New Modeling Method Improves the Behavior of 3D-Printed Multifunctional Structures

An international research team led by Universidad Carlos III de Madrid (UC3M), in collaboration with the University of Oxford, Imperial College London, and the BC Materials research center in the Basque Country, has developed a computational model that predicts and optimizes the behavior of 3D-printed multifunctional structures. Funded by the BBVA Foundation through a Leonardo Grant, the study was published in Nature Communications and could open new applications in biomedicine, soft robotics, and other engineering fields.

“Currently, conductive thermoplastics are very promising because of their ability to transmit electrical signals while providing structural support,” explains one of the study’s authors, Daniel García-González, from the UC3M Department of Mechanics of Continuous Media and Theory of Structures. “But the main challenge in the manufacture of these materials is the control of their internal structure, since the bonding between filaments and the presence of small cavities affect both their mechanical resistance and their capacity to transmit electrical signals,” explains the scientist.

These factors, previously considered inevitable limitations of the 3D printing process, have now been successfully controlled through the integration of advanced computational simulations and experimental testing.

A key aspect of the research is its transferability to other 3D printing technologies, particularly those utilizing softer materials. According to Javier Crespo, also from UC3M’s Department of Continuum Mechanics and Structural Theory, this discovery could pave the way for advancements in additive manufacturing. “A key point about this discovery is that it can be extrapolated to other types of 3D printing technology in which softer materials could be used,” adds Javier Crespo.

The findings could be particularly beneficial in the production of soft robots and in generating virtual datasets for machine learning applications.

Emilio Martínez-Pañeda, professor at the University of Oxford and co-author of the study, pointed out that “the research opens up endless opportunities, enabling the development of intelligent materials and sensors that could be of great use in the aerospace industry or in infrastructure monitoring.”

“And not only that,” adds Daniel García-González, “with these new materials we could also create patches or dressings that warn us how many times we are flexing our knee so that, in the event that we have an injury, we are alerted if we are passing certain critical points where we are going to cause damage to our muscles.”