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or joining thin-wall Titanium and Nickel alloys at high temperatures. Due to the unique material behaviours of these sheets and foils (0.1 mm to 0.5 mm thick), controlling variables in the forming process is
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laser pulses for next-generation spectroscopy, sensing, and light–matter control. The student will utilise different materials platforms with two-photon polymerisation (2PP) 3D printing to fabricate
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of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
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multidisciplinary research team within the School of Electrical, Electronic and Mechanical Engineering. SMG is known for its work in computational mechanics, fatigue, fracture, and advanced materials modeling
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digital twins, and life cycle assessment (LCA). A central component of the research will be the development of digital twins to simulate the entire production process, from raw materials to final product
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the successful and vibrant UK catalysis and central facilities communities, whilst building skills in inorganic and physical chemistry, applied and sustainable catalysis and advanced X-ray characterisation
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Applications are invited for a PhD position at the University of Nottingham addressing the behaviour of thin foil materials for aerospace forming applications. The successful candidate will have a
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of the brain, caused by a virus, an infection, or an autoimmune response. Following encephalitis, children and young people can experience physical/neurological consequences (e.g., headaches, seizures, sleep
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Physics, Theoretical physics, Maths or other closely related subject (e.g. Materials Science with evidence of strong computational background and skills). To apply, please contact the supervisors; Dr Thomas
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 3 months ago
: Analyse how curation and drying impact mechanical properties and hygrothermal performance. Develop a Predictive Model: Create a computational model linking operational variables and material properties