Supramolecular polymer-based gel fracturing fluid with a double network applied in ultra-deep hydraulic fracturing

A gel based on polyacrylamide,exhibiting delayed crosslinking characteristics,emerges as the preferred solution for mitigating degradation under conditions of high temperature and extended shear in ultralong wellbores.High viscosity/viscoelasticity of the fracturing fluid was required to maintain excellent proppant suspension properties before gelling.Taking into account both the cost and the potential damage to reservoirs,polymers with lower concentrations and molecular weights are generally preferred.In this work,the supramolecular action was integrated into the polymer,resulting in significant increases in the viscosity and viscoelasticity of the synthesized supramolecular polymer system.The double network gel,which is formed by the combination of the supramolecular polymer system and a small quantity of Zr-crosslinker,effectively resists temperature while minimizing permeability damage to the reservoir.The results indicate that the supramolecular polymer system with a molecular weight of(268—380)×10^(4)g/mol can achieve the same viscosity and viscoelasticity at 0.4 wt%due to the supramolecular interaction between polymers,compared to the 0.6 wt%traditional polymer(hydrolyzed polyacrylamide,molecular weight of 1078×10^(4)g/mol).The supramolecular polymer system possessed excellent proppant suspension properties with a 0.55 cm/min sedimentation rate at 0.4 wt%,whereas the0.6 wt%traditional polymer had a rate of 0.57 cm/min.In comparison to the traditional gel with a Zrcrosslinker concentration of 0.6 wt%and an elastic modulus of 7.77 Pa,the double network gel with a higher elastic modulus(9.00 Pa)could be formed only at 0.1 wt%Zr-crosslinker,which greatly reduced the amount of residue of the fluid after gel-breaking.The viscosity of the double network gel was66 m Pa s after 2 h shearing,whereas the traditional gel only reached 27 m Pa s.

Fluorescent Double Network Hydrogels with Ionic Responsiveness and High Mechanical Properties for Visual Detection

We developed a fluorescent double network hydrogel with ionic responsiveness and high mechanical properties for visual detection.The nanocomposite hydrogel of laponite and polyacrylamide serves as the first network,while the ionic cross-linked hydrogel of terbium ions and sodium alginate serves as the second network.The double-network structure,the introduction of nanoparticles and the reversible ionic crosslinked interactions confer high mechanical properties to the hydrogel.Terbium ions are not only used as the ionic cross-linked points,but also used as green emitters to endow hydrogels with fluorescent properties.On the basis of the “antenna effect” of terbium ions and the ion exchange interaction,the fluorescence of the hydrogels can make selective responses to various ions(such as organic acid radical ions,transition metal ions) in aqueous solutions,which enables a convenient strategy for visual detection toward ions.Consequently,the fluorescent double network hydrogel fabricated in this study is promising for use in the field of visual sensor detection.

Improved Double Deep Q Network Algorithm Based on Average Q-Value Estimation and Reward Redistribution for Robot Path Planning

By integrating deep neural networks with reinforcement learning,the Double Deep Q Network(DDQN)algorithm overcomes the limitations of Q-learning in handling continuous spaces and is widely applied in the path planning of mobile robots.However,the traditional DDQN algorithm suffers from sparse rewards and inefficient utilization of high-quality data.Targeting those problems,an improved DDQN algorithm based on average Q-value estimation and reward redistribution was proposed.First,to enhance the precision of the target Q-value,the average of multiple previously learned Q-values from the target Q network is used to replace the single Q-value from the current target Q network.Next,a reward redistribution mechanism is designed to overcome the sparse reward problem by adjusting the final reward of each action using the round reward from trajectory information.Additionally,a reward-prioritized experience selection method is introduced,which ranks experience samples according to reward values to ensure frequent utilization of high-quality data.Finally,simulation experiments are conducted to verify the effectiveness of the proposed algorithm in fixed-position scenario and random environments.The experimental results show that compared to the traditional DDQN algorithm,the proposed algorithm achieves shorter average running time,higher average return and fewer average steps.The performance of the proposed algorithm is improved by 11.43%in the fixed scenario and 8.33%in random environments.It not only plans economic and safe paths but also significantly improves efficiency and generalization in path planning,making it suitable for widespread application in autonomous navigation and industrial automation.

