Re-visitation of Two Models for Predicting Mechanically-Induced Disordering after Cryogenic Impact Milling.

Autor: Bookwala M; School of Pharmacy and Graduate School of Pharmaceutical Sciences, Duquesne University, 600 Forbes Avenue, 422C Mellon Hall, Pittsburgh, PA, 15282, USA., Wildfong PLD; School of Pharmacy and Graduate School of Pharmaceutical Sciences, Duquesne University, 600 Forbes Avenue, 422C Mellon Hall, Pittsburgh, PA, 15282, USA. wildfongp@duq.edu.
Jazyk: angličtina
Zdroj: Pharmaceutical research [Pharm Res] 2023 Dec; Vol. 40 (12), pp. 2887-2902. Date of Electronic Publication: 2023 Jul 31.
DOI: 10.1007/s11095-023-03569-y
Abstrakt: Purpose: To compare the prediction accuracy of two models used to characterize the complete disordering potential of materials after extensive cryogenic milling.
Methods: Elastic shear moduli (μ s ) were simulated in silico. Comparison with available literature values confirmed that computations were reasonable. Complete disordering potential was predicted using the critical dislocation density (ρ crit ) and bivariate empirical models. To compare the prediction accuracy of the models, each material added for dataset expansion was cryomilled for up to 5 hr. Mechanical disordering after comminution was characterized using PXRD and DSC, and pooled with previously published results.
Results: Simulated μ s enabled predictions using the ρ crit model for 29 materials. This model mischaracterized the complete disordering behavior for 13/29 materials, giving an overall prediction accuracy of 55%. The originally published bivariate empirical model classification boundary correctly grouped the disordering potential for 31/32 materials from the expanded dataset. Recalibration of this model retained a 94% prediction accuracy, with only 2 misclassifications.
Conclusions: Prediction accuracy of the ρ crit model decreased with dataset expansion, relative to previously published results. Overall, the ρ crit model was considerably less accurate relative to the bivariate empirical model, which retained very high prediction accuracy for the expanded dataset. Although the empirical model does not imply a mechanism, model robustness suggests the importance of glass transition temperature (T g ) and molar volume (M v ) on formation and persistence of amorphous materials following extensive cryomilling.
(© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)
Databáze: MEDLINE
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