A new study shows that a partial atom-to-atom map of a chemical reaction has a unique extension exactly when it covers the reaction center, and describes how such extensions can be computed using constrained graph-isomorphism searches on Imaginary Transition State…
Here we walk through how we built this molecule, why each design choice mattered, and what the measurements show. Several platforms, from trapped ions to defects in diamond, have made impressive progress on this list but meeting all four requirements…
ChromSoc is organizing a two-day symposium, Data Analytics and Ai in Chromatography, from 10–11 May 2027 in the Green Park Conference Centre in Reading, UK. The Chromatographic Society (ChromSoc) is organizing a two-day symposium called Data Analytics and Ai in Chromatography running…
Chemists at the University of Oxford have resolved the decade-old mystery of how hard carbon forms atom by atom... Seventy-five years after Rosalind Franklin’s foundational research into non-graphitising carbons, chemists at the University of Oxford have resolved the decade-old mystery…
Oxford chemists used machine learning-driven atomistic simulations to show how the polymer PVDC breaks down into hard carbon, whose five- and seven-membered carbon rings explain why the material resists forming graphite.
Machine learning models trained on finite element simulations predicted the photoionization cross section of a donor impurity in a GaAs/AlGaAs quantum dot–ring nanostructure with coefficients of determination above 0.9999.
Electrocatalysis sits at the heart of clean hydrogen production, fuel cells, and carbon dioxide conversion, yet progress toward scalable, high-performance catalysts has remained frustratingly slow. A growing body of research now suggests that artificial intelligence (AI) may be key to…
A research team maps the key tasks that define modern enzyme engineering—function annotation, structure modeling, and property prediction—and explain how AI methods now accelerate each step, from mining candidate enzymes in massive sequence databases to generating new variants…
By far, the most popular method in quantum chemistry and material science is Density Functional Theory (DFT) because it combines modest cost with relatively high accuracy. The use of DFT blossomed after the introduction of hybrid DFT by Becke in…
Up to the previous installment, we looked at what information exchange-correlation functionals use and how they have evolved. So, once energy values are obtained from a calculation program, how much can you trust those values? Having many digits is not…
Chemistry by computer: quantum-chemical calculations, molecular simulation, machine learning for molecules and quantum computers applied to chemistry.
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