Unlocking the potentials of gel conformance for water shutoff in fractured reservoirs: Favorable attributes of the double network gel for enhancing oil recovery

The double-network prepared with an in-situ monomer gel and a fast-crosslinked Cr(III) gel is introduced to develop a thixotropic and high-strength gel (THSG), which is found to have many advantages over the traditional gels. The THSG gel demonstrates remarkable thermal stability, and no syneresis is observed after 12 months with high salinity brine (95,500 mg/L). Moreover, the SEM and XRD results indicate that the gel is intercalated into the lamellar structures of Na-MMT, where the gel can form a uniform and compact structure. In addition, the THSG gel has an excellent swelling behavior, even in the high salinity brine. In the slim tube experiments, the THSG gel exhibits high rupture pressure and improves blocking capacity after being ruptured. The core flooding results show that a layer of gel filter cake is formed on the face of the fracture, which may be promoted by a high matrix permeability, a small aperture fracture, and a high injection rate. After the gel treatment, the fracture can be completely blocked by the THSG gel. It is found that a high incremental oil recovery (65.3%) can be achieved when the fracture was completely blocked, compared to 40.2% if the gel is ruptured. Although the swelling of ruptured gel can improve oil recovery, part of the injected brine may be channeled through the gel-filled fractures, resulting in a decrease in the sweep efficiency. Therefore, the improved blocking ability by gel swelling (e.g., in fresh water) may be less efficient to contribute to an enhancement of oil recovery. It is also found that the pressure gradient and residual resistance factor to water (Frrw) are higher if the matrix is less permeable, indicating that the fractured reservoir with lower matrix permeability may require a higher gel strength for treatment. The findings of this study may provide novel insights on designing robust double network gels for water shutoff in fractured reservoirs.

Cascading Delays for the High-Speed Rail Network Under Different Emergencies:A Double Layer Network Approach

High-speed rail(HSR) has formed a networked operational scale in China. Any internal or external disturbance may deviate trains’ operation from the planned schedules, resulting in primary delays or even cascading delays on a network scale. Studying the delay propagation mechanism could help to improve the timetable resilience in the planning stage and realize cooperative rescheduling for dispatchers. To quickly and effectively predict the spatial-temporal range of cascading delays, this paper proposes a max-plus algebra based delay propagation model considering trains’ operation strategy and the systems’ constraints. A double-layer network based breadth-first search algorithm based on the constraint network and the timetable network is further proposed to solve the delay propagation process for different kinds of emergencies. The proposed model could deal with the delay propagation problem when emergencies occur in sections or stations and is suitable for static emergencies and dynamic emergencies. Case studies show that the proposed algorithm can significantly improve the computational efficiency of the large-scale HSR network. Moreover, the real operational data of China HSR is adopted to verify the proposed model, and the results show that the cascading delays can be timely and accurately inferred, and the delay propagation characteristics under three kinds of emergencies are unfolded.

Simultaneous Determination of Gold and Platinum by Double Artificial Neural Network Analysis with Flow-injection Chemiluminescence

A highly sensitive double artificial neural network （DANN） analysis with flow-injection chemiluminescence （FI-CL） has been developed to simultaneously determine the trace amounts of the gold and platinum in simulated mixed samples, without the boring process.

DISTRIBUTED OPTIMAL LOCAL DOUBLE LOOP NETWORK

A distibuted optimal local double loop(DOLDL) network is presented. Emphasis is laid on the topology and distributed routing algorithms for the DOLDL. On the basis of building an abstract model, a set of definitions and theorems are described and proved. An algorithm which can optimize the double loop networks is presented. The optimal values of the topologic parameters for the DOLDL have been obtained by the algorithm, and these numerical results are analyzed. The study shows that the bounds of the optimal diameter (d) and average hop distance (a) for this class of networks are [square-root 3N -2] less-than-or-equal-to d less-than-or-equal-to [square-root 3N+1] and (5N/9(N-1)) (square-root 3N-1.8) < a < (5N/9 (N-1)). (square-root 3N - 0.23), respectively (N is the number of nodes in the network. (3 less-than-or-equal-to N less-than-or-equal-to 10(4)). A class of the distributed routing algorithms for the DOLDL and the implementation procedure of an adaptive fault-tolerant algorithm are proposed. The correctness of the algorithm has been also verified by simulating.

