3D printing next generation batteries

1 min read

A new method of 3D printing battery electrodes that creates a 3D microlattice structure with controlled porosity has been developed by a team of researchers from Carnegie Mellon in collaboration with Missouri University of Science and Technology.

"In the case of lithium-ion batteries, the electrodes with porous architectures can lead to higher charge capacities," says Associate Professor Rahul Panat."This is because such architectures allow the lithium to penetrate through the electrode volume leading to very high electrode utilisation, and thereby higher energy storage capacity.

“In normal batteries, 30-50% of the total electrode volume is unutilised. Our method overcomes this issue by using 3D printing where we create a microlattice electrode architecture that allows the efficient transport of lithium through the entire electrode, which also increases the battery charging rates."

According to the researchers, the microlattice structure (Ag) used as lithium-ion batteries' electrodes offered a fourfold increase in specific capacity and a twofold increase in areal capacity when compared to a solid block (Ag) electrode.

The electrodes also retained their 3D lattice structures after 40 electrochemical cycles, the researchers add. As a result, the batteries have high capacity for the same weight or, for the same capacity, a reduced weight.

With this method, the researchers say they were able to 3D print the battery electrodes by rapidly assembling individual droplets one-by-one into 3D structures. The resulting structures have complex geometries impossible to fabricate using typical extrusion methods.

"Because these droplets are separated from each other, we can create these new complex geometries," says Assoc Prof Panat. "If this was a single stream of material, as is in the case of extrusion printing, we wouldn't be able to make them. This is a new thing. I don't believe anybody until now has used 3D printing to create these kinds of complex structures."

The belief is that this method will have potential within the consumer, medical and aerospace space.

The researchers estimate the technology will be ready to translate to industrial applications in about 2-3 years.