Research progress on thermal conductivity of polyvinylidene fluoride composites
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摘要: 导热复合材料在电子封装、电机材料、电池及换热设备等领域具有广泛的应用价值。聚偏氟乙烯 (PVDF) 具有优异的电气性能、良好的机械强度和耐高温性能，是应用于电子电器、航空航天等行业的理想材料之一，但较低的热导率制约其进一步发展，亟待开发PVDF基高导热复合材料。其制备的关键在于如何选择高导热填料、设计导热通路及调控界面热阻。本文在聚合物基导热复合材料的机制、模型、方程及数值模拟等理论知识的基础上，结合PVDF自身晶体结构，介绍目前PVDF基导热复合材料热导率的发展水平，各种填料及制备工艺对其热导率的不同影响程度等内容，从复合策略、网络结构、界面结合等角度综述了高导热PVDF复合材料的最新研究进展。此外，对其未来发展也进行了展望。Abstract: Thermal conductive composites have a wide range of applications in the fields of electronic packaging, motor materials, batteries and heat exchange equipment. Polyvinylidene fluoride (PVDF) has excellent electrical properties, good mechanical strength and high temperature resistance. It is one of the ideal materials for applications in electronics, aerospace and other industries. However, the low thermal conductivity restricts its further development. It is urgent to develop PVDF-based high thermal conductivity composites. The key to its preparation is how to select high thermal conductivity fillers, design thermal conduction pathways, and regulate interface thermal resistance. Based on the theoretical knowledge of the mechanism, model, equation and numerical simulation of polymer-based thermal conductive composites, combined with the crystal structure of PVDF, this paper introduces the current development level of thermal conductivity of PVDF-based thermal conductive composites, and the different effects of various fillers and preparation processes on their thermal conductivity. The latest research progress of high thermal conductivity PVDF composites is reviewed from the perspectives of composite strategy, network structure and interface bonding. In addition, its future development is also prospected.
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城市化及工业化的快速发展极大地促进了水泥制品的产出，随即引发的一系列环境问题，如巨大能源资源消耗、二氧化碳及其他温室气体排放等引起了全世界的强烈担忧[1]。为此，国内外学者做出了巨大的努力来降低其环境负面效应并寻求可替代方案。凭借绿色可持续性[2-3]，碱激发材料(Alkali-activated material，AAM)近年来获得了广泛关注[4-6]。然而，类似于普通混凝土，AAM脆性大及抗拉强度低等缺点从一定程度上限制了该材料的推广应用。
借鉴高延性水泥基复合材料的设计理念，在AAM体系中引入适量纤维，研制出了高延性碱激发纤维增强复合材料(Alkali-activated fiber reinforced composites，AAFRC)；相似地，伴随有多条细密裂缝开裂的应变硬化行为也是AAFRC的显著特征[7-9]。
赤泥(RM，也称铝土矿渣)是精制铝/氧化铝过程中产出的固体废物[10]，每生产1吨氧化铝就会产出1.0~1.5吨的RM[11]。大量RM被随机存储在蓄水库或干堆在田地中，并没有得到有效的再利用[12]，如何开发RM的潜在资源化利用已经成为一个亟需解决的问题。
