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Jul 2026
Prediction of solubility of hydrogen in chemicals using QSPR-based machine learning approach: a comparative study
For the first time, a comprehensive and predictive MLR-based QSPR model has been developed for this target and the predictive capability of the MLR-QSPR model was acceptable for training set.
Ali Ebrahimpoor Gorji, V. Alopaeus
· Journal of Computer-Aided Mo... · 0 citations
Aug 2026
Machine learning prediction of organic compound melting points informed by condensed-phase and electronic descriptors.
Melting point (MP) is an important thermophysical property for the chemical process industry, yet accurate prediction of MP for organic compounds in the absence of experimental data remains challenging due to the complex interplay between molecular packing, intermolecular interactions, and electronic structure. Traditi...
Frank T. Mtetwa, Neil F. Giles, W. Wilding et al.
· Journal of Chemical Physics · 0 citations
Open access
Jul 2026
Machine learning-guided screening and validation of antioxidant small molecules from Clausena lansium
To discover natural antioxidants from Clausena lansium (Lour.) Skeels for food applications, we established a 474-compound database and applied a multiscale workflow integrating ensemble machine learning, molecular docking, structural clustering, molecular dynamics simulations, and quantum chemical calculations. The en...
Yufan Tong, Min Wang
· Food Chemistry: X · 0 citations
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Detour Ring Index as a Molecular Descriptor for Predicting Gas Chromatographic Retention of Sulfur Polycyclic Aromatics
Prediction of positional isomers in polycyclic aromatic sulfur compounds remains a challenge in analytical chemistry. Here, simple ring‐based topological descriptors derived from Distance/Detour Ring Indices (D/DIr05, D/DIr06, and D/DIr09) are evaluated for benzothiophene and dibenzothiophene positional isomers. D/...
N. Moustafa, Kout El‐Kloub Fars Mahmoud, Abdulelah H. Alsulami et al.
· Separation Science Plus · 0 citations
Open access
Jul 2026
Performance Prediction of Metal Nitride Energetic Materials Based on Structural Searching and Machine Learning
A design principle is proposed for advanced metal nitride HEDMs: prioritizing high nitrogen-to-metal ratios, light metal elements, and structures wherein nitrogen atoms are spatially separated by the metal matrix, which minimizes N-N bonds and favors dominant M-N bonding.
Yaozhong Liu, Huifang Du, Caimu Wang et al.
· Chinese Physics B · 0 citations
Open access
Aug 2026
Prediction of the Molecular Lipophilicity of an Alkylphenol Family Using Quantum Chemistry and QSPR Methods
This study examined the relationship between the water/octanol partition coefficient of eighteen alkylphenols and molecular descriptors derived from quantum-chemical calculations using a quantitative structure-property relationship (QSPR) approach. The experimental database was divided into a training set of fourteen c...
Fatogoma Diarrassouba, K. Bamba, N. Ziao
· Asian Journal of Chemical Sc... · 0 citations