Self-healing Research Articles

MXene-reinforced water insensitive self-healing piezoelectric nanogenerator for ambient and aquatic mechano-pressure sensing

The development of soft electronic devices capable of autonomous self-healing (SH) holds immense potential across various endeavours, promising to revolutionize product durability, reliability, and maintenance practices. Despite some progress has been made, underwater stable SH continues to be an active area of research. Herein, SH polymer PDMS-MDI0.4-TFB0.6 (SHP) with excellent mechanical property was composited with MXene to investigate the piezoelectric nature under various circumstance. By leveraging MXene into SHP not only improves the material properties of mechanical stress but also permittivity of the elastomer. Thus, MXene incorporated SHP (mSHP) induce high polarized charges under mechanical pressure. The fabrication of mSHP piezoelectric nanogenerator (mSHP-PENG) device via spray coating AgNWs on the surface forms ohmic contact, which facilitate high sensitivity and flexibility. Nevertheless, the generated piezoelectricity (30 V, 4.2 μA: 3 Hz) upon mechanical pressure gives maximum power density of 128 μW/m2 indicating that our device can act as a reliable power source for portable electronic gadgets. In addition, SHP with amphiphilic functional groups sustain the original shape even after immerse into water for so long. Taking this into account, our device undergoes effective deformation even at low pressures, thus render to fabricate touch sensitive piezo-switches for both atmospheric and aquatics environments.

3D Printing with Self-Healing Materials and Applications

3D printing also called as the additive manufacturing. It is revolutionizing various industries by enabling the production of complex objects directly from digital models. This technology offers significant advantages over traditional manufacturing methods. Especially in reducing material waste and increased design flexibility. The range of 3D printing application contains healthcare to aerospace, reflecting its growing importance in modern society. Recently, 3D printing advancements have introduced in self-healing (SH) materials, it saved limitations related to the durability and repairability of printed objects. SH materials are categorized into external and internal systems. External SH materials use embedded healing agents that repair damage through chemical reactions, while internal systems rely on dynamic bonding within the material itself. This innovation not only extends the functional life of 3D printed items but also supports trends in mass customization and sustainability. This paper explores the mechanisms, types, and applications of SH materials in 3D printing, and mainly focus on their potential to enhance product longevity and functionality across medical, construction, and consumer goods sectors.

Advancements in Castor Oil‐Derived Smart Materials: A Comprehensive Mini‐Review

AbstractSmart materials encompass a class of materials capable of reorienting themselves in response to external stimuli (heat, light, and chemical), and generate smart properties such as self‐healing (SH) and shape‐memory (SM), etc. Recently, castor oil has emerged as a bio‐renewable feedstock facilitating the synthesis of smart polymers such as polyurethanes and epoxidized castor oil (CO)‐based polymers. Furthermore, fillers and nanomaterials have been added to prepare responsive materials (SH and SM) and drug delivery systems. This review delves into the recent developments in CO‐based smart materials since 2015 under thermal, photo, and chemical stimuli and their applications in coating, adhesive, soft robotics, and drug delivery. Additionally, the challenges and future scopes for the development of castor oil‐based advanced smart materials have been discussed.

Capacitance Evaluation of Metallized Polypropylene Film Capacitors Considering Cumulative Self-Healing Damage

Self-healing (SH) in metallized polypropylene film capacitors (MPPFCs) can lead to irreversible damage to electrode and dielectric structures, resulting in capacitance loss and significant stability degradation, especially under cumulative SH conditions. To enhance the reliability assessment of MPPFCs post-SH, this study conducted SH experiments on MPPFCs, examined the damage patterns of the electrodes and dielectric films, and proposed a novel capacitance evaluation method for MPPFCs under cumulative SH conditions. The results reveal that with increasing SH voltage, the number of dielectric layers experiencing single SH breakdowns rises, SH energy significantly escalates, and the loss area of the electrode due to high-temperature evaporation expands. Under cumulative SH conditions, the number of SH events is linearly correlated with the total number of SH-breakdown film layers and shows an exponential decay with the average single SH energy. By utilizing a Support Vector Machine (SVM) to classify the SH condition and damage features within the capacitor based on the correlation and distribution patterns of SH feature parameters, this study introduces an advanced method for evaluating the capacitance of MPPFCs under cumulative SH conditions. This method promises to improve the predictive maintenance and reliability of power electronic systems utilizing MPPFCs.