尽管人们从不同角度对赤泥进行了大量的再利用尝试，包括作为吸收剂、中和剂、混凝剂和催化剂及从中回收铁、铝等有价金属和一些稀土元素[10,13]，且取得了一些进展，但由于一些技术或经济限制[14]，仅在这些领域回收利用如此大量的RM仍是不切实际的。考虑到RM潜在的火山灰效应[15]，土木工程领域的应用有望使其成为可能。近年来相关报道表明，RM已成功被用于制造水泥、砖和混凝土等建筑材料[16]；且也开展了以RM为原料生产AAM的研究。例如，He等[17]提出了一种基于混合RM和稻壳灰的新型AAM；Ye等[18]利用碱热RM合成了单组分AAM；Hu等[19]在低浓度NaOH激发下制备了一种RM-粉煤灰AAM。值得注意的是，现有RM-AAM的强度在大多数情况下无法与普通混凝土相比，即
⩽ 20 MPa [17-19]；而且类似于传统AAM的脆性缺点依然存在，这些弊端阻碍了该材料的实际工程应用。基于此，本文采用RM混合矿渣和硅灰并掺加聚乙烯(PE)纤维制备中高强、高延性的碱激发复合材料，通过单轴拉、压试验探究其宏观力学性能，结合三点抗弯与单裂缝拉伸等细观试验探究其高延性机制，并基于XRD及FTIR技术分析其水化产物，以期为RM的高附加值资源化利用提供新思路。
1. 试验材料及方法
1.1 原材料
赤泥(RM，山东魏桥创业集团有限公司)、矿渣(GGBS，河北天岩矿业公司)、硅灰(SF，山东温特实业有限公司)、普通河砂、自来水、碱激发剂及PE纤维(浙江全米特新材料科技有限公司)。其中，RM、GGBS及SF的主要化学组成见表1，其粒径分布见图1；碱激发剂由模数为3.3的水玻璃(山东优索化工有限公司)及99%的NaOH颗粒(国药集团化学药剂有限公司)配制而成；PE纤维性能参数如下：直径24 μm，长度12 mm，密度980 kg/m3，弹性模量110 GPa，抗拉强度3000 MPa，伸长率2%~3%。
表 1 赤泥(RM)、矿渣(GGBS)及硅灰(SF)的化学组成Table 1. Chemical compositions of red mud (RM), ground granulated blast furnace slag (GGBS) and silica fume (SF)wt% Material CaO SiO2 Al2O3 Fe2O3 MgO SO3 TiO2 Na2O K2O P2O5 RM 0.46 10.18 17.43 53.79 0.12 0.76 – 7.74 0.07 0.20 GGBS 44.39 33.20 13.20 0.38 6.31 – 0.82 0.33 0.28 – SF 0.49 92.26 0.89 1.97 0.96 – – 0.42 1.31 – 1.2 配合比及试件制备
基于前期预试验(0wt%~60wt%RM取代GGBS和SF)结果，选用40wt%RM掺量开展本研究。试件的具体配合比见表2，水胶比为0.39，PE/GGBS-SF为不含RM的对照组。
表 2 高延性碱激发纤维增强复合材料(AAFRC)配合比Table 2. Mixture proportion of alkali-activated fiber reinforced composites (AAFRC)Mixture RM/wt% SF/wt% GGBS/wt% Sand/wt% NaOH/wt% Na2SiO3/wt% Water/wt% Polyethylene
(PE) fiber/vol%PE/GGBS-SF 0.00 10.33 44.77 14.50 3.00 13.70 12.60 1.90 PE/RM-GGBS-SF 22.04 6.20 26.86 14.50 3.00 13.70 12.60 1.90 试件制备过程：将RM、GGBS、SF及砂按表2中配比倒入容量为5 L的水泥胶砂搅拌机慢速搅拌2~4 min，使原料混合均匀；将水和碱激发剂(Na2SiO3和NaOH提前配制冷却至室温)倒入，快速搅拌3~5 min直至浆体具有一定流动度；加入PE纤维，快速搅拌5~8 min，使纤维均匀分散。搅拌完毕后，立即将拌合物装入模具振捣密实，放置于实验室环境(温度为20℃~22℃、相对湿度为70%±5%)中养护24 h后脱模；试块表面覆盖保鲜膜，放置于80℃的烘箱中加热2 h后继续在室温中养护至28天。
1.3 试验方法
1.3.1 单轴拉伸及抗压试验
单轴拉伸试件为“狗骨状”[20]，中间标准段长度为80 mm，具体尺寸详见图2。采用济南川佰仪器设备有限公司生产的WDW-300型电子万能试验机，加载速度为0.3 mm/min。试验时，试件两边分别固定一套位移传感器(Linear variable displacement transducers，LVDT)记录标准段长度的变化，取两个测量结果的平均值来计算拉伸应变。
参考ASTM C109[21]，选用边长为50 mm的立方体试件进行抗压试验，加载速率为1.5 mm/min。注意保证试件承压表面的平整度，以最大程度地减少测试过程中的不确定性。
1.3.2 三点抗弯及单裂缝拉伸试验
为探究基体韧度对AAFRC拉伸延性的影响，根据ASTM E399[22]进行三点抗弯试验。首先依照表2配合比制作尺寸为354 mm×75 mm×40 mm的无纤维棱柱体试件，然后采用1.2中养护方法将试件养护至28天；试验前，用切割机在试件的中部底端切出一个30 mm深的切口(图3)，试验时试件底部跨径为300 mm，加载速率为0.3 mm/min。
通过单裂缝拉伸试验[23]，获得纤维最大桥接应力σoc和纤维桥接余能Jb′。试件形状为“小狗骨”(图4)；养护至28天后，在试件中心分别沿宽度、厚度方向切割6.5 mm、2 mm深的凹槽(宽度小于0.6 mm)，以便形成单裂缝。
1.3.3 水化产物分析
采用D8 Advance Bruker型XRD测试仪(赛默飞世尔(中国)科技有限公司)与Tensor-Bruker型光谱仪(德国布鲁克AXS有限公司)分析PE/RM-GGBS-SF的水化产物。为了避免砂和纤维的影响，根据表2配制不含砂和纤维的净浆试件，养护至28天后磨成粉末用于微观分析。
