The aerospace engineering industry is continuously striving for faster methods to solve and optimize engineering and research problems with a higher degree of accuracy. It is therefore relevant to investigate possibilities that are expected to accelerate computational speed, such as quantum computing. For this reason, the objective of this thesis is to investigate the feasibility of optimizing 2D determinate truss structures with a quantum algorithm run on a Gate-Based Quantum Computer (GBQC). The Quantum Approximate Optimization Algorithm (QAOA) is currently expected to be the most suitable quantum algorithm candidate for optimization problems, because of its simplicity and robustness. The most important take-away from this thesis is that it is possible to map a truss structure to QAOA format to optimize it on a GBQC. The program proves to be working on quantum virtual machines. However, it is currently not possible to obtain correct results when running on real quantum hardware due to noise.

Self-healing materials and, in particular, polymers are characterized by their ability to partially or fully restore their original properties or functions after damage. Amongst the healable polymer classes, thermoplastic polyurethanes have received increasing attention in the last years. This is mainly due to their broad application areas, the variety of chemical platforms that can be used, and the potential use of hydrogen bonding to assist the healing process. However, the combination of good mechanical properties and healing at near room temperature remains challenging. In order to learn how to find a better balance between healing and mechanical properties, dedicated studies on the impact of the monomer chemical architecture on the overall polymer performance are needed.In this work we study the impact of monomer mixtures with different chemical composition on the overall mechanical and healing behaviour of self-healing thermoplastic polyurethanes based on CroHeal™ 2000, biopolyol. The polymers are synthesized via one-shot technique, starting from three constituents: a long chain diol (CroHeal™ 2000), a chain extender (EHD) and a diisocyanate (aromatics - MDI and PPDI, and aliphatic - HMDI) or diisocyanate mixtures (MDI/HMDI and MDI/PPDI in different ratios).Fracture tests using Single Edge Notch Tension specimens show a clear increase in mechanical properties and interfacial strength recovery after damage for short healing times at room temperature when using higher aromatic content in the isocyanate mixture. Furthermore, IR mapping showed that initial compositional heterogeneity is decreased when more aliphatic isocyanates are used but also when longer annealing times are applied in the case of aromatic diisocyanates. The presence of compositional heterogeneities does not influence the healing response under the conditions studied.

Additive manufacturing of smart polymers is a rapidly growing field. Additive manufacturing presents a versatile, low-waste manufacturing method for functional materials. Self-healing polymers are a type of smart polymers that are able to mend damage, either by the incorporation of an encapsulated healing agent or by intrinsic polymer design. Beside this ability to repair damage, certain types of self-healing polymers have also shown to improve interlayer adhesion of 3D printed parts due to the formation of reversible cross-links. This thesis demonstrated the additive manufacturing of a self-healing polyurethane (CR1) by fused deposition modelling. A protocol was established in order to print with this self-healing polyurethane while minimising material loss. Measurable polymer properties that were relevant to fused deposition modelling were identified and measured in order to establish the processing window of the polymer. CR1 was synthesised, processed into a filament using a commercial filament maker and successfully printed using a modified commercial 3D printer. The elastomeric nature of the polymer combined with its high sensitivity to temperature, resulted in a narrow printing window. Beside the ability to 3D print the polymer into rectangular bars, the self-supportability of the 3D printed CR1 was demonstrated by the printing of a single-wall structure. Printing at 230 °C and 20 mm/s resulted in the most regular sample, with a very low void concentration in its cross-section. The mechanical response of 3D printed CR1 showed good resemblance to that of the bulk. Furthermore, the test showed that the polymer retained its self-healing ability after printing.

