Researchers led by Katzke et al. have launched Antscan, a digital repository featuring high-resolution 3D scans of approximately 800 ant species [1], [2].

This project provides an unprecedented look at ant morphology, offering an openly accessible resource for researchers, artists, and educators. By digitizing these specimens, the team removes the physical barriers to studying rare or fragile insects, allowing scientists worldwide to analyze anatomy without risking damage to original samples.

The creation of the library was made possible through a combination of robotics, artificial intelligence, and a synchrotron accelerator for X-ray imaging [2]. This advanced facility allowed the team to process specimens at an industrial scale. In a single week, the researchers scanned 2,000 specimens [4].

The resulting database includes 800 3D models [5]. These models represent 212 different genera [3], which covers roughly two-thirds of all known ant genera [1]. The high-resolution nature of the scans allows for the detailed study of physical traits that were previously difficult to document using traditional photography or manual sketching.

Project leaders said the findings in March 2026 [2]. The integration of AI helped streamline the transition from raw X-ray data to the final 3D models, reducing the time required to catalog such a vast array of biodiversity [1], [3].

By making the Antscan collection public, the researchers aim to foster collaboration across different scientific disciplines. The repository serves as a benchmark for how rapid scanning technology can be applied to other insect groups or endangered species to preserve biological data before specimens degrade or go extinct [3].

“Antscan spans two-thirds of all ant genera”

The Antscan project demonstrates a shift toward 'cyber-taxonomy,' where AI and high-energy physics accelerate the cataloging of Earth's biodiversity. By converting physical specimens into open-source digital assets, the project reduces the reliance on physical museum visits and minimizes the risk of specimen loss, potentially speeding up the discovery of new species and the understanding of evolutionary traits.