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In our recent study, we propose using machine learning (ML) to correct differences in properties calculated at two quantum chemical (QC) methods with different accuracy. In the Δ-ML approach ML model is trained on differences between some property calculated at…
Tagged with: APT
We propose using machine learning (ML) for improving semiempirical Hamiltonian. Given sufficiently large training set ML can be used to correct parameters of semiempirical quantum chemical (SQC) method individually for any target molecule. Such automatic parametrization technique (APT) stands in…
Tagged with: APT
In our study we reported synthesis, and experimental and theoretical characterization of new one-dimensional coordination polymers. Research article “Multiply Bonded Metal(II) Acetate (Rhodium, Ruthenium, and Molybdenum) Complexes with the trans-1,2-Bis(N-methylimidazol-2-yl)ethylene Ligand” (DOI: 10.1021/ic501435a) was published on November 13th in the…
Tagged with: Inorg. Chem.
If you need really huge data set to test your methods, then our data set with 133,885 species is one of the best choices. You can download it in figshare.
Did you know that the reactivity of alkyl radicals towards H-abstraction is related to their electron accepting properties? And that alkyl cations are much more reactive than alkyl radicals for the same reason? The same tool that clearly visualizes these…