Salts of trivalent cerium (Ce(III)) are known to successfully hinder localised corrosion phenomena typical of aerospace aluminium alloys by forming a thin passivation layer on top of the corrosion-active intermetallic phases. This is generally observed to happen when the alloy is under immersion conditions in a solution containing Ce3+ ions. However, some very preliminary works suggest that protection provided by this layer is lost once the passivated metal is re-exposed to a corrosive solution in absence of inhibitor (for example, aqueous solution of sodium chloride). This (in)stability process has not been directly addressed in literature and is, therefore, not well understood. A deeper understanding of such process and the strategies that could lead to a higher passive layer stability are needed to bring Ce-based inhibitor technologies closer to application and replacement of the harmful Cr(VI)-based primers. In this work we studied the inhibition mechanism and stability of cerium inhibiting layers created on AA 2024-T3 upon exposure to electrolytic solutions containing Ce(NO3)3 and NaCl. The stability of Ce(III) layers after re-exposure to corrosive electrolytes (i.e. without inhibitors) is investigated. Furthermore, the interaction between Ce(III) layers and different organic compounds, namely 2,5-Dimercapto-1,3,4-thiadiazole (DMTD), phytic acid and sodium alginate, was also explored as a potential strategy for stabilisation of Ce-based inhibitive layers.
Due to the complex interpretation of electrochemical signals typically used in corrosion studies (e.g. electrochemical noise and impedance spectroscopy), it was decided to combine such electrochemical methods with highly spatio-temporally resolved in-situ microscopy in order to assess both corrosion of AA 2024-T3 and its inhibition. For this purpose, a home made optical-electrochemical experimental setup was used, together with a protocol for optical data analysis. This hyphenated in-situ protocol is further supported with SEM-EDS, Raman and SKPFM analysis after exposure. In the work here presented, the unstable nature of Ce-inhibitive deposits was found to be associated to their dissolution after re-exposure to inhibitor-free electrolytes. Studies devoted to the stabilisation of Ce(III)-inhibitive layers with organic molecules indicated different behaviours and outcomes. Alginate oligomers efficiently passivate the Ce-protected intermetallic phase, but, at the same time, destabilise the Al-rich matrix, which became subject to general corrosion. Phytic acid was found to provide synergy with Ce(III) layers, which however lacked in stability. Treatment of Ce-passivated surfaces with DMTD, on the other hand, shows a significantly delayed onset of optical-electrochemical activity upon re-immersion in NaCl solution, which suggested the accomplishment of a more stable system. The results obtained confirm the power of in-situ (i.e. under immersion) optical investigation not only to support the understanding of complex electrochemical signals, but also to deliver quantitative information relevant in corrosion and inhibition studies. The approach proposed in this research is believed to be of future help for an improved design of Cr(VI)-free anticorrosion coating systems.

Self-healing materials have recently drawn the attention of industry as a new solution to the degradation of materials. Recent progress on the field of autonomous self-healing metals has been in the line of self-healing creep-resistant steels. This is challenging due to the nanometer scale of the creep cavities and the fact that only 3D partially filled cavities can be examined to understand the phenomenon. As a consequence, valuable information is hard and expensive to acquire. This thesis proposes to study the surface precipitation phenomenon as an easier alternative to understand creep-cavity precipitation. Surface precipitation have only been studied in binary steels, therefore, the thesis focuses on the influence of the addition of a second self-healing element by studying the time evolution of gold tungsten containing iron based steels. The results provide new insights into the theory of self-healing steels, where tungsten has been found to decelerate the gold precipitation kinetics.

For many aerospace applications, the dominant airfoil self-noise source is Turbulent Boundary Layer Trailing Edge (TBL-TE) noise. The replacement of solid airfoil trailing edges with permeable materials proved to be an adequate noise reduction mean in previous studies. This thesis project contributes to the development of innovative permeable materials by assessing the feasibility of actively influencing their noise mitigation characteristics. The proposed activation mechanism consists of heating up a polymerically coated, porous trailing edge and thereby influencing the material geometry and seepage fluid properties. Heating of the polymeric coating layer led to slightly decreasing pore diameters due to thermal expansion. The main limitation of actively changing the porous material geometry on a pore-scale level was the restriction of the coating layer thickness. Heating effects on the seepage flow through porous metal foams were analyzed experimentally. Characteristic material parameters, namely flow resistivity, permeability and form coefficient, were measured for varying fluid temperatures and it was shown that for low seepage velocities, the pressure communication across the material was negatively affected upon heating. The feasibility of actively changing far-field noise characteristics was demonstrated based on acoustic measurements in an anechoic wind tunnel. Increasing sound pressure levels were observed for both, coated and uncoated porous trailing edges upon heating. It is concluded that the dominant activation effect was the reduced communication across the porous trailing edge due to an increase in fluid temperature. The expansion of polymeric coating was not sufficient to alter the noise mitigation behavior of the porous trailing edge. Furthermore, no interactions between turbulent boundary layer wall pressure fluctuations and the soft coating layer were observed. However, it was shown that temperature control of the porous material offers a possibility to actively influence flow resistivity without modifying the geometrical structure.

