Self-healing Approach Research Articles

Enhancing Flexibility and Reliability in Smart Distribution Networks: A Self-Healing Approach

This paper presents a pioneering approach that integrates a Self-Healing System through a Smart Distribution Network, which employs a two-step implementation of a comprehensive Energy Management algorithm and a multi-agent system with an autonomous distributed regeneration method. The novel method improves network operation through optimized management of local microgrids, which include diverse components comprising renewable energy sources, electric vehicle charging infrastructure, and energy storage systems. The first phase concentrates on minimizing network operation costs by adhering to system utilization restrictions and optimal load distribution, while the second phase addresses the optimization of regeneration processes, which decreases discrepancies between recoverable priority loads and switching operations. The evaluation introduces a stochastic programming approach to model and manage uncertainties, and utilizes the Kantorovich method and the roulette wheel mechanism to improve reliability. ...

In Situ Alloying Enabled by Active Liquid Metal Filler for Self-Healing Composite Polymer Electrolytes.

Solid inorganics, known for kinetically inhibiting polymer crystallization and enhancing ionic conductivity, have attracted significant attention in solid polymer electrolytes. However, current composite polymer electrolytes (CPEs) are still facing challenges in Li metal batteries, falling short of inhibiting severe dendritic growth and resulting in very limited cycling life. This study introduces Ga62.5In21.5Sn16 (Galinstan) liquid metal (LM) as an active liquid alternative to conventional passive solid fillers, aiming at realizing self-healing protection against dendrite problems. Compared to solid inorganics, for example silica, LM droplets could more significantly reduce polymer crystallinity and enhance Li-ion conductivity due to their liquid nature, especially at temperatures below the polymer melting point. More importantly, LMs are unraveled as dynamic chemical traps, which are capable of blocking and consuming lithium dendrites upon contact via in situ alloying during battery operation and further inhibiting dendritic growth due to the lower deposition energy barrier of the formed Li-LM alloy. As a proof of concept, by strategically designing an asymmetric CPE with the active LM filling, a solid-state Li/LiFePO4 battery achieves promising full-cell functionality with notable rate performance and stable cycle life. This active filler-mediated self-healing approach could bring new insights into the battery design in versatile solid-state systems.

A full-depth self-healing strategy for cracks in cement-based materials under marine environment

The depth of crack self-healing is crucial in advancing self-healing technology in cement-based materials. An additional challenge arises in marine environments with the infiltration of corrosion ions into the cracks. A self-healing approach revolving around microbial mineralization and layered double metal hydroxides (LDHs) is proposed to address these dual challenges. The findings demonstrate a significant enhancement in the healing properties of the mortar when mixed with the healing agent, particularly in terms of ultrasonic speed and resistance to cross-cracking, which are indicative of internal self-healing effects. The depth of crack self-healing was greatly improved, with a wide distribution of healing products observed on the crack surface. This healing effect is attributed to the in-situ formation of LDHs within the cracks. LDHs immobilizes a substantial amount of hydroxide ions, chloride ions, sulfate ions, and water molecules, resulting in improved volume expansion performance and effective sealing of the cracks. Moreover, the physical and chemical conditions within the crack solution were optimized, enhancing the activity of microorganisms and thereby improving the healing rate of the crack opening area. This multi-modal synergy-based self-healing strategy holds promise as a potential solution for achieving efficient crack self-healing.

Engineering properties of microcapsules self-healing geopolymer cutoff wall backfill under dry-wet cycles

