Effect of elemental composition and size on electron confinement in self-assembled SiC quantum dots : a combinatorial approach

A high level of control over quantum dot (QD) properties such as size and composition during fabrication is required to precisely tune the eventual electronic properties of the QD. Nanoscale synthesis efforts and theoretical studies of electronic properties are traditionally treated quite separately. In this paper, a combinatorial approach has been taken to relate the process synthesis parameters and the electron confinement properties of the QDs. First, hybrid numerical calculations with different influx parameters for Si1-x Cx QDs were carried out to simulate the changes in carbon content x and size. Second, the ionization energy theory was applied to understand the electronic properties of Si1-x Cx QDs. Third, stoichiometric (x=0.5) silicon carbide QDs were grown by means of inductively coupled plasma-assisted rf magnetron sputtering. Finally, the effect of QD size and elemental composition were then incorporated in the ionization energy theory to explain the evolution of the Si1-x Cx photoluminescence spectra. These results are important for the development of deterministic synthesis approaches of self-assembled nanoscale quantum confinement structures.

Deterministic control of plasma-assembled self-organized Ge/Si quantum dot arrays

Self-assembly of size-uniform and spatially ordered quantum dot (QD) arrays is one of the major challenges in the development of the new generation of semiconducting nanoelectronic and photonic devices. Assembly of Ge QD (in the ∼5-20 nm size range) arrays from randomly generated position and size-nonuniform nanodot patterns on plasma-exposed Si (100) surfaces is studied using hybrid multiscale numerical simulations. It is shown, by properly manipulating the incoming ion/neutral flux from the plasma and the surface temperature, the uniformity of the nanodot size within the array can be improved by 34%-53%, with the best improvement achieved at low surface temperatures and high external incoming fluxes, which are intrinsic to plasma-aided processes. Using a plasma-based process also leads to an improvement (∼22% at 700 K surface temperature and 0.1 MLs incoming flux from the plasma) of the spatial order of a randomly sampled nanodot ensemble, which self-organizes to position the dots equidistantly to their neighbors within the array. Remarkable improvements in QD ordering and size uniformity can be achieved at high growth rates (a few nms) and a surface temperature as low as 600 K, which broadens the range of suitable substrates to temperature-sensitive ultrathin nanofilms and polymers. The results of this study are generic, can also be applied to nonplasma-based techniques, and as such contributes to the development of deterministic strategies of nanoassembly of self-ordered arrays of size-uniform QDs, in the size range where nanodot ordering cannot be achieved by presently available pattern delineation techniques.

Surface fluxes of Si and C adatoms at initial growth stages of SiC quantum dots

Self-assembly of highly stoichiometric SiC quantum dots still remains a major challenge for the gas/plasma-based nanodot synthesis. By means of a multiscale hybrid numerical simulation of the initial stage (0.1-2.5 s into the process) of deposition of SiCSi (100) quantum dot nuclei, it is shown that equal Si and kst atom deposition fluxes result in strong nonstoichiometric nanodot composition due to very different surface fluxes of Si and C adatoms to the quantum dots. At this stage, the surface fluxes of Si and C adatoms to SiC nanodots can be effectively controlled by manipulating the SiC atom influx ratio and the Si (100) surface temperature. It is demonstrated that at a surface temperature of 800 K the surface fluxes can be equalized after only 0.05 s into the process; however, it takes more then 1 s at a surface temperature of 600 K. Based on the results of this study, effective strategies to maintain a stoichiometric ([Si] [C] =1:1) elemental ratio during the initial stages of deposition of SiCSi (100) quantum dot nuclei in a neutral/ionized gas-based process are proposed.

