Results 61 to 70 of about 25,271,406 (229)

Factors Affecting Bubble Size in Ionic Liquids [PDF]

, 2017
This study reports on understanding the formation of bubbles in ionic liquids (ILs), with a view to utilising ILs more efficiently in gas capture processes. In particular, the impact of the IL structure on the bubble sizes obtained has been determined in
Ahlrichs, Al-Mashhadani, Andreatta, Arce, Bao, Becke, Calado, Canongia Lopes, Christopher Hardacre, Dong, Dong, Freire, Gacino, Garcia-Gutierrez, Grimme, Gutowski, Hanotu, Hanotu, Holbrey, Johan Jacquemin, Kazakov, Klamt, Kondor, Kowacz, Law, Lee, Lei, Lu, Marcelja, Marcelja, Masuch, Neale, Neves, Pratik Desai, Quéré, Rogers, Sarah F. R. Taylor, Seoane, Stuart A. Brittle, Tokuda, Wang, Wang, Weigend, Weigend, Wesley, Wesley, Wichmann, William A. Zimmerman, Ying, Zhang, Zhang, Zimmerman, Zimmerman   +52 more
core   +4 more sources

Molecular descriptor driven QSPR modeling of Papp, TEER and Efflux Ratio from Caco‐2 cells using machine learning for various phytochemicals

Journal of the Science of Food and Agriculture, EarlyView.
Abstract BACKGROUND The present study aimed to develop and validate quantitative structure–property relationship (QSPR) models for predicting permeability related bioavailability indicators including apparent permeability (Papp), trans‐epithelial electrical resistance (TEER) and efflux ratio (ER) based on molecular descriptors (n = 5003) of 83 ...
Jin‐Woo Kim, Rixing Cong, Jin‐Soo Park, Keunwan Park, Kyungsu Kang, Soon‐Mi Shim   +5 more
wiley   +1 more source

Structure‐Aware Machine Learning for Polymers: A Hierarchical Graph Network for Predicting Properties From Statistical Ensembles

Macromolecular Rapid Communications, EarlyView.
This work presents a structure‐aware graph convolutional network that models polymers as statistical ensembles to predict macroscopic properties. By combining topologically realistic graphs generated via kinetic Monte Carlo simulations with explicit molar mass distributions, the framework achieves high accuracy in classifying architectures and ...
Julian Kimmig, Yannik Köster, Timo Koswig, Punith Raviswamy, Subhash V. S. Ganti, Stefan Zechel, Christopher Kuenneth, Ulrich S. Schubert   +7 more
wiley   +1 more source

QSPR-driven prediction of analyte permeability for advancing CP-MIMS applications

Green Analytical Chemistry
Condensed Phase-Membrane Introduction Mass Spectrometry (CP-MIMS) is a sustainable and highly versatile approach within the framework of Direct Mass Spectrometry techniques, which enables real-time determination of target analytes by integrating sampling,
Enmanuel Cruz Muñoz, Veronica Termopoli, Davide Ballabio, Marco Orlandi, Viviana Consonni   +4 more
doaj   +1 more source

On the prediction of thermal stability of nitroaromatic compounds using quantum chemical calculations [PDF]

, 2009
International audienceThis work presents a new approach to predict thermal stability of nitroaromatic compounds based on quantum chemical calculations and on quantitative structure-property relationship (QSPR) methods.
Adamo, Carlo, Fayet, Guillaume, Joubert, Laurent, ROTUREAU, Patricia   +3 more
core   +3 more sources

QSPR analysis of some agonists and antagonists of α-adrenergic receptors [PDF]

Medicinal Chemistry Research, 2014
Thirty-three compounds belonging to the sympatholytics and sympathomimetics were analyzed during the study. The biological activity data for the parameters of binding affinity to the α1- and α2-adrenergic receptors together with parameters of the logarithm of the partition coefficient n-octanol/water (log P) were performed using a semi-empirical ...
Kawczak, Piotr, Bober, Leszek, Bączek, Tomasz   +2 more
openaire   +2 more sources

QSPR analysis of anti-hepatitis prescription drugs using degree based topological indices through M-polynomial and NM-polynomial

Chimica Techno Acta
Chemical graph theory plays a vital role in pharmaceutical research, particularly in the study of antiviral drugs such as those targeting hepatitis.
Adnan Asghar
semanticscholar   +1 more source

Predicting Drop‐Weight Impact Sensitivity From Molecular Graphs Using Physics‐Informed Artificial Intelligence

Propellants, Explosives, Pyrotechnics, EarlyView.
This work presents an approach for predicting the drop‐weight impact sensitivity of pure molecular explosives directly from 2D molecular graphs using physics‐informed artificial intelligence (AI) models. A dataset comprising experimentally measured sensitivities for 625 unique high‐explosive molecules is augmented with physics‐informed synthetic ...
Grant Hutchings, Jack V. Davis, Virginia W. Manner, Marc J. Cawkwell, Frank W. Marrs   +4 more
wiley   +1 more source

β‐Triketone‐Based Ionizable Cationic Lipids Synthesized via Click Chemistry for siRNA Delivery

Advanced Science, Volume 13, Issue 26, 8 May 2026.
This study innovatively applies β‐triketone‐based click chemistry in the synthesis of ionizable cationic lipids (ICLs), which allows the generation of a lipid library in large quantities and in a short time. The ICLs identified achieved effective lipid nanoparticles‐mediated hepatic gene silencing in vivo using siRNA, and computational simulations are ...
Huatian Li, Haocheng Tang, Yiqing Mu, Shangyu Chen, Paul Edward Floreancig, Junmei Wang, Yixian Huang, Song Li   +7 more
wiley   +1 more source

QSPR and QSTR analysis to explore pharmacokinetic and toxicity properties of antifungal drugs through topological descriptors

Scientific Reports
COVID-19 patients often develop serious fungal infections like Aspergillosis, Candidiasis, and Mucormycosis, which are treated with antifungal drugs like Amphotericin B, Posaconazole, and Isavuconazole.
W. Tamilarasi, B. J. Balamurugan
doaj   +1 more source