Study of the in situ test setup and analysis methods for self-healing properties of metallized film capacitors.

Metallized film capacitors (MFCs) are widely used in the power electronics industry due to their unique self-healing (SH) capability. SH performance is an essential assessment for MFC reliability verification in industrial production. The SH phenomenon of metallized films usually occurs rapidly in a very short period, and its real-time evolution details are often difficult to capture and analyze. In this paper, a test system for the SH performance of metallized films for capacitors was constructed. The system consists of three components: a voltage-current characteristic testing and current pulse capture device, a microscopic image real-time acquisition device, and an integrated analysis processing device. Through the voltage-current characteristic testing and current pulse capture device, the electrical parameters of the SH point, such as SH times, breakdown field strength, SH current, and SH energy, are obtained; through a microscopic image real-time acquisition device, the real-time spatial positioning of the SH point was obtained, and the interconnection between the morphology of the SH point and the electrical properties was established. The relationship between the SH point and the temperature distribution was further established using thermal imaging technology, which lays the foundation for a thorough and timely assessment and analysis of the failure mechanism and the real-time evolution of the metallized film SH process. This significantly improves the effectiveness of SH property research.

Self-Configuration and Self-Healing Framework Using Extreme Gradient Boosting (XGBoost) Classifier for IoT-WSN

In most Internet of Things (IoT) systems, Quality of service (QoS) must be confirmed with respect to the requirement of implementation domain. The dynamic nature of the IoT surroundings shapes it to complicate the fulfilment of these commitments. A wide range of unpredictable events endanger the quality of service. While execution the self-adaptive schemes handle with system’s unpredictable. In IoT-based Wireless Sensor Networks (WSNs), the significant self-management objectives are self-configuration (SC) and self-healing (SH). In this paper, Self-Configuration and Self-healing Framework using an extreme gradient boosting (XGBoost) Classifier are proposed. In this framework, the IoT traffic classes are categorized as several types under XGBoost classifier. In SC phase, the IoT devices are self-configured by allocating various transmission slots, contention access period (CAPs) on the basis of its categories with priorities. In SH phase, the source node cardinally establishes a confined route retrieval method if the residual power in-between node is truncated or the node has displaced far away. The proposed framework is executed in NS-2 and the results exhibit that the proposed framework has higher packet delivery ratio with reduced packet drops and computational cost. Therefore, the proposed approach has attained 24.7%, 28.9%, 12.75% higher PDR, and 16.8%, 19.87%, and 13.7% higher residual energy than the existing methods like Self-Healing and Seamless Connectivity using Kalman Filter among IoT Networks (SH-SC-KF-IoT), Provenance aware run-time verification mechanism for self-healing IoT (PA-RVM-SH-IoT), and Fully Anonymous Routing Protocol and Self-healing Capacity in Unbalanced Sensor Networks (FARP-SC-USN) methods, respectively.

