99% yield and 92% ee at room temperature, with just 5 mol% catalyst. Getting high reactivity and high selectivity together is the challenge. XtalPi and SUSTech used computational design to achieve both. We combined DFT calculations and noncovalent interaction analysis to guide the development of chiral antimony catalysts. This helped us identify structural changes that strengthen reactivity while favoring the desired enantiomer, then make and test those designs experimentally. Our optimized catalyst, CAC-10, delivered the performance above. Across the study, we demonstrated the chemistry with 33 epoxide-aniline combinations, producing β-amino alcohols, building blocks found in pharmaceuticals and natural products. Published in JACS, this work shows how computation can turn an understanding of chemical reactivity into the ability to design for it. Moving from trial-and-error screening toward predictive design offers a faster, less costly route to the chiral catalysts used in pharmaceutical synthesis. #AIforScience #AsymmetricCatalysis #JACS

Meet lcms2yield, XtalPi’s state-of-the-art model that predicts UV correction factors up to 1,000,000x faster than quantum chemistry, now open source. Already running in our automated labs, it predicts full-spectrum UV correction factors from a SMILES string in milliseconds. These predictions, together with LC-UV data and an internal standard, let us estimate reaction yields without purifying product standards or building product-specific calibration curves. On 178 real reactions (Suzuki, amide coupling, Buchwald-Hartwig, SN2): • 4.74 percentage-point mean absolute error vs traditional calibration curves • 59% within 5 percentage points, 89% within 10 Pretrained on QC calculations for 22,609 compounds, fine-tuned on 1,845 experimental measurements. Published in JACS Au. Links below 👇 What’s one task in your lab you wish you never had to do manually again? #AIforScience #OpenSource