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Yield stress fluids and fundamental particle statistics
Yield stress in complex fluids is described by resorting to fundamental statistical mechanics for clusters with different particle occupancy numbers. Probability distribution functions are determined for canonical ensembles of volumes displaced at the incipient motion in three representative states...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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The Royal Society of Chemistry
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9064768/ https://www.ncbi.nlm.nih.gov/pubmed/35515264 http://dx.doi.org/10.1039/c9ra02150g |
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author | Mezzasalma, Stefano A. |
author_facet | Mezzasalma, Stefano A. |
author_sort | Mezzasalma, Stefano A. |
collection | PubMed |
description | Yield stress in complex fluids is described by resorting to fundamental statistical mechanics for clusters with different particle occupancy numbers. Probability distribution functions are determined for canonical ensembles of volumes displaced at the incipient motion in three representative states (single, double, and multiple occupancies). The statistical average points out an effective solid fraction by which the yield stress behavior is satisfactorily described in a number of aqueous (Si(3)N(4), Ca(3)(PO(4))(2), ZrO(2), and TiO(2)) and non-aqueous (Al(2)O(3)/decalin and MWCNT/PC) disperse systems. Interestingly, the only two model coefficients (maximum packing fraction and stiffness parameter) turn out to be correlated with the relevant suspension quantities. The latter relates linearly with (Young’s and bulk) mechanical moduli, whereas the former, once represented versus the Hamaker constant of two particles in a medium, returns a good linear extrapolation of the packing fraction for the simple cubic cell, here recovered within a relative error ≈ 1.3%. |
format | Online Article Text |
id | pubmed-9064768 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | The Royal Society of Chemistry |
record_format | MEDLINE/PubMed |
spelling | pubmed-90647682022-05-04 Yield stress fluids and fundamental particle statistics Mezzasalma, Stefano A. RSC Adv Chemistry Yield stress in complex fluids is described by resorting to fundamental statistical mechanics for clusters with different particle occupancy numbers. Probability distribution functions are determined for canonical ensembles of volumes displaced at the incipient motion in three representative states (single, double, and multiple occupancies). The statistical average points out an effective solid fraction by which the yield stress behavior is satisfactorily described in a number of aqueous (Si(3)N(4), Ca(3)(PO(4))(2), ZrO(2), and TiO(2)) and non-aqueous (Al(2)O(3)/decalin and MWCNT/PC) disperse systems. Interestingly, the only two model coefficients (maximum packing fraction and stiffness parameter) turn out to be correlated with the relevant suspension quantities. The latter relates linearly with (Young’s and bulk) mechanical moduli, whereas the former, once represented versus the Hamaker constant of two particles in a medium, returns a good linear extrapolation of the packing fraction for the simple cubic cell, here recovered within a relative error ≈ 1.3%. The Royal Society of Chemistry 2019-06-14 /pmc/articles/PMC9064768/ /pubmed/35515264 http://dx.doi.org/10.1039/c9ra02150g Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/ |
spellingShingle | Chemistry Mezzasalma, Stefano A. Yield stress fluids and fundamental particle statistics |
title | Yield stress fluids and fundamental particle statistics |
title_full | Yield stress fluids and fundamental particle statistics |
title_fullStr | Yield stress fluids and fundamental particle statistics |
title_full_unstemmed | Yield stress fluids and fundamental particle statistics |
title_short | Yield stress fluids and fundamental particle statistics |
title_sort | yield stress fluids and fundamental particle statistics |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9064768/ https://www.ncbi.nlm.nih.gov/pubmed/35515264 http://dx.doi.org/10.1039/c9ra02150g |
work_keys_str_mv | AT mezzasalmastefanoa yieldstressfluidsandfundamentalparticlestatistics |