Vertical cutoff wall has been employed for decades to control groundwater flow and subsurface contaminant transport. Environmental stress fluctuations induced by alternating dry and wet conditions impair the permeability and durability of the cutoff wall, leading to the dispersion of contaminants. The objective of this study is to incorporate self-healing microcapsules into existing geopolymer cutoff wall backfill (GCWB) to form self-healing geopolymer cutoff wall backfill (SHGCWB) that hold promise for better durability and performance. The in-situ polymerization method was used to develop single-walled and double-walled microcapsules. The microcapsules use sodium silicate as the healing agent encapsulated in single-walled polyurethane (PU) and double-walled polyurethane/melamine-formaldehyde (PU/MF) microcapsules. The effect of microcapsules on the unconfined compressive strength (UCS) and hydraulic conductivity of SHGCWB were elaborated. The durability and hydraulic conductivity variation of SHGCWB in dry-wet cycle was thoroughly investigated by Scanning Electron Microscopy (SEM) test for understanding the self-healing mechanism. The overall performance demonstrated the significant potential of the use microcapsules as a self-healing approach for cutoff walls.

Toxic relationship in youth communication through self-love intervention strategy

This study set out to identify and analyze toxic relationships in interpersonal communication among adolescents. The toxic relationship, as an unhealthy relationship, does have an impact on the occurrence of internal conflicts. Such relationships often cause the people involved to encounter unproductiveness and mental disorders, which can trigger an emotional outburst that leads to violence. A qualitative approach was used as the research method. The data collection techniques comprised FGD, observation, and in-depth interviews with informants/participants as primary data. The study findings show that first, the perpetrators of toxic relationships, namely toxic people, could be those closest to the victims, such as the nuclear family (father, mother, and siblings). In addition, the perpetrator could be a lover in an unhealthy romantic relationship or peers and even friends who often do the bullying via verbal, physical, or even sexual violence. Second, toxic relationships can be categorized into several forms, namely unhealthy relationships with friends (‘toxic friendship’), parents/family (‘toxic parenting’), lovers, and cheating parents, which can affect a child’s mentality. Actions necessary include the raising of awareness and concern for the community. If violent behavior occurs, it is not permissible to act permissive. The individual approach carried out during victim assistance can entail consultations in the form of ‘vent sessions’. A powerful way to anticipate being trapped in an unhealthy relationship is via self-love. Counselling is carried out with a self-healing approach to restore victims’ self-confidence and maintain their mental health.

Shear strength recovery of sand with self-healing polymeric capsules

Self-healing approaches are increasingly being explored in various fields as a potential method to recover damaged material properties. By self-recovering without external intervention, self-healing techniques emerge as a potential solution to arrest or prevent the development of large strains problems in soils (e.g., landslides) and other ground effects that influence the serviceability of structures (e.g., differential settlement). In this study, a microcapsule-based self-healing sand was developed, and its performance during mixing and compaction, shearing, and recovery of shear strength was demonstrated. The cargo used for sand improvement, a hardening oil, tung oil, was encapsulated in calcium alginate capsules by the ionic gelation method. The surface properties, internal structure, thermal stability and molecular structure of the capsules were evaluated by advanced material characterization techniques. The survivability of capsules during mixing and compaction was assessed by measuring the content of tung oil released into the sand, while their influence on sand shear strength and its recovery was assessed with shear box tests. The results showed that the capsules could rupture due to movement of the sand particles, releasing the tung oil cargo, leading to its hardening and minimizing its strain-softening response and enhancing up to 76% of the sand shear strength (at a normal stress of 10 kPa and capsules content of 4%). This study demonstrates the potential of a capsules-based self-healing system to provide ‘smart’ autonomous soil strength recovery and thus with potential to actively control the large strain behavior of soils.

Sustainable biologically self-healing concrete by smart natural nanotube-hydrogel system

Biologically self-healing concretes are generally composed of immobilized or encapsulated bacterial spores and nutrients. The efficiency of this self-healing approach depends on the effective protection and storage by the carriers. This report describes a novel sustained-release strategy for the improved self-healing function and microcapsule resistance to the cement environment. Halloysite clay nanotubes (HNTs) loaded with the common microbiological nutrient, yeast extract (YE) were encapsulated in calcium alginate microcapsules alongside Bacillus pseudofirmus spores. The encapsulation of the YE-loaded HNTs improved the resistance of the microcapsules to the cement environment, improved the microcapsule-cement interface, while successfully retaining the nutrients after direct contact with the cement pore solution. The self-healing system effectively healed artificial concrete cracks compared to control samples, reducing the crack water tightness by over 95%, and improved the flexural strength regain by approximately 75% after 56 days of wet-dry incubation. The sustained-release mechanism considerably improved the self-healing performance.

