Jung, Seunghwan (2012-05). Numerical and Experimental Investigation of Inorganic Nanomaterials for Thermal Energy Storage (TES) and Concentrated Solar Power (CSP) Applications. Doctoral Dissertation. Thesis uri icon

abstract

  • The objective of this study is to synthesize nanomaterials by mixing molten salt (alkali nitrate salt eutectics) with inorganic nanoparticles. The thermo-physical properties of the synthesized nanomaterials were characterized experimentally. Experimental results allude to the existence of a distinct compressed phase even for the solid phase (i.e., in the nanocomposite samples). For example, the specific heat capacity of the nanocomposites was observed to be enhanced after melting and re-solidification - immediately after their synthesis; than those of the nanocomposites that were not subjected to melting and re-solidification. This shows that melting and re-solidification induced molecular reordering (i.e., formation of a compressed phase on the nanoparticle surface) even in the solid phase - leading to enhancement in the specific heat capacity. Numerical models (using analytical and computational approaches) were developed to simulate the fundamental transport mechanisms and the energy storage mechanisms responsible for the observed enhancements in the thermo-physical properties. In this study, a simple analytical model was proposed for predicting the specific heat capacity of nanoparticle suspensions in a solvent. The model explores the effect of the compressed phase - that is induced from the solvent molecules - at the interface with individual nanoparticles in the mixture. The results from the numerical simulations indicate that depending on the properties and morphology of the compressed phase - it can cause significant enhancement in the specific heat capacity of nanofluids and nanocomposites. The interfacial thermal resistance (also known as Kapitza resistance, or "Rk") between a nanoparticle and the surrounding solvent molecules (for these molten salt based nanomaterials) is estimated using Molecular Dynamics (MD) simulations. This exercise is relevant for the design optimization of nanomaterials (nanoparticle size, shape, material, concentration, etc.). The design trade-off is between maximizing the thermal conductivity of the nanomaterial (which typically occurs for nanoparticle size varying between ~ 20-30nm) and maximizing the specific heat capacity (which typically occurs for nanoparticle size less than 5nm), while simultaneously minimizing the viscosity of the nanofluid. The specific heat capacity of nitrate salt-based nanomaterials was measured both for the nanocomposites (solid phase) and nanofluids (liquid phase). The neat salt sample was composed of a mixture of KNO3: NaNO3 (60:40 molar ratio). The enhancement of specific heat capacity of the nanomaterials obtained from the salt samples was found to be very sensitive to minor variations in the synthesis protocol. The measurements for the variation of the specific heat capacity with the mass concentration of nanoparticles were compared to the predictions from the analytical model. Materials characterization was performed using electron microscopy techniques (SEM and TEM). The rheological behavior of nanofluids can be non-Newtonian (e.g., shear thinning) even at very low mass concentrations of nanoparticles, while (in contrast) the pure undoped (neat) molten salt may be a Newtonian fluid. Such viscosity enhancements and change in rheological properties of nanofluids can be detrimental to the operational efficiencies for thermal management as well as energy storage applications (which can effectively lead to higher costs for energy conversion). Hence, the rheological behavior of the nanofluid samples was measured experimentally and compared to that of the neat solvent (pure molten salt eutectic). The viscosity measurements were performed for the nitrate based molten salt samples as a function of temperature, shear rate and the mass concentration of the nanoparticles. The experimental measurements for the rheological behavior were compared with analytical models proposed in the literature. The results from the analytical and computational investigation

publication date

  • May 2012