Atomic layer deposition of interface control layers for the fabrication of III/V MOS devices

The continued advancement of metal oxide semiconductor field effect transistor (MOSFET) technology has shifted the focus from Si/SiO2 transistors towards high-κ/III-V transistors for high performance, faster devices. This has been necessary due to the limitations associated with the scaling of the SiO2 thickness below ~1 nm and the associated increased leakage current due to direct electron tunnelling through the gate oxide. The use of these materials exhibiting lower effective charge carrier mass in conjunction with the use of a high-κ gate oxide allows for the continuation of device scaling and increases in the associated MOSFET device performance. The high-κ/III-V interface is a critical challenge to the integration of high-κ dielectrics on III-V channels. The interfacial chemistry of the high-κ/III-V system is more complex than Si, due to the nature of the multitude of potential native oxide chemistries at the surface with the resultant interfacial layer showing poor electrical insulating properties when high-κ dielectrics are deposited directly on these oxides. It is necessary to ensure that a good quality interface is formed in order to reduce leakage and interface state defect density to maximise channel mobility and reduce variability and power dissipation. In this work, the ALD growth of aluminium oxide (Al2O3) and hafnium oxide (HfO2) after various surface pre-treatments was carried out, with the aim of improving the high-κ/III-V interface by reducing the Dit – the density of interface defects caused by imperfections such as dangling bonds, dimers and other unsatisfied bonds at the interfaces of materials. A brief investigation was performed into the structural and electrical properties of Al2O3 films deposited on In0.53Ga0.47As at 200 and 300oC via a novel amidinate precursor. Samples were determined to experience a severe nucleation delay when deposited directly on native oxides, leading to diminished functionality as a gate insulator due to largely reduced growth per cycle. Aluminium oxide MOS capacitors were prepared by ALD and the electrical characteristics of GaAs, In0.53Ga0.47As and InP capacitors which had been exposed to pre-pulse treatments from triethyl gallium and trimethyl indium were examined, to determine if self-cleaning reactions similar to those of trimethyl aluminium occur for other alkyl precursors. An improved C-V characteristic was observed for GaAs devices indicating an improved interface possibly indicating an improvement of the surface upon pre-pulsing with TEG, conversely degraded electrical characteristics observed for In0.53Ga0.47As and InP MOS devices after pre-treatment with triethyl gallium and trimethyl indium respectively. The electrical characteristics of Al2O3/In0.53Ga0.47As MOS capacitors after in-situ H2/Ar plasma treatment or in-situ ammonium sulphide passivation were investigated and estimates of interface Dit calculated. The use of plasma reduced the amount of interface defects as evidenced in the improved C-V characteristics. Samples treated with ammonium sulphide in the ALD chamber were found to display no significant improvement of the high-κ/III-V interface. HfO2 MOS capacitors were fabricated using two different precursors comparing the industry standard hafnium chloride process with deposition from amide precursors incorporating a ~1nm interface control layer of aluminium oxide and the structural and electrical properties investigated. Capacitors furnished from the chloride process exhibited lower hysteresis and improved C-V characteristics as compared to that of hafnium dioxide grown from an amide precursor, an indication that no etching of the film takes place using the chloride precursor in conjunction with a 1nm interlayer. Optimisation of the amide process was carried out and scaled samples electrically characterised in order to determine if reduced bilayer structures display improved electrical characteristics. Samples were determined to exhibit good electrical characteristics with a low midgap Dit indicative of an unpinned Fermi level

Practical assessment of hardware limitations on power aware wireless sensor networks - An anti-windup approach

This work considers the effect of hardware constraints that typically arise in practical power-aware wireless sensor network systems. A rigorous methodology is presented that quantifies the effect of output power limit and quantization constraints on bit error rate performance. The approach uses a novel, intuitively appealing means of addressing the output power constraint, wherein the attendant saturation block is mapped from the output of the plant to its input and compensation is then achieved using a robust anti-windup scheme. A priori levels of system performance are attained using a quantitative feedback theory approach on the initial, linear stage of the design paradigm. This hybrid design is assessed experimentally using a fully compliant 802.15.4 testbed where mobility is introduced through the use of autonomous robots. A benchmark comparison between the new approach and a number of existing strategies is also presented.