Temperature-dependent synergistic self-healing in thermoplastic-thermoset blends: Unraveling the role of thermoplastics and dynamic covalent networks

Two different self-healing approaches are studied in this work to analyze the possible contribution of each of the self-healing mechanisms at different temperatures and the possible synergetic effects between them. Thermal and mechanical properties were differently affected by the addition of each of the thermoplastic polymers. This was caused by different phase separations induced during the curing reaction in terms of size and number of the thermoplastic phase domains dispersed within the epoxy matrix and due to the different amounts of thermoplastic polymer that remain solved in the matrix. When using the vitrimeric matrix, phase separation only occurred at the nanometer scale when utilizing poly(bisphenol-A-co-epichlorohydrin) (PBAE) as a thermoplastic agent or higher contents of polycaprolactone (PCL).Self-healing capabilities showed a strong dependence on the temperature used and the type of crack. Low temperatures allowed the thermoplastic phase to flow and fill partially the cracks with moderate levels of self-healing which were only available when phases were separated. Higher temperatures allowed dynamic bonds to induce material healing reaching very high efficiencies but, more importantly, a synergic effect was observed when material was removed from the cracks. In these cases, the flow of the thermoplastic phase filled better the crack and there was an enhanced cooperation between the two healing mechanisms. At higher self-healing temperatures, materials with nanometric size phase separation enabled greater self-healing efficiencies (above 90 %) due to the vitrimeric self-healing capability while the thermoplastic phase helped fill the gaps due to material removal.

Extremum Seeking Approach for Real-Time Self-healing of Position Sensor Offset Error in PMSMs

Extremum Seeking Approach for Real-Time Self-healing of Position Sensor Offset Error in PMSMs

DQN Approach for Adaptive Self-Healing of VNFs in Cloud-Native Network

DQN Approach for Adaptive Self-Healing of VNFs in Cloud-Native Network

Self-Healing Networks AI-Based Approaches for Fault Detection and Recovery

The reliability and robustness of communication networks are critical for ensuring seamless connectivity in today's interconnected world. However, network faults and failures can disrupt services, leading to significant downtime and financial losses. [1]In response to these challenges, self-healing networks empowered by artificial intelligence (AI) have emerged as a promising solution for proactively detecting and autonomously recovering from network faults. This paper presents a comprehensive review and analysis of AI-based approaches for fault detection and recovery in self-healing networks, aiming to enhance network reliability and minimize service disruptions. It provides an overview of the key challenges associated with traditional fault detection and recovery methods in communication networks.[2] It discusses the limitations of reactive approaches that rely on manual intervention or predefined rules to identify and mitigate network faults, highlighting the need for more proactive and adaptive solutions. Subsequently, the paper explores the role of artificial intelligence, particularly machine learning and deep learning techniques, in enabling self-healing capabilities in communication networks. By leveraging vast amounts of network data, AI algorithms can learn complex patterns and anomalies indicative of network faults, enabling timely detection and response. The paper reviews various AI-based fault detection techniques, including anomaly detection, supervised learning, and reinforcement learning approaches. It examines their strengths and limitations in different network environments, considering factors such as data availability, scalability, and real-time processing requirements. Furthermore, the integration of AI-based fault detection with network monitoring systems and telemetry data sources is discussed, highlighting the importance of comprehensive data-driven approaches for accurate fault identification. In addition to fault detection, the paper investigates AI-driven recovery mechanisms for self-healing networks. It explores proactive recovery strategies, such as predictive maintenance and network reconfiguration, enabled by AI-based predictive analytics. By harnessing the power of machine learning and deep learning, communication networks can achieve greater resilience, adaptability, and autonomy in mitigating network faults and ensuring uninterrupted service delivery.

