The proposed project wishes to investigate an encapsulation phenomenon driven by airflow. The processing science and technology is referred to as aerodynamically assisted jets or jetting (AAJ). The apparatus used in this technology has a needle partially fitted in a crystal glass chamber, which can hold a large pressure, which is supplied via a compressor. The central needle axis is in line with the centre of an exit orifice which is on the opposite side to the needle, namely on the base of the glass chamber. As the process utilises airflow for drawing a growing drop of liquid a pendant-like shape is formed from the liquid at the exit of the needle. From the apex of this pendant-shaped droplet a jet evolves which goes onto break down after flowing past the exit orifice of the device. The entire process from the formation of the pendent-like droplet to the generation of droplets will all be recorded in real time with the specialist equipment supplied in-kind by both the project partners namely, Oxford lasers Ltd and Photo-Sonics International Ltd.The first stage is where the construction of a single needle device takes place. Here this device will be constructed and tested with water and ethanol for forming droplets and more importantly monodisperse droplets. Following this study a family of commercially available silicone oils will be employed as their viscosities range from 1-100000mPa s. These liquids will be processed using a single needle device, which will initiate significant modifications to be made on the single needle prototype to accommodate such a large regime of viscosities. There will be several devices constructed for processing a particular range of viscosity respective to that device. Hence the project later introduces a polymer, namely poly(ethylene) oxide (PEO) which when processed in this route will solidify at ambient temperature allowing the characterisation of the collected droplet relics.The next stage employees the know-how in single needle AAJ device design and construction to build a co-axial or concentric needle AAJ device. The idea is to have the inner needle accommodating the flow of a gas stream (could either accommodate a viscous liquid or suspension) with the outer having at the test phase the silicone oils. Subsequently after a robust device is designed and tested for handling both droplet encapsulation and the wide range in viscosities, PEO blends will be processed. PEO blends will be formulated by mixing with water and ethanol making it a liquid medium, which can be made to aerodynamically flow through the exit orifice. At this stage the device will be capable of forming hollow structures and micro-foams from both silicone oils and PEO blends. Note that silicone oils have only been used for testing the devices for the range of viscosities. PEO blends comprising a varying vol. % of PEO will mimic those viscosities of the silicone oils. PEO is employed as it solidifies in ambient temperature hence the hollow droplets or bubbles can be characterised.The final stage will incorporate the addition of commercially available ceramics powders into the PEO blends. The intention here is to heat treat the generated bubbles to obtain a sintered hollow structure. Furthermore the co-axial needle AAJ configuration will be scaled up to accommodate an array of needles for mass scale processing.

Lasers are used for an extremely wide range of manufacturing processes. This is due, in part, to their significant flexibility with respect to parameters such as pulse length, pulse energy, wavelength, and beam size. However, this flexibility comes at a price, namely the significant amount of time that must be dedicated to finding the optimal set of parameters, for each and every manufacturing process or customer specification. The standard practice in industry is the mechanical collection of laser machining data for all parameter combinations, in order to find the optimal combination of parameters. However, this process is both time-consuming and unfocussed, and it can take days or weeks, hence costing unnecessary time and money. Even when the optimal parameters have been determined, small changes, for example in laser power or beam shape, during manufacturing, can result in a final product quality that is below the required standard, once again costing time and money. There will also be instances where the specification is not known in advance due to variability in the manufacturing process. What is needed, therefore, are a series of methodologies for identifying optimal parameters before manufacturing, for providing real-time monitoring and error correction during manufacturing, and for enabling process-control (for example stopping the laser exactly at task completion, or varying the laser power for the final finishing steps). The research field of machine learning has seen some extremely significant developments in recent years, and it is now widely understood to be a catalyst for a fundamental change across almost all manufacturing industries. The objective of this proposal is to develop the technological and human expertise required for the integration of machine learning approaches into the UK laser-based manufacturing industry and the NHS. This proposal therefore seeks to leverage state-of-the-art machine learning techniques for solving well-known problems in laser-based manufacturing and materials processing, resulting in improvements in efficiency, reliability, and precision. The results of this proposal will lead to time and money savings for both the UK laser-based manufacturing industry and the NHS. This proposal will cover the application of neural networks for modelling and optimising of femtosecond laser machining, instantly identifying laser-based manufacturing parameters for any customer specification, automatically compensating for residual cavity effects in fibre lasers, enabling targeted delivery of laser light for psoriasis treatment, and laser welding process enhancement in real-time via multi-sensor data.

Micro-robots have great potential for evaluation and treatment of medical conditions. Such devices require highly controlled actuation at a micro-scale to provide controlled motion, testing of tissue compliance, biopsy, etc, and this is a prospect offered by functionally-graded shape memory alloys (SMAs). An SMA has the ability to "remember" its original shape and that when deformed returns to its pre-deformed shape when heated. Such alloys have sparked great interest ever since their first development. Functional grading of SMAs (i.e. locally modifying the properties of the material to tailor the SMA effect in different parts of the device) allow the design of more complex and hence much more controllable actuation mechanisms. Devices and components manufactured from functionally graded SMAs can provide actuation in response to external stimulation (stress or temperature variation, e.g. via induction heating), outperforming conventional actuation mechanisms such as electromagnets or electrical motors in terms of work output density. Such performance is ideal for micro-devices for minimally invasive medical applications such as precise incision, tissue identification, tactile sensing for disease and tweezing, as well as more ambitious shape transformations for "unpacking" structures in situ and "intelligent" stents and patches. The manufacturing challenge here is to achieve that functional grading at a micro-scale, by a combination of locally tailoring the material composition and thermal history. This will be achieved via development of a novel process, functionally graded Laser Induced Forward Transfer (FG-LIFT). This process will use a multi-track 'donor ribbon' (rather like a multicoloured typewriter ribbon) to deposit "sub-voxels" (of typical dimensions a few microns across and hundreds of nm high) of different metals, e.g. Ti, Ni and Cu onto a target substrate, in order to construct voxels each consisting of a number of subvoxel layers of different metals. By altering the laser parameters, subsequent thermal treatment will be used to provide control of interdiffusion within and between voxels providing very tight localised control of composition. 3D microstructures will hence be constructed by continuing to add additional voxels. This FG-LIFT process will be used to manufacture sub-mm and mm-scale SMA components with functional grading at a scale of 10's of microns. This highly challenging concept requires 3D control - at the micro-scale - of both material composition and thermal treatment. By depositing the functionally graded SMA material onto substrates with appropriate material properties (e.g. carbon fibre mats or trace heaters), additional tailoring of the overall performance of the device will be achieved.