Study On Preparation And Thermal Properties Of Phase Change Composites Containing Inorganic Nanoparticles

Phase change materials (PCMs) include organic PCM and inorganic PCM. Due to the high storage density and small temperature variation from storage to retrieval, organic materials have been applied as PCMs for thermal energy storage in solar heating and cooling applications. In spite of their desirable properties of the organic, low thermal conductivity is its major drawback decreasing the rates of heat storage and retrieval during melting and crystallization processes which in turn limits their utility areas. In these years, studies have been carried out with the purpose of developing LHTES systems with enhanced thermal performance, like dispersing high conductivity particles and inserting a metal matrix into organic matrix. In this study, Heat storage nanocomposites consisting of organic matrix and nanoparticles have been prepared and how size, shape and the like of additions affect on their thermal properties have been investigated.Firstly, one dimension carbon nanotubes (CNTs) were dispersed into organic base to prepare phase change composites. Due to their high thermal conductivities and low weight carbon nanotubes (CNTs) are superior candidates for applications as fillers in composite materials to enhance thermal transport. However, interfacial thermal resistance between the CNTs and the matrix is considered to account dominantly for the discrepancy of high theoretical thermal conductivity and low measured data. Before adding into PA, four different methods, acid oxidation, mechanochemical reaction, ball milling, and grafting following acid oxidation, were used to treat CNTs. During treatment, hydroxyl groups, carboxylic groups, and amidocyanogen were introduced onto the surfaces of the CNTs. Both chemical treatment and ball milling help to break the CNT aggregates and to enhance their dispersibility. Ball milling shortened the CNTs considerably. SEM observation found that there existed extra attachments on the surfaces of G-MWCNTs. Shiver can be seen in between A-CNTs, which treated at120℃. M-CNTs were shown straighter than others. Measurements show that the thermal conductivity increase of the composites is highly depended on the CNT pretreatment process. We propose that the difference in the interfacial thermal resistance between the CNTs and the matrix is due to the difference of the CNT surface state caused by different treatment processes. At a specified temperature under solid state, the thermal conductivity enhancement is in the order of M-MWCNT/PA>A-MWCNT/PA>B-MWCNT/PA>P-MWCNT/PA> G-MWCNT/PA. Whereas the order changes into M-MWCNT/PA> A-MWCNT/PA> G-MWCNT/PA>B-MWCNT/PA>P-MWCNT/PA at a specified temperature under liquid state, that is, the thermal conductivity enhancement ratios of G-MWCNT/PA surpass the corresponding values of B-MWCNT/PA and P-MWCNT/PA. In all the CNT/PA composites, the one containing CNTs with hydroxyl groups, treated by a mechanochemical reaction, has the highest thermal conductivity increase, which, at room temperature, is0.339W/(m·K), which up to51.6%for a CNT addition of1.0wt%.Secondly, oxide nanoparticles including ZnO, γ-Al2O3and γ-Fe2O3were added into organic matrix to prepare nanocomposite. Intensive sonication was used to make well dispersed and homogeneous composites. Differential scanning calorimetric (DSC) analysis and transient short-hot-wire (SHW) method were employed to measure the thermal properties of the composites. The composites γ-Al2O3/PW increase the latent heat thermal energy storage capacity, Ls, and melting point, Tm, in low nanoparticle loadings, while they decrease the Ls and Tm with high nanoparticle loading of5.0wt%compared with those of organic matrices. γ-Al2O3/PW and γ-Fe2O3/PW decrease Ls with the nanoparticle loadings. With nanoparticle loading of5.0wt%, Ls of γ-Al2O3/PW/PW and γ-Fe2O3/PW are135.1and133.4kJ/kg。 ZnO/PW increase Ls with low nanoparticle loadings, while Ls of5.0wt%ZnO/PW is137kJ/kg, which is lower than142.2kJ/kg of PW,. For the composite with metal oxide nanoparticles, γ-Al2O3/PW has the highest thermal conductivity in solid state, while γ-Fe2O3/PW has the highest thermal conductivity in liquid state. At15℃, thermal conductivities of γ-Al2O3/PW、γ-Fe2O3/PW and ZnO/PW with nanoparticle loading of1.0wt%are0.23,0.25and0.26W/(m·K), respectively.Thirdly, the thermal properties of composite with sheet like particles were investigated. graphene nanoplatelets (GNPs) were prepared by typical acid oxidation and ultrasound stirring. The morphology and microstructure of the composites were examined by scanning electron microscope (SEM) and optical microscope images. The GNPs were not thicker than20nm and about2um in diameter. GNP/PA composites were prepared by adding GNPs into the melting PA with intensive ultrasonic. The GNP/PA composites were more steadier compared with the flake graphite (FG)/PA and expanded graphite (EG)/PA. The GNP/PA composite enhanced the thermal conductivity in both liquid state and solid state. The thermal conductivity of the composite GNP/PA is much higher than the result of the theoretical model. When the GNPs loading is no more than1.0wt%, thermal conductivity of the composites increase slightly, while it quiken from1.0wt%to5.0wt%, and acutely more than5.0wt%. Thermal conductivity of composite with10.0wt%GNPs is more than1.0W/(m·K).Lastly, CNTs and their composites were simulated by first principle and molecular dynamics for the structure, front orbits, band structure, phonon spectra and thermal properties. How size, length and temperature effect on the thermal properties of CNT were analyzed. The results showed that the electrons in the n bond should contribute much in thermal conductivity. The molecular dynamics was used to simulate the thermal properties of the CNT composites. At298K, thermal conductivity of CNT increases with the length, and it quikens when lenger than20nm. The results showed that the function on the end of CNT affect the thermal conductivity in the random model. The thermal conductivity of the composite by end model accords the results of our experiments.