3D printing is any of various processes in which material is joined or solidified under computer control to create a three-dimensional object, with the material being added together (such as liquid molecules or powder grains being fused together), typically layer by layer. The research also lends itself to designing 3D-printable models of different networks. While 3D printing technology has not yet advanced to the point where researchers can print something as complex as a working hard drive or a functional robot brain, printed models provide researchers a new way to study the layout and connections of a network.
It’s known, however, that much of the brain’s work occurs in orchestrating the intricate networks that connect its processing units. Physical networks, which are restricted by the laws of three-dimensional space, captured the interest of Nima Dehmamy, a postdoctoral researcher at the Northeastern University’s Centre for Complex Network Research.
A student in industrial engineering built a physics-based computer model to find the most efficient layout for those networks, considering factors such as the thickness of the connections, the size of the nodes being connected, and whether those nodes could be moved around. The more connections you have, the more space you will require. Simpler networks respond as an irregular solid might: Stress spreads unevenly. A simple network tends to resemble an old ball-and-stick molecule set, with large nodes linked by small, relatively straight connections. There is plenty of space for connections to pass by each other without interfering. As a network becomes more complicated, however, it behaves increasingly as a gel would.
Viewing networks in their full physicality, being able to walk around them and understand the details of their wiring, offers a completely different, very personal perspective on complex systems.