of allocated data, the better the performance of a scheme. Moreover, quantum data is very hard and expensive to deal with, therefore, it is desirable to use as little quantum data as possible. To achieve this goal, we first construct extended unitary operations by the tensor product of n, n ≥ 2, basic unitary operations, and then by using those extended operations, we design two quantum secret sharing schemes. The resulting dual compressible hybrid quantum secret sharing schemes, in which classical data play a complementary role to quantum data, range from threshold to access structure. Compared with the existing hybrid quantum secret sharing schemes, our proposed schemes not only reduce the number of quantum participants, but also the number of particles and the size of classical shares. To be exact, the number of particles that are used to carry quantum data is reduced to 1 while the size of classical secret shares also is also reduced to l−2 m−1 based on ((m+1, n′)) threshold and to l−2 r2 (where r2 is the number of maximal unqualified sets) based on adversary structure. Consequently, our proposed schemes can greatly reduce the cost and difficulty of generating and storing EPR pairs and lower the risk of transmitting encoded particles.

Exploiting parallax in panoramic capture to construct light fields

We show that the parallax motion resulting from non-nodal rotation in panorama capture can be exploited for light field construction from commodity hardware. Automated panoramic image capture typically seeks to rotate a camera exactly about its nodal point, for which no parallax motion is observed. This can be difficult or impossible to achieve due to limitations of the mounting or optical systems, and consequently a wide range of captured panoramas suffer from parallax between images. We show that by capturing such imagery over a regular grid of camera poses, then appropriately transforming the captured imagery to a common parameterisation, a light field can be constructed. The resulting four-dimensional image encodes scene geometry as well as texture, allowing an increasingly rich range of light field processing techniques to be applied. Employing an Ocular Robotics REV25 camera pointing system, we demonstrate light field capture,refocusing and low-light image enhancement.

Quantum cognition: A new theoretical approach to psychology

What type of probability theory best describes the way humans make judgments under uncertainty and decisions under conflict? Although rational models of cognition have become prominent and have achieved much success, they adhere to the laws of classical probability theory despite the fact that human reasoning does not always conform to these laws. For this reason we have seen the recent emergence of models based on an alternative probabilistic framework drawn from quantum theory. These quantum models show promise in addressing cognitive phenomena that have proven recalcitrant to modeling by means of classical probability theory. This review compares and contrasts probabilistic models based on Bayesian or classical versus quantum principles, and highlights the advantages and disadvantages of each approach.

Aspect-based opinion mining from product reviews using conditional random fields

Product reviews are the foremost source of information for customers and manufacturers to help them make appropriate purchasing and production decisions. Natural language data is typically very sparse; the most common words are those that do not carry a lot of semantic content, and occurrences of any particular content-bearing word are rare, while co-occurrences of these words are rarer. Mining product aspects, along with corresponding opinions, is essential for Aspect-Based Opinion Mining (ABOM) as a result of the e-commerce revolution. Therefore, the need for automatic mining of reviews has reached a peak. In this work, we deal with ABOM as sequence labelling problem and propose a supervised extraction method to identify product aspects and corresponding opinions. We use Conditional Random Fields (CRFs) to solve the extraction problem and propose a feature function to enhance accuracy. The proposed method is evaluated using two different datasets. We also evaluate the effectiveness of feature function and the optimisation through multiple experiments.

Post-quantum key exchange for the TLS protocol from the ring learning with errors problem

Lattice-based cryptographic primitives are believed to offer resilience against attacks by quantum computers. We demonstrate the practicality of post-quantum key exchange by constructing cipher suites for the Transport Layer Security (TLS) protocol that provide key exchange based on the ring learning with errors (R-LWE) problem, we accompany these cipher suites with a rigorous proof of security. Our approach ties lattice-based key exchange together with traditional authentication using RSA or elliptic curve digital signatures: the post-quantum key exchange provides forward secrecy against future quantum attackers, while authentication can be provided using RSA keys that are issued by today's commercial certificate authorities, smoothing the path to adoption. Our cryptographically secure implementation, aimed at the 128-bit security level, reveals that the performance price when switching from non-quantum-safe key exchange is not too high. With our R-LWE cipher suites integrated into the Open SSL library and using the Apache web server on a 2-core desktop computer, we could serve 506 RLWE-ECDSA-AES128-GCM-SHA256 HTTPS connections per second for a 10 KiB payload. Compared to elliptic curve Diffie-Hellman, this means an 8 KiB increased handshake size and a reduction in throughput of only 21%. This demonstrates that provably secure post-quantum key-exchange can already be considered practical.

Enhanced electron lifetime of CdSe/CdS quantum dot (QD) sensitized solar cells using ZnSe core–shell structure with efficient regeneration of quantum Ddots

