2024-10-10 19:01:00
A team of engineers led by researchers from the University of Glasgow have developed a system capable of modeling the complex physics of 3D printed composites for the first time. Only by measuring the electrical current does the system detect stretch, strain and damage to these self-sensing materials.
The university calls this a breakthrough in the development of self-sensing materials for aircraft, robotics, bridges and other applications. In the aircraft industry, these self-sensing materials could register the structural integrity of a component in real time. In infrastructural parts, such a material could ensure that the condition of a bridge, tunnel or building is continuously monitored and signals are received long before serious problems arise. The researchers think this is a breakthrough for 3D printing.
Cheap, relatively easy-to-manufacture materials can be equipped with the remarkable ability to detect when they are damaged
How do they monitor behavior?
By adding nanotubes to a 3D printing material, a low electrical current can be sent through the material. The structural integrity of the part or product can then be monitored via what is called the piezoresistivity phenomenon. When the measured current changes value, this indicates that the material is crushed or stretched, so action can be taken to correct the fault. The existence of piezoresistive behavior has been known to scientists for some time. However, until now they have not been able to apply this in a useful way in materials. It was not known in advance how effective these self-sensing materials are. That had to be determined by trial and error. In the article, the researchers describe how they developed their system through a series of laboratory experiments combined with modeling.
Predicting behavior of self-sensing materials
They used a commonly used plastic, polyetherimide (PEI), mixed with carbon nanotubes to create four different lightweight lattice structure designs. These designs were then tested for stiffness, strength, energy absorption and self-sensitivity. Using advanced computer models, they developed a system to predict how the materials would respond to a varied range of loads. They then validated the predictions of their finite element model at multiple scales by subjecting the materials to intensive analysis under real-world conditions, using infrared thermal imaging to visualize the electrical current flowing through the materials in real time.
Monitor performance without additional hardware
Professor Shanmugam Kumar from the James Watt School of Engineering University of Glasgow led the research, which was published as an article in the journal Advanced Functional Materials. He says: “Adding piezoresistive behavior to 3D printed cellular materials allows them to control their own performance without additional hardware. This means we can provide cheap, relatively easy-to-manufacture materials with the remarkable ability to detect when they are damaged and measure how damaged they are. These types of autonomous materials with sensor architecture offer significant untapped potential to create advanced new components. The results can support future developments in additive manufacturing by providing insight into how proposed new materials will perform before the first prototype is printed in the real world.
Also for other materials
The research builds on previous developments by the team, which recently completed a article published about a different approach to modeling that allows researchers to predict how defects caused by additive manufacturing can affect the structural integrity of a new design. Professor Kumar: “With this research, we have developed a comprehensive system capable of modeling the performance of self-detecting, 3D printed materials. This is the first system of its kind that enables the modeling of 3D printed materials at multiple scales and encompasses multiple types of physics.” The principle can also be applied to materials other than PEI with nano tubes.
The results of the team’s research, titled ‘Autonomous Sensing Architected Materials’was published in Advanced Functional Materials.
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