The data-driven approach shows great potential for designing new materials with unprecedented properties by using machine learning and optimization. Recently, a data-driven framework was successfully applied to design a unit cell of metamaterial achieving super-compressibility, despite being built out of brittle base material. The key element of the framework is the algorithm called Gaussian processes regression (GPs) – a unique machine learning method that provides with the uncertainty of the prediction, which can be used during the design process to account for inherent material imperfections, ensuring the robustness of the design. Despite their superior predictive performance, however, GPs suffer from scalability issues, which limit their application to relatively small design problems. In the future, those limitations could be surpassed by quantum computing.

This research aims at demonstrating how quantum computing could enhance the computational design of materials, specifically by replacing the expensive machine learning step of the data-driven design framework with an exponentially faster quantum algorithm for Gaussian processes (QGP). This objective is achieved in two steps. First, the QGP algorithm was Implementation and simulated within a quantum computing framework (Qiskit), which allowed to understand and control its performance (in particular its accuracy), proving the feasibility for practical applications. Furthermore, the numerical tests exposed a mechanism for inducing a low-rank approximation, which allows for additional speed-up, making the QGP algorithm similar to classical sparse Gaussian processes, which rely on low-rank approximations to improve the scalability of full GPs. In the second part of this research, the implemented QGP algorithm was integrated within a computational framework for the data-driven design of materials and applied to two example design problems of optimization a unit cell for a super-compressible metamaterial. The results obtained with the QGP were comparable to those obtained with classical methods (also from literature), which proved the feasibility of the concept.

Incorporating carbon nanomaterials such as carbon nanotubes into a polymer matrix not only enhances the mechanical properties of the composite, but also induces good electrical properties. This makes carbon nanocomposite interesting for potential electronic applications, such as electromagnetic interference shielding by means of creating housings for electronic devices. One potential option of producing carbon nanocomposites is via injection molding, which is widely used in the plastics industry since it is a fast and cost effective method to mass-produce plastic parts.

Looking at the current state-of-the-art literature a lot of research in this area can be found. It has been identified that injection molding is not beneficial for high electrical properties of the composite and it leads to a non-uniform in-plane distribution of the electrical properties. Moreover treatments such as annealing have been described to enhance the electrical properties of the composites. However some shortcomings in the current research have been identified.

Hence this master thesis research aims at eliminating those shortcomings by characterizing the electrical properties of different injection-molded nanocomposites and their in-plane distribution. Moreover it has been investigated how additional treatments such as below melt temperature annealing and dielectricphoresis enhance the electrical properties and their in-plane distribution.