2. 结果与讨论
2.1 两种AAFRC拉伸性能
两种AAFRC的典型拉伸应力-应变曲线如图5所示。初裂强度(初始裂缝的拉伸应力)、抗拉强度(极限拉伸应力)及拉伸应变(极限拉伸应力对应的应变)详见表3。
可以看出，RM的引入导致AAFRC的初裂、抗拉强度均有所下降。与参照试件(PE/GGBS-SF)相比，PE/RM-GGBS-SF的初裂强度降低了12.1%，为(1.89±0.41) MPa；抗拉强度降低了26.4%，为(2.43±0.04) MPa。在碱激发体系中，CaO与SiO2是生成胶凝产物、贡献强度的重要组分。由表1可知，RM中CaO与SiO2的含量明显低于GGBS和SF (即CaO：0.46wt% vs 44.39wt%+0.49wt%，SiO2：10.18wt% vs 33.20wt%+92.26wt%)；且RM中的SiO2主要以石英相的形式存在[16]。RM的掺入会明显减少体系内Ca、Si含量，从而减少水化凝胶产物的生成，导致强度降低。同时，由图1可知，绝大多数RM的粒径大于GGBS和SF，RM的引入可能会降低基体的密实度，从而对强度不利。另一方面，RM中包含较多的碱金属(Na2O+K2O=7.74%+0.07%)，导致复合材料体系内的碱性得以提升，有利于强度的发展[24]。当前试验结果可认为由上述机制共同作用产生，强度的降低则说明，本研究中反应组分减少及RM较大粒径带来的不利影响可能占主导地位。
表 3 AAFRC的拉伸性能Table 3. Tensile properties of AAFRCMixture Initial cracking strength/MPa Tensile strength/MPa Tensile strain/% PE/GGBS-SF 2.15±0.13 3.30±0.13 3.07±0.32 PE/RM-GGBS-SF 1.89±0.41 2.43±0.04 3.58±0.11 对比二者拉伸应变发现，RM的引入提高了AAFRC的拉伸延性；相比参照试件，PE/RM-GGBS-SF的拉伸应变增加了16.6%，高达3.5%。纤维增强脆性基体复合材料的拉伸延性受基体初裂强度的影响，通常情况下，初裂强度越低，获得较大应变的可能性越大[23]。仅从这点来看，当前的应变结果可以通过基体初裂强度的变化合理地得以解释。不过，具体的应变机制比较复杂，更多的参数(包括基体、纤维、基体-纤维界面特性等)都影响着试件的拉伸行为，进一步的讨论将在2.3节(基于细观试验[25])给出。
2.2 两种AAFRC抗压强度
表4为两种AAFRC的抗压强度，其中PE/GGBS-SF抗压强度为(69.13±2.16) MPa，PE/RM-GGBS-SF抗压强度为(48.83±1.86) MPa。掺入RM后，抗压强度降低了29.4%。抗压强度与初裂、抗拉强度的变化相似，表明上述强度变化机制可能也同样适用于抗压强度。也即，反应组分减少导致胶凝产物含量降低及较大粒径RM引入导致基体的不致密，可能也是抗压强度减少的主要原因。总体来看，尽管RM的引入使AAFRC的强度有所下降，但仍处于较高水平，近50 MPa的抗压强度可满足大部分工程的使用要求；且拉伸应变水平与高延性水泥基复合材料近乎相当[26]。因此，可以认为RM制备高延性碱激发复合材料具有一定的可行性，这为实现其大规模、高附加值的资源化利用提供了新的思路。
表 4 AAFRC抗压强度Table 4. Compressive strength of AAFRCMixture Compressive strength/MPa PE/GGBS-SF 69.13±2.16 PE/RM-GGBS-SF 48.83±1.86 2.3 AAFRC高延性机制
纤维增强脆性基体复合材料产生应变硬化行为需要满足两个核心准则[23]：(1) 强度准则：基体初始开裂强度σcr必须小于纤维最大桥接应力σoc；(2) 能量准则：基体断裂能Jtip不得超过纤维桥接余能Jb′。此外，两个应变硬化性能指数PSHS(强度指数，σoc/σcr)和PSHE(能量指数，Jb′/Jtip) 可用来评估复合材料的应变硬化潜力，饱和应变硬化行为的实现需要满足两个更严格的条件：(1) PSHS
\geqslant 1.20~1.35；(2) PSHE\geqslant 2.7~3.0[27-28]。理论上，PSH指标越大，越容易获取较高的拉伸延性[25]。基于三点抗弯试验得到的峰值荷载FQ，按照以下各式可计算出基体断裂韧度Km和基体断裂能Jtip：
{K}_{\mathrm{m}}=\frac{1.5\left({F}_{\mathrm{Q}}+\dfrac{mg}{2} \times{10}^{-3}\right)\times {10}^{-3} S {{a}_{0}}^{0.5}}{t{h}^{2}}f \left(\alpha \right) (1) f \left(\alpha \right)=\frac{1.99-\alpha \left(1-\alpha \right)\left(2.15-3.93\alpha +2.7{\alpha }^{2}\right)}{\left(1+2\alpha \right){\left(1-\alpha \right)}^{\frac{3}{2}}} (2) \alpha ={a}_{0}/h (3) {J}_{\mathrm{t}\mathrm{i}\mathrm{p}}=\frac{{{K}_{\mathrm{m}}}^{2}}{{E}_{\mathrm{m}}} (4) 式中：m为试件质量；S为试件跨度；a0为切槽深度；t和h分别为试件宽度和高度；Em为拉伸试验获得的弹性模量；f(α)为形状参数；g=9.8 N/kg。
