In this work, a quantitative structure-antioxidant activity relationship of flavonoids was performed using a machine learning (ML) method. To achieve lipid-soluble, highly antioxidant flavonoids, 398 molecular structures with various substitute group...
Solvatochromism occurs in both homogeneous solvents and more complex biological environments, such as proteins. While in both cases the solvatochromic effects report on the surroundings of the chromophore, their interpretation in proteins becomes mor...
Prediction of organismal viability upon exposure to a nanoparticle in varying environments─as fully specified at the molecular scale─has emerged as a useful figure of merit in the design of engineered nanoparticles. We build on our earlier finding th...
We present a formalism of a neural network encoding bonded interactions in molecules. This intramolecular encoding is consistent with the models of intermolecular interactions previously designed by this group. Variants of the encoding fed into a cor...
Of the various factors influencing kinetically controlled product ratios, the role of nonstatistical dynamics is arguably the least well understood. In this paper, reactions were chosen in which dynamics played a dominant role in product selection, b...
The correct description of catalytic reactions happening on bimetallic particles is not feasible without proper accounting of the segregation process. In this study, we tried to shed light on the structure of large CoCu particles, for which quite con...
Recently, the development of machine learning (ML) potentials has made it possible to perform large-scale and long-time molecular simulations with the accuracy of quantum mechanical (QM) models. However, for different levels of QM methods, such as de...
Neural network potentials are emerging as promising classical force fields that can enable long-time and large-length scale simulations at close to accuracies. They learn the underlying potential energy surface by mapping the Cartesian coordinates o...
Machine learning (ML) methods extract statistical relationships between inputs and results. When the inputs are solid-state crystal structures, structure-property relationships can be obtained. In this work, we investigate whether a simple neural net...
Cyclohexane oxidation chemistry was investigated using a near-atmospheric pressure jet-stirred reactor at = 570 K and equivalence ratio ϕ = 0.8. Numerous intermediates including hydroperoxides and highly oxygenated molecules were detected using sync...