THERMODYNMICS AND STRUCTURE OF POLY(ETHYLENE OXIDE) IN MIXTURES OF WATER AND ETHANOL

Poly(ethylene oxide) (PEO) is one of the most researched synthetic polymers due to the complex behavior which arises from the interplay of the hydrophilic and hydrophobic sites on the polymer chain. PEO in ethanol forms an opaque gel-like mixture with a partially crystalline structure. Addition of a small amount of water disrupts the gel: 5 wt % PEO in ethanol becomes a transparent solution with the addition of 4 vol % water. The phase behavior of PEO in mixed solvents have been studied using small-angle neutron scattering (SANS). PEO solutions (5 wt % PEO) which contain 4 vol % - 10 vol % (and higher) water behave as an athermal polymer solution and the phase behavior changes from UCST to LCST rapidly as the fraction of water is increased. 2 wt % PEO in water and 10 wt % PEO in ethanol/ water mixtures are examined to assess the role of hydration. The observed phase behavior is consistent with a hydration layer forming upon the addition of water as the system shifts from UCST to LCST behavior. At the molecular level, two or three water molecules can hydrate one PEO monomer (water molecules form a sheath around the PEO macromolecule) which is consistent with the suppression of crystallization and change in the mentioned phase behavior as observed by SANS. The clustering effect of aqueous PEO solution (M.W of PEO = 90,000 g/mol) is monitored as an excess scattering intensity at low-Q. Clustering intensity at Q = 0.004 Å^-1 is used for evaluating the clustering effect. The clustering intensity is proportional to the inverse temperature and levels off when the temperature is less than 50 ˚C. When the temperature is increased over 50 ˚C, the clustering intensity starts decreasing. The clustering of PEO is monitored in ethanol/ water mixtures. The clustering intensity increases as the fraction of water is increased. Based on the solvation intensity behavior, we confirmed that the ethanol/ water mixtures obey a random solvent mixing rule, whereby solvent mixtures are better at solvating the polymer that any of the two solvents. The solution behavior of PEO in ethanol was investigated in the presence of salt (CaCl2) using SANS. Binding of Ca2+ ions to the PEO oxygens transforms the neutral polymer to a weakly charged polyelectrolyte. We observed that the PEO/ethanol solution is better solvated at higher salt concentration due to the electrostatic repulsion of weakly charged monomers. The association of the Ca2+ ions with the PEO oxygen atoms transforms the neutral polymer to a weakly charged polyelectrolyte and gives rise to repulsive interactions between the PEO/Ca2+ complexes. Addition of salt disrupts the gel, which is consistent with better solvation as the salt concentration is increased. Moreover, SANS shows that the phase behavior of PEO/ethanol changes from UCST to LCST as the salt concentration is increased.

ENGINEERING DIGITAL SHARING PLATFORM TO CREATE SOCIAL CONTAGION: EVIDENCE FROM LARGE SCALE RANDOMIZED FIELD EXPERIMENTS

Peer-to-peer information sharing has fundamentally changed customer decision-making process. Recent developments in information technologies have enabled digital sharing platforms to influence various granular aspects of the information sharing process. Despite the growing importance of digital information sharing, little research has examined the optimal design choices for a platform seeking to maximize returns from information sharing. My dissertation seeks to fill this gap. Specifically, I study novel interventions that can be implemented by the platform at different stages of the information sharing. In collaboration with a leading for-profit platform and a non-profit platform, I conduct three large-scale field experiments to causally identify the impact of these interventions on customers’ sharing behaviors as well as the sharing outcomes. The first essay examines whether and how a firm can enhance social contagion by simply varying the message shared by customers with their friends. Using a large randomized field experiment, I find that i) adding only information about the sender’s purchase status increases the likelihood of recipients’ purchase; ii) adding only information about referral reward increases recipients’ follow-up referrals; and iii) adding information about both the sender’s purchase as well as the referral rewards increases neither the likelihood of purchase nor follow-up referrals. I then discuss the underlying mechanisms. The second essay studies whether and how a firm can design unconditional incentive to engage customers who already reveal willingness to share. I conduct a field experiment to examine the impact of incentive design on sender’s purchase as well as further referral behavior. I find evidence that incentive structure has a significant, but interestingly opposing, impact on both outcomes. The results also provide insights about senders’ motives in sharing. The third essay examines whether and how a non-profit platform can use mobile messaging to leverage recipients’ social ties to encourage blood donation. I design a large field experiment to causally identify the impact of different types of information and incentives on donor’s self-donation and group donation behavior. My results show that non-profits can stimulate group effect and increase blood donation, but only with group reward. Such group reward works by motivating a different donor population. In summary, the findings from the three studies will offer valuable insights for platforms and social enterprises on how to engineer digital platforms to create social contagion. The rich data from randomized experiments and complementary sources (archive and survey) also allows me to test the underlying mechanism at work. In this way, my dissertation provides both managerial implication and theoretical contribution to the phenomenon of peer-to-peer information sharing.

Structure dependencies for multiscale polymer composites using extrusion processes

Multiscale reinforcement, using carbon microfibers and multi-walled carbon nanotubes, of polymer matrix composites manufactured by twin-screw extrusion is investigated for enhanced mechanical and thermal properties with an emphasis on the use of a diverging flow in the die for fluid mechanical fiber manipulation. Using fillers at different length scales (microscale and nanoscale), synergistic combinations have been identified to produce distinct mechanical and thermal behavior. Fiber manipulation has been demonstrated experimentally and computationally, and has been shown to enhance thermal conductivity significantly. Finally, a new physics driven predictive model for thermal conductivity has been developed based on fiber orientation during flow, which is shown to successfully capture composite thermal conductivity.