□ Professor Joongoo Kang's team from the Department of Physics and Chemistry at DGIST (President Kunwoo Lee) and Professor Sohee Jeong's team from the Department of Energy Science at Sungkyunkwan University developed a technology that visualizes the synthetic reaction pathways of semiconductor nanocrystals (colloidal quantum dots) using artificial intelligence (AI). This innovative achievement allows AI to analyze complex chemical reaction flows, which are difficult to understand through experiments alone, and to display them intuitively like a ‘subway map.’ It is expected to significantly accelerate development of next-generation display and sensor materials.
□ Semiconductor nanocrystals (colloidal quantum dots) are nanometer-sized semiconductor particles and next-generation nanomaterials whose absorption and emission color and intensity can be precisely controlled by size. They are a key material for high-color reproducibility displays, attracting attention from global companies like Samsung Display as innovative quantum dot luminescent materials. Their significance is also increasing in the field of infrared cameras and sensors.
□ However, investigating and revealing the steps involved in the formation of each nanocrystal is very challenging. Previously, researchers had to estimate reaction pathways using a method similar to ‘inference’ based on limited experimental data, which limited their ability to interpret results accurately due to data insufficiency and complex reaction behavior.
□ To address this issue, the research team combined ‘Transformer’-based AI, renowned as the latest natural language processing technology, with ‘topological data analysis.’ Using this approach, the AI automatically completes incomplete data to accurately reconstruct the entire reaction flow and identify structural connections between different data sets. Through this, the research team successfully visualized the complex reaction process as a single ‘map.’
□ The team used this technology to synthesize InAs (indium arsenide) nanocrystals, a next-generation infrared semiconductor material, and confirmed that the growth pathway, previously thought to be single, actually branches into multiple pathways. They also discovered that materials added during synthesis act as ‘traffic lights’ and are crucial in determining the reaction flow.
□ Professor Joongoo Kang said, "This study is a significant achievement demonstrating that AI can act as an 'invisible navigation' to uncover hidden pathways in chemical reactions that are difficult for humans to observe." Professor Sohee Jeong expressed her expectations, "This technology will significantly enhance research efficiency in various new fields in material development."
□ This research was funded by the National Research Foundation of Korea's Future Materials Discovery Project and the National Strategic Technology Materials Development (HUB) Project under the Nano and Materials Technology Development Program. The results were published in the Journal of the American Chemical Society (JACS), one of the world's most prestigious academic journals in chemistry.
Journal
Journal of the American Chemical Society
Article Title
Topological Machine Learning Unveils Hidden Reaction Pathways in Nanocrystal SynthesisClick to copy article link
Article Publication Date
28-Nov-2025