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Modeling Diffusive Mixing in Antisolvent Crystallization
[Image: see text] Diffusion controls local concentration profiles at interfaces between segregated fluid elements during mixing processes. This is important for antisolvent crystallization, where it is intuitively argued that local concentration profiles at interfaces between solution and antisolven...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9007412/ https://www.ncbi.nlm.nih.gov/pubmed/35431661 http://dx.doi.org/10.1021/acs.cgd.1c01269 |
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author | Miller, Russell Sefcik, Jan Lue, Leo |
author_facet | Miller, Russell Sefcik, Jan Lue, Leo |
author_sort | Miller, Russell |
collection | PubMed |
description | [Image: see text] Diffusion controls local concentration profiles at interfaces between segregated fluid elements during mixing processes. This is important for antisolvent crystallization, where it is intuitively argued that local concentration profiles at interfaces between solution and antisolvent fluid elements can result in significant supersaturation overshoots over and above that at the final mixture composition, leading to poorly controlled nucleation. Previous work on modeling diffusive mixing in antisolvent crystallization has relied on Fickian diffusion, where concentration gradients are the driving force for diffusion. This predicts large overshoots in the supersaturation at interfaces between solution and antisolvent, as is often intuitively expected. However, chemical potential gradients provide a more physically realistic driving force for diffusion, and in highly nonideal solutions, such as those in antisolvent crystallization, this leads to nonintuitive behavior. In particular, as solute diffusion toward antisolvent is severely hindered, it can diffuse against its concentration gradient away from antisolvent. We apply thermodynamically consistent diffusion model based on the multicomponent Maxwell–Stefan formulation to examine diffusive mixing in a nonideal antisolvent crystallization system. Large supersaturation overshoots above that at the final mixture composition are not found when a thermodynamically consistent approach is used, demonstrating that these overshoots are modeling artifacts and are not expected to be present in physical systems. In addition, for certain conditions, localized liquid–liquid spinodal demixing is predicted to occur during the diffusive mixing process, even when the final mixture composition is outside the liquid–liquid phase separation region. Intermittent spinodal demixing driven by diffusive mixing may provide a novel explanation for differences of nucleation behaviors among various antisolvents. |
format | Online Article Text |
id | pubmed-9007412 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-90074122022-04-14 Modeling Diffusive Mixing in Antisolvent Crystallization Miller, Russell Sefcik, Jan Lue, Leo Cryst Growth Des [Image: see text] Diffusion controls local concentration profiles at interfaces between segregated fluid elements during mixing processes. This is important for antisolvent crystallization, where it is intuitively argued that local concentration profiles at interfaces between solution and antisolvent fluid elements can result in significant supersaturation overshoots over and above that at the final mixture composition, leading to poorly controlled nucleation. Previous work on modeling diffusive mixing in antisolvent crystallization has relied on Fickian diffusion, where concentration gradients are the driving force for diffusion. This predicts large overshoots in the supersaturation at interfaces between solution and antisolvent, as is often intuitively expected. However, chemical potential gradients provide a more physically realistic driving force for diffusion, and in highly nonideal solutions, such as those in antisolvent crystallization, this leads to nonintuitive behavior. In particular, as solute diffusion toward antisolvent is severely hindered, it can diffuse against its concentration gradient away from antisolvent. We apply thermodynamically consistent diffusion model based on the multicomponent Maxwell–Stefan formulation to examine diffusive mixing in a nonideal antisolvent crystallization system. Large supersaturation overshoots above that at the final mixture composition are not found when a thermodynamically consistent approach is used, demonstrating that these overshoots are modeling artifacts and are not expected to be present in physical systems. In addition, for certain conditions, localized liquid–liquid spinodal demixing is predicted to occur during the diffusive mixing process, even when the final mixture composition is outside the liquid–liquid phase separation region. Intermittent spinodal demixing driven by diffusive mixing may provide a novel explanation for differences of nucleation behaviors among various antisolvents. American Chemical Society 2022-03-14 2022-04-06 /pmc/articles/PMC9007412/ /pubmed/35431661 http://dx.doi.org/10.1021/acs.cgd.1c01269 Text en © 2022 American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Miller, Russell Sefcik, Jan Lue, Leo Modeling Diffusive Mixing in Antisolvent Crystallization |
title | Modeling Diffusive Mixing in Antisolvent Crystallization |
title_full | Modeling Diffusive Mixing in Antisolvent Crystallization |
title_fullStr | Modeling Diffusive Mixing in Antisolvent Crystallization |
title_full_unstemmed | Modeling Diffusive Mixing in Antisolvent Crystallization |
title_short | Modeling Diffusive Mixing in Antisolvent Crystallization |
title_sort | modeling diffusive mixing in antisolvent crystallization |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9007412/ https://www.ncbi.nlm.nih.gov/pubmed/35431661 http://dx.doi.org/10.1021/acs.cgd.1c01269 |
work_keys_str_mv | AT millerrussell modelingdiffusivemixinginantisolventcrystallization AT sefcikjan modelingdiffusivemixinginantisolventcrystallization AT lueleo modelingdiffusivemixinginantisolventcrystallization |