结果详见表5。可以看出，相比于对照试件，PE/RM-GGBS-SF的Km表现出下降趋势，与基体初裂强度的变化相一致；基体断裂能Jtip也从(5.05±0.23) J·m−2减小至(4.28±0.75) J·m−2，较小的Jtip有利于获得较大的
{J}_{\mathrm{b}}{{{'}}}/{J}_{\mathrm{tip}} ，这从一定程度上反映了PE/RM-GGBS-SF获取较高拉伸应变(延性)的潜能，或者认为RM的掺入使基体趋于多缝开裂：{J}_{\mathrm{b}}{{{'}}}={\sigma }_{\mathrm{o}\mathrm{c}}{\delta }_{\mathrm{o}\mathrm{c}}-{\int }_{0}^{{\delta }_{\mathrm{o}\mathrm{c}}}\sigma \left(\delta \right)\mathrm{d}\delta (5) 式中：σoc和δoc分别为纤维最大桥接应力与对应的裂缝开口位移；σ(δ)为纤维桥接应力。
表 5 AAFRC的基体断裂韧度与基体断裂能Table 5. Matrix fracture toughness and fracture energy of AAFRCMixture Mass m/kg Peak load FQ/kN Km/(MPa·m1/2) Jtip/(J·m−2) PE/GGBS-SF 1.99±0.06 0.27±0.03 0.30±0.05 5.05±0.23 PE/RM-GGBS-SF 2.03±0.05 0.23±0.04 0.26±0.07 4.28±0.75 Notes: Km—Fracture toughness of matrix; Jtip—Fracture energy of matrix. 单裂缝拉伸试验得到应力-裂缝开口位移曲线如图6所示，由此可得到纤维最大桥接应力σoc和相应的裂缝开口位移δoc，进而根据式(5)可计算出纤维桥接余能
{J}_{\mathrm{b}}{{{'}}} 。结合已经得到的基体初裂强度σcr和基体断裂能Jtip，即可计算出PSHS及PSHE性能指数，结果如表6所示。![]()
图 6 AAFRC的单裂缝拉伸应力-开口位移曲线Figure 6. Stress-crack opening displacement curves of AAFRCfrom single crack tensile tests表 6 AAFRC单裂缝拉伸试验结果与强度指数PSHS及能量指数PSHETable 6. Results from single crack tensile test and strength index PSHS and energy index PSHE of AAFRCMixture Peak stress σoc/MPa Crack opening δoc/mm Jb′/(J·m−2) PSHS PSHE PE/GGBS-SF 3.14±0.05 0.24±0.04 50.23±37.33 1.47±0.11 10.30±7.86 PE/RM-GGBS-SF 3.03±0.09 0.20±0.07 63.58±24.83 1.72±0.39 16.37±8.67 Notes: Jb′—Complementary energy of fibers. 由表6可看出，本研究中两种AAFRC的PSH指数均大于1 (即σoc>σcr，且Jb′>Jtip)，表明产生应变硬化行为的两个核心准则均得到满足，这合理地解释了两种试件表现出明显应变硬化行为(图5)的原因。进一步注意到，两种试件的PSH指数均满足饱和应变硬化条件：PE/GGBS-SF的PSHS指数略大于1.30，PSHE指数远大于3.0；PE/RM-GGBS-SF的两个性能指数均明显大于各自建议值。基于此，两种试件获得较高拉伸应变性能(3%以上)的结果得到了较好的印证。此外，对比PE/GGBS-SF 与PE/RM-GGBS-SF拉伸应变与PSH指数之间的关系，发现随着RM引入后拉伸应变的增加，PSHS和PSHE指数均表现出增加趋势。这从一定程度上说明，使用PSH指数理解本研究中碱激发复合材料体系的拉伸延性行为是可行的。
2.4 AAFRC的水化产物
图7(a)、7(b)分别为矿粉、RM及两种AAFRC试样的XRD图谱。可以看出，矿粉的主要衍射峰为白云石相(CaMg(CO3)2)，RM则为赤铁矿(Fe2O3)和针铁矿(FeO(OH))相。随着碱激发反应的进行，两种AAFRC体系内均未出现白云石相；而PE/RM-GGBS-SF的XRD衍射峰则含有明显的赤铁矿和针铁矿相，这主要与RM的引入密切相关[22]。而且，RM及PE/RM-GGBS-SF的XRD图谱中均出现了较多的赤铁矿衍射峰，这也很好地对应了RM化学组分中较高的Fe2O3含量(表1)。值得注意，两种AAFRC试样的XRD图谱均在20°~36°之间出现了明显的隆起，这是无定形(或类凝胶状)地聚合反应产物的典型衍射模式[29]。即碱激发体系内生成了与地聚合反应产物相似的胶凝物相。不过，引入RM后，隆起部位趋于平缓，这从一定程度上说明了PE/RM-GGBS-SF体系中胶凝产物量的减少，很好地对应了宏观力学强度降低的试验结果。
