Traditional lithographic techniques used to fabricate a magnetic structure are often complex, time consuming, dependent on other techniques and expensive. Laser direct writing (LDW) can potentially overcome many of these drawbacks and may be a cheaper, faster and easier route to fabricating technique micro-/nano-magnetic structures. The main aim of this project is to fabricate magnetic structures through LDW. Two types of LDW were used to fabricate magnetic structures: subtractive LDW (LDW-) and laser-induced forward transfer (LIFT). LIFT was used to transfer permalloy (Ni81Fe19) using three laser systems. Numerous parameters were varied, including thin film thickness, scanning speed, pulse energy, distance between donor/acceptor and acceptor material. These attempts did not succeed in transferring the magnetic materials as a uniform shape. The differences of heat conductivity between the permalloy and acceptor substrate (glass and silicon), shock wave effects and the landing speed of material on the acceptor are the most possible reasons that the uniform structures and the magnetic properties were lost. LDW- was used to successfully pattern 90nm thick Permalloy into 1-D and 2-D microstructures. Magnetic wires with a range of widths, arrays of squares, rectangles with a range of aspect ratios and rhombic elements were patterned. These structures were fabricated using an 800-picosecond pulse laser and a 0.75 NA lens to give a 1.85µm diameter spot. Scan speeds were controlled to give 30% overlap between successive laser pulses and reduce the extent of width modulation in the final structures compared with lower levels of pulse overlap. Continuous magnetic wires that adjoined the rest of the film were fabricated with widths from 150 nm - 6.7µm and showed coercivity reducing across this range from 47 Oe to 10 Oe. Squares, rectangles and diamonds These elements demonstrated shape-sensitive magnetic behaviour with increasing the shape aspect ratio. Wires of different width were also fabricated by LDW- and their anisotropic magnetoresistance (AMR) determined to show a simple width-dependent magnetic field response, making them interesting as magnetic field sensors. This approach is extremely rapid and does not requires masks or chemical processing as part of the patterning procedure. The time required to patterned 1-D area of 4 x 0.18 mm was 85 s and the average fabrication time per element of 2-D structures was 4.7x10 4 s. The microstructures may be of use for AMR sensors or for biological applications, such as cell trapping.

The modelling, prediction and prevention of material failures is the key issue during material design and processing. Finite Element Methods (FEM) combined with physically-based models are a popular approach to modelling fracture characteristics. However, in industrial practice, the interlinked process with high dimensions and complexities could be too complicated to be expressed purely on the principles of physics. Mathematical models via data-driven modelling approaches, were developed to remedy the aforementioned disadvantages of physically-based models. Therefore, this project focuses on developing a hybrid model to assess the toughness of metal alloys, and to improve the current material design techniques through the model-based optimal design. Firstly, a data-driven model of the crack propagation of compact tension test is constructed; an error compensation strategy is also developed and tested. In order to improve the current material design technique through the model-based optimal design, a multi-objective particle swarm optimisation algorithm is proposed and tested using different benchmark functions. A data-driven model based finite element model structure is then proposed. Finally, the optimisation algorithm is applied together with the finite element analysis to the optimal design of material. The results show that the constructed model for compact tension test and the error compensation strategy performed well. The proposed multi-objective particle swarm optimisation algorithm outperforms the compared two particle swarm optimisation algorithms; it is also applied successfully to the optimal design of the small punch test.

