Ralph E. Martin Department of Chemical Engineering, University of Arkansas, Fayetteville, AR 72701, USA.
Nanoscale. 2018 Jun 21;10(24):11531-11543. doi: 10.1039/c8nr00977e.
Embedding soft matter with nanoparticles (NPs) can provide electromagnetic tunability at sub-micron scales for a growing number of applications in healthcare, sustainable energy, and chemical processing. However, the use of NP-embedded soft material in temperature-sensitive applications has been constrained by difficulties in validating the prediction of rates for energy dissipation from thermally insulating to conducting behavior. This work improved the embedment of monodisperse NPs to stably decrease the inter-NP spacings in polydimethylsiloxane (PDMS) to nano-scale distances. Lumped-parameter and finite element analyses were refined to apportion the effects of the structure and composition of the NP-embedded soft polymer on the rates for conductive, convective, and radiative heat dissipation. These advances allowed for the rational selection of PDMS size and NP composition to optimize measured rates of internal (conductive) and external (convective and radiative) heat dissipation. Stably reducing the distance between monodisperse NPs to nano-scale intervals increased the overall heat dissipation rate by up to 29%. Refined fabrication of NP-embedded polymer enabled the tunability of the dynamic thermal response (the ratio of internal to external dissipation rate) by a factor of 3.1 to achieve a value of 0.091, the largest reported to date. Heat dissipation rates simulated a priori were consistent with 130 μm resolution thermal images across 2- to 15-fold changes in the geometry and composition of NP-PDMS. The Nusselt number was observed to increase with the fourth root of the Rayleigh number across thermally insulative and conductive regimes, further validating the approach. These developments support the model-informed design of soft media embedded with nano-scale-spaced NPs to optimize the heat dissipation rates for evolving temperature-sensitive diagnostic and therapeutic modalities, as well as emerging uses in flexible bioelectronics, cell and tissue culture, and solar-thermal heating.
将软物质嵌入纳米颗粒 (NPs) 可以在亚微米尺度上提供电磁可调性，这在医疗保健、可持续能源和化学加工等越来越多的应用中得到了广泛应用。然而，由于难以验证从绝热到导电行为的能量耗散速率的预测，NP 嵌入软材料在温度敏感应用中的使用受到了限制。本工作通过改进单分散 NPs 的嵌入，稳定地减小聚二甲基硅氧烷 (PDMS) 中 NP 之间的间距至纳米级距离，从而提高了 NP 嵌入软聚合物的嵌入稳定性。集中参数和有限元分析得到了改进，以分配 NP 嵌入软聚合物的结构和组成对导电、对流传热和辐射散热速率的影响。这些进展允许合理选择 PDMS 尺寸和 NP 组成，以优化测量的内部（导电）和外部（对流传热和辐射）散热速率。将单分散 NP 之间的距离稳定地减小到纳米级间隔，可将整体散热速率提高高达 29%。对 NP 嵌入聚合物的精细制造能够使动态热响应（内部与外部散热速率之比）的可调性提高 3.1 倍，达到 0.091 的最大值，这是迄今为止报道的最大值。通过在 NP-PDMS 的几何形状和组成变化 2 到 15 倍的情况下进行 130μm 分辨率的热成像，模拟了散热速率，结果一致。在热绝缘和导电区域，努塞尔数随瑞利数的四次根增加，进一步验证了该方法。这些发展支持了对嵌入纳米级间距 NPs 的软介质进行模型指导设计，以优化用于不断发展的温度敏感诊断和治疗模式的散热速率，以及在柔性生物电子学、细胞和组织培养以及太阳能加热等新兴应用中的使用。
