Energy | Al₂O₃纳米颗粒对二元碱金属氯化盐热物性的强化机理

文摘   科学   2024-06-03 15:33   北京  

原文信息Zizhou Huang, Qing Li, Yu Qiu. Enhancements in thermal properties of binary alkali chloride salt by Al2O3 nanoparticles for thermal energy storage[J]. Energy, 2024, 301: 131584. https://doi.org/10.1016/j.energy.2024.131584

注:发布者水平有限,疏漏在所难免,所有内容请以英文摘要和论文原文为准。

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HIGHLIGHTS
  • Nanofluids based on a molten chloride salt and Al2O3 nanoparticles were proposed

  • Thermal properties of nanofluids were predicted by molecular dynamics simulations
  • Al2O3 nanoparticles can enhance the thermophysical properties significantly
  • A compressed layer with high ionic short-range order surrounds the nanoparticle
  • The compressed layer can serve as a thermal conduit to improve heat transfer

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文章概述

在工业革命以来,人类对化石能源的使用量持续增加,同时也向环境排放了大量CO₂和污染物,对环境造成了明显的破坏和污染。为了解决上述问题,亟需开发太阳能、地热能、风能和海洋能等可再生能源在上述可再生能源中,太阳能具有储量丰富、分布广泛、清洁无污染的特性,具有极大的开发潜力。太阳能光热发电通过聚集太阳辐射来产生热能用于发电,并利用储热系统实现可调度的发电,是一种有前途的技术。硝酸盐由于具有较高的比热容、低廉的成本和较低的蒸汽压,广泛应用于太阳能光热电站的储热系统。然而,下一代太阳能光热电站需要在高于973 K的温度下运行,而在这种温度下硝酸盐会发生分解。相比之下,熔融氯化盐不仅具备与硝酸盐相当的储热性能,还具有更好的高温稳定性和低廉的成本。特别是最近,在研究熔融氯化盐对合金的腐蚀机理方面取得了显著进展。同时,开发耐氯化盐腐蚀的合金和改进氯化盐纯化技术也有了突破。这些进展使得在高温下使用熔融氯化盐作为传热流体变得更加可行。

然而熔盐作为传热流体存在一些缺点,例如导热系数低、比热容小和动力粘度高,导致太阳能集热器与储热系统的效率降低。与此同时,熔盐的低导热系数会导致换热设备存在较大的传热温差,增加了设备的热应力,降低了设备的安全性。因此,设备安全性和系统效率的提高都依赖于熔盐热物性的增强。目前,不少实验和模拟研究都致力于通过添加纳米颗粒强化熔盐的热物性。然而,一方面,熔盐离子的运动难以通过实验观察和分析,导致难以通过实验阐明纳米颗粒增强储热性能的机理;另一方面,在分子动力学模拟研究方面,尚缺乏同时从微观结构演化和能量分布两个方面对强化机理进行揭示。

鉴于此,本文提出了一种由二元氯化盐(50 mol.% KCl, 50 mol.% NaCl)和Al₂O₃纳米颗粒组成的熔盐基纳米流体,并通过分子动力学研究其热物性随纳米颗粒的体积分数的变化。在此基础上,从离子的微观结构演变、自扩散系数和纳米颗粒附近能量空间分布三个角度,探讨了Al₂O₃纳米颗粒对导热系数的强化机理。


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文章概述

针对熔融氯化盐比热容较小、导热系数较低的关键问题,本文提出了一种基于二元氯化盐(50 mol.% NaCl, 50 mol.% KCl)与Al₂O₃纳米颗粒的熔盐基纳米流体,并采用分子动力学模拟方法,揭示了纳米颗粒对熔盐热物性的强化机理。

首先,基于分子动力学模拟,研究了该纳米流体在1100~1600 K范围内的热物性随Al₂O₃纳米颗粒体积分数的变化。研究结果表明,当纳米颗粒的体积分数从0%增加到7%时,比热容动力粘度分别提高了约14.9%34.8%~38.6%,同时导热系数提高了10.0%~16.5%

然后,研究了纳米颗粒附近离子的密度分布。结果表明,负电性的纳米颗粒表面选择性地吸引Na+K+,导致在Al₂O₃纳米颗粒周围形成一个离子压缩层接着,分析了压缩层内外的离子径向分布函数的变化,发现了压缩层以内的离子短程有序性被增强,而压缩层以外并没受到影响因此,得出结论,离子压缩层作为Al₂O₃纳米颗粒与压缩层以外的熔盐离子之间的传热通道,显著增强了熔盐基纳米流体的导热系数。

最后,分析了离子的自扩散系数的变化,发现了纳米颗粒的添加抑制了离子的扩散能力。同时,研究了近纳米颗粒能量密度分布,发现近纳米颗粒的离子陷入低势能区域进一步表明离子运动受限这些结果间接证实了离子压缩层的存在,并进一步支撑了导热系数增强的机理。


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英文摘要

The cost-effective molten chloride salts are promising heat transfer fluids for next-generation concentrating solar plants. However, their limited specific heat capacities and thermal conductivities hinder their applications. In this paper, molten salt-based nanofluids based on a binary chloride (50 mol.% NaCl, 50 mol.% KCl) with Al2O3 nanoparticles were proposed to enhance the thermal properties. Firstly, molecular dynamics simulations were employed to investigate the thermal properties of these nanofluids, focusing on various nanoparticle volume fractions within 1100~1600 K. The findings reveal that as the nanoparticle fraction increases from 0% to 7%, the specific heat capacity and dynamic viscosity improve by ≈14.9% and 34.8%~38.6%, respectively. Concurrently, the thermal conductivity increases by 10.0%~16.5%. Then, microstructure evolution was analyzed to elucidate the enhancing mechanism of the thermal conductivity. Specifically, the negatively charged nanoparticle surface selectively attracts Na+ and K+, resulting in the formation of a compressed layer around the nanoparticle where the short-range order of ions was intensified. As a result, the compressed layer serves as a thermal conduit between the Al2O3 nanoparticle and the surrounding salt, resulting in the enhancement of the thermal conductivity. Furthermore, additional analyses of thermal diffusion properties and energy density distributions provide indirect evidence for the existence of the compressed layer where ionic motion is restricted, further validating the enhancing mechanism.


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主要图文结果


Fig.Physical model of the MSBNF.

Fig.2 Simulation methodology in this work.

Fig.3 The schematic diagram of the RNEMD method for simulating η.

Fig.4 Comparisons between present dynamic viscosities and those of Xian et al. [44].

Fig. 5  Effects of the volume fraction of the nanoparticles (f) on the dynamic viscosity.
Fig.6 Energy change and thermal storage with the temperature escalating.

Fig.7 The schematic diagram of the RNEMD method for simulating λ.

Fig.8 Comparisons between present thermal conductivity (λ) data and those of Ding et al. [43].

Fig. 9 Effects of the volume fraction of the nanoparticles (f) on the thermal conductivity (λ).

Fig. 10 Sketch of the spherical shell zones in the MSBNF.

Fig.10 Variations of ion densities with the distance d from the nanoparticle surface.

Fig. 11 Distributions of ion density ratios surrounding the nanoparticle.

Fig. 12 The g(r) of ions outside the nanoparticle when f=0% and f=7%.

Fig. 13 The g(r) of ions outside the compressed layer when f=0% and f=7%.

Fig. 14 Ionic diffusion abilities: (a)~(e) MSD of ions when f=0%~7%; (f) D of ions when f=0%~7%.

Fig. 15 Energy density distributions surrounding the nanoparticle.


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