Polycaprolactone strengthening keratin/bioactive glass composite scaffolds with double cross-linking networks for potential application in bone repair

In this study,we aimed at constructing polycaprolactone(PCL)reinforced keratin/bioactive glass composite scaffolds with a double cross-linking network structure for potential bone repair application.Thus,the PCL-keratin-BG composite scaffold was prepared by using keratin extracted from wool as main organic component and bioactive glass(BG)as main inorganic component,through both cross-linking systems,such as the thiol-ene click reaction between abundant sulfhydryl groups of keratin and the unsaturated double bond of 3-methacryloxy propyltrimethoxy silane(MPTS),and the amino-epoxy reaction between amino groups of keratin and the epoxy group in(3-glycidoxymethyl)methyldiethoxysilane(GPTMS)molecule,along with introduction of PCL as a reinforcing agent.The success of the thiol-ene reaction was verified by the FTIR and 1H-NMR analyses.And the structure of keratin-BG and PCL-keratin-BG composite scaffolds were studied and compared by the FTIR and XRD characterization,which indicated the successful preparation of the PCL-keratin-BG composite scaffold.In addition,the SEM observation,and contact angle and water absorption rate measurements demonstrated that the PCL-keratin-BG composite scaffold has interconnected porous structure,appropriate pore size and good hydrophilicity,which is helpful to cell adhesion,differentiation and proliferation.Importantly,compression experiments showed that,when compared with the keratin-BG composite scaffold,the PCL-keratin-BG composite scaffold increased greatly from 0.91±0.06 MPa and 7.25±1.7 MPa to 1.58±0.21 MPa and 14.14±1.95 MPa,respectively,which suggesting the strong reinforcement of polycaprolactone.In addition,the biomineralization experiment and MTT assay indicated that the PCL-keratin-BG scaffold has good mineralization ability and no-cytotoxicity,which can promote cell adhesion,proliferation and growth.Therefore,the results suggested that the PCL-keratin-BG composite scaffold has the potential as a candidate for application in bone regeneration field.

Deep reinforcement learning for UAV swarm rendezvous behavior

The unmanned aerial vehicle(UAV)swarm technology is one of the research hotspots in recent years.With the continuous improvement of autonomous intelligence of UAV,the swarm technology of UAV will become one of the main trends of UAV development in the future.This paper studies the behavior decision-making process of UAV swarm rendezvous task based on the double deep Q network(DDQN)algorithm.We design a guided reward function to effectively solve the problem of algorithm convergence caused by the sparse return problem in deep reinforcement learning(DRL)for the long period task.We also propose the concept of temporary storage area,optimizing the memory playback unit of the traditional DDQN algorithm,improving the convergence speed of the algorithm,and speeding up the training process of the algorithm.Different from traditional task environment,this paper establishes a continuous state-space task environment model to improve the authentication process of UAV task environment.Based on the DDQN algorithm,the collaborative tasks of UAV swarm in different task scenarios are trained.The experimental results validate that the DDQN algorithm is efficient in terms of training UAV swarm to complete the given collaborative tasks while meeting the requirements of UAV swarm for centralization and autonomy,and improving the intelligence of UAV swarm collaborative task execution.The simulation results show that after training,the proposed UAV swarm can carry out the rendezvous task well,and the success rate of the mission reaches 90%.

