Small organic molecules underpin modern life, from medicines and flavours to advanced materials. Much of this functional diversity comes from shape: modest changes in a molecule's 3D structure can completely change its properties.
Now, researchers have created an artificial-intelligence system that vastly simplifies and accelerates the process of chemical synthesis. The system, which is called MOSAIC and is described in a study published in Nature on 19 January, recommended conditions that researchers were able to use to generate 35 compounds with the potential to become products like pharmaceuticals, agrochemicals or cosmetics without needing to do any further trawling or tweaking.
The exponential growth of scientific literature presents an increasingly acute challenge across disciplines. Hundreds of thousands of new chemical reactions are reported annually, yet translating them into actionable experiments becomes an obstacle1,2. Recent applications of large language models (LLMs) have shown promise3,4,5,6, but systems that reliably work for diverse transformations across de novo compounds have remained elusive. Here we introduce MOSAIC (Multiple Optimized Specialists for AI-assisted Chemical Prediction), a computational framework that enables chemists to harness the collective knowledge of millions of reaction protocols.
Calling nanoscientists: your field needs you to try to replicate a landmark finding that quantum dots can act as biosensors inside living cells. As part of the first large-scale effort in the physical sciences to tackle the reproducibility crisis, researchers in France and the Netherlands are offering funds and resources in exchange for a few months of work. "We are trying to use