| Heat exchanger is an important equipment for efficient use of heat in the industry,but the corrosion of the heat-transfer walls will cause equipment failure.This problem has always been a challenge in corrosion and protection field because the coatings need to have both thermal conductivity and corrosion resistance in order to meet the requirements of heat exchanger.However,the emergence of two-dimensional graphite materials provides an opportunity for the preparation of thermally conductive anti-corrosion coatings.Graphene and graphite nanoplatelets are both two-dimensional nanomaterials composed of sp~2 hybrid carbon atoms with ion impermeability and high thermal conductivity.But some factors such as production cost,preparation process and dispersion limit their application.This paper has developed high-efficiency preparation technology of graphene and graphite nanoplatelets,and their influence of the coatings on the thermal conductivity and corrosion resistance was studied.At the same time,the effect of size synergistic effects of graphite nanoplatelets on the coating properties was studied,and the neural network was introduced to predict and optimize the thermal conductivity of graphite nanoplatelets coatings.The main contents of this paper include the following aspects:(1)Preparation of graphene-based materials/Epoxy composites and their thermal and anticorrosive properties.Firstly,the rapid and simple preparation of reduced graphene oxide was developed,which combined with Fe reduction method and microwave reduction method.Meanwhile,the dopamine-modified graphene was prepared by non-covalent bond.The results show that graphene has a high carbon-oxygen ratio and the dispersibility has been improved after surface modification.And then,when 5 wt%dopamine-modified graphene is added to epoxy resin,the thermal conductivity of coating reaches 0.72 W/m·K,which is 400%higher than that of epoxy coating.Electrochemical tests show that the corrosion resistance of coatings increases first and then decreases with the increase of the amount of fillers.When doping with3 wt%dopamine-modified graphene,the coating still maintains the high coating resistance(10~9?·cm~2)after soaking for 11 days,and the thermal conductivity is 0.52 W/m·K.This coating has excellent thermal conductivity and corrosion resistance.(2)Preparation of graphite nanoplatelets-based materials/Epoxy composites and their thermal and anticorrosive properties.Firstly,a high-efficiency and low-cost method was developed to prepare graphite nanoplatelets with controlled size.Graphite nanoplatelets with an average size around 20?m(LGNPs)is obtained by a facile nitric acid treatment and 1-5?m graphite nanoplatelets(SGNPs-0.5~6h)are produced by controlling ultrasonic time in cheap commercial detergent.In addition,thermal network was fabricated by combining LGNPs with SGNPs-0.5~6h in epoxy.Thermal conductivity test results show that the size of SGNPs,the ratio of LGNPs to SGNPs and the content of fillers will affect the thermal conductivity of coatings through size synergistic effects.When the hybrid filler loading is 20 wt%,LGNPs:SGNPs-3h=17:3,the thermal conductivity of the coating reaches 1.33 W/m·K.Further,electrochemical tests show the anti-corrosion effect decreases with the increase of filler content when the amount of fillers exceeds 3 wt%.Among them,Epoxy/LGNPs-4.25 wt%/SGNPs-3h-0.75 wt%coating still maintains the high coating resistance(10~8?·cm~2)after soaking for 11days,and the thermal conductivity is 0.50 W/m·K.(3)Thermal conductivity optimization of multi-size graphite nanoplatelets/Epoxy composites.The BP neural network was introduced to predict the thermal conductivity of composites and an optimization scheme was given.This paper improved the prediction accuracy by controlling the number of hidden layers and the number of neurons.The average error rate of the optimized neural network is 4.5%.According to the predicted results,the prepared Epoxy/LGNPs-16 wt%/SGNPs-2h-4 wt%coating thermal conductivity reaches 1.42W/m·K. |
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