Cecilia Persson

Project 1: AM4Life Competence Centre in Additive Manufacturing for the Life Sciences (VINNOVA)

AM4Life aims to develop, give access to and provide a future supply of competence in AM for the life sciences, through synergetic research projects between academia, industry and healthcare. We address several needs in society

Project 2: AM of magnesium-based alloys

Magnesium based alloys have the potential to provide healthcare with a material solution where both degradability and load-bearing possibilities are combined. This could allow for e.g. bone substitutes and fracture fixation, where the implant is over time replaced by the body’s own tissue. Combining this with 3D-printing could allow for patient-specific implant designs. However, AM of Mg is challenging and an immense amount of research is still needed to develop materials for and through AM to achieve adequate microstructures and hence macroscopic properties. We have several sub-directions within this topic to achieve an enhanced understanding of the relationship between raw material, process parameters and resulting material structure and properties, including material modelling as well as experimental studies.

Project 3: AM of titanium-based alloys

Titanium based alloys have been used as permanent implant materials for a very long time, with great success in terms of osteointegration. With the advent of additive manufacturing, new possibilities open up, not only in terms of patient-specific implants, but also to use the manufacturing process to develop new alloys with improved properties, that could allow for e.g. improved wear performance. This could allow for a reduced use of materials that have a negative health- and/or sustainability impact during manufacturing.

Project 4: AM of degradable polymer-ceramic composites

Biodegradable materials could allow for use in paediatric surgery, as a material being replaced by the body’s own tissue over time would be ideal for a growing individual. Here, we aim to combine the beneficial effects of bioactive ceramics with the more ductile polymers into printable, functional materials. An understanding of the effect of process parameters on the individual and combined material components will be developed.

Project 5: Structural optimization of implants

With the advent of additive manufacturing, almost any complex structure could be achieved, and hence a complete design freedom is possible. Therefore, structural optimization can be used to develop implants that are adapted to the local loading situation, while minimizing the amount of permanent material e.g. Numerical modelling can also be used to develop more complex designs, with integrated local functions, and thereafter printed. The size of individual parts of a component however has an effect on the local microstructure during printing, and hence both design and process parameters need to be taken into account when developing an implant. Here, we aim to take advantage of the knowledge developed on AM of biomaterials in combination with numerical modelling, to achieve implants that provide patients with less complications and a higher quality of life.

Project 6: AI in AM

While AM is itself considered a resource-efficient manufacturing method, the development of materials for and through AM require an immense amount of research efforts and resources, including energy and material waste. We aim to develop machine learning methods and frameworks to make this process more efficient, but also to achieve a better understanding of the underlying melting and solidification mechanisms during printing, especially in the laser powder bed fusion processes.