Researchers at North Carolina State University have introduced Rainbow, a multi-robot self-driving laboratory designed to autonomously discover and optimize quantum dots. Quantum dots are semiconductor nanoparticles used in advanced displays, solar cells, LEDs, and technologies related to quantum engineering.
According to Milad Abolhasani, corresponding author of the study and ALCOA Professor of Chemical and Biomolecular Engineering at NC State, “Rainbow brings together multiple robots working in concert to autonomously explore and optimize complex chemistries with extraordinary efficiency. Rainbow’s robots automatically prepare chemical precursors, mix them, and execute multiple reactions in parallel using miniaturized batch reactors – up to 96 reactions at a time. The system then automatically transfers all reaction products to a characterization robot, which analyzes the outcomes. From start to finish, every step is fully automated and intelligently coordinated.”
The lab uses artificial intelligence alongside robotics to perform up to 1,000 experiments daily without human involvement. Users set a target material property—such as emission wavelength or bandgap—and an experimental limit for Rainbow. The system then designs, conducts, and analyzes each experiment using real-time optical characterization and machine learning to guide its next steps.
“Rainbow doesn’t sleep; it works around the clock, performing in days what would take human researchers years,” Abolhasani says. “But it’s not designed to replace scientists; it’s built to empower them by handling the tedious, time-intensive parts of discovery so they can focus on design and innovation.”
Abolhasani noted that unlike previous self-driving labs he developed, Rainbow’s robotic components allow for experiments with a broader range of precursor chemistries. This flexibility enables researchers to investigate more potential compositions for high-quality quantum dots.
“Because we are not confined to a fixed set of precursors, there is a wider range of potential outcomes in terms of what the highest quality quantum dot will be made of,” Abolhasani says. “In addition, Rainbow allows us to explore various ligand structures on the surface of these nanocrystals, which can play a key role in controlling the properties of these quantum dots.
“With Rainbow, we’ve built a system that not only finds the best quantum dots faster than ever before, it also tells us why they work,” said Abolhasani. “That’s the power of combining robotics, AI and chemistry in a single, intelligent lab platform.”
Once optimal synthesis recipes are identified by Rainbow for specific quantum dots, the system can transition from small-scale research reactors to larger manufacturing reactors without major changes.
“Rainbow makes scaling up a seamless transition,” Abolhasani says.
The research paper titled “Autonomous multi-robot synthesis and optimization of metal halide perovskite nanocrystals” was published on August 22 in Nature Communications (DOI: 10.1038/s41467-025-63209-4). Jinge Xu is listed as first author along with several other co-authors from NC State University.
Funding for this project came from the University of North Carolina Research Opportunities Initiative (UNC ROI) and grants from the National Science Foundation.
