This work demonstrates a green method for the encapsulation of a natural phase change material (PCM), lauric acid (LA), in polystyrene (PS) hollow fibers through a solvent-assisted diffusion process inside fiber nanochannels. The obtained LAPS composite fibers had a melting enthalpy of up to 147.8 J/g, which was 82.0% the heat storage capacity of pristine LA (180.2 J/g). This capacity was higher than the values (generally less than 60%) reported in the literature. The LA content in the composite fibers could be controlled by the solution concentration and the solvent. On the contrary, encapsulation time had little effect on the final LA loading beyond 1 h due to the rapid diffusion of the LA solution. The optimal LA loading (82.2%) was achieved in 0.4 g/mL LA ethanol solution for 1 h, which was more than 4 times the weight of PS fibers. Simultaneous TGA–DSC, ATR, Raman, and SEM measurements confirmed the homogeneous distribution of LA inside the fibers across the whole membranes. Further, the LAPS composite fibers showed a long-lasting stability during cycling without storage capacity deterioration, as well as an exceptional structural stability without LA leaking and fiber rupture during 100 heating–cooling cycles. The energy-dense and form-stable LAPS composite fibers have a great potential for various thermal energy storage applications like “temperature-smart” buildings and textiles.

中文翻译：

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聚苯乙烯空心纤维中自然相变材料的溶剂辅助纳米通道封装，用于高性能热能存储

这项工作展示了一种绿色方法，可通过溶剂辅助扩散过程在纤维纳米通道内部将天然相变材料（PCM），月桂酸（LA）封装在聚苯乙烯（PS）中空纤维中。所获得的LAPS复合纤维的熔融焓高达147.8J / g，是原始LA的储热容量（180.2J / g）的82.0％。该容量高于文献中报道的值（通常小于60％）。复合纤维中的LA含量可以通过溶液浓度和溶剂来控制。相反，由于LA溶液的快速扩散，包封时间对超过1 h的最终LA负载影响很小。在0.4 g / mL的LA乙醇溶液中1 h达到了最佳的LA负载量（82.2％），是PS纤维重量的4倍以上。同时进行的TGA-DSC，ATR，拉曼和SEM测量证实了LA在整个膜内纤维内的均匀分布。此外，LAPS复合纤维在循环过程中显示出持久的稳定性，而不会降低储存容量，并且在100次加热-冷却循环中也具有出色的结构稳定性，而不会出现LA泄漏和纤维断裂的情况。能量密集且形状稳定的LAPS复合纤维在诸如“温度智能”建筑和纺织品等各种热能存储应用中具有巨大潜力。以及出色的结构稳定性，在100个加热-冷却循环中不会出现LA泄漏和纤维断裂。能量密集且形状稳定的LAPS复合纤维在诸如“温度智能”建筑和纺织品等各种热能存储应用中具有巨大潜力。以及出色的结构稳定性，在100个加热-冷却循环中不会出现LA泄漏和纤维断裂。能量密集且形状稳定的LAPS复合纤维在诸如“温度智能”建筑和纺织品等各种热能存储应用中具有巨大潜力。