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图 7 RM和GGBS (a) 及AAFRC (b) 的XRD图谱Figure 7. XRD patterns of RM, GGBS (a) and AAFRC (b)对比图8两种AAFRC的FTIR图谱，发现两种试样的波带起伏状态基本保持一致、不同特征波峰出现的位置没有明显差异，这说明RM的掺入并没有导致新物质的产生。3415 cm−1与1630 cm−1处的波峰分别与(H)—OH基团的伸缩振动、弯曲振动有关[30]，(H)—OH基团可能源自于样品表面的物理吸附水[29]，也可能来自于反应产物中的化学结合水[31]。这两个波峰峰强均比参照试样弱，结合XRD图谱分析结果，可以认为波峰减弱的主要原因为水化产物的减少。1402 cm−1与875 cm−1处的波峰分别对应CO32−基团中C—O—C键的不对称伸缩[31]与平面外弯曲振动[32]，说明两种材料体系内均发生了碳化。根据Yu等[32]和Zhang等[33]的研究，1035 cm−1处波峰的出现归因于Si—O—Al/Si键的不对称伸缩振动，表明体系内有铝硅酸盐无定型产物，例如水化硅铝酸钙(C-A-S-H)及碱性硅铝酸盐(N-A-S-H)凝胶。465 cm−1处的波峰与Si—O—Si键的弯曲振动有关，与其相邻且在较高波数位置(近600 cm−1)波峰的出现则意味着体系内存在有水化硅酸钙(C-S-H)或C-A-S-H凝胶[31]。进一步注意到，RM的掺入导致1035 cm−1及600 cm−1处的波峰峰强均有所减弱，这意味着对应胶凝产物的减少，与XRD分析结果相一致。
3. 结 论
(1) 聚乙烯纤维增强赤泥-碱矿渣复合材料(PE/RM-GGBS-SF)的抗拉强度可以达到2.4 MPa，同时具有与高延性水泥基复合材料相当的高拉伸应变性能，为3.5%；抗压强度可以高达近50 MPa。
(2) 三点抗弯和单裂缝拉伸等细观试验结果可以很好地解释本研究中碱激发纤维增强复合材料(AAFRC)的高延性行为。两种体系均满足实现拉伸应变硬化的两个核心(强度及能量)准则；且PE/RM-GGBS-SF试件的强度指数(PSHS)和能量指数(PSHE)均大于参照试件，很好地对应了其表现出的较大拉伸应变。
(3) XRD和FTIR分析结果显示：赤泥(RM)的引入导致碱激发体系内出现明显的针铁矿及赤铁矿衍射峰；除水化硅酸钙(C-S-H)或水化硅铝酸钙(C-A-S-H)凝胶外，PE/RM-GGBS-SF水化产物中也存在有与地聚合反应产物相似的物相，即碱性硅铝酸盐(N-A-S-H)凝胶。
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图 2 (a) 用于钠离子电池的PVDF/聚丙烯腈(PAN)静电纺隔膜[37]；(b) 具有PVDF聚合物堆叠结构的自旋阀装置[38]；(c) 基于PVDF开发药物输送载体的工作流程[39]；(d) 基于PVDF的可穿戴传感器[40]
Figure 2. (a) PVDF/polyacrylonitrile (PAN) electrospun membrane for sodium ion batteries[37]; (b) Spin valve device with PVDF polymer stacking structure[38]; (c) Workflow of developing drug delivery carriers based on PVDF[39]; (d) PVDF-based wearable sensors[40]
HA—Hyaluronic acid; API-IL—Active pharmaceutical ingredient ionic liquids; H—Magnetic field intensity; I—Electric current; V—Voltage
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图 4 (a) 纯PVDF和PVDF复合材料的热扩散率和热导率；(b) 纯PVDF与PVDF复合材料关于热导率增强程度的对比；(c) 纯PVDF、PVDF/富勒烯(SF)、PVDF/CNT和PVDF/石墨烯(GS)复合材料在加热时的红外图像；(d) 纯PVDF、PVDF/SF、PVDF/CNT和PVDF/GS复合材料在加热和冷却时表面温度随时间的变化；(e) 含SF、CNT和GS的PVDF复合材料的热流模型[62]
Figure 4. (a) Thermal diffusivity and thermal conductivity of pure PVDF and PVDF composites; (b) Comparison of thermal conductivity enhancement between pure PVDF and PVDF-based composites materials; (c) Infrared images of pure PVDF, PVDF/superfullerene (SF), PVDF/CNT and PVDF/graphene sheets (GS) composites when heated; (d) Surface temperature of pure PVDF, PVDF/SF, PVDF/CNT and PVDF/GS composites changes with time during heating and cooling; (e) Heat flux model of PVDF composites containing SF, CNT and GS[62]
TCE—Thermal conductivity enhancement; dT/dt—Rate of change of temperature with respect to time
