Narrow Results

We investigate the dynamics of a first order transition when the order parameter field undergoes resonant oscillations, driven by a periodically varying parameter of the free energy. This parameter could be a background oscillating field as in models of pre-heating after inflation. In the context of condensed matter systems, it could be temperature T, or pressure, external electric/magnetic field etc. We show that with suitable driving frequency and amplitude, the system remains in a type of mixed phase, without ever completing transition to the stable phase, even when the oscillating parameter of the free energy remains below the corresponding critical value (for example, with oscillating temperature, T always remains below the critical temperature T_c). This phenomenon may have important implications. In cosmology, it will imply prolonged mixed phase in a first order transition due to coupling with background oscillating fields. In condensed matter systems, it will imply that using oscillating temperature (or, more appropriately, pressure waves) one may be able to sustain liquids in a mixed phase indefinitely at low temperatures, without making transition to the frozen phase.

Results of molecular motion studies carried out in two liquid crystal forming compounds n-p-cyano-p-hexyloxybiphenyl (M18) and n-p-ethoxybenzylidene-p-butylaniline (EBBA) using positron lifetime spectroscopy (PLS) are presented. Temperature dependent positron lifetime measurements have been performed in each compound during the heating cycle of samples prepared by either quenching or slow cooling from the respective liquid crystalline phase of the compounds. In both the compounds, behaviors of the quenched and slow cooled samples are found to be different. The material in the quenched sample, unlike the slow-cooled sample, exhibits strong temperature dependence before it undergoes a glass transition. In each case, the temperature dependence of o-Ps pick-off lifetime in the quenched sample shows broad peaks at various characteristic temperatures. These peaks have been attributed to various intra- and inter-molecular motions associated with these compounds. The characteristic frequencies of some of the modes observed in the present work agree well with the literature reported values obtained from FIR and Raman studies. The present study demonstrates the usefulness of PLS in the study of molecular motions.

Droplet oscillation method is a noncontact experimental approach, which can be used to measure the surface tension of acoustically levitated droplet. In this paper, we obtained huge amounts of experimental data of deionized water and water-based graphene oxide nanofluids within the temperature range of $-$8.2–$11.2^{\circ }$C. Based on the experimental data, we analyzed the influence of droplet’s deformation and frequency shift phenomenon on the surface tension of levitated droplet. Eight parameters that strongly correlate with surface tension were found and used as input neurons of artificial neural network model to predict the surface tension of supercooling graphene oxide nanofluids. The experimental data of nonsupercooling graphene oxide nanofluids were used as training set to optimize artificial neural network model, and that of deionized water were served as validation set, which was used to verify the predictive ability of artificial neural network model. The root mean square error of the optimized artificial neural network model to validation set is only 0.2558mN/m, and the prediction values of the surface tension of supercooling deionized water were in good agreement with the theoretical values calculated by Vargaftik equation, which indicates that artificial neural network model can deal well with the complex nonlinear relationship. Afterwards, we successfully predicted the surface tension of supercooling nanofluids by means of the optimized artificial neural network model and obviously reduced the dispersion and deviation caused by droplet deformation and other problems during oscillation process.

Ice storage is one technique for effective use of thermal energy. Application of bionucleant (a protein from the bacterium Pseudomonas syringae) as a snow inducer in ski field has shown great potential to enhance the quantity of snow and increase freezing temperature. In this study, differential scanning calorimeter (DSC) and lab-built ice formation reactor were employed to study experimentally the heterogeneous ice nucleation under super-cooled conditions at different dissolved bionucleant concentrations. It was found the degree of supercooling is reduced by addition of bionucleant. However, ice nucleation-activity of bionucleant will drop down when bionucleant solution is saturated/supersaturated. In our DSC measured heat release study, when bionucleant acts as ice nucleation agent in aqueous solution, prior to reaching its saturation/supersaturation, there is an increase in latent heat release during freezing/melting as the amount of dissolved bionucleant increases. In another test, the supercooling does not occur in 0.5% bionucleant solution, it began to freeze around 0°C. Our results suggest that, the addition of bionucleant may help induce ice nucleation and increase freezing temperature thereby reduces the energy consumption of ice formation for cold storage.