From Independent to Related: Voltage Ramp Rate Effects on Self-Healing Scaling in Metallized Polypropylene Film Capacitors

Metallized polypropylene film capacitors (MPPFCs) are well-suited for high-frequency and high-electric-field applications, such as electric vehicles, aerospace, and pulsed power systems, due to their self-healing (SH) properties. However, the SH process is affected by operating conditions such as voltage level and ramp rate. It is not well understood whether the SH mechanism is consistent across various operating conditions, which may lead to inaccurate assessments of MPPFC reliability. This paper explores the effect of the DC voltage ramp rates on the SH performance of MPPFC. A more specific classification of SH processes under a high electrical field: independent SH (ISH) and related SH (RSH, composed of two or more sub-SHs). Additionally, the SH process of MPPFCs can be characterized using multiple Weibull subpopulation distributions for various voltage ramp rates. At slow ramp rates (<500 V/s), both ISH and RSH processes are present in the MPPFC, whereas at rapid ramp rates (≥500 V/s), the SH process is mainly dominated by ISH. Moreover, the cumulative SH energy of the MPPFC at the 30 V/s ramp rate is about 10 times that of the 900 V/s ramp rate. The ISH at the 900 V/s ramp rate causes several point-like damaged regions on the metalized PP film (~0.06% decrease in capacitance). In comparison, the RSH at the 30 V/s ramp rates induces clusters of holes across multiple layers in the MPPFC (~9.85% decrease in capacitance), implying that the MPPFC has overreached its expected lifetime.

Effect of hard segment chemistry and structure on the self‐healing properties of UV‐curable coatings based on the urethane acrylates with built‐in Diels–Alder adduct

AbstractThe development of new photoreactive resins to obtain smart coatings and enhance the self‐healing (SH) properties of photoreactive resins has attracted great interest in the past few years, and the investigation of the relationship between phase structure and smart properties is necessary. Herein, four types of urethane acrylate resins with built‐in DA structures with different hard segment structures, and a slight change in the length of the polyol soft segment were prepared. The hard segments were made of hexamethylene diisocyanate (HDI) with a linear structure and isophorone diisocyanate (IPDI) with an alicyclic structure, and the soft segments consisted of polyethylene glycols (PEG 400 and PEG 1000, respectively). The obtained resins were used to prepare polymer films that were cured using UV radiation. The coatings obtained in this way were tested for the influence of the polymer chain architecture on the kinetics of photopolymerization, the properties of the cured coatings, as well as the thermal characteristics and thermoreversibility performance of the cured coatings and their SH ability.

High-Speed and High-Resolution 3D Printing of Self-Healing and Ion-Conductive Hydrogels via μCLIP

Conductive and self-healing (SH) hydrogels have been receiving continuous attention, which could broaden the design of ionotronic devices for health monitoring systems and soft robots with the ability to repair damage autonomously. So far, three-dimensional (3D) fabrication of such SH hydrogels is mainly limited to traditional molding/casting or extrusion-based 3D printing methods, which limits the formation of sophisticated structures with high-resolution features. Furthermore, the need of external stimuli (e.g., water, heat, and pH change) to achieve SH behavior could restrict their wide application. Herein, we report an ion-conductive SH hydrogel suitable for a home-built high-resolution and high-speed 3D printing process, micro continuous liquid interface production (μCLIP). This material system relies on interpenetrating polymer networks (IPN) hydrogel formed by physically cross-linked poly(vinyl alcohol) combined with chemically/ionically cross-linked poly(acrylic acid) and ferric chloride. By carefully optimizing the resin’s composition, we can balance high-resolution printability and superb SH capability, at the same time manifesting sufficient ion conductivity. Specifically, complex 3D structures with microscale features (down to 100 μm) can be printed at speeds up to 16.5 μm s–1. Upon damage occurs, hydrogen bonds within hydroxyl and carboxyl groups, as well as ionic bonds generated from ferric ions, contribute together to achieve fast and high efficiency SH, which can restore 90% (100%) of the original mechanical strength at room temperature within 4 h (8 h) without any external stimulus. In addition, both the as-printed and self-healed hydrogels manifest superior ion conductivity and stretchability. Therefore, the SH hydrogels can be rapidly printed and tailored as customized wearable sensors, and the sensing capabilities were quantitatively investigated and compared. In terms of applications, SH hydrogel-based knuckle sensors were prototyped to detect a finger’s folding and unfolding motions.

