A high functionalization density and inter-planar bundling interaction remarkably improve both the storage capacity and lifetime of solar thermal fuels using an azobenzene/graphene nano-template.
An important method for establishing a high-energy, stable and recycled molecular solar heat system is by designing and preparing novel photo-isomerizable molecules with a high enthalpy and a long thermal life by controlling molecular interactions. A meta- and ortho-bis-substituted azobenzene chromophore (AZO) is covalently grafted onto reduced graphene oxide (RGO) for solar thermal storage materials. High grafting degree and close-packed molecules enable intermolecular hydrogen bonds (H-bonds) for both trans-(E) and cis-(Z) isomers of AZO on the surface of nanosheets, resulting in a dramatic increase in enthalpy and lifetime. The metastable Z-form of AZO on RGO is thermally stabilized with a half-life of 52 days by steric hindrance and intermolecular H-bonds calculated using density functional theory (DFT). The AZO-RGO fuel shows a high storage capacity of 138 Wh kg(-1) by optimizing intermolecular H-bonds with a good cycling stability for 50 cycles induced by visible light at 520 nm. Our work opens up a new method for making advanced molecular solar thermal storage materials by tuning molecular interactions on a nano-template.
With increasingly stringent environmental regulations on emission standards, enterprises and investigators are looking for effective ways to decrease GHG emission from products. As an important method for reducing GHG emission of products, low-carbon product family design has attracted more and more attention. Existing research, related to low-carbon product family design, did not take into account remanufactured products. Nowadays, it is popular to launch remanufactured products for environmental benefit and meeting customer needs. On the one hand, the design of remanufactured products is influenced by product family design. On the other hand, the launch of remanufactured products may cannibalize the sale of new products. Thus, the design of remanufactured products should be considered together with the product family design for obtaining the maximum profit and reducing the GHG emission as soon as possible. The purpose of this paper is to present an optimization model to concurrently determine product family design, remanufactured products planning and remanufacturing parameters selection with consideration of the customer preference, the total profit of a company and the total GHG emission from production. A genetic algorithm is applied to solve the optimization problem. The proposed method can help decision-makers to simultaneously determine the design of a product family and remanufactured products with a better trade-off between profit and environmental impact. Finally, a case study is performed to demonstrate the effectiveness of the presented approach.
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