From dental crowns to airplane parts, 3D printing has become a vital tool for making precise, customized products quickly.
Among the many techniques available, one of the most popular is photocurable 3D printing, where light is used to solidify liquid resin into detailed structures.
This method is fast and highly accurate, but it has a major drawback: the printed objects are fragile and can easily break under impact.
Now, researchers at the Korea Advanced Institute of Science and Technology (KAIST) have developed a breakthrough technology that makes photocurable 3D printing much stronger, more adaptable, and more economical.
Led by Professor Miso Kim in the Department of Mechanical Engineering, the team has combined new materials, light-based printing, and artificial intelligence (AI) to overcome the weaknesses of traditional approaches.
Their results are published in Advanced Materials.
The challenge has always been balancing flexibility with durability. Injection molding, for example, produces extremely tough products but requires costly and time-consuming molds.
Photocurable 3D printing, on the other hand, offers speed and design freedom but lacks strength. Professor Kim’s team tackled this by addressing both the material and the design process.
First, they created a new resin called polyurethane acrylate (PUA), which incorporates dynamic chemical bonds.
These bonds allow the material to absorb shocks and vibrations much better than traditional photocurable resins.
This means printed objects can range from soft, rubber-like parts to rigid, plastic-like components while still resisting damage.
Second, the researchers used a technique called grayscale digital light processing (DLP). Instead of curing the resin with uniform light, they adjusted the intensity of the light in different areas.
This produces varying levels of strength within the same object, much like how bones and cartilage work together in the human body—bones provide rigidity, while cartilage absorbs shocks.
To decide where each part should be stronger or softer, the team turned to AI. A machine learning algorithm analyzes the design and predicts where stresses and loads will occur. It then recommends an optimal distribution of material strength, automatically tailoring each structure for its intended use.
This integration of material science and computational design makes the process not only smarter but also more efficient.
The economic benefits are striking. In the past, achieving different material properties within a single product required multi-material printing—an expensive and complex process involving multiple resins and printers.
The KAIST method achieves the same results with one resin, one printer, and one streamlined process. This reduces costs, simplifies production, and accelerates product development.
Professor Kim highlighted the wide range of potential applications. Medical implants could be designed to match a patient’s body more comfortably and last longer.
Aerospace components could be lighter yet more robust. Robotics could benefit from stronger and more flexible parts. The ability to control material strength with such precision opens doors across industries.
“This technology expands both the material possibilities and the design freedom of 3D printing,” Kim explained. “It not only improves performance but also ensures economic feasibility. We expect it to have a major impact in biomedical engineering, aerospace, and robotics.”
By merging light, AI, and new materials, KAIST researchers are pushing 3D printing into a new era—one where products are stronger, smarter, and more affordable than ever before.