Imparting Reprocessability, Quadruple Shape Memory, Self-Healing, and Vibration Damping Characteristics to a Thermosetting Poly(urethane-urea)

The advent of dynamic covalent bond chemistry (DCBC) has sparked renewed research interest in reprocessability of thermosetting polymers. However, combining reprocessability with stimuli-responsiveness remains a challenge for futuristic applications. Usually, a combination of complementary DCBCs is employed to integrate reprocessability with shape memory as well as self-healing (SH) attributes in a single polymeric system. In the present work, we report two-component poly(urethane-urea) (PUU) networks, with varied hard segment (HS) concentrations, that exhibit quadruple shape memory (QSM), efficacious vibration damping, thermally activated intrinsic SH as well as multiple cycles of thermal reprocessability. The component A is an isocyanate capped bi-soft segment blend of polybutadiene diol and polypropylene glycol, while the second component comprises an aromatic diamine chain extender solubilized in an oligomeric polyoxypropylene triol. The networks characterized through FTIR as well as small- and wide-angle X-ray scattering (SAXS and WAXD) revealed a phase-separated morphology with extensive hydrogen-bonding (H-bonding) interactions in the HS domains of the PUU networks. Dynamic mechanical analysis (DMA) measurements revealed broad dissipation factor (tan δ) vs temperature and frequency profiles of the networks, which could be leveraged for efficacious passive vibration damping applications. A dissociative mechanism of urethane and urea bond exchange, evidenced from temperature-dependent FTIR studies enabling facile stress relaxation, is proposed to be the mechanistic origin of the reprocessability and SH of the networks. A broad dissipation factor (tan δ) vs temperature profiles endowed the networks with QSM characteristics. We posit that the study is relevant for expanding the scope of DCBCs for development of reprocessable thermosetting polyurethanes with multiple smart functionalities.

Self-Healing Mechanical Properties of Selected Roofing Felts.

In this work, roof felts are considered. Special attention is paid to the mechanical properties and self-healing (SH) phenomena under elevated temperatures. The results of the heating and strength tests for the entire range of material work, from the first load to sample breaking, are shown with respect to the angle of reinforcement relative to the longitudinal axis of the sample and different ways of breaking the continuity of the material. The influence that the material thickness and modifiers used for the production of the base material have on the obtained results was also pointed out. The meaningful SH strength is reported-from 5% up to 20% of the strength of the undamaged material-which, in perspective, can provide comprehensive knowledge of the optimal use of roofing felts and its proper mathematical modeling.

Signal Processing with Machine Learning for Context Awareness in 5G Communication Technology

To meet users’ expectations for speed and reliability, 5th Generation (5G) networks and other forms of mobile communication of the future will need to be highly efficient, flexible, and nimble. Because of the expected density and complexity of 5G networks, sophisticated network control across all layers is essential. In this context, self-organizing network (SON) is among the essential solutions for managing the next generation of mobile communication networks. Self-optimization, self-configuration, and self-healing (SH) are typical SON functions. This research creates a framework for analyzing SH by exploring the impact of recovery measures taken in precarious stages of health. For this reason, our suggested architecture takes into account both detection and compensating operations. The system is broken down into some faulty states and the “fuzzy c-means” (FCM) approach is used to conduct the classifying. In the compensation process, the network is characterized as the Markov decision model (MDM), and the linear programming (LP) technique is implemented to find the most effective strategy for reaching a goal. Numerical findings acquired from a variety of situations with varying objectives show that the suggested method with optimized operations in the compensation stage exceeds the approach with randomly chosen actions.