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图 5 (a) 溶液共混方法制备MXene/PVDF复合材料示意图[82]；(b) 静电纺丝方法制备BN纳米片(BNNS)/PVDF复合薄膜示意图[85]
Figure 5. (a) Schematic diagram of PVDF/MXene composite prepared by solution blending method[82]; (b) Schematic diagram of PVDF/boron nitridenanosheets (BNNS) composite film prepared by electrospinning method[85]
DMF—Dimethylformamide
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图 6 (a) PVDF复合材料的初始棒材涂布工艺[99]；(b) L形扭结管中熔融压缩溶液浇注PVDF和石墨烯纳米片薄膜[100]；(c) 磁场定向控制磁性CNT的取向提高其热导率示意图[101]
Figure 6. (a) Initial bar coating process of PVDF composites[99]; (b) PVDF and graphene nanosheet films were cast by melt-compression solution in an L-shaped kink tube[100]; (c) Magnetic field oriented control of the orientation of magnetic CNT (mCNT) to improve its thermal conductivity[101]
GNF—Graphene nanoflake; PSS—Poly(sodium 4-styrene sulfonate)
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图 7 (a) 不同BN纳米片(BNNS)含量的BNNS/PVDF复合材料的热导率；(b) 不同BNNS含量的BNNS@树脂复合材料的热导率；(c) 不同BNNS含量的PVDF/BNNS和BNNS@树脂/PVDF的热导率；(d) 构建导热通道的理论模型；(e) 模拟不同BNNS含量的BNNS/PVDF复合材料的传热过程[111]
Figure 7. (a) Thermal conductivity of PVDF/boron nitride nanosheets (BNNS) composites with different BNNS content; (b) Thermal conductivity of BNNS@resin composites with different BNNS content; (c) Thermal conductivity of PVDF/BNNS and BNNS@resin/PVDF with different BNNS content; (d) Construct the theoretical model of thermal conduction channel; (e) Heat transfer process of PVDF/BNNS composites with different BNNS content was simulated[111]
MS—Melamine-formaldehyde resin sponge
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图 8 (a) 单一ZnO填料复合材料的热传导模型；(b) 两种不同尺寸ZnO填料经过杂化而成的复合材料的热传导模型； (c) 3种不同尺寸ZnO填料经过杂化而成的复合材料的热传导模型[113]；(d) 室温下，Al/PVDF复合材料的热导率与Al填料 (微米和纳米尺寸下) 的体积比例的关系[88]
Figure 8. (a) Heat conduction model of composites with single filler; (b) Heat conduction model of composites with hybrid fillers of two different sizes; (c) Heat conduction model of composites with hybrid fillers of three different sizes[113]; (d) At room temperature, the relationship between the thermal conductivity of Al/PVDF composites and the volume ratio of Al fillers (micron size and nano size)[88]
λmax—Maximum value of the thermal conductivity; Y—Volume ratio Vmicro∶Vnano
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图 9 ((a)~(g)) AlN晶须与球体混合填料的示意图(体积比分别为1:0、6:1、3:1、1:1、1:3、1:6和0:1)[114]；(h) PVDF复合材料示意图；(i) 25℃下BaTiO3/PVDF、SiC/PVDF和BaTiO3/SiC/PVDF复合材料的热导率[117]
