Science & Technology (Commonwealth Union) – As 3D printing becomes more and more significant a key drawback remains: many of the plastic materials used by these printers are not easily recyclable. Despite the emergence of new sustainable materials for 3D printing, their adoption is hindered by the need to manually adjust 3D printer settings for each material.
The rapid advancement of 3D printing has seen this technology continuously improve and adapt. Research last year demonstrated how 3D printing can use Computer vision that can make it possible to print with high-performance materials.
Typically, printing a new material entail configuring up to 100 parameters in the software that governs how the printer extrudes the material to create an object. Established materials have standardized parameter sets honed through arduous trial-and-error processes.
However, renewable and recyclable materials exhibit variable properties, making it nearly impossible to establish fixed parameter sets. Consequently, users must manually determine these parameters.
In response, researchers devised a solution: a 3D printer capable of autonomously identifying parameters for unknown materials. A collaborative effort between MIT’s Center for Bits and Atoms (CBA), the U.S. National Institute of Standards and Technology (NIST), and the National Center for Scientific Research in Greece (Demokritos) led to the modification of the extruder—the core component of a 3D printer—to measure material forces and flow.
The data, obtained through a brief 20-minute test, are input into a mathematical function to automatically generate printing parameters. These parameters can then be integrated into standard 3D printing software, enabling printing with previously untried materials.
Researchers of the study indicated that the automatically produced parameters have the potential to replace approximately half of the parameters typically requiring manual tuning. Through a series of test prints utilizing diverse materials, including various renewable sources, the researchers have demonstrated the consistent viability of their method.
It was further indicated that this advancement in additive manufacturing holds promise for reducing its environmental footprint, which often relies on non-recyclable polymers and fossil fuel-derived resins.
Neil Gershenfeld, senior author and head of CBA, pointed out that in this paper, they showcase a method capable of leveraging bio-based and sustainably sourced materials, allowing the printer to autonomously adapt to print them. their aim is to enhance the sustainability of 3D printing.
The team comprises first author Jake Read, a graduate student at CBA who spearheaded printer development; Jonathan Seppala, a chemical engineer at NIST’s Materials Science and Engineering Division; Filippos Tourlomousis, formerly a postdoc at CBA and now leading the Autonomous Science Lab at Demokritos; James Warren, heading the Materials Genome Program at NIST; and Nicole Bakker, a research assistant at CBA. Their findings are published in the journal Integrating Materials and Manufacturing Innovation.
In the process of fused filament fabrication (FFF), commonly utilized in rapid prototyping, heated polymers are extruded through a nozzle in a layered fashion to construct a part. A software tool, known as a slicer, directs the machine; however, configuring the slicer for a specific material is crucial.
Incorporating renewable or recycled materials into an FFF 3D printer poses significant challenges due to numerous factors impacting material properties. For example, bio-based polymers or resins may consist of varying plant compositions depending on the season. Similarly, recycled materials exhibit diverse properties depending on the available recyclables.
“In ‘Back to the Future,’ there is a ‘Mr. Fusion’ blender where Doc just throws whatever he has into the blender and it works [as a power source for the DeLorean time machine]. That is the same idea here. Ideally, with plastics recycling, you could just shred what you have and print with it. But, with current feed-forward systems, that won’t work because if your filament changes significantly during the print, everything would break,” explained Read.
In addressing these obstacles, the researchers devised a 3D printer and accompanying workflow capable of autonomously discerning suitable process parameters for any unfamiliar material.
Their endeavor commenced with the utilization of a pre-existing 3D printer from their laboratory, equipped with data capturing capabilities and feedback mechanisms during operation. Augmentations were made to the printer’s extruder through the integration of three instruments tasked with measurements crucial for parameter determination.
One instrument, a load cell, gauges the pressure exerted on the printing filament, while another, a feed rate sensor, monitors both filament thickness and the rate at which it is being fed through the printer.
“This fusion of measurement, modeling, and manufacturing is at the heart of the collaboration between NIST and CBA, as we work develop what we’ve termed ‘computational metrology,’” said Warren.
