The present research extends the existing literature in at least three aspects. Firstly, it looks at what makes firms perceive patents as more or less important. Secondly, it examines how patents do (if at all) interact with other appropriability mechanisms. Finally, it looks at how firms act with respect to why, where, what and when to patent. The manufacturing industry is still the major source of patent applications. Thus, a firm-level study in manufacturing was chosen. The adopted methodology consists of i) a series of interviews with decision-makers on patents in six pharmaceuticals firms, using a semi-structured questionnaire, and ii) two postal surveys of firms in UK manufacturing, conducted through structured questionnaires. One survey, also known as the Community Innovation Survey, was undertaken by the UK Office for National Statistics on behalf of the UK Department of Trade industry. Another survey, encompassing particular aspects of patenting activities, was administered by the researcher to firms listed in the UK R&D Scoreboard. Contrary to our suspicions patent numbers may be a good proxy for evaluating the importance of patents as a mechanism of protection, but not necessarily for measuring the level of innovativeness of a firm. Secondly, our findings suggest that some mechanisms of appropriability are more correlated to patents than others but, overall, they lead to the same sort of conclusions. Finally, we found that i) firms seek patents mainly as a protective device against copying; ii) patents tend to be filed early in the innovation process when the prospects may still be uncertain; iii) in general broader patent scope is sought but a narrow scope can also be valuable; and iv) the attractiveness of the market is central when firms decide to pursue cross-border proprietary control of the knowledge they create.

In-situ sensors are crucially important for understanding the physico-chemical processes that occur in natural water environments. Manual sampling with laboratory analysis cannot provide the temporal and spatial resolution required to characterize marine and fresh water ecosystems, and this approach is both expensive and time consuming, and may also be affected by artefacts during handling and storage. In-situ sensors minimize these drawbacks and provide a tool to obtain long-term data banks which will allow a more synoptic interpretation of the biogeochemical cycles of key elements in water systems. The trace metals iron and manganese are examples of key elements that shape the biogeochemistry of aquatic systems. Processes influenced by them include phytoplankton growth, deep-sea vent chemistry and redox equilibria in environments with strong oxygen concentration gradients. This thesis describes the development, optimisation and application in environment of two sequential prototypes of a Lab-On-A-Chip microfluidic autonomous analyser for the in-situ determination iron and manganese in aquatic environments. A first prototype (Prototype 1,P1) of the device existed at the beginning of this project. It was labtested and deployed at depth in the Lucky Strike Vents Field (Mid Atlantic Ridge) for the determination of Fe(II). An operative fault during the deployment triggered a trouble shooting process which highlighted some weak points in the device. Those weaknesses were addressed and solved in a second version of the device (Prototype 2, P2) whose novel feature was the in-line mixing by diffusion of reagents and samples. Total Fe, Fe(II) and Mn could be measured with a frequency of up to 12 and 6 samples per hour respectively, with limits of detection of 35 nM and 27 nM for Total Fe and Fe(II) and 28 nM for Mn. The robustness and reliability of P2 was tested in the laboratory and in the environment in both marine (Baltic Sea) and fresh (Beaulieu River) waters. The results of these deployments are presented and directions for further developments of the technology are proposed.

The title of the project, ‘FutureFactories’, describes an exploration of direct digital manufacturing and the use of this technology in creating new models for consumer product design practice. In additive fabrication itself, there is no economic advantage in producing identical artefacts: given this, and the free-form potential of a technology that can deliver almost any form imaginable, the project examines the possibility of modifying the design with every artefact produced. The aim is to create automated systems capable of volume production, establishing mass individualisation: the industrial scale production of one-off artefacts. This work explores the potential to combine parametric CAD modelling with computer programming to create animated meta-designs that change in real time. These scripts introduce a random computer generated element into each physical product ‘printed out’ using direct digital manufacturing. The intention is to combine qualities normally associated with the vagaries of the hand-made with the technical resolution of industrial mass-manufacture; whilst at the same time maintaining a coherent design and identity. The outputs from this practice-based research project consist of inspirational products ranging from gallery pieces to commercial retail products and, alongside the real-world artefacts, the scripted meta-designs from which they are created. The use of such software processes and real-time networks as generative tools, questions existing transient boundaries of practice, and exposes the irrelevance of conventional definitions of role. It is clear that the outcomes of such a new model of creative production cannot be thought of as traditionally conceived pieces. The outcomes of the research suggest that the resulting artefacts can be considered both functionally useful and as art. Outside of that, existing definitions convey little of the reality of their production, as they lie in some new, as yet unspecified, arena of production.

The work presented in this thesis explores the investigation and development of programmable modular synthesis. A computer-controlled system has been used to navigate through a network of organic reactions. In particular, this decision making system was developed in order to navigate reaction networks according to the reaction diversity. Finally, the potentiality of increasing the versatility of this platform is demonstrated by developing novel flow architectures including in-line analytics, which exploits three-dimensional (3D) printing technologies.