Graphene fiber-based supercapacitors (SCs) are rising as having the greatest potential for portable/wearable energy storage devices. However, their rate performance is not well pleasing, which greatly impedes their broad practical applications. Herein, three-dimensional porous carbon nanotube/reduced graphene oxide fibers were prepared by a nonsolvent-induced rapid phase separation method followed by hydrazine vapor reduction. Benefitting from their three-dimensional porous structure, large specific surface area, and high conductivity, the fabricated SC exhibits a high volume capacitance of 54.9 F cm–3 and high energy and power densities (4.9 mW h cm–3 and 15.5 W cm–3, respectively). Remarkably, the SC works well at a high scan rate of 50 V s–1 and shows a fast frequency response with a short time constant of 78 ms. Furthermore, the fiber-shaped SC also exhibits very stable electrochemical performances when it is subjected to mechanical bending and succeeding straightening process, indicating its great potential application in flexible electronic devices.

Conductive polymer composites (CPCs) for electromagnetic interference shielding have received significant attention and shown rapid development. According to the electromagnetic wave interface conduction theory of Schelkunoff, excellent conductive performance and perfect conductive network structure are prerequisites for high shielding efficiency of electromagnetic interference shielding composites. Effective multiple interface reflection absorption, dielectric loss, and hysteresis loss characteristics of the materials are crucial for realizing the regulation of the electromagnetic interference shielding performance of CPCs. Therefore, the structural design of conductive and magnetic network for CPCs is crucial for achieving high shielding performance. In this study, it is established that an electromagnetic shielding composite with a uniform structure is widely used because of its simple preparation process, but its inefficient conductive network causes a high percolation threshold. The inefficiency can be solved by designing a composite structure and improving the efficiency of the conductive network. Currently, common structural designs include segregated structural, layered structural, and foam structural designs. These structural designs effectively solve the problem of high percolation threshold of CPCs and coordinate the contradiction between the performance of electromagnetic interference shielding and other advantages.

related operations, and destroy the operation of the whole equipment (system). Bao and his colleagues developed a novel self-healing and mechanical force-sensing flexible sensor using micro-structured elastomeric dielectrics, which served as a foundation to improve the stability and lifetime of flexible sensors. [8] Self-healing flexible materials can be divided into two categories, one is solvent-less or water-free after curing and high degree of polymerization of elastomers, such as polyamide, polyurethane, etc., the other is hydrogels, low degree of polymerization, structural cross-linking. In self-healing flexible elastomer sensors, the structure of elastomer is mostly linear structure or semi-cross-linked structure; the elastomer of cross-linked structure is poor flexibility and fragile due to its high degree of polymerization. The elasticity of semi-crosslinked structure has excellent resilience and great potential in the field of flexible flexural sensors. In the past two years, self-healing flexible hydrogels have attracted extensive attention due to their excellent stretchability and resilience, as well as outstanding performance in the preparation of sensors with high sensitivity and fast response. [9,10] Sensors with elastomers and hydrogels as flexible matrices face great difficulties in conductivity, which affects the sensitivity and stability of the sensors. Filling conductive materials is the most commonly method, in which organic conductive polymers (polyaniline, [11] polypyrrole [12]) are filled to construct conductive networks, and good interfacial compatibility results in uniform conductive polymer elastomers, but the inherent color fillers affect the transparency of flexible sensors, limiting their applications in the biomedical field. [13-17] Flexible materials filled with inorganic conductive particles (graphene, nano-silver wire) have high conductivity, but phase separation between filler and matrix usually reduces the tensile, toughness and fatigue resistance, and even affects the self-healing ability of flexible materials. Modified fillers are often required to improve affinity for flexible matrices and inhibit phase separation. However, many hydrogel matrices are intrinsically weak and cannot withstand cyclic loadings. [18] Although surface modified fillers can improve strength and toughness, it is difficult to compensate for the inherent weaknesses. For self-healing flexible elastomers, conductive flexible materials can still be endowed with conductivity by scraping or printing conductive particles on the Flexible pressure and strain sensors have great potential for applications in wearable and implantable devices, soft robots, and artificial skin. The introduction of self-healing performance has made a positive contribution to the lifetime and stability of flexible sensors. At present, many self-healing flexible sensors with high sensitivity have been developed to detect the signal of organism activity. The sensitivity, reliability, and stability of self-healing flexible sensors depend...

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Attachment theory provides a framework for understanding the correlations among interpersonal relationships, stress, and health. Moreover, adult attachment is an important predictor of mental health. However, there is a lack of systematic reviews that simultaneously examine the associations between adult attachment and both positive and negative indicators of mental health. Consequently, we meta-analyzed 224 studies examining the associations between adult attachment and mental health, using robust variance estimation with random effects. The results (k = 245 samples, N = 79,722) showed that higher levels of attachment anxiety and avoidance were positively correlated with negative affect (e.g., depression, anxiety, loneliness) and they were negatively correlated with positive affect (e.g., life satisfaction, self-esteem). More specifically, there were moderate associations between attachment avoidance and negative mental health (r = .28) and positive mental health (r = −.24). Likewise, there were moderate associations between attachment anxiety and negative mental health (r = .42) and positive mental health (r = −.29). Furthermore, the association between the attachment dimensions and mental health outcomes was also moderated by several variables (e.g., gender, age). Finally, these associations remained statistically significant even when the attachment dimensions were mutually controlled using meta-analytic structural equation modeling. Overall, attachment anxiety had larger associations with mental health than did attachment avoidance. Thus, the current results support robust links between adult attachment and mental health. This may have implications for future research and mental health treatments.