A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
General approach for partitioning and phase separation in macromolecular coexisting phases; 
Tekijät: Varma, Vikki Anand; Scacchi, Alberto
Kustantaja: American Physical Society (APS)
Julkaisuvuosi: 2026
Lehti: Physical Review E
Artikkelin numero: 065414
Vuosikerta: 113
Numero: 6
ISSN: 2470-0045
eISSN: 2470-0053
DOI: https://doi.org/10.1103/v6nd-87cd
Julkaisun avoimuus kirjaamishetkellä: Avoimesti saatavilla
Julkaisukanavan avoimuus : Osittain avoin julkaisukanava
Verkko-osoite: https://doi.org/10.1103/v6nd-87cd
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/527029136
Preprintin osoite: https://arxiv.org/abs/2509.14392v1
Rinnakkaistallenteen lisenssi: CC BY
Rinnakkaistallennetun julkaisun versio: Kustantajan versio
Partitioning of (bio)materials in polymeric mixtures is a key phenomenon both in cellular environments, as well as in industrial applications. In cells, macromolecules are distributed among distinct biomolecular phases. The coexistence of polymeric aqueous phases in multicomponent systems has been widely exploited for the extraction and purification of (bio)materials from aqueous environments. Despite their relevance, key physical and chemical properties controlling the phase behavior of these complex systems are still lacking. Here, we have developed a classical density functional theory approach for describing the phase coexistence and partitioning of an arbitrary number of polymers and suspended materials. As a case example, we focus on a binary mixture of phase separating polymers in which a third material is dispersed. We explore the effect of size ratios and affinities between the different materials and address their distribution and coexisting densities, and find optimal conditions for partitioning.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
Julkaisussa olevat rahoitustiedot:
This work was supported by the Jane ja Aatos Erkon Säätiö under Grant No. 230052 (A.S.). Computational resources by CSC IT Center for Finland are also gratefully acknowledged. The work was conducted within the #SUSMAT profiling measure at the University of Turku, Finland. We are also thankful to Prof. A. Archer for fruitful discussions.
V.A.V. carried out the work under the supervision of A.S. and wrote the first draft of the manuscript. A.S. conceived the idea and secured the funding for the work. All authors contributed to writing and reviewing.