A Self-Healing System for Polydicyclopentadiene Thermosets.

Self-healing offers promise for addressing structural failures, increasing lifespan, and improving durability in polymeric materials. Implementing self-healing in thermoset polymers faces significant manufacturing challenges, especially due to the elevated temperature requirements of thermoset processing. To introduce self-healing into structural thermosets, the self-healing system must be thermally stable and compatible with the thermoset chemistry. This article demonstrates a self-healing microcapsule-based system stable to frontal polymerization (FP), a rapid and energy-efficient manufacturing process with a self-propagating exothermic reaction (≈200 °C). A thermally latent Grubbs-type complex bearing two N-heterocyclic carbene ligands addresses limitations in conventional G2-based self-healing approaches. Under FP's elevated temperatures, the catalyst remains dormant until activated by a Cu(I) co-reagent, ensuring efficient polymerization of the dicyclopentadiene (DCPD) upon damage to the polyDCPD matrix. The two-part microcapsule system consists of one capsule containing the thermally latent Grubbs-type catalyst dissolved in the solvent, and another capsule containing a Cu(I) coagent blended with liquid DCPD monomer. Using the same chemistry for both matrix fabrication and healing results in strong interfaces as demonstrated by lap-shear tests. In an optimized system, the self-healing system restores the mechanical properties of the tough polyDCPD thermoset. Self-healing efficiencies greater than 90% via tapered double cantilever beam tests are observed.

Properties and Applications of Self-Healing Polymeric Materials: A Review.

Self-healing polymeric materials, engineered to autonomously self-restore damages from external stimuli, are at the forefront of sustainable materials research. Their ability to maintain product quality and functionality and prolong product life plays a crucial role in mitigating the environmental burden of plastic waste. Historically, initial research on the development of self-healing materials has focused on extrinsic self-healing systems characterized by the integration of embedded healing agents. These studies have primarily focused on optimizing the release of healing agents and ensuring rapid self-healing capabilities. In contrast, recent advancements have shifted the focus towards intrinsic self-healing systems that utilize their inherent reactivity and interactions within the matrix. These systems offer the advantage of repeated self-healing over the same damaged zone, which is attributed to reversible chemical reactions and supramolecular interactions. This review offers a comprehensive perspective on extrinsic and intrinsic self-healing approaches and elucidates their unique properties and characteristics. Furthermore, various self-healing mechanisms are surveyed, and insights from cutting-edge studies are integrated.

Exploring the Potential of Polypropylene Fibers and Bacterial Co-Culture in Repairing and Strengthening Geopolymer-Based Construction Materials

This study explored self-healing in geopolymer mortar cured at ambient temperature using polypropylene fibers and bacterial co-cultures of Bacillus subtilis and Bacillus megaterium. Damage degree, compressive strength, ultrasonic pulse velocity (UPV), strength-regain percentage, and self-healing percentage were evaluated. A full factorial design was used, which resulted in an eight-run complete factorial design with four levels in the first factor (polypropylene content: 0%, 0.25%, 0.5%, and 0.75%) and two levels in the second factor (bacteria concentration: 0 (without) and 1 (with)). The results indicate that increasing the polypropylene fiber content enhanced strength regains up to 199.97% with 0.75% fibers and bacteria. The bacteria alone improved strength-regain percentages by 11.22% through mineral precipitation. The analysis of variance (ANOVA) showed no interaction between fibers and bacteria, but both independently improved the compressive strength. Only bacterial samples exhibited positive self-healing, ranging from 16.77 to 147.18%. The analysis using a scanning electron microscope with energy dispersive X-ray (SEM-EDX) and X-ray fluorescence (XRF) also revealed greater calcite crystal formation in bacterial samples, increasing the strength-regain and self-healing percentages. The results demonstrate that polypropylene fibers and bacteria cultures could substantially enhance the strength, durability, and self-healing percentage of geopolymer mortars. The findings present the potential of a bio-based self-healing approach for sustainable construction and repair materials.

