Double network self-healing hydrogel based on hydrophobic association and ionic bond for formation plugging

Self-healing hydrogels have attracted tremendous attention in the field of oil and gas drilling and production engineering because of their excellent self-healing performance after physical damage.In this study,a series of double network self-healing(DN_(SA))hydrogels based on hydrophobic association and ionic bond were prepared for plugging pores and fractures in formations in oil and gas drilling and production engineering.The mechanical,rheological,and self-healing properties of the DN_(SA)hydrogels were investigated.Results revealed that the DN_(SA)hydrogels exhibited excellent mechanical properties with a tensile stress of 0.67 MPa and toughness of 7069 kJ/cm^(3) owing to the synergistic effect of the double network.In addition,the DN_(SA)hydrogels exhibited excellent compression resistance,notch insensitivity,and self-healing properties.The DN_(SA)-2 hydrogel was granulated and made into gel particles with different particle sizes and used as a plugging agent.The self-healing mechanism of DN_(SA)-2 hydrogel particles in fractures was explored,and it’s plugging effect on fractures of different widths and porous media of different permeabilities were investigated.Experimental results revealed that the plugging capacity of the DN_(SA)-2 hydrogel particles for a fracture with width of 5 mm and a porous medium with a permeability of 30μm^(2) was 3.45 and 4.21 MPa,respectively,which is significantly higher than those of commonly used plugging agents in the oilfield.The DN_(SA)hydrogels with excellent mechanical and self-healing properties prepared in this study will provide a new approach for applying hydrogels in oil and gas drilling and production engineering.

Flexible,thermal processable,self-healing,and fully bio-based starch plastics by constructing dynamic imine network

The serious environmental threat caused by petroleum-based plastics has spurred more researches in developing substitutes from renewable sources.Starch is desirable for fabricating bioplastic due to its abundance and renewable nature.However,limitations such as brittleness,hydrophilicity,and thermal properties restrict its widespread application.To overcome these issues,covalent adaptable network was constructed to fabricate a fully bio-based starch plastic with multiple advantages via Schiff base reactions.This strategy endowed starch plastic with excellent thermal processability,as evidenced by a low glass transition temperature(T_(g)=20.15℃).Through introducing Priamine with long carbon chains,the starch plastic demonstrated superior flexibility(elongation at break=45.2%)and waterproof capability(water contact angle=109.2°).Besides,it possessed a good thermal stability and self-adaptability,as well as solvent resistance and chemical degradability.This work provides a promising method to fabricate fully bio-based plastics as alternative to petroleum-based plastics.

Mechanical reliable,NIR light-induced rapid self-healing hydrogel electrolyte towards flexible zinc-ion hybrid supercapacitors with low-temperature adaptability and long service life

Hydrogel electrolytes hold great potential in flexible zinc ion supercapacitors(ZICs)due to their high conductivity,good safety,and flexibility.However,freezing of electrolytes at low temperature(subzero)leads to drastic reduction in ionic conductivity and mechanical properties that deteriorates the performance of flexible ZICs.Besides,the mechanical fracture during arbitrary deformations significantly prunes out the lifespan of the flexible device.Herein,a Zn^(2+)and Li^(+)co-doped,polypyrrole-dopamine decorated Sb_(2)S_(3)incorporated,and polyvinyl alcohol/poly(N-(2-hydroxyethyl)acrylamide)double-network hydrogel electrolyte is constructed with favorable mechanical reliability,anti-freezing,and self-healing ability.In addition,it delivers ultra-high ionic conductivity of 8.6 and 3.7 S m^(-1)at 20 and−30°C,respectively,and displays excellent mechanical properties to withstand tensile stress of 1.85 MPa with tensile elongation of 760%,together with fracture energy of 5.14 MJ m^(-3).Notably,the fractured hydrogel electrolyte can recover itself after only 90 s of infrared illumination,while regaining 83%of its tensile strain and almost 100%of its ionic conductivity during−30–60°C.Moreover,ZICs coupled with this hydrogel electrolyte not only show a wide voltage window(up to 2 V),but also provide high energy density of 230 Wh kg^(-1)at power density of 500 W kg^(-1)with a capacity retention of 86.7%after 20,000 cycles under 20°C.Furthermore,the ZICs are able to retain excellent capacity even under various mechanical deformation at−30°C.This contribution will open up new insights into design of advanced wearable flexible electronics with environmental adaptability and long-life span.