Flexible electronics have become the subject of industry focus, generating a market desire for fully flexible temperature sensors. To the best of our knowledge, there are no current systems that can adequately satisfy both the mechanical flexibility and sensing performance demanded for commercial applications. This work focused on a design for a flexible temperature sensor by designing a thermistor using functional granular composites using ceramic NTC fibre particles and a resistive polymer matrix. The objective was to achieve good thermistor performance (high sensitivity: B-value > 3000 K, and low resistivity: rho ˜ 10^1 - 10^2 Ocm) while being mechanically flexible (surviving bending radii = 1 cm over 100 cycles). To achieve this objective this thesis work was organised into 5 major phases. Due to the high commercial value of NTC ceramic thermistors, no reference composition with its exact processing conditions are available in literature that produce a thermistor with commercially desirable properties. Phase 1 was therefore to select a NTC ceramic composition and Phase 2 was to investigate the necessary processing conditions to be able to produce bulk ceramics with adequate temperature sensing performance. Phase 3 involved making NTC ceramic fibres by wet fibre spinning and modifying the processing conditions developed in Phase 2. Phase 4 involved the selection of an appropriate polymer matrix and to attempt to create thermistor composites. Phase 5 involved creating more optimal composite thermistors using stencil printing and to test its thermistor and bending performance. Using an isotropic mixture of Mn2.4 Ni0.5 Cu0.1 O4 NTC ceramic fibre particles in an Electrodag matrix, composite thermistors were created by stencil printing onto thin-film substrates of polyethylene terephthalate that have silver inkjet printed interdigitate electrodes. A percolated network is formed with as little as 10 wt% of fibres (˜ 2.86 vol%). The composite with 10 wt% of fibres has good thermistor performance at a low fibre content. The average resistivity at 25°C (rho_25) is low around 920 · 10^3 Ocm (with a standard deviation of 220 · 10^3 Ocm) and the sensitivity is high with a B-value = 3290 K and alpha = -3.7 %/K. The overall composite resistance and sensitivity can be tailored and customised by changing the gap width of the interdigitate electrodes. At an electrode gap width of 0.13 mm, with our interdigitate electrodes, R_25 = 280 kO and R_85 = 45 kO. The composite with 10 wt% fibre particle content and an electrode gap of 0.13 mm can survive 300 bends cycles (100 cycles with bending radius 10 mm (strain ˜ 0.621%), 100 cycles with bending radius 5 mm (strain ˜ 1.23%), 100 cycles with bending radius 2.5 mm (strain ˜ 2.44%) without any observable, aesthetic damage. The relative resistance (R/R0) does increase with bending, but after 20 bend cycles it appears to stabilise for every bending radius. In comparison to other flexible temperature sensors in recent literature, this thermistor composite is found to deliver a superior combination of thermistor performance and mechanical flexibility.

The autonomous filling of creep-induced grain-boundary cavities by tungsten-rich precipitates has been studied for Fe-W alloys at various temperatures, loading conditions and creep rupture times. To this aim, scanning electron microscopy, energy-dispersive spectroscopy and X-ray nano-tomography were used. Additionally, the effect of local plastic deformation, followed by ageing processes, on the surface precipitation in these alloys has been studied by means of scanning electron microscopy, together with energy-dispersive spectroscopy. Finally, a diffusion-based finite element analysis has been performed to study cavity filling for different combination of diffusion mechanisms. From scanning electron micrographs it can be confirmed, that Fe-W alloys show damage-selective precipitation of the Laves phase (Fe2W). Furthermore, the filling ratios of individual cavities are determined and it is found, that the autonomous healing strongly depends on the duration of the loading at of elevated temperature. From the quantitative analysis of the size and shape of the precipitates and cavities it is found, that the orientation of grain boundaries to the stress direction has an influence on the morphology of the induced-cavities, as well as, the filling ratio. The grain-boundary cavities orientated favourably for the cavity growth show low filling ratios, due to the fact, that their propagation proceeds with a higher rate than the solute transport. The critical volume of a cavity, that can be fully filled with solute atoms, is found to be of the order of 10 μm3, while the average filling ratio for Fe-W alloys is found to be around 50% for the sample loaded to 100% of its lifetime. Moreover, the scanning electron micrographs of the indentation-deformed samples subjected to ageing revealed surface precipitates (Fe2W), which existence has to be further researched. The hardness measurements of Fe-W samples showed that after 200 hours of ageing at 580oC, the strength of the alloy is only reduced if the material has been pre-strained, but it remains constant for the solution heat treated specimens. This result shows, that the process of dislocation recovery dominates over work-hardening only in the case of a high dislocation density. Finally, the finite element analysis revealed, that during the diffusive cavity filling of an equilibrium-shaped void, three different diffusion profile regimes are plausible. Namely, a diffusive filling dominated by volume diffusion, which occurs for a relatively small spacing between neighbouring cavities and is independent of the ratio of bulk and grain-boundary diffusion. Secondly, a diffusive filling governed by volume diffusion with contributing grain-boundary diffusion, which occurs for relatively low ratios of bulk and grain-boundary diffusion. And ultimately, a diffusive filling governed by grain-boundary diffusion, which occurs for relatively high ratios of bulk and grain-boundary diffusion.