Results 61 to 70 of about 11,633 (209)
Advanced Science, Volume 13, Issue 19, 2 April 2026.UHSR translates complex chemical behavior into clear and explainable equations. Applied to thin‐layer chromatography, it automatically uncovers the mathematical rules linking a molecule's structure to its polarity. This approach matches the accuracy of advanced AI while providing interpretable results, earning greater trust from chemists. The method is
Siyu Lou +4 more
wiley +1 more source
Feature Learning applied to the Estimation of Tensile Strength at Break in Polymeric Material Design
Journal of Integrative Bioinformatics, 2016 Several feature extraction approaches for QSPR modelling in Cheminformatics are discussed in this paper. In particular, this work is focused on the use of these strategies for predicting mechanical properties, which are relevant for the design of ...
Fiorella Cravero +4 more
doaj +1 more source
Effect of Energy Harvesting on Stable Throughput in Cooperative Relay Systems
, 2015 In this paper, the impact of energy constraints on a two-hop network with a source, a relay and a destination under random medium access is studied.
Ephremides, Anthony +4 more
core +1 more source
Chemistry–Methods, Volume 6, Issue 4, April 2026.Hydration free energy is essential to understanding stability and reactivity in aqueous environments. Recently, we reported a machine learning model Mole2Solv to predict experimental hydration free energies of molecules (J. Phys. Chem. Lett., 2023, 14, 1877).
Luyang Jia +4 more
wiley +1 more source
Chemical Graph Theory for Property Modeling in QSAR and QSPR—Charming QSAR & QSPR
Mathematics, 2020 Quantitative structure-activity relationship (QSAR) and Quantitative structure-property relationship (QSPR) are mathematical models for the prediction of the chemical, physical or biological properties of chemical compounds.
Paulo C. S. Costa +3 more
doaj +1 more source
Computational and Machine‐Learning Studies of Ethylene Oligomerization
Carbon and Hydrogen, Volume 28, Issue 1, Page 40-65, March 2026.This review focuses on recent advances in computational and machine‐learning studies of ethylene oligomerization, highlighting mainstream catalyst systems based on Co, Ta, Ti, Zr, and Hf, with particular emphasis on Fe‐ and Cr‐based catalysts and their controlling factors governing reactivity and LAO distribution.
Zhixin Qin +3 more
wiley +1 more source
Harary-Albertson index of graphs [PDF]
Contributions to Mathematics, 2021 Zhen Lin
doaj +1 more source
Modeling of the Acute Toxicity of Benzene Derivatives by Complementary QSAR Methods [PDF]
, 2013 A data set containing acute toxicity values (96-h LC50) of 69 substituted benzenes for fathead minnow (Pimephales promelas) was investigated with two Quantitative Structure- Activity Relationship (QSAR) models, either using or not using molecular ...
Bertinetto, Carlo +3 more
core
A Closed‐Loop Hybrid Discovery System of Type I Photosensitizers for Hypoxic Tumor Therapy
Advanced Science, Volume 13, Issue 9, 13 February 2026.The work developed a closed‐loop hybrid discovery system to rationally design and predict high‐performance Type I PSs for hypoxic tumor therapy. 664 Potential candidates are identified from a dataset through a support vector machine (SVM) classification model, and two candidates are experimentally verified as Type I PSs, which highlighted the potential
Xia Ling +9 more
wiley +1 more source
Beyond Silicon: Toward Sustainable, NIR‐II, and Conformable Organic Photodiodes
Advanced Energy Materials, Volume 16, Issue 6, 11 February 2026.In this perspective, a strategic shift in organic photodetector (OPD) research is proposed: instead of the incremental advances in silicon's stronghold arena, the most impactful future for OPDs lies in addressing silicon's intrinsic limitations, i.e., detection in the longer wavelength range above silicon's coverage (>1100 nm, termed as near infrared ...
Hrisheekesh Thachoth Chandran +7 more
wiley +1 more source