High performance photodegradation resistant PVA@TiO_(2)/carboxyl-PES self-healing reactive ultrafiltration membrane

The occurrence of ultrafiltration(UF)membrane fouling frequently hampers the sustainable advancement of UF technology.Reactive self-cleaning UF membranes can effectively alleviate the problem of membrane fouling.Nevertheless,the self-cleaning process may accelerate membrane aging.Addressing these concerns,we present an innovative design concept for composite self-healing materials based on self-cleaning UF membranes.To begin,TiO_(2)nanoparticles were incorporated into the polymer molecular structure via molecular design,resulting in the synthesis of TiO_(2)/carboxyl-polyether sulfone(PES)hybrid materials.Subsequently,the nonsolvent-induced phase inversion technique was employed to prepare a novel of UF membrane.Lastly,a polyvinyl alcohol(PVA)hydrogel coating was applied to the hybrid UF membrane surface to create PVA@TiO_(2)/carboxyl-PES self-healing reactive UF membranes.By establishing a covalent bond,the TiO_(2)nanoparticles were effectively and uniformly dispersed within the UF membrane,leading to exceptional self-cleaning properties.Furthermore,the water-absorbing and swelling properties of PVA hydrogel,along with its capacity to form hydrogen bonds with water molecules,resulted in UF membranes with improved hydrophilicity and active self-healing abilities.The results demonstrated that the water contact angle of PVA@5%TiO_(2)/carboxyl-PES UF membrane was 43.1°.Following a 1-h exposure to simulated solar exposure,the water flux recovery ratio increased from 48.16%to 81.03%.Moreover,even after undergoing five cycles of 12-h simulated sunlight exposure,the UF membranes exhibited a consistent retention rate of over 97%,thus fully demonstrating their exceptional self-cleaning,antifouling,and selfhealing capabilities.We anticipate that the self-healing reactive UF membrane system will serve as a pioneering and comprehensive solution for the self-cleaning antifouling challenges encountered in UF membranes while also effectively mitigating the aging effects of reactive UF membranes.

An intrinsically self-healing and anti-freezing molecular chains induced polyacrylamide-based hydrogel electrolytes for zinc manganese dioxide batteries

The anti-freezing strategy of hydrogels and their self-healing structure are often contradictory,it is vital to break through the molecular structure to design and construct hydrogels with intrinsic anti-freezing/self-healing for meeting the rapid development of flexible and wearable devices in diverse service conditions.Herein,we design a new hydrogel electrolyte(AF/SH-Hydrogel)with intrinsic anti-freezing/self-healing capabilities by introducing ethylene glycol molecules,dynamic chemical bonding(disulfide bond),and supramolecular interaction(multi-hydrogen bond)into the polyacrylamide molecular chain.Thanks to the exceptional freeze resistance(84%capacity retention at-20℃)and intrinsic self-healing capabilities(95%capacity retention after 5 cutting/self-healing cycles),the obtained AF/SH-Hydrogel makes the zinc||manganese dioxide cell an economically feasible battery for the state-of-the-art applications.The Zn||AF/SH-Hydrogel||MnO_(2)device offers a near-theoretical specific capacity of 285 m A h g^(-1)at 0.1 A g^(-1)(Coulombic efficiency≈100%),as well as good self-healing capability and mechanical flexibility in an ice bath.This work provides insight that can be utilized to develop multifunctional hydrogel electrolytes for application in next generation of self-healable and freeze-resistance smart aqueous energy storage devices.

The Optimization Study about Fault Self-Healing Restoration of Power Distribution Network Based on Multi-Agent Technology

In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network,a fault recovery method based on multi-objective optimization algorithm is proposed.The optimization of the power distribution network fault system based on multiagent technology realizes fast recovery of multi-objective fault,solve the problem of network learning and parameter adjustment in the later stage of particle swarm optimization algorithm falling into the local extreme value dilemma,and realize the multi-dimensional nonlinear optimization of the main grid and the auxiliary grid.The system proposed in this study takes power distribution network as the goal,applies fuzzy probability algorithm,simplifies the calculation process,avoids local extreme value,and finally realizes the energy balance between each power grid.Simulation results show that the Multi-Agent Technology enjoys priority in restoring important load,shortening the recovery time of power grid balance,and reducing the overall line loss rate of power grid.Therefore,the power grid fault self-healing system can improve the safety and stability of the important power grid,and reduce the economic loss rate of the whole power grid.

