QSPR AND ARTIFICIAL NEURAL NETWORK PREDICTIONS OF HYPERGOLIC IGNITION DELAYS FOR ENERGETIC IONIC LIQUIDS [PDF]
, 2023 Due to their negligible volatility, energetic ionic liquids are being considered as next generation hypergolic fuels for replacing toxic monomethylhydrazine.
Debasis, Sengupta +3 more
core +1 more source
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
doaj +1 more source
ACS Nano, 2023 To control stability in a biological medium, several factors affecting the zeta potential (ζ) of nanoparticles (NPs) must be considered, including complex interactions between the nanostructure and the composition of the protein corona (PC). Effective in
Selvaraj Sengottiyan +4 more
semanticscholar +1 more source
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
core +3 more sources
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
doaj +1 more source
A study on anti-malaria drugs using degree-based topological indices through QSPR analysis.
Mathematical biosciences and engineering : MBE, 2023 The use of topological descriptors is the key method, regardless of great advances taking place in the field of drug design. Descriptors portray the chemical characteristic of a molecule in numerical form, that is used for QSAR/QSPR models. The numerical
Xiujun Zhang +5 more
semanticscholar +1 more source
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
core +1 more source
QSPR and Nano-QSPR: Which One Is Common? The Case of Fullerenes Solubility
Inorganics, 2023 Background: The system of self-consistent models is an attempt to develop a tool to assess the predictive potential of various approaches by considering a group of random distributions of available data into training and validation sets. Considering many different splits is more informative than considering a single model.
Alla P. Toropova +2 more
openaire +2 more sources
Can Ai Revolutionize Qspr Models for the Chemical Mixtures Hazards? [PDF]
Chemical Engineering TransactionsThe physical hazards of chemical mixtures are typically characterized using experimental tools that could benefit to be prioritized by using predictive methods.
Guillaume Fayet +2 more
doaj +2 more sources
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
doaj +1 more source