Quantitative Structure-Properties Relationship of Lubricating Oil Additives and Molecular Dynamic Simulations Studies of Diamond-Like-Carbon (DLC) [PDF]
Iranian Journal of Chemistry & Chemical Engineering, 2020 Quantitative Structure-Properties Relationship (QSPR) and molecular dynamics simulations studies were carried out on the 53 lubricating oil additives and hydrogen-containing DLC (a-C: H).
Usman Abdulfatai +3 more
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New structure-based models for the prediction of normal boiling point temperature of ternary azeotropes [PDF]
Journal of the Serbian Chemical Society, 2021 Recently, development of the QSPR models for mixtures has received much attention. The QSPR modelling of mixtures requires the use of the appropriate mixture descriptors.
Faramarzi Zohreh +3 more
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How can polydispersity information be integrated in the QSPR modeling of mechanical properties?
Science and Technology of Advanced Materials: Methods, 2022 Polymer informatics is an emerging discipline that has benefited from the strong development that data science has experienced over the last decade. Machine learning methods are useful to infer QSPR (Quantitative Structure-Property Relationships) models ...
F. Cravero +4 more
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QSPR designer – a program to design and evaluate QSPR models. Case study on pKaprediction [PDF]
Journal of Cheminformatics, 2011 Nowadays, a large amount of experimental and predicted data about the 3D structure of organic molecules and biomolecules is available. Advanced computational methods and high performance computers allow us to obtain large sets of descriptors that can be used to estimate physicochemical properties.
Ondrej Skrehota +6 more
openaire +2 more sources
Corrections of Molecular Morphology and Hydrogen Bond for Improved Crystal Density Prediction
Molecules, 2019 Density prediction is of great significance for molecular design of energetic materials, since detonation velocity linearly with density and detonation pressure increases with the density squared.
Linyuan Wang +7 more
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QSPR Models for Predicting Critical Micelle Concentration of Gemini Cationic Surfactants Combining Machine-Learning Methods and Molecular Descriptors [PDF]
, 2020 A data set of 231 diverse gemini cationic surfactants has been developed to correlate the logarithm of critical micelle concentration (cmc) with the molecular structure using a quantitative structure-property relationship (QSPR) methods. The QSPR models
Mudasir, Mudasir +2 more
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PREDICTION OF LIPOPHILIC PROPERTIES OF ADAMANTANE DERIVATIVES
Siberian Journal of Life Sciences and Agriculture, 2020 The article explores QSPR models for predicting the lypophilicity of chemicals in the adamantane family. The study of the lypophilicity parameter is carried out using the developed nonlinear models using absolute entropy.
Alexander Leonidovich Osipov +1 more
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Estimating flavonoid oxidation potentials: mechanisms and charge-related regression models
Arhiv za Higijenu Rada i Toksikologiju, 2023 In this paper, I tested our quadratic regression models for the estimation of flavonoid oxidation potentials based on spin populations, the differences in the net atomic charges between a cation and a neutral flavonoid, between a radical and an anion of ...
Miličević Ante
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QSPR Modeling of Bioconcentration Factors of Nonionic Organic Compounds [PDF]
, 2010 The terms bioaccumulation and bioconcentration refer to the uptake and build-up of chemicals that can occur in living organisms. Experimental measurement of bioconcentration is time-consuming and expensive, and is not feasible for a large number of ...
Padmakar V. Khadikar +5 more
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A simple 2D-QSPR model for the prediction of Setschenow constants of organic compounds
Macedonian Journal of Chemistry and Chemical Engineering, 2016 A quantitative structure-property relationship (QSPR) analysis of the Setschenow constants (Ksalt) of organic compounds in a sodium chloride solution was carried out using only two-dimensional (2D) descriptors as input parameters.
Qi Xu, Lingling Fan, Jie Xu
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