Power system resilience against climatic faults: An optimized self-healing approach using conservative voltage reduction

The resilience of power systems is critical in mitigating faults caused by the impending effects of climate change. Typical operational methods, such as network reconfiguration, may be insufficient to mitigate faults in the event of a contingency. On the other hand, reducing system demand may help increase the number of restored loads. As a result, this paper proposes a novel self-healing optimization approach based on a power grid concept known as conservative voltage reduction (CVR), which results in system demand reduction. The proposed optimization model is formulated as a mixed integer non-linear (MINLP) problem to fulfill an objective of minimizing unserved loads within the system. Voltage, thermal capacity, system radiality, and several more constraints have been taken into consideration while formulating the proposed model to handle both grid-connected and isolated modes of operation. Both dispatchable and non-dispatchable distributed generators (DGs) are taken into consideration. Dispatchable DGs are assumed to be capable of switching back and forth between constant power (PQ) and droop controls for the purpose of grid following and grid forming in grid-connected and isolated modes of operation, respectively. The proposed optimization approach is coded and solved using the General Algebraic Modeling System (GAMS) software. The IEEE 69-bus power distribution test system is utilized to test the validity and superiority of the proposed model. The results show that the proposed model effectively increases the system resilience by reducing the unserved power/energy within the system following a contingency.

Application of Shape Memory and Self-Healable Polymers/Composites in the Biomedical Field: A Review.

Shape memory-assisted self-healing polymers have drawn attention over the past few years owing to their interdisciplinary and wide range of applications. Self-healing and shape memory are two approaches used to improve the applicability of polymers in the biomedical field. Combining both these approaches in a polymer composite opens new possibilities for its use in biomedical applications, such as the "close then heal" concept, which uses the shape memory capabilities of polymers to bring injured sections together to promote autonomous healing. This review focuses on using shape memory-assisted self-healing approaches along with their respective affecting factors for biomedical applications such as tissue engineering, drug delivery, biomaterial-inks, and 4D printed scaffolds, soft actuators, wearable electronics, etc. In addition, quantification of self-healing and shape memory efficiency is also discussed. The challenges and prospects of these polymers for biomedical applications have been summarized.

A self-healing restoration of power grid based on two-stage adaptive decision-making strategy to enhance grid resilience

Large-scale power outages can affect the economy of the country and jeopardize the lives of millions of people, so there is a need for a fast, reliable, and self-healing tool to reduce these losses. Hence, the power system restoration performance can be improved by considering both restoring and operating performance, however, current restoration strategies only consider the restoring performance but ignore the operational performance which can enhance the power system resiliency. Given this background, challenging tasks such as optimal restoration planning (ORP) and optimal real-time operation (ORO) are planned to be tackled by developing an adaptive decision-making strategy (ADMS). In order to reduce the effects of emergency power outages on power systems, this study presents the ADMS, a two-stage self-healing restoration approach. Moreover, a novel metric of capacity accessibility (NMCA) is developed to determine the capacity adequacy status during severe events. The proposed ADMS has two steps, each of which is conducted at a certain time, and is referred to as ORP for the first stage and ORO functions for the second stage. The goal of the ORP optimization model is to maximize system-wide power capacity for electricity demand under extreme events by considering practical constraints, including non-black-start generators (NBSGs) constraints, network topology constraints, and power balance constraints. In order to reduce generation costs, the ORO optimization model adjusts the generated output power to enhance one or more operating performance metrics. The first stage problem is formulated using mixed-integer linear programming (MILP), and it is resolved using the branch-and-bound technique. Moreover, the interior point method solves AC optimal power flow for the second stage. Finally, simulation studies are performed on the modified IEEE 118-bus power systems. The outcomes demonstrate the effectiveness of the proposed strategy for planning (ORP) and real-time operation (ORO); the proposed two-stage strategy is capable of providing an optimal solution for a high-performance online restoration decision support system; the proposed strategy can adapt against the system conditions and contingencies.