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Currently the electronic industry has a market demand for over a billion multi layer ceramic capacitors per annum. Electrical characterisation of the electroceramic component of these devices is required for optimisation of existing materials and to aid material discovery. Impedance spectroscopy is a technique that is commonly used to characterise the electrical properties of electroceramics. Experimental data is analysed using an equivalent circuit (usually some combination of resistors and capacitors connected in series and/or in parallel) to extract resistances and capacitances for specific components of a microstructure, e.g. bulk (grains), core-shell grains and grain boundaries. The ability to extract this information depends on the use of an appropriate equivalent circuit and on how to analyse the impedance data. Here an investigation of how the physical microstructure of an electroceramic can affect its impedance response using finite element modelling (FEM) is presented. By using a simulation-based approach the simulator can use the same methodology that would be used experimentally to obtain information on different microstructural components with prior knowledge of what the values should be, since the simulator has defined them. By comparing the values extracted to those originally inputted into the simulation allows the accuracy of the data analysis methods used to extract information to be evaluated and under what conditions these methods can be applied. The results presented in this thesis (chapters four to six) are divided into three studies. Chapter four considers the characterisation of core-shell grain microstructures by estimating core and shell volume fractions from the core to shell capacitance ratio. FEM simulation of the impedance response of a core-shell microstructure allows the capacitance ratio of the core and shell to be obtained from the electric modulus formalism. Several microstructures were considered: a nested cube; nested truncated octahedra; and a series layer model (SLM). The first two microstructures are approximations for a core-shell grain and were simulated using FEM. The layer model is an idealised case that can be solved analytically and with FEM for validation purposes. Here the relative permittivity of the core and shell regions is fixed at a value of 100 and the core has a conductivity three orders of magnitude greater than the shell. As the core volume fraction decreases, the core volume fraction extracted from the SLM is always accurate but becomes increasing inaccurate for the other models. This discrepancy agrees with the results of effective medium theory proving that our conclusions are physically reasonable. Plots of the electrical microstructure using a stream tracer method to view current flow showed increased heterogeneity in the current density in the core and shell. A quantitative study of the electrical microstructure showed the formation of conduction pathways through the parallel shell and increased curvature of the pathways through the core as the core volume fraction decreased. The electrical microstructure no longer resembled the physical microstructure, making extraction of volume ratios increasingly unreliable. Only for core volume fractions of 0.7 or greater could the core volume fraction be extracted from capacitance ratios with errors of less than 25%. Chapter five also considers the extraction of volume fractions from core-shell grains and other idealised microstructures. Here the conductivity of the core and shell regions is fixed and the permittivity of the core is greater than the shell. The impedance responses of an encased model, SLM and a parallel layer model (PLM) are simulated. The response of the encased model is shown to be more similar to the SLM than the PLM, implying serial connectivity in the encased model. Due to the difference in permittivity in the core and shell regions, the core volume fraction could not be obtained from capacitance ratios but only from resistance ratios obtained from the impedance formalism. The core-shell volume fractions of the encased model and SLM were varied and then extracted using resistance ratios. Similar trends to chapter four were observed, in chapter five, where the volume fraction could be accurately obtained for the SLM from resistance ratios for all input volume fractions. For the encased model, the error when extracting the core volume from resistance ratios increased as the core volume fraction decreased. Again, this error was in excess of 25% when the core volume fraction was less than 0.7. Finally, a stream tracer investigation of electrical microstructure revealed heterogeneous current density in the encased model caused by the formation of capacitive pathways through the microstructure. Chapter six examines the case where the microstructure is fixed and the material properties are varied. An encased model with a core volume fraction of 0.8 was chosen as it had been shown in the previous chapters that larger core volume fractions minimised the effects of conduction and capacitive pathways through the parallel shell but was still comparable to the volume fractions of core-shell microstructures in the literature. The core conductivity and relative permittivity was fixed at 0.1 mSm-1 and 2000, respectively. The shell conductivity was varied from 0.1 mSm-1 to 0.1 μSm-1 and the relative permittivity from 2000 to 10. One hundred combinations over a range of shell properties was simulated. The resultant spectra were then fitted with three equivalent circuits where the fits were compared to find the best equivalent circuit using all four impedance formalisms. The first circuit was based upon a SLM with the same material properties and volume fractions inputted into the encased model. The second was called the series brick layer model (SBLM) and based on the encased model but neglecting the contribution of the parallel shell region. The third circuit was called the parallel brick layer model (PBLM) which included a separate resistor capacitor branch for the parallel shell region. The SLM provided a poor fit for all encased simulations with errors between ±34 to ±163%. The SBLM and PBLM provided better fits to the encased simualtions with errors from ±0.7 to ±20% and from ±0.55 to ±20%, respectively. Analysis showed that the SBLM provided the best fit when both the conductivty and the permittivity values of the core and shell were more than an order of magnitude different. The PBLM was best when either the shell conductivty or permititvty was within an order of magnitude of the core values. Finally, the best equivalent circuit for a given set of shell material properties was used to extract values of conductivity and permittivity (for both the core and shell) in all four impedance formalisms. The accuracy of the extracted values was calculated with respect to the input values for the simulation. This allowed the most reliable form of data analysis (i.e. formalism) for extracting conductivity and permittivity values for a given combination of material properties to be established. The accuracy of the most reliable formalism was mapped out for every material property combination. This optimal methodology was used to show the best case accuracy that could be achieved for extracting intrisic material properties from a core shell microstructure as the shell properties were systematically varied.

Additive Manufacturing (AM) process development was conducted to the production of high- Niobium Titanium Aluminide components with properties suitable for structural aerospace applications. Computational analysis of experimental data from statistically designed experiments and numerical heat source modelling revealed the effect of key Electron Beam Melting (EBM) process parameters on the melting response of ?- Titanium Aluminides. Dimensionless terms for melt pool depth and operational parameters for various literature data and experimental data from this study show a very good fitting; which proves that predictive models and process windows could be generated and used to rapidly and efficiently develop process themes for a given material and required melting response. Heating, preheating and melting EBM process themes were developed for fabricating simple geometries. Using a Design of Experiments (DOE) approach melting (hatching) process themes were optimised for surface finish, maximum component density without process defects and minimum Aluminium evaporation loss. Post-processing for eliminating defects and porosity from the bulk and surface was performed by machining and hot isostatic pressing (HIP). Optimum HIP treatment conditions were identified. Microstructural analysis and mechanical properties were investigated for the as-built and HIPed specimens at room and elevated temperatures. Excess Aluminium evaporation loss was identified as the main issue during the process development of this study. Evaporation per surface area, during EBM processing, from a metallic substrate mainly depends on surface temperature, heating time and chamber pressure and is a function of material properties and operational parameters. The main parameters affecting evaporation were investigated by numerical modelling using a modified Rosenthal equation. Impeding pressure for suppressing Aluminium evaporation versus surface temperature was also investigated.

