Network Junctions Research Articles

Effects of network junctions and defects on the crystallization of model poly(ethylene glycol) networks.

Polymer crystallization drastically changes the physical properties of polymeric materials. However, the crystallization in polymer networks has been little explored. This study investigated the crystallization behavior of a series of poly(ethylene glycol) (PEG) networks consisting of well-defined branched precursors. The PEG networks were prepared by drying gels synthesized at various conditions. The PEG networks showed slower crystallization with lower final crystallinity than uncrosslinked PEGs with amine end groups. Surprisingly, the effect of network formation was not as significant as that of the relatively bulky end-groups introduced in the uncrosslinked polymer. The molecular weight of the precursor PEG, or equivalently the chain length between neighboring junctions, was the primary parameter that affected the crystallization of the PEG networks. Shorter network chains led to lower crystallization rates and final crystallinity. This effect became less significant as the network chain length increased. On the other hand, the spatial and topological defects formed in the gel synthesis process did not affect the crystallization in the polymer networks at all. The crystallization in the polymer networks seems insensitive to these mesoscopic defects and can be solely controlled by the chain length between junctions.

Effect of the degree of polymerization and water content on the thermal transport phenomena in PEGDA hydrogel: a molecular-dynamics-based study.

A hydrogel is a 3D cross-linked polymer network that can absorb copious amounts of water or biological fluid. Due to their biocompatibility and non-toxicity, hydrogels have a wide range of applications in biomedical engineering. To develop hydrogels with superior thermal dissipation properties, atomistic-level studies are required to quantify the effect of the water content and the degree of polymerization. Classical mechanics-based non-equilibrium molecular dynamics (NEMD) simulations were performed in conjunction with a mathematical formulation developed by Müller-Plathe to explore the thermal conductivity of the poly(ethylene glycol)diacrylate (PEGDA) hydrogel. This work reveals that the thermal conductivity of the PEGDA hydrogel is enhanced with the increase in water content and approaches the value of the thermal conductivity of water at 85% water content in the hydrogel. The PEGDA-9 hydrogel, with a lower level of degree of polymerization, has a superior thermal conductivity than the PEGDA-13 and PEGDA-23 hydrogels. The lower level of degree of polymerization is associated with the higher mesh density of polymer chain network junctions that help to achieve the superior thermal conductivity at higher water contents. Increasing the water content improves the structural stability and compactness of the polymer chains, which can be further associated with the enhanced phonon transfer in PEGDA hydrogels. The work will help in the development of PEGDA-based hydrogels with superior thermal dissipation properties for tissue engineering.

Exploration of road closure time characteristics of tunnel traffic accidents: A case study in Pennsylvania, USA

With the increase of roadway tunnels, tunnel traffic accidents are also increasing. Compared with open roadways, road closures caused by traffic accidents in the tunnel have greater influences on traffic operations, as tunnels are often the key junctions of the roadway network. With the traffic accident data of Pennsylvania from 1997 to 2020, this study is designed to identify the features and trends of road closure time due to tunnel traffic accidents. First, features of tunnel and non-tunnel traffic accidents are compared from the perspectives of accident consequences, environmental factors, risky driver behavior, and vehicle features. The data confirms that tunnel traffic accidents are more likely to lead to road closures than non-tunnel ones. Besides, tunnel traffic accidents are mainly consisted of rear-end and hit-fixed-object collisions with many speeding cases. Then, a Negative Binomial model is built to statistically identify the factors significantly influencing the road closure time, which is recorded as non-negative integer in the data. The estimation results indicate that collision type, accident severity, road type, driving under the influence, the involvement of heavy trucks, and the number of involved vehicles could significantly influence the road closure time, whereas lighting, road condition, speeding, and area are insignificant. Finally, based on the research findings, some countermeasures are proposed to reduce the road closure time caused by tunnel traffic accidents.

Raw data for 'Light-induced assembly and disassembly of polymers with PdnL2n-type network junctions'

raw data for 'Light-induced assembly and disassembly of polymers with PdnL2n-type network junctions'

A Stacking Ensemble Learning Method to Classify the Patterns of Complex Road Junctions

Recognizing the patterns of road junctions in a road network plays a crucial role in various applications. Owing to the diversity and complexity of morphologies of road junctions, traditional methods that rely heavily on manual settings of features and rules are often problematic. In recent years, several studies have employed convolutional neural networks (CNNs) to classify complex junctions. These methods usually convert vector-based junctions into raster representations with a predefined sampling area coverage. However, a fixed sampling area coverage cannot ensure the integrity and clarity of each junction, which inevitably leads to misclassification. To overcome this drawback, this study proposes a stacking ensemble learning method for classifying the patterns of complex road junctions. In this method, each junction is first converted into raster images with multiple area coverages. Subsequently, several CNN-based base-classifiers are trained using raster images, and they output the probabilities of the junction belonging to different patterns. Finally, a meta-classifier based on random forest is used to combine the outputs of the base-classifiers and learn to arrive at the final classification. Experimental results show that the proposed method can improve the classification accuracy for complex road junctions compared to existing CNN-based classifiers that are trained using raster representations of junctions with a fixed sampling area coverage.