Tailoring the composition of self-assembled Si1−xCx quantum dots : simulation of plasma/ion-related controls

Precise control of composition and internal structure is essential for a variety of novel technological applications which require highly tailored binary quantum dots (QDs) with predictable optoelectronic and mechanical properties. The delicate balancing act between incoming flux and substrate temperature required for the growth of compositionally graded (Si1-xC x; x varies throughout the internal structure), core-multishell (discrete shells of Si and C or combinations thereof) and selected composition (x set) QDs on low-temperature plasma/ion-flux-exposed Si(100) surfaces is investigated via a hybrid numerical simulation. Incident Si and C ions lead to localized substrate heating and a reduction in surface diffusion activation energy. It is shown that by incorporating ions in the influx, a steady-state composition is reached more quickly (for selected composition QDs) and the composition gradient of a Si1-xCx QD may be fine tuned; additionally (with other deposition conditions remaining the same), larger QDs are obtained on average. It is suggested that ionizing a portion of the influx is another way to control the average size of the QDs, and ultimately, their internal structure. Advantages that can be gained by utilizing plasma/ion-related controls to facilitate the growth of highly tailored, compositionally controlled quantum dots are discussed as well.

Nanopowder management and plasma parameters in nanofabrication of low-dimensional quantum structures in reactive silane-based plasmas

Management of nanopowder and reactive plasma parameters in a low-pressure RF glow discharge in silane is studied. It is shown that the discharge control parameters and reactor volume can be adjusted to ensure lower abundance of nanopowders, which is one of the requirements of the plasma-assisted fabrication of low-dimensional quantum nanostructures. The results are relevant to micro- and nanomanufacturing technologies employing low-pressure glow discharge plasmas of silane-based gas mixtures.

Ge/Si quantum dot formation from non-uniform cluster fluxes

The controlled growth of ultra-small Ge/Si quantum dot (QD) nuclei (≈1 nm) suitable for the synthesis of uniform nanopatterns with high surface coverage, is simulated using atom-only and size non-uniform cluster fluxes. It is found that seed nuclei of more uniform sizes are formed when clusters of non-uniform size are deposited. This counter-intuitive result is explained via adatom-nanocluster interactions on Si(100) surfaces. Our results are supported by experimental data on the geometric characteristics of QD patterns synthesized by nanocluster deposition. This is followed by a description of the role of plasmas as non-uniform cluster sources and the impact on surface dynamics. The technique challenges conventional growth modes and is promising for deterministic synthesis of nanodot arrays.

Numerical simulation of self-organized nano-islands in plasma-based assembly of quantum dot arrays

This work presents the details of the numerical model used in simulation of self-organization of nano-islands on solid surfaces in plasma-assisted assembly of quantum dot structures. The model includes the near-substrate non-neutral layer (plasma sheath) and a nanostructured solid deposition surface and accounts for the incoming flux of and energy of ions from the plasma, surface temperature-controlled adatom migration about the surface, adatom collisions with other adatoms and nano-islands, adatom inflow to the growing nano-islands from the plasma and from the two-dimensional vapour on the surface, and particle evaporation to the ambient space and the two-dimensional vapour. The differences in surface concentrations of adatoms in different areas within the quantum dot pattern significantly affect the self-organization of the nano-islands. The model allows one to formulate the conditions when certain islands grow, and certain ones shrink or even dissolve and relate them to the process control parameters. Surface coverage by selforganized quantum dots obtained from numerical simulation appears to be in reasonable agreement with the available experimental results.

Controlling electronic and adiabatic isolation of quantum dots from the substrate : an ionization-energy theoretic study

Recent controversy on the quantum dots dephasing mechanisms (between pure and inelastic) is re-examined by isolating the quantum dots from their substrate by using the appropriate limits of the ionization energy theory and the quantum adiabatic theorem. When the phonons in the quantum dots are isolated adiabatically from the phonons in the substrate, the elastic or pure dephasing becomes the dominant mechanism. On the other hand, for the case where the phonons from the substrate are non-adiabatically coupled to the quantum dots, the inelastic dephasing process takes over. This switch-over is due to different elemental composition in quantum dots as compared to its substrate. We also provide unambiguous analysis as to understand why GaAs/AlGaAs quantum dots may only have pure dephasing while InAs/GaAs quantum dots give rise to the inelastic dephasing as the dominant mechanism. It is shown that the elemental composition plays an important role (of both quantum dots and substrate) in evaluating the dephasing mechanisms of quantum dots.

