Machine learning-enabled prediction of chemical durability of A2B2O7 pyrochlore and fluorite
Sign Up to like & getrecommendations! Published in 2021 at "Computational Materials Science"
DOI: 10.1016/j.commatsci.2021.110820
Abstract: Abstract Pyrochlore-structure type and its derivative in a general formula A2B2O7 (A = rare earth elements and actinides; B = Ti, Sn, Zr, Hf, Pb, Si, etc.) display excellent structural flexibility and rich crystal chemistry as promising nuclear waste… read more here.
Keywords: durability; machine learning; prediction chemical; chemical durability ... See more keywords
In silico prediction of chemical aquatic toxicity for marine crustaceans via machine learning.
Sign Up to like & getrecommendations! Published in 2019 at "Toxicology research"
DOI: 10.1039/c8tx00331a
Abstract: Aquatic toxicity is a crucial endpoint for evaluating chemically adverse effects on ecosystems. Therefore, we developed in silico methods for the prediction of chemical aquatic toxicity in marine environment. At first, a diverse data set… read more here.
Keywords: toxicity; aquatic toxicity; chemical aquatic; prediction chemical ... See more keywords
Insight into in silico prediction and chemical degradation study of osimertinib mesylate by LC-HRMS and NMR: Investigation of a typical case of alkaline pH-mediated oxidative degradation product
Sign Up to like & getrecommendations! Published in 2023 at "European Journal of Mass Spectrometry"
DOI: 10.1177/14690667231162345
Abstract: Osimertinib mesylate is a third-generation epidermal growth factor receptor tyrosine kinase inhibitor used to treat nonsmall-cell lung cancer. The objective was to understand in silico prediction and chemical-based stress testing of the osimertinib mesylate. A… read more here.
Keywords: degradation; silico prediction; prediction chemical; osimertinib mesylate ... See more keywords