Physical chemistry chemical physics : PCCP
Nov 9, 2022
Graph neural networks (GNNs) have been proven effective in the fast and accurate prediction of nuclear magnetic resonance (NMR) chemical shifts of a molecule. Existing methods, despite their effectiveness, suffer from high space complexity and are th...
Physical chemistry chemical physics : PCCP
Oct 5, 2022
Efficient prediction of the partition coefficient (log ) between polar and non-polar phases could shorten the cycle of drug and materials design. In this work, a descriptor, named 〈 - ACSFs〉, is proposed to take the explicit polarization effects in t...
Physical chemistry chemical physics : PCCP
Sep 21, 2022
We provide a comprehensive overview of the chemical information from electron density: not only how to extract information, but also how to obtain and how to assess the quality of the electron density itself. After introducing several indexes derived...
Physical chemistry chemical physics : PCCP
Aug 10, 2022
Water suppression is of paramount importance for many biological and analytical NMR spectroscopy applications. Here, we report the design of a new set of binomial-like radio frequency (RF) pulses that elude water irradiation while exciting or refocus...
Physical chemistry chemical physics : PCCP
Jun 1, 2022
In this study, a total of 302 molecular structures of phenylnaphthylamine antioxidants based on -phenyl-1-naphthylamine and -phenyl-2-naphthylamine skeletons with various substituents were modeled by exhaustive methods. Antioxidant parameters, includ...
Physical chemistry chemical physics : PCCP
Jun 1, 2022
There has been increasing attention in using machine learning technologies, such as neural networks (NNs) and Gaussian process regression (GPR), to model multi-dimensional potential energy surfaces (PESs). A PES constructed using NNs features high ac...
Physical chemistry chemical physics : PCCP
May 11, 2022
-Butyl hydroperoxide (BuOOH) is a common intermediate in the oxidation of organic compounds that needs to be accurately quantified in complex gas mixtures for the development of chemical kinetic models of low temperature combustion. This work present...
Physical chemistry chemical physics : PCCP
May 4, 2022
While state-of-art models can predict reactions through the transfer learning of thousands of samples with the same reaction types as those of the reactions to predict, how to prepare such models to predict "unseen" reactions remains an unanswered qu...
Physical chemistry chemical physics : PCCP
May 4, 2022
Evaluating the protein-ligand binding affinity is a substantial part of the computer-aided drug discovery process. Most of the proposed computational methods predict protein-ligand binding affinity using either limited full-length protein 3D structur...
Physical chemistry chemical physics : PCCP
Mar 2, 2022
Predicting quantum mechanical properties (QMPs) is very important for the innovation of material and chemistry science. Multitask deep learning models have been widely used in QMPs prediction. However, existing multitask learning models often train m...