EPFL develops new 3D printing method for dense metal and ceramic structures from hydrogels

Researchers at the École Polytechnique Fédérale de Lausanne (EPFL) have presented a novel 3D printing process that enables the production of dense and stable metal and ceramic structures. The method is based on a water-based hydrogel in which metals and ceramics can directly “grow.” According to a report in Advanced Materials, the technique opens up new perspectives for applications in energy, sensor, and medical technologies.

The process utilizes the principles of so-called “vat photopolymerization,” in which photosensitive materials are cured layer by layer using laser or UV light. In contrast to conventional methods, which are limited to photoreactive polymers, the EPFL approach separates the 3D printing process from the choice of material for the first time. First, a stable hydrogel scaffold is created, which is then infused with metal salts. These are chemically transformed into metal-containing nanoparticles that uniformly permeate the gel. After several such growth cycles, the hydrogel is thermally removed, leaving behind a dense metal or ceramic body in the desired shape.

“Our work not only enables the fabrication of high-quality metals and ceramics with an accessible, low-cost 3D printing process; it also highlights a new paradigm in additive manufacturing where material selection occurs after 3D printing, rather than before,” said Daryl Yee, head of the ALCHEMY lab.

“Our work highlights a new paradigm in additive manufacturing where material selection occurs after 3D printing, rather than before”, said Yee.

The researchers tested the method on complex lattice structures, known as gyroids, made from iron, silver, and copper. Such geometries are relevant for applications requiring high stability at low weight, such as in catalysts, heat exchangers, or biomedical implants.

“Our materials could withstand 20 times more pressure compared to those produced with previous methods, while exhibiting only 20% shrinkage versus 60-90%,” says PhD student and first author Yiming Ji.

“We are already working on bringing the total processing time down by using a robot to automate these steps,” Yee says.

In the future, the team aims to increase process speed, including through automation of the infusion cycles. This could make the method attractive for industrial applications in additive manufacturing.