Adaptive 3D printing system for the selection and placement of organisms

A first-of-its-kind adaptive 3D printing system developed by researchers at the University of Minnesota can recognize the positions of randomly distributed organisms and place them safely in specific locations for assembly.

This autonomous technology offers significant advantages in areas such as bioimaging, cybernetics, cryopreservation and the integration of living organisms into technical devices. The results of this research have been published in the journal Advanced Science and the technology is already patent pending.

The system works by detecting and accurately positioning organisms, regardless of whether they are stationary, enclosed in droplets or in motion. It uses a pick-and-place method driven by real-time data to visually and spatially detect the organisms. These adaptive capabilities enable precise placement of the organisms, which was previously done manually and with great effort.

“The printer itself can act like a human would, with the printer acting as hands, the machine vision system as eyes, and the computer as the brain,” said Guebum Han, a former University of Minnesota mechanical engineering postdoctoral researcher and first author on the paper. “The printer can adapt in real-time to moving or still organisms and assemble them in a certain array or pattern.”

Traditionally, this process requires manual intervention, which is not only time-consuming but can also lead to inconsistent results. The new system not only reduces the time researchers have to spend on these tasks, but also ensures more consistent results. The technology could also increase efficiency in processing organisms for cryopreservation, sorting living organisms from dead ones and positioning them on curved surfaces, as well as integrating them into materials and devices with customizable shapes.

A practical example of the application of this technology is the improvement of cryopreservation methods in zebrafish embryos, where manual handling was accelerated twelvefold by the new system. Another example shows how the system tracks and records randomly moving beetles and integrates them into functional devices.

In the future, the research team plans to further develop the technology and combine it with robotics to make it portable for use in the field. This could enable researchers to collect organisms or samples in places that are difficult to access. In addition to Han, doctoral students Kieran Smith and Daniel Wai Hou Ng as well as professors JiYong Lee and John Bischof were involved in the research. The work was carried out in collaboration with the Engineering Research Center for Advanced Technologies for the Preservation of Biological Systems (ATP-Bio).