Research on development of efficient passivation materials for high performance and stable quantum dot sensitized solar cells (QDSCs) is highly important. While ZnS is one of the most widely used passivation material in QDSCs, an alternative material based on ZnSe which was deposited on CdS/CdSe/TiO2 photoanode to form a semi-core/shell structure has been found to be more efficient in terms of reducing electron recombination in QDSCs in this work. It has been found that the solar cell efficiency was improved from 1.86% for ZnSe0 (without coating) to 3.99% using 2 layers of ZnSe coating (ZnSe2) deposited by successive ionic layer adsorption and reaction (SILAR) method. The short circuit current density (Jsc) increased nearly 1-fold (from 7.25 mA/cm2 to13.4 mA/cm2), and the open circuit voltage (Voc) was enhanced by 100 mV using ZnSe2 passivation layer compared to ZnSe0. Studies on the light harvesting efficiency (ηLHE) and the absorbed photon-to-current conversion efficiency (APCE) have revealed that the ZnSe coating layer caused the enhanced ηLHE at wavelength beyond 500 nm and a significant increase of the APCE over the spectrum 400−550 nm. A nearly 100% APCE was obtained with ZnSe2, indicating the excellent charge injection and collection process in the device. The investigation on charge transport and recombination of the device has indicated that the enhanced electron collection efficiency and reduced electron recombination should be responsible for the improved Jsc and Voc of the QDSCs. The effective electron lifetime of the device with ZnSe2 was nearly 6 times higher than ZnSe0 while the electron diffusion coefficient was largely unaffected by the coating. Study on the regeneration of QDs after photoinduced excitation has indicated that the hole transport from QDs to the reduced species (S2−) in electrolyte was very efficient even when the QDs were coated with a thick ZnSe shell (three layers). For comparison, ZnS coated CdS/CdSe sensitized solar cell with optimum shell thickness was also fabricated, which generated a lower energy conversion efficiency (η = 3.43%) than the ZnSe based QDSC counterpart due to a lower Voc and FF. This study suggests that ZnSe may be a more efficient passivation layer than ZnS, which is attributed to the type II energy band alignment of the core (CdS/CdSe quantum dots) and passivation shell (ZnSe) structure, leading to more efficient electron−hole separation and slower electron recombination.

Modelling of Electric Fields

South Africa has an electrical transmission grid of over 25 000 km of overhead power lines with voltages of 132 kV to 765 kV. The grid has been largely designed and built by the power utility, Eskom. This book embodies the planning philosophies, design principles and construction practices of Eskom. It is the culmination of decades of thought, study, research and the practical experience of many overhead power line engineers and researchers. The book covers the main aspects of overhead power line design and construction, from electrical first principles, system planning, insulation co-ordination (including live line working), mechanical design through to environmental impact management and power line communications. The content emphasises the need for close interaction between all technical disciplines involved and the importance of optimising designs for economy and performance. Additional challenges in South Africa are the relatively high altitude of the interior plateau (1 000 m to 1 700 m above sea level), severe lightning in some areas and long transmission distances. The book explains how these factors are accommodated in modern designs. Other advanced work covered includes the use and understanding of polymeric insulators, the judicious reduction of phase-to-phase spacings and the adoption of guyed structures.

Group 14 element-based non-centrosymmetric quantum spin hall insulators with large bulk gap

To date, a number of two-dimensional (2D) topological insulators (TIs) have been realized in Group 14 elemental honeycomb lattices, but all are inversionsymmetric. Here, based on first-principles calculations, we predict a new family of 2D inversion-asymmetric TIs with sizeable bulk gaps from 105 meV to 284 meV, in X2–GeSn (X = H, F, Cl, Br, I) monolayers, making them in principle suitable for room-temperature applications. The nontrivial topological characteristics of inverted band orders are identified in pristine X2–GeSn with X = (F, Cl, Br, I), whereas H2–GeSn undergoes a nontrivial band inversion at 8% lattice expansion. Topologically protected edge states are identified in X2–GeSn with X = (F, Cl, Br, I), as well as in strained H2–GeSn. More importantly, the edges of these systems, which exhibit single-Dirac-cone characteristics located exactly in the middle of their bulk band gaps, are ideal for dissipationless transport. Thus, Group 14 elemental honeycomb lattices provide a fascinating playground for the manipulation of quantum states.

Mapping bound plasmon propagation on a nanoscale stripe waveguide using quantum dots: Influence of spacer layer thickness

In this paper we image the highly confined long range plasmons of a nanoscale metal stripe waveguide using quantum emitters. Plasmons were excited using a highly focused 633 nm laser beam and a specially designed grating structure to provide stronger incoupling to the desired mode. A homogeneous thin layer of quantum dots was used to image the near field intensity of the propagating plasmons on the waveguide. We observed that the photoluminescence is quenched when the QD to metal surface distance is less than 10 nm. The optimised spacer layer thickness for the stripe waveguides was found to be around 20 nm. Authors believe that the findings of this paper prove beneficial for the development of plasmonic devices utilising stripe waveguides.

A rapid and label-free dual detection of Hg (II) and cysteine with the use of fluorescence switching of graphene quantum dots

A simple and rapid method of analysis for mercury ions (Hg2+) and cysteine (Cys) was developed with the use of graphene quantum dots (GQDs) as a fluorescent probe. In the presence of GQDs, Hg2+ cations are absorbed on their negatively charged surface by means of electrostatic interactions. Thus, the fluorescence (FL) of the GQDs would be significantly quenched as a result of the FL charge transfer, e.g. 92% quenching at 450 nm occurs for a 5 μmol L−1 Hg2+ solution. However, when Cys was added, a significant FL enhancement was observed (510% at 450 nm for a 8.0 μmol L−1 Cys solution), and Hg2+ combined with Cys rather than with the GQDs in an aqueous solution. This occurred because a strong metalsingle bondthiol bond formed, displacing the weak electrostatic interactions, and this resulted in an FL enhancement of the GQDs. The limits of detection (LOD) for Hg2+ and Cys were 0.439 nmol L−1 and 4.5 nmol L−1, respectively. Also, this method was used successfully to analyze Hg2+ and Cys in spiked water samples.