Author: Pavlo Dral

Synergy Between Theory and Experiment: Stability of Pyridyl N-Heterotriangulene Ions

The stability of odd- vs even-electron ions derived from pyridine-substituted N-heterotriangulenes has been investigated by both experiment and theory.

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OMx Methods Score Well in Set from SAMPL5 Challenge

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

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Pyridyl N-Heterotriangulenes for Photovoltaics

Erlangen colleagues synthesized a series of N-heterotriangulenes, which can be used for dye-sensitized solar cells and potentially for fluorescent pH sensors.

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Benchmark of Semiempirical Methods

What is the best semiempirical method to use for your system? Find out in the most extensive benchmark study.

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Details on OMx Methods

Details about theory and implementation of up-to-now most advanced semiempirical quantum-chemical methods are published.

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Highlight about Δ-ML Approach Most Viewed in 2015

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

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New Script for Translating Wikipedia Links

Wikipedia is treasure trove of free knowledge shared by volunteers. While English Wikipedia is the most known and has the largest number of articles, you may find information in more than 200 different languages. Obviously some topics are covered better

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Correcting Differences with Machine Learning

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

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Machine Learning of Semiempirical Parameters

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

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National Wealth and High-Quality Research

In a response to my previous post “Geography of High-Quality Science” Rasmus Persson has raised an interesting question: to what extent does or does not national GDP correlate with the “research output”? Here I try to answer it and analyze

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