A novel replication technique for the production of open-celled aluminium foam has recently been devised and is undergoing commercial development by the company Constellium. The technique allows close control over the pore size and shape; a feature that is uncharacteristic of metal foam production methods in general and control to such an extent is unprecedented. The method provides an excellent pathway for the exploration of pore geometry/heat transfer behaviour relations, which is the objective of this study. This also aligns with the commercial goals of Constellium as heat transfer applications have been identified as a key market for their foams. Based on the technique; the focus of this work was the development of a laboratory protocol to allow the production of aluminium foam samples with a range of different mesostructures. The heat transfer behaviour, including permeability, of foams with differing matrix metal, pore size, pore aspect ratio and pore shape were examined under forced convection conditions. Decreasing pore size was found to provide enhanced heat transfer, although for pores < 3mm the benefit was outweighed by a large decrease in permeability. Small changes in pore shape as a result of preform compaction during processing may be exploited to provide improved heat transfer without reducing permeability. Elongation of pores provided no enhancement of heat transfer or permeability.

This thesis demonstrates progress towards a step-change in the economics of titanium. Titanium's properties make it desirable to designers, but it is frequently overlooked due to high costs; making research into reducing costs of considerable interest. Examining the literature shows cost reduction possibilities in two main areas; extraction and downstream processing. Lower-cost extraction has previously received much attention, but in isolation will not produce the required reductions. Powder metallurgy techniques allow near net shape (NNS) production with limited material wastage and processing steps; also allowing utilisation of powders/particulates produced by many developing extraction methods. Combining products from alternative extraction with novel solid-state downstream processing has potential to produce truly cost-effective titanium alloy components. Chapter 4 establishes field assisted sintering technology (FAST) as a rapid and effective method to fully consolidate commercial and developing titanium alloy powders, with a wide variety of chemistries, morphologies, and sizes, including material from the Metalysis FFC process. FAST scalability was successfully tested by producing a 5.5 kg, 250 mm diameter, specimen. Chapter 5 shows that titanium alloy preforms produced via FAST behave equivalently to conventionally processed melt, multi-step forged, products. The shapes and microstructures produced were not those typically required for components. Consequently, chapter 6 investigates the proposed cost-effective processing route of producing wrought microstructures in two steps from powder, which has been termed FAST-forge. A fully dense, microstructurally homogeneous, shaped preform billet formed via FAST was finished with a precision one-step forging operation that refined the microstructure, verifying the FAST-forge concept at laboratory-scale. It is anticipated with further development, and by utilising finite element modelling, that it will be possible to produce semi-complex NNS components with competitive mechanical properties in just two steps. Therefore, FAST-forge has potential to be disruptive technology that could enable the desired step-change in the economics of titanium.

To succeed in a demanding and competitive market, great attention needs to be given to the process of product design. Incorporating optimization into the process enables the designer to find high-quality products according to their simulated performance. However, the actual performance may differ from the simulation results due to a variety of uncertainty factors. Robust optimization is commonly used to search for products that are less affected by the anticipated uncertainties. Changeability can improve the robustness of a product, as it allows the product to be adapted to a new configuration whenever the uncertain conditions change. This ability provides the changeable product with an active form of robustness. Several methodologies exist for engineering design of changeable products, none of which includes optimization. This study presents the Active Robust Optimization (ARO) framework that offers the missing tools for optimizing changeable products. A new optimization problem is formulated, named Active Robust Optimization Problem (AROP). The benefit in designing solutions by solving an AROP lies in the realistic manner adaptation is considered when assessing the solutions' performance. The novel methodology can be applied to optimize any product that can be classified as a changeable product, i.e., it can be adjusted by its user during normal operation. This definition applies to a huge variety of applications, ranging from simple products such as fans and heaters, to complex systems such as production halls and transportation systems. The ARO framework is described in this dissertation and its unique features are studied. Its ability to find robust changeable solutions is examined for different sources of uncertainty, robustness criteria and sampling conditions. Additionally, a framework for Active Robust Multi-objective Optimization is developed. This generalisation of ARO itself presents many challenges, not encountered in previous studies. Novel approaches for evaluating and comparing changeable designs comprising multiple objectives are proposed along with algorithms for solving multi-objective AROPs. The framework and associated methodologies are demonstrated on two applications from different fields in engineering design. The first is an adjustable optical table, and the second is the selection of gears in a gearbox.