Comparative behavior of CdS and CdSe quantum dots in poly(3-hexylthiophene) based nanocomposites

CdS and CdSe nanoparticles have been prepared using conducting poly(3-hexylthiophene) (P3HT) matrix with an objective to understand the effect of nanoparticles on the polymer matrix using electrochemical and spectroscopic techniques. The spectroscopic results reveal that the electronic structure of polymer is strongly influenced by the characteristics of embedded semiconducting nanoparticles. SEM and TEM images show the ordered morphology of the CdS and CdSe nanoparticles in presence of the polymer matrix. Cyclic voltammetry performed both in the presence and absence of light enables us to understand the redox changes in P3HT due to CdS and CdSe quantum dots such as the generation of free radical in the excited state and their electrochemical band gaps.

Zinc oxide quantum dot nanostructures

Zinc oxide (ZnO) is one of the most intensely studied wide band gap semiconductors due to its many desirable properties. This project established new techniques for investigating the hydrodynamic properties of ZnO nanoparticles, their assembly into useful photonic structures, and their multiphoton absorption coefficients for excitation with visible or infrared light rather than ultraviolet light. The methods developed are also applicable to a wide range of nanoparticle samples.

Explanation of relevance judgement discrepancy with quantum interference

A key concept in many Information Retrieval (IR) tasks, e.g. document indexing, query language modelling, aspect and diversity retrieval, is the relevance measurement of topics, i.e. to what extent an information object (e.g. a document or a query) is about the topics. This paper investigates the interference of relevance measurement of a topic caused by another topic. For example, consider that two user groups are required to judge whether a topic q is relevant to a document d, and q is presented together with another topic (referred to as a companion topic). If different companion topics are used for different groups, interestingly different relevance probabilities of q given d can be reached. In this paper, we present empirical results showing that the relevance of a topic to a document is greatly affected by the companion topic’s relevance to the same document, and the extent of the impact differs with respect to different companion topics. We further analyse the phenomenon from classical and quantum-like interference perspectives, and connect the phenomenon to nonreality and contextuality in quantum mechanics. We demonstrate that quantum like model fits in the empirical data, could be potentially used for predicting the relevance when interference exists.

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.

The potential for new understandings of normal and abnormal cognition by integration of neuroimaging and behavioral data : Not an exercise in carrying coals to Newcastle

Discovering the means to prevent and cure schizophrenia is a vision that motivates many scientists. But in order to achieve this goal, we need to understand its neurobiological basis. The emergent metadiscipline of cognitive neuroscience fields an impressive array of tools that can be marshaled towards achieving this goal, including powerful new methods of imaging the brain (both structural and functional) as well as assessments of perceptual and cognitive capacities based on psychophysical procedures, experimental tasks and models developed by cognitive science. We believe that the integration of data from this array of tools offers the greatest possibilities and potential for advancing understanding of the neural basis of not only normal cognition but also the cognitive impairments that are fundamental to schizophrenia. Since sufficient expertise in the application of these tools and methods rarely reside in a single individual, or even a single laboratory, collaboration is a key element in this endeavor. Here, we review some of the products of our integrative efforts in collaboration with our colleagues on the East Coast of Australia and Pacific Rim. This research focuses on the neural basis of executive function deficits and impairments in early auditory processing in patients using various combinations of performance indices (from perceptual and cognitive paradigms), ERPs, fMRI and sMRI. In each case, integration of two or more sources of information provides more information than any one source alone by revealing new insights into structure-function relationships. Furthermore, the addition of other imaging methodologies (such as DTI) and approaches (such as computational models of cognition) offers new horizons in human brain imaging research and in understanding human behavior.