A first-of-its-kind adaptive 3D printing system developed by researchers at the University of Minnesota Twin Cities can identify the locations of randomly distributed organisms and safely move them to specific locations for assembly. This autonomous technology could save researchers time and money in devices that integrate bioimaging, cybernetics, cryopreservation, and living organisms.
The study results will be published at: Advanced ScienceA peer-reviewed scientific journal. The researchers are applying for a patent on the technology.
The system can track, collect and accurately place insects and other organisms, whether stationary, in droplets or moving. Guided by real-time visual and spatial data, the pick-and-place method can adapt and ensure accurate placement of organisms.
“The printer itself can act like a human, with the printer acting as the hand, the machine vision system acting as the eyes, and the computer acting as the brain,” said Guebom Han, a postdoctoral researcher in mechanical engineering at the University of Minnesota and first author of the paper. “The printer can adapt in real time to the moving or stationary organism, and assemble it into specific arrangements or patterns.”
Typically, this process is done manually and requires extensive training, which can lead to inconsistencies in organism-based applications. This new type of system saves researchers time and allows for more consistent results.
This technology could increase the number of organisms processed for cryopreservation, sort living and dead organisms, place organisms on curved surfaces, and integrate organisms with materials and devices of customizable shapes. It could also lay the foundation for creating complex arrangements of organisms, such as superorganism hierarchies, which are organized structures found in insect colonies such as ants and bees. This research could also lead to advances in autonomous biofabrication by enabling organisms to be evaluated and assembled.
For example, this system has been used to improve the cryopreservation of zebrafish embryos, which was previously performed manually. The new technology allowed the researchers to show that the process could be completed 12 times faster than the manual process. Another example shows how adaptive strategies can track, pick up, and place randomly moving beetles, and integrate them with functional devices.
In the future, researchers hope to further develop this technology and combine it with robotics to make it portable for field research, allowing researchers to collect organisms or samples from areas that are normally inaccessible.
In addition to Professor Han, the team from the University of Minnesota’s Department of Mechanical Engineering included graduate research assistants Kieran Smith and Daniel Wai-Ho Ng, assistant professor Jiyong Lee, professor John Bischoff, professor Michael McAlpine, and former postdoctoral researchers Kanab Khosla and Xiao Ouyang. The research also collaborated with the Engineering Research Center (ERC) for Advanced Technologies in the Conservation of Biological Systems (ATP-Bio).
This research was funded by the National Science Foundation, the National Institutes of Health, and the Minnesota Institute for Regenerative Medicine.