Application of interpolated double network model for carbon nanotube composites in electrothermal shape memory behaviors

Multi-wall carbon nanotube filled shape memory polymer composite(MWCNT/SMC)possessed enhanced modulus,strength,and electric conductivity,as well as excellent electrothermal shape memory properties,showing wide design scenarios and engineering application prospects.The thermoelectrically triggered shape memory process contains complex multi-physical mechanisms,especially when coupled with finite deformation rooted on micro-mechanisms.A multi-physical finite deformation model is necessary to get a deep understanding on the coupled electro-thermomechanical properties of electrothermal shape memory composites(ESMCs),beneficial to its design and wide application.Taking into consideration of micro-physical mechanisms of the MWCNTs interacting with double-chain networks,a finite deformation theoretical model is developed in this work based on two superimposed network chains of physically crosslinked network formed among MWCNTs and the chemically crosslinked network.An intact crosslinked chemical network is considered featuring with entropic-hyperelastic properties,superimposed with a physically crosslinked network where percolation theory is based on electric conductivity and electric-heating mechanisms.The model is calibrated by experiments and used for shape recoveries triggered by heating and electric fields.It captures the coupled electro-thermomechanical behavior of ESMCs and provides design guidelines for MWCNTs filled shape memory polymers.

Polyzwitterionic cross-linked double network hydrogel electrolyte enabling high-stable Zn anode

Zn metal anode suffers from dendrite issues and passive byproducts,which severely plagues the practical application of aqueous Zn metal batteries.Herein,a polyzwitterionic cross-linked double network hydrogel electrolyte composed of physical crosslinking(hyaluronic acid)and chemical crosslinking(synthetic zwitterionic monomer copolymerized with acrylamide)is introduced to overcome these obstacles.On the one hand,highly hydrophilic physical network provides an energy dissipation channel to buffer stress and builds a H_(2)O-poor interface to avoid side reactions.On the other hand,the charged groups(sulfonic and imidazolyl)in chemical crosslinking structure build anion/cation transport channels to boost ions’kinetics migration and regulate the typical solvent structure[Zn(H_(2)O)_(6)]^(2+)to R-SO_(3)^(−)[Zn(H_(2)O)_(4)]^(2+),with uniform electric field distribution and significant resistance to dendrites and parasitic reactions.Based on the above functions,the symmetric zinc cell exhibits superior cycle stability for more than 420 h at a high current density of 5 mA·cm^(−2),and Zn||MnO_(2)full cell has a reversible specific capacity of 150 mAh·g^(−1)after 1000 cycles at 2 C with this hydrogel electrolyte.Furthermore,the pouch cell delivers impressive flexibility and cyclability for energy-storage applications.

Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization

Edge computing nodes undertake an increasing number of tasks with the rise of business density.Therefore,how to efficiently allocate large-scale and dynamic workloads to edge computing resources has become a critical challenge.This study proposes an edge task scheduling approach based on an improved Double Deep Q Network(DQN),which is adopted to separate the calculations of target Q values and the selection of the action in two networks.A new reward function is designed,and a control unit is added to the experience replay unit of the agent.The management of experience data are also modified to fully utilize its value and improve learning efficiency.Reinforcement learning agents usually learn from an ignorant state,which is inefficient.As such,this study proposes a novel particle swarm optimization algorithm with an improved fitness function,which can generate optimal solutions for task scheduling.These optimized solutions are provided for the agent to pre-train network parameters to obtain a better cognition level.The proposed algorithm is compared with six other methods in simulation experiments.Results show that the proposed algorithm outperforms other benchmark methods regarding makespan.

The construction of infinite families of any k-tight optimal and singular k-tight optimal directed double loop networks

The double loop network(DLN)is a circulant digraph with n nodes and outdegree 2.It is an important topological structure of computer interconnection networks and has been widely used in the designing of local area networks and distributed systems.Given the number n of nodes,how to construct a DLN which has minimum diameter?This problem has attracted great attention.A related and longtime unsolved problem is:for any given non-negative integer k,is there an infinite family of k-tight optimal DLN?In this paper,two main results are obtained:(1)for any k≥0,the infinite families of k-tight optimal DLN can be constructed,where the number n(k,e,c)of their nodes is a polynomial of degree 2 in e with integral coefficients containing a parameter c.(2)for any k≥0, an infinite family of singular k-tight optimal DLN can be constructed.

