http://hdl.handle.net/20.500.12128/12500
Tytuł: | Effects of cooling rate on structural relaxation in amorphous drugs: elastically collective nonlinear langevin equation theory and machine learning study |
Autor: | Phan, Anh D. Wakabayashi, Katsunori Paluch, Marian Lamef, Vu D. |
Słowa kluczowe: | Amorphous drugs; Machine learning method |
Data wydania: | 2019 |
Źródło: | "RSC Advances" 2019, iss. 69, s. 40214-40221 |
Abstrakt: | Theoretical approaches are formulated to investigate the molecular mobility under various cooling rates of amorphous drugs. We describe the structural relaxation of a tagged molecule as a coupled process of cage-scale dynamics and collective molecular rearrangement beyond the first coordination shell. The coupling between local and non-local dynamics behaves distinctly in different substances. Theoretical calculations for the structural relaxation time, glass transition temperature, and dynamic fragility are carried out over twenty-two amorphous drugs and polymers. Numerical results have a quantitatively good accordance with experimental data and the extracted physical quantities using the Vogel-Fulche-Tammann fit function and machine learning. The machine learning method reveals the linear relation between the glass transition temperature and the melting point, which is a key factor for pharmaceutical solubility. Our predictive approaches are reliable tools for developing drug formulations. |
URI: | http://hdl.handle.net/20.500.12128/12500 |
DOI: | 10.1039/c9ra08441j |
ISSN: | 2046-2069 |
Pojawia się w kolekcji: | Artykuły (WNŚiT) |
Plik | Opis | Rozmiar | Format | |
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Phan_Effects_of_cooling_rate_on_structural_relaxation_in_amorphous.pdf | 870,25 kB | Adobe PDF | Przejrzyj / Otwórz |
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