Preparation of alkaline-responsive nano-electrospinning and anticorrosion properties of self-healing coating

In this paper,1-butyl-3-methylimidazole tetrafluoroborate([BMIM]BF4)is used as corrosion inhibitor.Polyacrylonitrile(PAN)is used to load the corrosion inhibitor.PAN/[BMIM]BF4 hybrid nanofibers are successfullysynthesized by electrospinning technology.The alkyd varnish is coated on the fiber membrane to prepare a compositecoating,and then a series of tests are carried out on the self-healing and anticorrosive performance of the compositecoating.It is observed by scanning electron microscope that the fiber morphology is stable and there is no bead-likestructure.The composition of the composite fiber is analyzed by Fourier infrared spectroscopy,and it is confirmed thatthe hybrid nanofiber was successfully prepared.3D laser confocal scanning microscope was used to observe thecorrosion morphology and profile of the carbon steel.The composite coating shows good self-healing performance.[BMIM]BF4 can form a protective film on the surface of the bare carbon steel substrate through physical adsorption orchemical adsorption in an alkaline environment.Electrochemical impedance spectroscopy was tested and analyzed.It isfound that the maximum corrosion inhibition efficiency of the coating is 88.5%in 3.5 wt.%alkaline NaCl solution.Compared with the blank coating without nanofibers,the composite fiber varnish composite coating exhibits good selfhealingand anti-corrosion properties.

A Self-Healing Optoacoustic Patch with High Damage Threshold and Conversion Efficiency for Biomedical Applications

Compared with traditional piezoelectric ultrasonic devices,optoacoustic devices have unique advantages such as a simple preparation process,anti-electromagnetic interference,and wireless long-distance power supply.However,current optoacoustic devices remain limited due to a low damage threshold and energy conversion efficiency,which seriously hinder their widespread applications.In this study,using a self-healing polydimethylsiloxane(PDMS,Fe-Hpdca-PDMS)and carbon nanotube composite,a flexible optoacoustic patch is developed,which possesses the self-healing capability at room temperature,and can even recover from damage induced by cutting or laser irradiation.Moreover,this patch can generate high-intensity ultrasound(>25 MPa)without the focusing structure.The laser damage threshold is greater than 183.44 mJ cm^(-2),and the optoacoustic energy conversion efficiency reaches a major achievement at 10.66×10^(-3),compared with other carbon-based nanomaterials and PDMS composites.This patch is also been successfully examined in the application of acoustic flow,thrombolysis,and wireless energy harvesting.All findings in this study provides new insight into designing and fabricating of novel ultrasound devices for biomedical applications.

Photothermal self-healing polyurethane coating based on hollow nanofillers in seawater

Herein,a novel composite coating with excellent self-healing and corrosion resistance activated byphotothermal responsive hollow core-shell nanofillers was developed.A photothermal nanofiller(Co_(9)S_(8)@Bi_(2)S_(3))with ahollow core-shell structure was synthesized and then added to polyurethane(PU)to prepare PU-Co_(9)S_(8)@Bi_(2)S_(3)compositecoating.Applying 808 nm near-infrared irradiation induces a photothermal effect in Co_(9)S_(8)@Bi_(2)S_(3),which subsequentlyinitiates the reconstruction of reversible hydrogen bonds,facilitating the self-healing of coating scratches.The excellentphotothermal self-healing performance of PU-Co_(9)S_(8)@Bi_(2)S_(3)coating was demonstrated by scratch tests and moleculardynamics simulations.The electrochemical impedance spectroscopy test results showed that the PU-Co_(9)S_(8)@Bi_(2)S_(3)coating has good self-healing and anti-corrosion properties.The low-frequency impedance modulus of the coating afterthree self-healing sessions was still close to 109Ω·cm^(2)after 30 d of immersion in seawater.This study provides a newstrategy for developing multi-cycle self-healing coatings triggered by photothermal effects.

Multifunctional phase change film with high recyclability, adjustable thermal responsiveness, and intrinsic self-healing ability for thermal energy storage

Phase change materials(PCMs) present promising potential for guaranteeing safety in thermal management systems.However,most reported PCMs have a single application in energy storage for thermal management systems,which does not meet the growing demand for multi-functional materials.In this paper,the flexible material and hydrogen-bonding function are innovatively combined to design and prepare a novel multi-functional flexible phase change film(PPL).The 0.2PPL-2 film exhibits solid-solid phase change behavior with energy storage density of 131.8 J/g at the transition temperature of42.1℃,thermal cycling stability(500 cycles),wide-temperature range flexibility(0-60℃) and selfhealing property.Notably,the PPL film can be recycled up to 98.5% by intrinsic remodeling.Moreover,the PPL film can be tailored to the desired colors and configurations and can be cleverly assembled on several thermal management systems at ambient temperature through its flexibility combined with shape-memory properties.More interestingly,the transmittance of PPL will be altered when the ambient temperature changes(60℃),conveying a clear thermal signal.Finally,the thermal energy storage performance of the PPL film is successfully tested by human thermotherapy and electronic device temperature control experiments.The proposed functional integration strategy provides innovative ideas to design PCMs for multifunctionality,and makes significant contributions in green chemistry,highefficiency thermal management,and energy sustainability.