State-of-the-Art Report: The Self-Healing Capability of Alkali-Activated Slag (AAS) Concrete.

Alkali-activated slag (AAS) has emerged as a potentially sustainable alternative to ordinary Portland cement (OPC) in various applications since OPC production contributed about 12% of global CO2 emissions in 2020. AAS offers great ecological advantages over OPC at some levels such as the utilization of industrial by-products and overcoming the issue of disposal, low energy consumption, and low greenhouse gas emission. Apart from these environmental benefits, the novel binder has shown enhanced resistance to high temperatures and chemical attacks. However, many studies have mentioned the risk of its considerably higher drying shrinkage and early-age cracking compared to OPC concrete. Despite the abundant research on the self-healing mechanism of OPC, limited work has been devoted to studying the self-healing behavior of AAS. Self-healing AAS is a revolutionary product that provides the solution for these drawbacks. This study is a critical review of the self-healing ability of AAS and its effect on the mechanical properties of AAS mortars. Several self-healing approaches, applications, and challenges of each mechanism are taken into account and compared regarding their impacts.

Toward Self-Healing Concrete Infrastructure: Review of Experiments and Simulations across Scales.

Cement and concrete are vital materials used to construct durable habitats and infrastructure that withstand natural and human-caused disasters. Still, concrete cracking imposes enormous repair costs on societies, and excessive cement consumption for repairs contributes to climate change. Therefore, the need for more durable cementitious materials, such as those with self-healing capabilities, has become more urgent. In this review, we present the functioning mechanisms of five different strategies for implementing self-healing capability into cement based materials: (1) autogenous self-healing from ordinary portland cement and supplementary cementitious materials and geopolymers in which defects and cracks are repaired through intrinsic carbonation and crystallization; (2) autonomous self-healing by (a) biomineralization wherein bacteria within the cement produce carbonates, silicates, or phosphates to heal damage, (b) polymer-cement composites in which autonomous self-healing occurs both within the polymer and at the polymer-cement interface, and (c) fibers that inhibit crack propagation, thus allowing autogenous healing mechanisms to be more effective. In all cases, we discuss the self-healing agent and synthesize the state of knowledge on the self-healing mechanism(s). In this review article, the state of computational modeling across nano- to macroscales developed based on experimental data is presented for each self-healing approach. We conclude the review by noting that, although autogenous reactions help repair small cracks, the most fruitful opportunities lay within design strategies for additional components that can migrate into cracks and initiate chemistries that retard crack propagation and generate repair of the cement matrix.

Dual dynamic bonds approach for polyurethane recycling and self-healing of emulsified asphalt

To recycle polyurethane and extend the service life of polyurethane-modified emulsified asphalt, this study developed novel perspectives for a lower carbon-footprint and cleaner preparation of recyclable polyurethane (RWPU) and its modified emulsified asphalt (RPUA-x) by using self-emulsification and dual dynamic bonds. Particle dispersion and zeta potential tests reflected that the emulsions of RWPU and RPUA-x existed excellent dispersion and storage stability. Microscopic and thermal analyses indicated that RWPU possessed dynamic bonds and maintained thermal stability below 250 °C as anticipated. Concurrently, RWPU provided RPUA-x with a strong physical cross-linking network, and a homogeneous phase was observed in RPUA-x after drying. Self-healing and mechanical evaluation results revealed that the regeneration efficiencies of RWPU were 72.3 % (stress) and 100 % (strain), respectively, and the stress-strain healing efficiency of RPUA-x was >73 %. The energy dissipation performance and plastic damage principle of RWPU were investigated using cyclic tensile loading. The multiple self-healing mechanisms of RPUA-x were revealed through microexamination. Furthermore, the viscoelasticity of RPUA-x and variations in flow activation energy were determined based on Arrhenius fitting from dynamic shear rheometer tests. In conclusion, disulfide bonds and hydrogen bonds endow RWPU with remarkable regenerative properties and grant RPUA-x with both asphalt diffusion self-healing and dynamic reversible self-healing capabilities.