Manipulation Of Soft Matter System In Nonequilibrium Conditions
Soft matter systems can be easily manipulated to drive out of equilibrium by external perturbations, like shear, temperature gradient, tuning electric and magnetic field, applying pressure. The simplest non-equilibrium state of a system is steady state, where there is a time independent current in the system. Soft matter systems in nonequilibrium steady state are often important even for various applications.
In the thesis, we have investigated a couple of problems on soft matter systems in non-equilibrium situation: (1) Long ranged structures in systems with temperature sensitive interactions in the presence of temperature gradient. (2) Motion of particles driven through a polymeric network. These systems in non-equilibrium situation may be helpful in various technological applications.
Recent experiments show that the inter-particle interaction in metallic nanoparticles with ligand capping is sensitive to temperature. The zeta potential of the nano particles is reduced in the cold region. Such nano particles form aggregates in cold region of the system in presence of temperature difference. These aggregates are important sensory applications. Experiments further report on thermoresponsive particles where particles get larger in size and show emergence of ordered structure in cold region in presence of temperature gradient. The microscopic insight to these non-equilibrium steady state structure with temperature sensitive interaction is lacking.
We study here systems with temperature sensitive interaction. First, we consider temperature sensitive interaction as in ligand capped metal nanoparticles. In our model calculations particle interaction consists of repulsive term coming from zeta potential and also attractive terms coming from hydrophobic ligands over the nanoparticles. The repulsive term decreases with temperature, while the hydrophobic attraction increases with temperature. Particles diffusion is larger at high temperature. As soon as a particle enters in a temperature region from other, its interaction strength and diffusivity changes corresponding to that region. We study the system using the Brownian dynamics(BD) simulations. We find long-ranged structural order using unsupervised machine learning(UML) and bond order parameter in the cold region of the system with the Avrami like crystal growth kinetics. Physically, the long-ranged order in cold region form due to increase in density and slow diffusion.
We also study system with thermoresponsive particle with temperature dependent size using Molecular dynamics(MD) simulation. We tune ratio of diameter of cold and hot region as a parameter for a particular temperature gradient. Here, we observe long-ranged order both in cold and hot region for higher diameter ratio. Physically, increase in diameter in cold region pushes out particles from cold to hot region. Thus, the packing fraction increases in both cold and hot region, leading to crystallization in both region.
Next we study a couple of cases on driven particles through a polymer network.
Face Mask(FM) has become common-place in contemporary times following the COVID-19 pandemic. FMs are typically made of fabric materials of entangled polymeric networks. FMs intercept respiratory droplets of micrometer size and thereby helps to prevent spreading of air-borne diseases. But FMs need to exchange essential molecules between the human body and the atmosphere so that normal breathing takes place. For comfortable breathing pressure drop inside FM for different types of FM materials, found to be around 2.5 ± 0.4 Pa. Designing efficient FM ensuring normal breathability is a challenge. This needs an understanding of the droplet movement inside FM in presence of pressure difference which we model here. We model droplet movement through FM under pressure difference as required for normal breathing. In our model the mask is treated as a polymeric network in an asymmetric confinement, while the droplet is taken as a micrometer sized tracer colloidal particle, subject to driving force that mimics the breathing pressure difference. We study tracer permeation from the air side of the FM towards the side facing the mouth, using the Langevin dynamics simulation. We observe that droplet permeation is an activated Arrhenius process with temperature. The efficiency of the mask depends on the barrier height of activation which can be tuned by composition of polymer, interaction strength of tracer and the network, the network rigidity and the thickness of the confinement.
Pressure-driven Reverse Osmosis(RO) membrane are widely used nowadays both separation processes in industry and household purposes, like water purification. In RO, the solvent is forced by pressure drops through a semipermeable membrane. It is yet a challenge to design RO membrane with better permeation, solute rejection and less fouling. This needs microscopic understanding of relative interaction of mixture with membrane. Here we model RO process. In our model the membrane is created as a polymeric network in an asymmetric confinement situation to the experimental conditions. We attach two reservoir on two sides of membrane, one is a binary mixture with low concentration of large solute particles while the other is a pure solvent. We study separation of this binary mixture through the polymeric membrane where solvent is driven by force from mixed side to the pure side. We tune relative interaction strength which is defined by ratio of interaction between solute particles and two polymeric network beads. The solute rejection and fouling increases with increasing relative interaction strength, while solvent extraction ranges around 40\%. We further observe that the fouling reduces with increasing relative interaction of solvent with membrane matrix.
We show possibility of of formation of long-ranged order in non-equilibrium
conditions. Further we show how the particle movement driven through a polymeric network can be controlled. Our work can be helpful for sensory application, designing new materials. It can also be helpful in designing face mask with better efficiency while retaining normal breath-ability conditions and to design better RO membrane.