Development of nanomodified self-healing mortar and a U-Net model based on semantic segmentation for crack detection and evaluation

In this study, a cement-based self-healing (SH) mortar mixed with multiwalled carbon nanotubes (MWCNTs) was developed, and the effect of MWCNT addition on the electromechanical properties of mortar was studied. In addition, a deep learning based U-shaped Network (U-Net) model was adopted for the crack healing evaluation in SH mortar specimens. The trained U-net model is capable to detect the cracks with the accuracy of 99 %. The MWCNT content in the mortar was varied from 0.05 % to 0.10 % by weight of the cement. A minerals-based SH admixture was incorporated at concentrations of 2.5 %, 5 %, and 7.5 % by weight of cement. Compression and flexural strength tests were performed to investigate the mechanical performance of the nanomodified mortar. Piezoresistive sensing properties of MWCNT/cement composite were monitored during flexural test. For crack healing evaluation, cracked mortar prisms were exposed to water for 28 days. Mechanical and piezoresistive sensing evaluation demonstrated improved mechanical performance of SH mortar with appreciable self-sensing properties. Specimens with 2.5 % admixture exhibited a crack sealing efficiency of approximately 90 %, while the cracks in specimens with 5 % and 7.5 % SH admixture content healed 100 % after 28 days of water exposure.

Self-Healable Lithium-Ion Batteries: A Review.

The inner constituents of lithium-ion batteries (LIBs) are easy to deform during charging and discharging processes, and the accumulation of these deformations would result in physical fractures, poor safety performances, and short lifespan of LIBs. Recent studies indicate that the introduction of self-healing (SH) materials into electrodes or electrolytes can bring about great enhancements in their mechanical strength, thus optimizing the cycle stability of the batteries. Due to the self-healing property of these special functional materials, the fractures/cracks generated during repeated cycles could be spontaneously cured. This review systematically summarizes the mechanisms of self-healing strategies and introduces the applications of SH materials in LIBs, especially from the aspects of electrodes and electrolytes. Finally, the challenges and the opportunities of the future research as well as the potential of applications are presented to promote the research of this field.

Optimal Number and Locations of Smart RMUs for Self-Healing Distribution Networks

Smart grids with self-healing (SH) capability provide an important intelligent feature to help in fast correction actions in case of network faults. SH architecture consists of modern communication systems, smart equipment, and intelligent sensors. With the high cost of SH components (especially smart ring main unit (SRMU)), optimization is required to achieve optimum performance with minimum cost. This study presents a proposed methodology to determine the optimum number and locations of SRMUs in electricity distribution networks considering various cost issues. The disconnection cost of on-grid photovoltaic (PV) plants is taken into consideration as an important factor in determining the locations of the SRMUs. The nonlinear programming (NLP) optimization technique is used to determine the required number of SRMUs, considering the cost/benefit analysis (cost of upgrading MRMUs to SRMUs/benefit due to interruption time reduction), which is the most important factor from DISCOs’ perspective. The mixed integer linear programming (MILP) optimization technique is employed for selecting the optimal locations of the SRMUs considering the cost of losses, energy not supplied (ENS), and PV disconnection, which improves network operation cost. The methodology takes into consideration the cable failure rate and the interest rate. Moreover, the study introduces the Egyptian electrical distribution network and a pilot project for control centre development using SRMUs. The methodology is applied to a modified IEEE 37-node test feeder and a part of a specific district network in South Cairo consisting of 158 nodes; both systems include a number of PV distributed generation plants. Simulation results are presented to show the effectiveness of the proposed method.

Effects of Ligands in Rare Earth Complex on Properties, Functions, and Intelligent Behaviors of Polyurea-Urethane Composites.

