TY - JOUR
T1 - Simulation of Mixing in Structured Fluids with Dissipative Particle Dynamics and Validation with Experimental Data
AU - Boccardo, Gianluca
AU - Buffo, Antonio
AU - Marchisio, Daniele
N1 - Publisher Copyright:
© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
PY - 2019/8
Y1 - 2019/8
N2 - Structured fluids are simulated with dissipative particle dynamics and the predictions are validated with experimental data. The structured fluid considered is a mixture of the triblock copolymer Pluronic P103 and water. This attempt follows a first investigation with the same model parameters of a mixture with another Pluronic, L64, and water. Dissipative particle dynamics simulations are applied to identify, via a clustering algorithm, the different microstructures observed at different temperatures and compositions. This algorithm is also employed to determine the cluster mass distributions and to calculate the resulting chemical potentials associated with the different microstructures. The chemical potentials are in turn used to extract the critical micellar concentration and important shape factors. Comparison of model predictions with experimental data from the literature indicates decent agreement.
AB - Structured fluids are simulated with dissipative particle dynamics and the predictions are validated with experimental data. The structured fluid considered is a mixture of the triblock copolymer Pluronic P103 and water. This attempt follows a first investigation with the same model parameters of a mixture with another Pluronic, L64, and water. Dissipative particle dynamics simulations are applied to identify, via a clustering algorithm, the different microstructures observed at different temperatures and compositions. This algorithm is also employed to determine the cluster mass distributions and to calculate the resulting chemical potentials associated with the different microstructures. The chemical potentials are in turn used to extract the critical micellar concentration and important shape factors. Comparison of model predictions with experimental data from the literature indicates decent agreement.
KW - Dissipative particle dynamics
KW - Mixing
KW - Non-Newtonian fluids
KW - Structured fluids
UR - http://www.scopus.com/inward/record.url?scp=85066134637&partnerID=8YFLogxK
U2 - 10.1002/ceat.201800731
DO - 10.1002/ceat.201800731
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AN - SCOPUS:85066134637
SN - 0930-7516
VL - 42
SP - 1654
EP - 1662
JO - Chemical Engineering and Technology
JF - Chemical Engineering and Technology
IS - 8
ER -