Structure-based sampling and self-correcting machine learning is used for precise representation of molecular potential energy surfaces and calculating vibrational levels with spectroscopic accuracy (errors less than 1 cm−1 relative to the reference ab initio spectrum) decreasing the number of required …

Self-Correcting Machine Learning and Structure-Based Sampling Read more »

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A series of the substituted two-electron acceptors with a dicyanomethylene-bridged acridophosphine scaffold has been prepared and compared with the nitrogen-containing counterpart using various spectroscopic, electrochemical and theoretical methods.

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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 »

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A highlight by Jan Jensen about the Δ-ML approach proposed by us [1] was the most viewed highlight in Computational Chemistry Highlights in 2015. This marks a pleasant ending of the last-year research on improving accuracy of computationally less demanding …

Highlight about Δ-ML Approach Most Viewed in 2015 Read more »

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