Figure 9. ((a)-(g)) Schematic diagrams of AlN whisker and sphere mixed fillers with volume ratios of 1:0, 6:1, 3:1, 1:1, 1:3, 1:6 and 0:1, respectively[114]; (h) Schematic diagram of PVDF composite; (i) Thermal conductivity of BaTiO3/PVDF, SiC/PVDF and BaTiO3/SiC/PVDF composites at 25℃[117]
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图 10 (a) SiC与BN桥接形成的导热路径[130]；(b) 不同填料负载的PVDF复合膜的导热系数[131]；(c) PVDF/CNT和PVDF/CNT/氧化石墨烯(GO)复合材料中填料分散状态[133]
Figure 10. (a) Thermal conduction path formed by the network bridging of SiC nanowires and BN nanosheets[130]; (b) Thermal conductivity of PVDF composite membranes loaded with different fillers[131]; (c) Dispersion of fillers in PVDF/CNT and PVDF/CNT/graphene oxide (GO) composites[133]
f-SiC—Functionalized SiC; hBN—Hexagonal BN; POSS—Polyhedral oligomeric silsesquioxane
表 1 具有不同晶型的聚偏氟乙烯(PVDF)晶体的性质[36]
Table 1 Properties of polyvinylidene fluoride (PVDF) crystals with different crystal forms[36]
Category α β γ Molecular conformation TGTG' TTT TTGTTG' Melting point Low Medium High Polarity None Strong Intermediate Electronically active None High
piezo-electric,
ferro-electricIntermediate Elasticity — Greatest — Solvent resistance — — Strong Thermal stability — Weak Strong Radiotolerance — — Strong 
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Category Filler Thermal conductivity/
(W·m–1·K–1)Metallic fillers Ni 158.00 Al 204.00 Au 345.00 Ag 450.00 Cu 483.00 Ceramic fillers Al2O3 30.00 SiC 30.00-270.00 AlN 200.00 BN 250.00-300.00 Carbon fillers Graphite 100.00-400.00 Diamond 2000.00 CNT 2000.00-6000.00 Graphene 4800.00-5300.00
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表 3 室温下不同单一填料及成型工艺所制备PVDF复合材料的热导率
Table 3 Thermal conductivity of PVDF composites prepared by different fillers and molding process at room temperature
Filling material type Preparation technology Thermal conductivity/
(W·m–1·K–1)Ag[53] Solution blending 6.50 Zn[54] Solution blending 1.20 Zn@ZnO[87] Solution blending 0.54 Al[88] Melt blending 3.26 Ni[89] Solution blending 1.13 SiC[55] Masterbatch process 1.88 β-SiC[90] Solution blending 1.82 BN[56] Electrostatic spinning 7.29 BNNS[85] Electrostatic spinning 18.33 h-BN[91] Salt template, thermal curing process 1.47 CCB[92] Solution blending 0.44 CNT[93] Melt blending 1.40 Graphene[86] Solvent casting 0.56 GnPs[94] Spray coating, thermal annealing 12.00 MXene[82] Solution blending 0.36 Notes: h-BN—Hexagonal boron nitride; CCB—Conducting carbon black; GnPs—Graphene nanoplatelets.