Safe Navigation for UAV-Enabled Data Dissemination by Deep Reinforcement Learning in Unknown Environments

Unmanned aerial vehicles(UAVs) are increasingly considered in safe autonomous navigation systems to explore unknown environments where UAVs are equipped with multiple sensors to perceive the surroundings. However, how to achieve UAVenabled data dissemination and also ensure safe navigation synchronously is a new challenge. In this paper, our goal is minimizing the whole weighted sum of the UAV’s task completion time while satisfying the data transmission task requirement and the UAV’s feasible flight region constraints. However, it is unable to be solved via standard optimization methods mainly on account of lacking a tractable and accurate system model in practice. To overcome this tough issue,we propose a new solution approach by utilizing the most advanced dueling double deep Q network(dueling DDQN) with multi-step learning. Specifically, to improve the algorithm, the extra labels are added to the primitive states. Simulation results indicate the validity and performance superiority of the proposed algorithm under different data thresholds compared with two other benchmarks.

Polycaprolactone strengthening keratin/ bioactive glass composite scaffolds with double cross-linking networks for potential application in bone repair

In this study, we aimed at constructing polycaprolactone (PCL) reinforced keratin/bioactive glass composite scaffolds with a double cross-linking network structure for potential bone repair application. Thus, the PCL-keratin-BG com-posite scaffold was prepared by using keratin extracted from wool as main organic component and bioactive glass (BG) as main inorganic component, through both cross-linking systems, such as the thiol-ene click reaction between abundant sulfhydryl groups of keratin and the unsaturated double bond of 3-methacryloxy propyltrimethoxy silane (MPTS), and the amino-epoxy reaction between amino groups of keratin and the epoxy group in (3-glycidoxymethyl) methyldiethoxysilane (GPTMS) molecule, along with introduction of PCL as a reinforcing agent. The success of the thiol-ene reaction was verified by the FTIR and 1H-NMR analyses. And the structure of keratin-BG and PCL-keratin-BG composite scaffolds were studied and compared by the FTIR and XRD characterization, which indicated the successful preparation of the PCL-keratin-BG composite scaffold. In addition, the SEM observation, and contact angle and water absorption rate measurements demonstrated that the PCL-keratin-BG composite scaffold has interconnected porous structure, appropriate pore size and good hydrophilicity, which is helpful to cell adhesion, differentiation and prolifera-tion. Importantly, compression experiments showed that, when compared with the keratin-BG composite scaffold, the PCL-keratin-BG composite scaffold increased greatly from 0.91 ± 0.06 MPa and 7.25 ± 1.7 MPa to 1.58 ± 0.21 MPa and 14.14 ± 1.95 MPa, respectively, which suggesting the strong reinforcement of polycaprolactone. In addition, the biomineralization experiment and MTT assay indicated that the PCL-keratin-BG scaffold has good mineralization abil-ity and no-cytotoxicity, which can promote cell adhesion, proliferation and growth. Therefore, the results suggested that the PCL-keratin-BG composite scaffold has the potential as a candidate for application in bone regeneration field.

Natural polymers-enhanced double-network hydrogel as wearable flexible sensor with high mechanical strength and strain sensitivity

Conductive hydrogels have shown great prospects as wearable flexible sensors.Nevertheless,it is still a challenge to construct hydrogel-based sensor with great mechanical strength and high strain sensitivity.Herein,an ion-conducting hydrogel was fabricated by introducing gelatin-dialdehydeβ-cyclodextrin(Gel-DACD)into polyvinyl alcohol-borax(PVA-borax)hydrogel network.Natural Gel-DACD network acted as mechanical deformation force through non-covalent cross-linking to endow the polyvinyl alcoholborax/gelatin-dialdehydeβ-cyclodextrin hydrogel(PGBCDH)with excellent mechanical stress(1.35 MPa),stretchability(400%),toughness(1.84 MJ/m3)and great fatigue resistance(200%strain for 100 cycles).Surprisingly,PGBCDH displayed good conductivity of 0.31 S/m after adding DACD to hydrogel network.As sensor,it showed rapid response(168 ms),high strain sensitivity(gage factor(GF)=8.57 in the strain range of 200%-250%)and reliable sensing stability(100%strain for 200 cycles).Importantly,PGBCDHbased sensor can accurately monitor complex body movements(knee,elbow,wrist and finger joints)and large-scale subtle movements(speech,swallow,breath and facial expressions).Thus,PGBCDH shows great potential for human monitoring with high precision.

