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By Posted on Posted in Electronic Structure Calculations, Machine Learning in Chemistry, News, Semiempirical Methods No Comments Tagged with , , , , , , , , ,

Alkyne-embedding [11]cycloparaphenylene ([11]CPPs) was functionalized with electron-donating, -neutral, and -withdrawing aryl substituents to yield a series of nanolassos via click chemistry. We used our state-of-the-art, artificial intelligence-enhanced quantum mechanical method 1 (AIQM1) to thoroughly analyze the electronic and photophysical properties of these …

Large Cycloparaphenylene Nanolassos Characterized with AIQM1 Read more »

By Posted on Posted in Machine Learning in Chemistry, Method Development, News, Semiempirical Methods No Comments Tagged with , , , , ,

We have developed artificial intelligence-enhanced quantum mechanical method 1 (AIQM1), which can be used out of the box for very fast quantum chemical calculations with the accuracy of the gold-standard coupled-cluster method. Read more »

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OMx methods have once again been shown to give as accurate results as DFT methods, but substantially faster.  The OM2 method has outperformed other semi-empirical methods and has essentially the same accuracy as BLYP for the distribution coefficient part of …

OMx Methods Score Well in Set from SAMPL5 Challenge Read more »

By Posted on Posted in Machine Learning in Chemistry, Method Development, News, Semiempirical Methods 1 Comment Tagged with , , , , , ,

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 …

Correcting Differences with Machine Learning Read more »

By Posted on Posted in Machine Learning in Chemistry, Method Development, News, Semiempirical Methods No Comments Tagged with , , , ,

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 …

Machine Learning of Semiempirical Parameters Read more »

By Posted on Posted in Method Development, Nanoelectronics, News, Semiempirical Methods No Comments Tagged with , , , ,

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 …

The Unrestricted Local Properties Read more »