Spatial and energetic mode dynamics of cold atomic systems

In this thesis we relate the formal description of various cold atomic systems in the energy eigenbasis, to the observable spatial mode dynamics. Herein the `spatial mode dynamics' refers to the direction of photon emission following the spontaneous emission of an excited fermion in the presence of a same species and spin ideal anisotropic Fermi sea in its internal ground state. Due to the Pauli principle, the presence of the ground state Fermi sea renders the phase space, anisotropic and only partially accessible, thereby a ecting the direction of photon emission following spontaneous emission. The spatial and energetic mode dynamics also refers to the quantum `tunneling' interaction between localised spatial modes, synonymous with double well type potentials. Here we relate the dynamics of the wavefunction in both the energetic and spatial representations. Using this approach we approximate the relationship between the spatial and energetic representations of a wavefunction spanning three spatial and energetic modes. This is extended to a process known as Spatial Adiabatic Passage, which is a technique to transport matter waves between localised spatial modes. This approach allows us to interpret the transport of matter waves as a signature of a geometric phase acquired by the one of the internal energy eigenstates of the system during the cyclical evolution. We further show that this geometric phase may be used to create spatial mode qubit and qutrit states.

Multi-scale modelling of atomic layer deposition

High-permittivity ("high-k") dielectric materials are used in the transistor gate stack in integrated circuits. As the thickness of silicon oxide dielectric reduces below 2 nm with continued downscaling, the leakage current because of tunnelling increases, leading to high power consumption and reduced device reliability. Hence, research concentrates on finding materials with high dielectric constant that can be easily integrated into a manufacturing process and show the desired properties as a thin film. Atomic layer deposition (ALD) is used practically to deposit high-k materials like HfO2, ZrO2, and Al2O3 as gate oxides. ALD is a technique for producing conformal layers of material with nanometer-scale thickness, used commercially in non-planar electronics and increasingly in other areas of science and technology. ALD is a type of chemical vapor deposition that depends on self-limiting surface chemistry. In ALD, gaseous precursors are allowed individually into the reactor chamber in alternating pulses. Between each pulse, inert gas is admitted to prevent gas phase reactions. This thesis provides a profound understanding of the ALD of oxides such as HfO2, showing how the chemistry affects the properties of the deposited film. Using multi-scale modelling of ALD, the kinetics of reactions at the growing surface is connected to experimental data. In this thesis, we use density functional theory (DFT) method to simulate more realistic models for the growth of HfO2 from Hf(N(CH3)2)4/H2O and HfCl4/H2O and for Al2O3 from Al(CH3)3/H2O.Three major breakthroughs are discovered. First, a new reaction pathway, ’multiple proton diffusion’, is proposed for the growth of HfO2 from Hf(N(CH3)2)4/H2O.1 As a second major breakthrough, a ’cooperative’ action between adsorbed precursors is shown to play an important role in ALD. By this we mean that previously-inert fragments can become reactive once sufficient molecules adsorb in their neighbourhood during either precursor pulse. As a third breakthrough, the ALD of HfO2 from Hf(N(CH3)2)4 and H2O is implemented for the first time into 3D on-lattice kinetic Monte-Carlo (KMC).2 In this integrated approach (DFT+KMC), retaining the accuracy of the atomistic model in the higher-scale model leads to remarkable breakthroughs in our understanding. The resulting atomistic model allows direct comparison with experimental techniques such as X-ray photoelectron spectroscopy and quartz crystal microbalance.

Current methods and advances in forecasting of wind power generation

Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised.