Cecilia Persson

Professor at Department of Materials Science and Engineering; Biomedical Engineering

Telephone:
+46 18 471 79 11
Mobile phone:
+46 70 248 96 24
E-mail:
cecilia.persson@angstrom.uu.se
Visiting address:
Ångströmlaboratoriet, Regementsvägen 10
Postal address:
Box 35
751 03 UPPSALA

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Short presentation

I lead the BioMaterial Systems (BMS) research group within the Division of Biomedical Engineering, focussing on the development of new biomaterials for and through additive manufacturing.

I also direct a Competence Centre in Additive Manufacturing for the Life Sciences, and the national Research Technology Platform WISE Additive.

Keywords

  • biomaterials
  • biomechanics
  • materials science
  • biomedical engineering
  • additive manufacturing

Biography

Commissions of trust and larger assignments within my role as professor have included e.g. Section Dean of Engineering (2020-2023), President of the Scandinavian Society of Biomaterials (2019-2023), Coordinator of EU Innovative Training Network NU-SPINE (2019-2023), Uppsala University representative in the WISE (KAW) URG group (2023-).

ACADEMIC QUALIFICATIONS:

2018, Professor in Materials Science. Uppsala University.

2015, Docent (Assoc. Prof.) in Engineering Science with Specialization in Materials Science. Uppsala University.

2009, PhD in Mechanical Engineering. University of Leeds. Thesis title: Biomechanical modelling of spinal cord and bone fragment interactions during a vertebral burst fracture.

2004, MSc in Materials Engineering. European degree (EEIGM) with triple diploma from Luleå University of Technology, Lorraine University of Technology (EEIGM), Technical University of Catalonia. Master thesis at Istituto Ortopedico Rizzoli, on bone cements.

ACADEMIC POSITIONS:

2020-2023. Section Dean Engineering, Uppsala University.

2018-ongoing. Professor, Uppsala University.

2015 - 2018. Senior lecturer / Assoc. Prof., Uppsala University.

2011 - 2015. Lecturer / Ass. Prof., Uppsala University.

2009 - 2011. Researcher, Uppsala University.

2006 - 2009. PhD student, University of Leeds.

2005 - 2006. Researcher, Istituto Ortopedico Rizzoli.

Research

I lead the BioMaterial Systems (BMS) research group, where the aim is to take an integrated approach to solving clinical and sustainability problems, going from a fundamental understanding of underlying scientific mechanisms to high societal relevance. To do this, we use our combined competence in materials science, mechanical and biological engineering in combination with new technologies such as additive manufacturing (3D-printing) and machine learning.

Examples of research projects:

  1. 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.
  2. 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.
  3. 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.
  4. 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.

Funding from the Swedish Research Council (VR), the Knut and Alice Wallenberg Foundation (KAW), the Swedish Foundation for Strategic Research (SSF), Sweden’s Innovation Agency (VINNOVA) and the EU is gratefully acknowledged.

Media

Short presentation of research in BioMaterial Systems

https://media.medfarm.uu.se/play/kanal/515/video/9738

Cecilia Persson

Publications

Recent publications

All publications

Articles in journal

Articles, review/survey

Chapters in book

Conference papers

Datasets

Manuscripts (preprints)

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