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目的
导热复合材料在电子封装、电机材料、电池以及换热设备等领域具有广泛的应用价值。聚偏氟乙烯 (PVDF) 具有优异的电气性能、良好的机械强度和耐高温性能，是应用于电子电器、航空航天等行业的理想材料之一，但较低的导热率制约其进一步发展，因而以PVDF为基体的导热复合材料的开发成为该领域研究的重点。研究PVDF复合材料导热性能的目的是探究该材料的导热特性，以进一步了解其在导热领域的应用潜力。了解PVDF复合材料导热特性的基本原理和机制，探索改善PVDF复合材料导热性能的方法和策略，评估不同添加剂或改性方法对导热性能的影响，从而更好地拓展PVDF复合材料在导热领域的应用。
方法采用对PVDF复合材料采用横向整理热导率发展水平，纵向分析提升导热性能的基本途径的方法。通过制备不同组分和结构的PVDF复合材料，并使用热传导性能测试技术(如热导率测试)来测量其导热性能。对实验结果的分析和比较，获得关于导热机制和影响因素的实验数据，并进一步了解PVDF复合材料导热特性的基本原理。利用计算方法(如分子动力学模拟、有限元分析等)对PVDF复合材料的结构进行建模和模拟，以预测其导热性能。通过模拟计算可以揭示PVDF复合材料中热传导的机制和路径，有助于理解导热特性的基本原理。基于已有的导热理论和数学模型，对PVDF复合材料的导热特性进行理论分析。通过推导和求解数学方程，可以研究不同因素对导热特性的影响，从而揭示导热机制的基本原理。利用数值模拟和优化算法，结合现有导热性能理论，探索和优化不同方法和策略对PVDF复合材料导热性能的影响。通过对以上手段和方法，将PVDF导热复合材料的填料选择、负载水平、界面工程、制备工艺、表面改性等方面信息进行收集与整理，进行综述。
结果(1)组分选择：选择填料和添加剂对导热性能有重要影响。常用的填料包括石墨、碳纳米管、金属纳米颗粒等高导热性材料。当这些填料添加到PVDF基体中时，可以形成导热路径，提高导热性能。(2)填料浓度：填料浓度的变化会直接影响PVDF复合材料的导热性能。较高的填料浓度会增加填料之间的接触面积，从而增强热传导。(3)界面相互作用：填料与基体之间的界面相互作用也会影响导热性能。良好的界面相互作用可以促进热能的传递，而界面失效可能会导致热能的反射或散射，从而降低导热性能。(4)网络结构设计：填料的分散性对导热性能起着关键作用。如果填料没有良好的分散性，就会形成聚集体，导致热传导途径的中断和效率的降低。因此，通过合适的处理方法(如超声处理、表面改性等)来提高填料的分散性是非常重要的。
结论PVDF复合材料导热性能的基本机制涉及填料的导热路径、界面热阻、填料分散性、填料浓度和形貌、聚合物基体热导率、组分相互作用，以及复合材料的结晶度和晶体结构等因素。通过优化这些因素，可以实现对PVDF复合材料导热性能的提升。PVDF复合材料导热性能在电子器件、热管理、纳米复合材料、热传导材料和热感温度传感器等各个领域都具有广泛的应用前景。
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导热复合材料在电子封装、电机材料、电池以及换热设备等领域具有广泛的应用价值。聚偏氟乙烯 (PVDF) 具有优异的电气性能、良好的机械强度和耐高温性能，是应用于电子电器、航空航天等行业的理想材料之一，但较低的导热率制约其进一步发展，因而以PVDF为基体的导热复合材料的开发成为该领域研究的重点。目前，关于如何更高效地提升PVDF复合材料的导热性能的系统介绍有待进一步完善，因此本文在前人的研究成果基础上进行综述，旨在深入探讨如何有效提升PVDF复合材料的导热性能。高导热PVDF复合材料的制备关键在于填料种类、复合工艺、结构设计、界面调控等。本文围绕PVDF导热复合材料中复合策略的选择、导热网络的构建以及界面热阻的调控展开介绍。从导热复合材料的组成与结构设计(微观-宏观尺度)、制备工艺与性能优化(局部-整体方面)等角度，综述最新成果，并对其发展趋势进行展望。
PVDF基复合材料导热性能提升方式
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