Effect of drying cracks on swelling and self-healing of bentonite-sand blocks used as engineered barriers for radioactive waste disposal

Experiments were conducted to evaluate the healing of drying cracks in air-dried bentonite-sand blocks after hydration and swelling in groundwater,providing justifications to simplify the protection of blocks prior to installation in a high-level radioactive waste repository.Synthetic groundwater was prepared to represent the geochemistry of Beishan groundwater,and was used to hydrate the blocks during the swelling pressure and swelling strain measurements,as Beishan is the most promising site for China's repository.Healing of the surface cracks was recorded by photography,and healing of the internal cracks was visualized by CT images and hydraulic conductivity of air-dried blocks.The results indicate that the maximum swelling pressure and swelling strain are primarily affected by the geochemistry of Beishan groundwater,but not affected by the drying cracks.The maximum swelling pressure and swelling strain of air-dried blocks are comparable to or even higher than the pressure and strain of fresh blocks.The maximum swelling pressure measured in strong(i.e.high ion strength)Beishan groundwater was 44%of the pressure measured in deionized(DI)water,and the maximum swelling strain was reduced to 23%of the strain measured in DI water.Nevertheless,the remained swelling of the blocks hydrated in strong Beishan groundwater was sufficient to heal the surface and internal drying cracks,as demonstrated by the pictures of surface cracks and CT images.The hydraulic conductivity of the air-dried block permeated with strong groundwater was comparable(3.7×higher)to the hydraulic conductivity of the fresh block,indicating the self-healing of drying cracks after hydration and swelling in groundwater.A simplified method of protecting the block with plastic wraps before installation is recommended,since the remained swelling of the block hydrated in Beishan groundwater is sufficient to heal the drying cracks.

An Average Distance Based Self-Relocation and Self-Healing Algorithm for Mobile Sensor Networks

The sensing coverage of a wireless sensor network is an important measure of the quality of service. It is desirable to develop energy efficient methods for relocating mobile sensors in order to achieve optimum sensing coverage. This paper introduces an average distance based self-relocation and self-healing algorithm for randomly deployed mobile sensor networks. No geo-location or relative location information is needed by this algorithm thereby no hardware such as GPS is required. The tradeoff is that sensors need to move longer distance in order to achieve certain coverage. Simulations are conducted in order to evaluate the proposed relocation and self-healing algorithms. An average of 94% coverage is achieved in the cases that we are examined with or without obstacles.

Synthesis of Lignin-based Nonisocyanate Poly(imine-hydroxyurethane)s Networks.Part II:Self-healing,Reprocessing,and Degradation

This study provides a comprehensive understanding of the polymeric properties of lignin-based non-isocyanate poly(iminehydroxyurethane)s(LNIPUs).The properties of the LNIPUs are affected by changes in the stoichiometric feed ratios of the bis(6-membered cyclic carbonate)(BCC)and levulinate enzymatic hydrolysis lignin(LEHL).The results showed that the LNIPUs exhibited a short relaxation time and excellent thermal repair and degradation properties.With a change in the LEHL content in the LNIPUs to 45.53%,a relaxation time of only 9 s was achieved,and the thermal repair rate of the scratches reached 93%.Furthermore,the tensile strength of the LNIPUs decreased with an increase in the LEHL content after two hot-pressing processes,while a higher than 75% tensile strength was maintained after the second hot-pressing treatment.The LNIPUs exhibited thermoresponsive shape memory property with deformation and shape fixing at 80℃.In addition,the as-synthesized LNIPUs were soluble in ethylene glycol in the absence of any organic solvents.This work demonstrates the synthesis of LNIPUs with self-healing,reprocessing,shape memory,and degradation properties.

THE EFFECT OF VP SWITCHES ON THE PERFORMANCE OF BACKUP-VP ALGORITHM IN ATM SELF-HEALING NETWORKS

In this approach, three typical implementation schemes of self-healing function in VP switches are discussed and three corresponding queue models for backup-VP self-healing algorithm are established. Computer simulations are made to these queue models, and detailed analyses are presented to the effect of both the three implementation schemes of self-healing function and some architecture parameters in VP switches on self-healing performance.

