Smart materials can find a valuable use in many applications. In particular, varying the type and content of magnetic filler embedded in a matrix material enables to tailor mechanical and magnetic properties of these composites and thus enables real-time self-sensing of strain/stress and long-term deformation monitoring.
MagNano3D – Magnetic Nanoparticles for 3D printed multifunctional materials
This project aims to test the feasibility of embedding magnetic nanomaterials in wood- and polymer-based matrices to produce 3D-printed multi-functional composites with self-sensing and self-heating capabilities. The idea relies upon the emergence of two advanced manufacturing technologies that are enabling more cost- and resource-efficient production, namely nanotechnology and 3D printing.
Smart materials, also referred to as intelligent or responsive materials, have properties that respond to changes in their environment. This means that one or more of their properties can be changed by an external condition, such as stress, moisture, temperature, etc. Smart materials can find a valuable use in many applications. In particular, varying the type and content of magnetic filler embedded in a matrix material enables to tailor mechanical and magnetic properties of these composites and thus enables real-time self-sensing of strain/stress and long-term deformation monitoring, as the composite material itself acts as a sensing element. These smart materials can find a valuable use in applications that rely on sensors being integrated within the material structure, such as for cost-effective, in-service diagnostic systems for condition monitoring and predictive maintenance of industrial devices and structural health monitoring (SHM). This is of particularly interest for extensively technical materials such as polymers that extensively used in industry and infrastructures, as well as wood-based construction materials.
In addition to self-sensing, magnetic nanoparticles (MNPs) also enable self-heating based on the fact that MNPs can transform electromagnetic energy from an external applied AC magnetic field to heat. This is due to the magnetic hysteresis of the MNPs when subjected to an alternating magnetic field, and it is the basis for magnetic hyperthermia treatment of cancer. When embedded in a matrix such as wood-based 3D printed parts, the self-heating of MNPs could be used for homogeneous and well-controlled drying process. Magnetically triggered self-heating can also be exploited for self-healing of cracks in non-conductive materials. Self-healing is the process whereby the material can partially recover from damage and, therefore, produce an increase in the lifetime of the component and can limit the need for its maintenance. In other words, self-healing provides an opportunity to reduce breakdown disruptions and attenuate the economic and environmental impacts stemming from the natural resources required to undertake traditional maintenance practices. For instance, the use of magnetic nanoparticles has been demonstrated as an additive in asphalt mixtures to heal micro-cracks through magnetically triggered self-heating.
In both self-sensing and self-heating applications, a significant practical advantage of using magnetic nanoparticles is that no direct physical connections, such as wires or cables, are required to either obtain information or activate the material. This enables to remotely measure the response from the material or activate it without contact with the component or structural element.
The increased versality of 3D printed polymer and bio-based components will contribute to a broader adoption and larger number of possible applications of 3D printing processes.
Monitoring the 3D printing process by means of self-sensing technology will give more insights in process and minimize quality issues, e.g. in the drying process and the level of moist required or exceeded in the 3D printed construction. Also, distributed self-heating from within the printed material will improve the printing process thus increase quality and reduce the amount of material wasted.
Self-sensing functionality will contribute to enhanced predictive maintenance and structural health monitoring, thus contributing to the minimization of environmental impact of the system, reduction of life cycle costs and enhancement of equipment durability.
Wood is one of Sweden’s most abundant natural resources and a cornerstone of Swedish industry. The wood industry generates a lot of side-stream materials that are currently mostly treated as waste. By finding uses of these materials within 3D-printing it is possible to construct with local materials, reducing waste and minimizing the transport required in the process.
Västra Götaland Region
Coordinator, participant, project manager