There is a need to create next-generation polymer composites having high property, unique function, and intelligent behaviors, such as shape memory effect (SME) and self-healing (SH) capability. Rare earth complexes can provide luminescence for polymers, and their dispersion is highly affected by ligand structures. Here, we created three different REOCs with different ligands before studying the effects of ligands on REOC dispersion in polyurea–urethane (PUU) with disulfide bonds in main chains. In addition, the effects of different REOCs on mechanical properties, luminescent functions, and intelligent behaviors of PUU composites were studied. The results showed that REOC I (Sm(TTA)3phen: TTA, thenoyltrifluoroacetone; phen, 1,10-phenanthroline) has incompatible ligands with the PUU matrix. REOC I and REOC III (Sm(BUBA)3phen: BUBA, 4-benzylurea-benzoic acid) with amine and urea groups facilitate their dispersion. It was REOC III that helped the maintenance of mechanical properties of PUU composites due to the good dispersion and the needle-like morphologies. Due to more organic ligands of REOC III, the fluorescence intensity of composite materials is reduced. The shape recovery ratio of the composite was not as good as that of pure PUU when a large amount of fillers was added. Besides, REOC I reduced the self-healing efficiency of PUU composites due to poor dispersion, and the other two REOCs increased the self-healing efficiency. The results showed that ligands in REOCs are important for their dispersion in the PUU matrix. The poor dispersion of REOC I is unbeneficial for mechanical properties and intelligent behavior. The high miscibility of REOC II (Sm(PABA)3phen: PABA, 4-aminobenzoic acid) decreases mechanical properties as well but ensures the good shape recovery ratio and self-healing efficiency. The mediate miscibility and needle-like morphology of REOC III are good for mechanical properties. The shape recovery ratio, however, was decreased.

Self-Healing and Shape Memory Behavior of Functionalized Polyethylene Elastomer Modified by Zinc Oxide and Stearic Acid

There is still a great need to develop self-healing polymers (SHPs) using a cost-effective modification approach for commercial polymers. Herein, we describe our preparation of self-healing (SH), acrylic acid-functionalized, metallocene polyethylene elastomer (mPE-g-AA) composites containing ZnO and stearic acid (SA) that feature both supramolecular hydrogen bonding and ionic interactions. Regarding mechanical properties, with the addition of various contents of ZnO/SA in the mPE-g-AA matrix, their tensile strength increased to be higher than that of mPE-g-AA. As for the shape memory properties, with this synergistic effect of zinc oxide (ZnO), SA, and grafting AA, both the shape fixing ratio and shape recovery ratio of those functionalized polyethylene samples modified by ZnO and SA increased up to above 80% as a result of the hydrogen bonding and reversible ionic crosslinked networks acting as physical crosslinks. Among all of the samples, mPE-g-AA/ZnO 4/SA 1 (4 phr of ZnO and 1 phr of SA) exhibited the highest SH efficiency, at 44.6% for half-hour healing and up to 64.4% under 6 h healing, being higher than those related self-healing mPE studies in the literature. These hydrogen bonded reversible networks, along with the enhanced molecular flow at high temperatures in addition to ionic interactions, could also have a great potential in self-healing applications, besides the shape memory performance. So far, to the authors’ best knowledge, there have been no published reports of the design of polyolefin elastomers with thermally-triggered shape memory effect by adding ZnO to assist the self-healing behavior. The current synergistic approach paves the way for preparing various SH commercial polymers where surface scratches and cuts have previously been hard to repair.

“Investigating the differences between steel slag and natural limestone in asphalt mixes in terms of microscopic mechanism, fatigue behavior and microwave-induced healing performance”

