A team of researchers announced on May 4 that an autonomous laboratory has identified brighter, lead-free light-emitting nanomaterials within just 12 hours. The discovery could speed up the development of safer nanoplatelets for use in technologies such as photodetectors and solar energy production.
The new system, called PoLARIS (perovskite laboratory for autonomous reaction inference and synthesis), is designed to search through billions of possible material recipes quickly. Nanoplatelets are thin crystals that can be adjusted at the atomic level to change how they absorb and emit light. The AI-driven approach aims to overcome the slow pace of traditional trial-and-error methods used by human researchers.
Milad Abolhasani, Alcoa Professor and University Faculty Scholar at North Carolina State University, said, “One of the big challenges in developing safer optical nanomaterials is the sheer size of the material universe.” He continued, “These materials are chemically complex, and the synthesis process is challenging. There are a vast number of possible combinations of ingredients, ratios, temperatures, and reaction environments that need to be explored to synthesize light-emitting nanoplatelets with the desired optical properties. Traditional trial-and-error approaches are slow and can miss important interactions between reaction parameters.”
PoLARIS uses artificial intelligence to run experiments with different combinations automatically. It analyzes each result and adjusts its next experiment based on what it learns. Within one day, PoLARIS completed 120 experiments—improving brightness levels—and found a best-in-class recipe for safer nanoplatelets without heavy metals like lead.
“What is exciting about PoLARIS is that it does more than speed up trial and error,” Abolhasani said. “It learns from every experiment and builds a map of how chemistry, composition and temperature control material performance. That means we can discover promising materials faster, use less material and understand why the best recipes work.” He added: “Many AI-guided systems can help find an answer, but the scientific value increases dramatically when the system can also help explain the answer. PoLARIS not only found a better recipe; it helped us understand why that recipe worked.”
According to Abolhasani, PoLARIS could also serve as a small-scale factory for continuous production once optimal conditions are discovered: “The beauty of PoLARIS is that it is both a GPS for materials discovery and a miniature materials factory,” he said.
This research was published in Nature Communications with support from grants by the National Science Foundation.