Double network hydrogel with high mechanical strength:Performance,progress and future perspective

With high water content(～90 wt%) and significantly improved mechanical strength(～MPa),double network(DN) hydrogels have emerged as promising biomaterials with widespread applications in biomedicine.In recent years,DN hydrogels with extremely high mechanical strength have achieved great advance,and scientists have designed a series of natural and biomimetic DN hydrogels with novel functions including low friction,low wear,mechanical anisotropy and cell compatibility.These advances have also led to new design of biocompatible DN hydrogels for regeneration of tissues such as cartilage.In this paper,we reviewed the strategies of designing high-strength DN hydrogel and analyzed the factors that affect DN hydrogel properties.We also discussed the challenges and future development of the DN hydrogel in view of its potential as biomaterials for their biomedical applications.

Tough Poly(L-DOPA)-containing Double Network Hydrogel Beads with High Capacity of Dye Adsorption

Developing a low-cost and well-recyclable adsorbent with high adsorption capacity is greatly desirable in dye wastewater treatment. Here, we demonstrate a kind of novel tough and reusable hydrogel beads with quite high capacity of dye adsorption via incorporating mussel-bioinspired poly（L-DOPA） （PDOPA） into alginate/poly（acrylamide） double network （DN） hydrogels. The synthesized PDOPA nanoaggregates were introduced into the DN hydrogels by simple one-pot mixing with the monomers prior to polymerization. The fabricated hydrogel beads exhibited high mechanical strength and good elastic recovery due to the interpenetrating Ca2＋-alginate and poly（acrylamide） networks. It was shown that the beads exhibited relatively high dye adsorption capacity compared to other adsorbents reported in literature, and the introduction of PDOPA with an appropriate amount raised the adsorption capacity. It is believed that the addition of PDOPA and the matrix of double network architecture contributed synergistically to the high adsorption capacity of hydrogel beads. Moreover, the desorption of dyes could be easily realized via rinsing in acidic water and ethanol solution. The hydrogel beads remained the high adsorption capacity even after 5 times of adsorption and desorption cycles. This tough and stable hydrogel with high adsorption capacity may have potential in treatment of dye wastewater released by textile dyeing industry.

Highly antifouling double network hydrogel based on poly(sulfobetaine methacrylate)and sodium alginate with great toughness

Hydrogels with good antifouling and mechanical properties as well as biocompatibility have great application potential in the field of biomedicine.In this paper,a newly double network(DN)hydrogel was prepared based on zwitterionic material sulfobetaine methacrylate(SBMA)and natural polysaccharide,sodium alginate(SA).The PSBMA network is covalently crosslinked while the SA network is ionically crosslinked by Ca^(2+).The hybrid crosslinked double network structure endows the DN hydrogel with excellent mechanical properties(E=0.19±0.01 MPa,σ=0.73±0.03 MPa),fast self-recovery ability as well as excellent fatigue resistance.Moreover,the results show that the PSBMA/SA-Ca^(2+)DN hydrogel is biocompatible and resists the absorption of non-specific proteins and adhesion of microorganisms,such as cells and algae,exhibiting outstanding antifouling properties.These unique characteristics of PSBMA/SA-Ca^(2+)DN hydrogel make it a promising candidate for biomedical application,such as artificial connective tissues,implantable devices,and underwater equipment.

Designing soft/hard double network hydrogel microsphere/UHMWPE composites to promote water lubrication performance

Several soft tissues residing in the living body have excellent hydration lubrication properties and can provide effective protection during relative motion.In order to apply this advantage of soft matters in practical applications and try to avoid its disadvantage,such as swelling and weakening in water,a design strategy of a soft/hard double network(DN)hydrogel microsphere modified ultrahigh molecular weight polyethylene(UHMWPE)composite is proposed in this study.A series of microspheres of urea-formaldehyde(UF),polyacrylamide(PAAm)hydrogel,UF/PAAm double network,and their composites were prepared.The mechanical properties,swelling,wettability,friction properties,and the lubrication mechanisms of the composites were investigated.The results show that DN microspheres can have an excellent stability and provide hydration lubrication.The performance of 75 DN-1 composite was superior to others.This finding will provide a novel strategy for the development of water-lubricated materials and have wide application in engineering fields.