Multi-Stage-Based Siamese Neural Network for Seal Image Recognition

Seal authentication is an important task for verifying the authenticity of stamped seals used in various domains to protect legal documents from tampering and counterfeiting.Stamped seal inspection is commonly audited manually to ensure document authenticity.However,manual assessment of seal images is tedious and laborintensive due to human errors,inconsistent placement,and completeness of the seal.Traditional image recognition systems are inadequate enough to identify seal types accurately,necessitating a neural network-based method for seal image recognition.However,neural network-based classification algorithms,such as Residual Networks(ResNet)andVisualGeometryGroup with 16 layers(VGG16)yield suboptimal recognition rates on stamp datasets.Additionally,the fixed training data categories make handling new categories to be a challenging task.This paper proposes amulti-stage seal recognition algorithmbased on Siamese network to overcome these limitations.Firstly,the seal image is pre-processed by applying an image rotation correction module based on Histogram of Oriented Gradients(HOG).Secondly,the similarity between input seal image pairs is measured by utilizing a similarity comparison module based on the Siamese network.Finally,we compare the results with the pre-stored standard seal template images in the database to obtain the seal type.To evaluate the performance of the proposed method,we further create a new seal image dataset that contains two subsets with 210,000 valid labeled pairs in total.The proposed work has a practical significance in industries where automatic seal authentication is essential as in legal,financial,and governmental sectors,where automatic seal recognition can enhance document security and streamline validation processes.Furthermore,the experimental results show that the proposed multi-stage method for seal image recognition outperforms state-of-the-art methods on the two established datasets.

A Self-Healing and Nonflammable Cross-Linked Network Polymer Electrolyte with the Combination of Hydrogen Bonds and Dynamic Disulfide Bonds for Lithium Metal Batteries

The self-healing solid polymer electrolytes(SHSPEs)can spontaneously eliminate mechanical damages or micro-cracks generated during the assembly or operation of lithium-ion batteries(LIBs),significantly improving cycling performance and extending service life of LIBs.Here,we report a novel cross-linked network SHSPE(PDDP)containing hydrogen bonds and dynamic disulfide bonds with excellent self-healing properties and nonflammability.The combination of hydrogen bonding between urea groups and the metathesis reaction of dynamic disulfide bonds endows PDDP with rapid self-healing capacity at 28°C without external stimulation.Furthermore,the addition of 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide(EMIMTFSI)improves the ionic conductivity(1.13×10^(−4)S cm^(−1)at 28°C)and non-flammability of PDDP.The assembled Li/PDDP/LiFePO_(4)cell exhibits excellent cycling performance with a discharge capacity of 137 mA h g^(−1)after 300 cycles at 0.2 C.More importantly,the self-healed PDDP can recover almost the same ionic conductivity and cycling performance as the original PDDP.

Dynamic Multi-Graph Spatio-Temporal Graph Traffic Flow Prediction in Bangkok:An Application of a Continuous Convolutional Neural Network

The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.

Application of virtual reality technology improves the functionality of brain networks in individuals experiencing pain

Medical procedures are inherently invasive and carry the risk of inducing pain to the mind and body.Recently,efforts have been made to alleviate the discomfort associated with invasive medical procedures through the use of virtual reality(VR)technology.VR has been demonstrated to be an effective treatment for pain associated with medical procedures,as well as for chronic pain conditions for which no effective treatment has been established.The precise mechanism by which the diversion from reality facilitated by VR contributes to the diminution of pain and anxiety has yet to be elucidated.However,the provision of positive images through VR-based visual stimulation may enhance the functionality of brain networks.The salience network is diminished,while the default mode network is enhanced.Additionally,the medial prefrontal cortex may establish a stronger connection with the default mode network,which could result in a reduction of pain and anxiety.Further research into the potential of VR technology to alleviate pain could lead to a reduction in the number of individuals who overdose on painkillers and contribute to positive change in the medical field.

Self-Healing Based on Cooperative Transmission via Bender's Decomposition in Cloud Radio Access Network

To employ the network resources more effectively and fl exibly,cloud radio access network(C-RAN) adopts centralized network construction and management. Since the new network characteristics,the self-healing is reliable distinguish compared with previous studies. This paper drives a solution for selfhealing based on cooperative transmission and power adjustment under C-RAN self-healing management architecture. This compensation model with the aim to maximize the number of connected UEs and optimize power regulation is solved by Benders' decomposition algorithm. And through the simulation,this paper verifies the speediness and effectiveness of this scheme.

Network pharmacology:Changes the treatment mode of"one disease-one target"in cancer treatment

The article concluded that network pharmacology provides new ideas and insights into the molecular mechanism of traditional Chinese medicine(TCM)treatment of cancer.TCM is a new choice and hot spot in the field of cancer treatment.We have also previously published studies on TCM and network pharmacology.In this letter,we summarize the new paradigm of network pharmacology in cancer treatment mechanisms.