The conductor-like polarizable continuum model (C-PCM), which is a low-cost solvation model, cannot treat characteristic interactions between the solvent and substructure(s) of the solute. Moreover, the error in a charged system is significant. Using...
Journal of chemical theory and computation
Apr 28, 2022
The theoretical prediction of molecular electronic spectra by means of quantum mechanical (QM) computations is fundamental to gain a deep insight into many photophysical and photochemical processes. A computational strategy that is attracting signifi...
Journal of chemical information and modeling
Apr 27, 2022
An adequate understanding of molecular structure-property relationships is important for developing new molecules with desired properties. Although deep learning optical spectroscopy (DLOS) has been successfully applied to predict the optical and pho...
Journal of chemical theory and computation
Apr 1, 2022
The outcomes of computational chemistry and biology research, including drug design, are significantly influenced by the underlying force field (FF) used in molecular simulations. While improved FF accuracy may be achieved via inclusion of explicit t...
Journal of chemical information and modeling
Mar 15, 2022
Fluorescent molecules are important tools in biological detection, and numerous efforts have been made to develop compounds to meet the desired photophysical properties. For example, tuning the wavelength allows an appropriate penetration depth with ...
Unraveling challenging problems by machine learning has recently become a hot topic in many scientific disciplines. For developing rigorous machine-learning models to study problems of interest in molecular sciences, translating molecular structures ...
Journal of the American Chemical Society
Mar 8, 2022
Applications of machine learning (ML) to synthetic chemistry rely on the assumption that large numbers of literature-reported examples should enable construction of accurate and predictive models of chemical reactivity. This paper demonstrates that a...
Journal of chemical information and modeling
Jan 19, 2022
We present a group contribution method (SoluteGC) and a machine learning model (SoluteML) to predict the Abraham solute parameters, as well as a machine learning model (DirectML) to predict solvation free energy and enthalpy at 298 K. The proposed gr...
In this work, we develop a machine learning (ML) strategy to map the molecular structure to condensed phase charge-transfer (CT) properties including CT rate constants, energy levels, electronic couplings, energy gaps, reorganization energies, and re...
In recent years the degree of automation in life science laboratories increased considerably by introducing stationary and mobile robots. This trend requires intensified considerations of the occupational safety for cooperating humans, since the robo...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.