Login / Signup

Phase Behavior of the Mixtures of 2- and 3-Components for Poly(styrene- co -octafluoropentyl methacrylate) by Dispersion Polymerization under CO 2 .

Uma Sankar BeheraDivya BaskaranHun-Soo Byun
Published in: ACS omega (2024)
The dispersed-phase polymerization of poly(styrene- co -2,2,3,4,4,4-octafluoropentyl methacrylate), also known as p(styrene- co -OFPMA), took place in supercritical carbon dioxide (sc-CO 2 ). The chemical and physical properties of p(styrene- co -OFPMA) were studied by varying the styrene-to-OFPMA ratios (40:1, 30:1, and 20:1) and 2,2'-azobis(isobutyronitrile) (AIBN) initiator amounts (wt %: 1.0, 2.0, 3.0). The cloud-point data were obtained for various systems, including the binary mixtures of p(styrene- co -OFPMA) (30:1 ratio, AIBN wt %: 1.0, 2.0, 3.0) with supercritical solvents such as sc-CO 2 , sc-CH 3 OCH 3 , sc-C 3 H 6 , sc-C 4 H 8 , and sc-CHClF 2 . Phase behavior (i.e., mixtures) was studied at temperatures of 324-455 K and pressure below 201 MPa. In the binary system of p(styrene- co -OFPMA) + sc-CH 3 OCH 3 , a lower critical solution temperature (LCST)-type curve was observed, characterized by a positive slope. Conversely, the binary systems of p(styrene- co -OFPMA) + (sc-C3H 6 , sc-C 4 H 8 , sc-CHClF 2 ) exhibited an upper critical solution temperature (UCST) behavior with a decreasing slope. The phase equilibrium curves were obtained for p(styrene- co -OFPMA) [30:1; 1.0% ( M w = 42,400), 2.0% ( M w = 33,800), and 4.0% ( M w = 24,100); AIBN: 1.0 wt %] + sc-C 3 H 6 , sc-C 4 H 8 , and sc-CHClF 2 mixtures. These curves exhibited an increasing slope for p(styrene- co -OFPMA) + sc-CH 3 OCH 3 and a negative slope for p(styrene- co -OFPMA) + (sc-C 3 H 6 , sc-C 4 H 8 , sc-CHClF 2 ) systems, indicating distinct phase behavior. Tetramethyl orthosilicate (TMOS) addition (0.0-68.9 wt %) to P(styrene- co -OFPMA) (30:1; AIBN wt %: 1.0) + solvents altered the phase equilibrium, switching from UCST to LCST, as evidenced by changes in the pressure-temperature slope.
Keyphrases
  • ionic liquid
  • molecular dynamics
  • molecular dynamics simulations
  • deep learning
  • artificial intelligence
  • data analysis