Reducing the consumption of non-renewable aggregate and replacing it with steel slag waste is one of the feasible measures to produce cleaner asphalt pavement, which is conducive to the sustainable development of transportation infrastructure. This investigation was to assess the differentiation between steel slag and natural limestone in asphalt mastic and fine aggregate matrix (FAM) from perspectives of microscopic characteristics of raw materials, fatigue behavior and microwave induced healing capacity. First, differences in the characteristics of steel slag and limestone fillers and the microscopic interactions between fillers and bitumen were evaluated by scanning electron microscope, X-ray diffraction, X-ray photoelectron spectroscopy, thermo gravimetric analyzer, and Fourier transform infrared spectroscopy. Second, the fatigue behavior and microwave heating capability of steel slag asphalt mastic (70-SS) and limestone asphalt mastic (70-LS) were performed on dynamic shear rhemeter device and microwave generator in a laboratory. Third, the fatigue life of steel slag FAM (SS-FAM) and limestone FAM (LS-FAM) were predicted under the framework of viscoelastic continuum damage (VECD) model, and performance of FAM mixes under microwave-induced healing (MIH) and self-healing (SH) mechanisms was also analyzed. Furthermore, a comprehensive statistical analysis was accomplished by radar plots from micro- and macro-view. Microscopic characterization indicates that steel slag is porous and contains microwave-absorbing components, and reveals that 70-SS has better crystallization and superior thermal stability than 70-LS. The fatigue life of unaged 70-LS is greater than that of 70-SS and vice versa for aged specimen. The microwave absorption and heating rate of 70-SS are promoted by its magnetic components. Fatigue resistance and healing capacity under microwave radiation of SS-FAM are better than those of LS-FAM, and MIH efficiency is obviously greater than that under SH mechanism. Statistical outcomes demonstrates that the performance ranking of the mastic system is in agreement with that of the corresponding FAM system.

Ultrasound phantom with solids mimicking cancerous tissue for needle breast biopsy.

This study aimed at synthesizing hydrogels to simulate opaque breast tissue (BT) and coloured cancerous tissues (CT) at different densities of the designed phantom to improve the biopsy-related skills along with ultrasonography. Both tissues are tear-resistant and therefore, the phantom can be trained multiple times in order to lower the price and improve the eye-hand coordination of users. For this purpose, self-healing (SH) polyacrylamide (PAAm) hydrogels (SH hydrogel) obtained by free-radical polymerization of AAm, in the presence of chemical cross-linker, BAAm, physical cross-linker stearyl methacrylate, C18, and ammonium persulfate APS as initiator were used in the design of phantoms. Psyllium was added to the BT to differentiate density and obtain human skin color and it could be distinguished from the CT which was also colored with methyl violet. BT and CTs were characterized with FTIR spectroscopy, mechanical, swelling, and refractive index measurements. Designing phantoms from BT and CT were characterized by ultrasonography, mechanical tests, observation of needle track after biopsy, and stabilization tests to follow the self-healing behaviours of tissues with time. As a result of this study, self-healing, low-cost, and suitable for multi-usage ultrasonographic phantom for needle breast biopsy was designed and cancerous tissue was successfully detected.

Toughening and Healing of CFRPs by Electrospun Diels–Alder Based Polymers Modified with Carbon Nano-Fillers

In the present investigation, thermo-reversible bonds formed between maleimide and furan groups (Diels–Alder (DA)-based bis-maleimides (BMI)) have been generated to enable high-performance unidirectional (UD) carbon fiber-reinforced plastics (CFRPs) with self-healing (SH) functionality. The incorporation of the SH agent (SHA) was performed locally, only in areas of interest, with the solution electrospinning process (SEP) technique. More precisely, reference and modified CFRPs with (a) pure SHA, (b) SHA modified with multi-walled carbon nano-tubes (MWCNTs) and (c) SHA modified with graphene nano-platelets (GNPs) were fabricated and further tested under Mode I loading conditions. According to experimental results, it was shown that the interlaminar fracture toughness properties of modified CFRPs were considerably enhanced, with GNP-modified ones to exhibit the best toughening performance. After the first fracture and the activation of the healing process, C-scan inspections revealed, macroscopically, a healing efficiency (H.E.) of 100%; however, after repeating the tests, a low recovery of mechanical properties was achieved. Finally, optical microscopy (OM) examinations not only showed that the epoxy matrix at the interface was partly infiltrated by the DA resin, but it also revealed the presence of pulled-out fibers at the fractured surfaces, indicating extended fiber bridging between crack flanks due to the presence of the SHA.