A first-of-its-kind adaptive 3D printing system developed by researchers at the University of Minnesota Twin Cities can identify the positions of randomly distributed organisms and safely move them to specific locations for assembly. This autonomous technology will save researchers time and money in bioimaging, cybernetics, cryopreservation and devices that integrate living organisms.

The study was published in Higher Science entitled “3D-printed organisms enabled by aspiration-assisted adaptation strategies.” The researchers have filed a patent for the technology.

The system can track, collect and precisely position insects and other organisms whether they are at rest, in droplets or in motion. The pick-and-place method, guided by real-time visual and spatial data, adapts and can ensure precise placement of the organisms.

“The printer itself can behave like a human, with the printer acting as the hands, the machine vision system as the eyes and the computer as the brain,” said Guebum Han, a former postdoctoral fellow in mechanical engineering at the University of Minnesota and lead author of the paper. “The printer can adapt to moving or stationary organisms in real time and assemble them in a specific arrangement or pattern.”

Typically, this process is done manually and requires extensive training, which can lead to inconsistencies in organism-based applications. This new type of system reduces the time required by researchers and produces more consistent results.

This technology could be used to increase the number of organisms processed for cryopreservation, separate living from dead organisms, place organisms on curved surfaces, and integrate organisms into materials and devices in customizable shapes.

It could also lay the foundation for the creation of complex organismal arrangements, such as superorganism hierarchies – organized structures found in insect colonies such as ants and bees. In addition, the research could lead to advances in autonomous bioproduction by enabling the evaluation and assembly of organisms.

For example, this system was used to improve cryopreservation methods for zebrafish embryos, which were previously performed through manual manipulation. Using this new technology, researchers were able to show that the process could be completed 12 times faster compared to the manual method. Another example shows how the adaptive strategy tracked, picked up and placed randomly moving beetles and integrated them into functional devices.

In the future, researchers hope to further develop this technology and combine it with robots to make it portable for field research. This could allow researchers to collect organisms or samples in areas that would normally be inaccessible.

In addition to Han, the team from the University of Minnesota’s Department of Mechanical Engineering included graduate assistants Kieran Smith and Daniel Wai Hou Ng, Assistant Professor JiYong Lee, Professor John Bischof, Professor Michael McAlpine, and former postdoctoral fellows Kanav Khosla and Xia Ouyang. In addition, the work was carried out in collaboration with the Engineering Research Center (ERC) for Advanced Technologies for the Preservation of Biological Systems (ATP-Bio).