Molecular Dynamics Simulation of Entangled Melts at High Rates: Identifying Entanglement Lockup Mechanism Leading to True Strain Hardening.

In the present work, molecular dynamics simulations are carried out based on the bead-spring model to indicate how the entanglement lockup manifests in the late stage of fast Rouse-Weissnberg number (WiR >>1) uniaxial melt stretching of entangled polymer melts. At high strains, distinct features show up to reveal the emergence of an increasingly tightened entanglement network. Chain tension can build up, peaking at the middle of the chain, to a level for chain scission, through accumulated interchain interactions, as if there is a tug-of-war ongoing for each load-bearing chain. Thanks to the interchain uncrossability, network junctions form by the pairing of two or more hairpins. It is hypothesized that the interchain entanglement at junctions can lockup through prevailing twist-like interchain couplings as long as WiR > 9. In this limit, a significant fraction of chains act like cyclic chains to form a network held by interchain uncrossability, and appreciable chain tension emerges.

MTORC1/C2 regulate spermatogenesis in Eriocheir sinensis via alterations in the actin filament network and cell junctions.

Spermatogenesis is a finely regulated process of germ cell proliferation and differentiation that leads to the production of sperm in seminiferous tubules. Although the mammalian target of rapamycin (mTOR) signaling pathway is crucial for spermatogenesis in mammals, its functions and molecular mechanisms in spermatogenesis remain largely unknown in nonmammalian species, particularly in Crustacea. In this study, we first identified es-Raptor (the core component of mTOR complex 1) and es-Rictor (the core component of mTOR complex 2) from the testis of Eriocheir sinensis. Dynamic localization of es-Raptor and es-Rictor implied that these proteins were indispensable for the spermatogenesis of E. sinensis. Furthermore, es-Raptor and es-Rictor knockdown results showed that the mature sperm failed to be released, causing almost empty lumens in the testis. We investigated the reasons for these effects and found that the actin-based cytoskeleton was disrupted in the knockdown groups. In addition, the integrity of the testis barrier (similar to the blood-testis barrier in mammals) was impaired and affected the expression of cell junction proteins. Further study revealed that es-Raptor and es-Rictor may regulate spermatogenesis via both mTORC1- and mTORC2-dependent mechanisms that involve es-rpS6 and es-Akt/es-PKC, respectively. Moreover, to explore the testis barrier in E. sinensis, we established a cadmium chloride (CdCl2)-induced testis barrier damage model as a positive control. Morphological and immunofluorescence results were similar to those of the es-Raptor and es-Rictor knockdown groups. Altogether, es-Raptor and es-Rictor were important for spermatogenesis through maintenance of the actin filament network and cell junctions in E. sinensis.

Identification of Suitable Locations in a Small Water Supply Network for the Placement of Water Quality Sensors Based on Different Criteria under Demand-Driven Conditions

Drinking water quality monitoring in real time is of utmost importance to ensure public health. Although water utilities, following the related legislative framework, monitor drinking water quality through samplings, the likelihood of detecting contaminants in consumers’ taps is low, depending on the scale of the monitoring programme. Additionally, even if the monitoring frequency is high, there is a time delay since sampling and analysis processes take some time. The selection of suitable locations for the installation of online water quality sensors is a hard task for a water utility due to the complexity of the water distribution system, the limitations of certain network junctions which are not easily accessible, and the computational burden involved. This topic has been extensively studied in recent years and sophisticated methods have been developed using optimization techniques. However, small water utilities do not have the means to implement such tools. This paper applies a methodology to identify the suitable junctions for the installation of online water quality sensors based on different objectives and under demand-driven conditions. This paper utilizes the hydraulic simulation model of a standard network to set up the water quality simulation model. A thorough analysis of various contamination scenarios takes place with different injection nodes and at different starting injection times for 24 h. The latter relates to the contaminant’s spread due to varying water demand. After a thorough analysis of 816 scenarios, a prioritized list of the most suitable nodes for the installation of the sensors is available for each optimization objective. Comparing the prioritized list of nodes achieved from each single or multi-objective function, the detection probability is almost the same. The analysis revealed that, due to varying water demand conditions, the ranking of the proposed nodes suitable for the installation of water quality monitoring sensors differs. Thus, varying hourly water demand should be part of analyses seeking to get reliable results.

Evaluasi Kinerja Simpang Empat Bersinyal di Kota Malang

An intersection is a part of a road where currents from various directions or directions meet. This is what causes conflicts between currents from opposite directions and intersect each other, resulting in congestion along the intersection arm. The signalized intersection on Jl. Panglima Sudirman – Jl. Urip Sumoharjo – Jl. Pattimura is one of the main network junctions in Malang City, precisely located in an area that provides several public facilities, namely the National Defense Field, Kota Baru Station and Klojen Market. This intersection connects to public places such as the city center, schools, offices and others. This reseach aims to evaluate the performance of the intersection and the degree of saturation as well as the level of service at the signalized intersection at the current condition based on the Indonesian Road Capacity Manual (MKJI) 1997. This reseach uses empirical methods to obtain data from observations that occur in the field. From the results of the reseach the degree of saturation (DS) on the north approach was 0.89, with queue length (QL) = 140.30 m, south approach 0.84, with queue length (QL) = 97.25 m, east approach 0, 49 with queue length (QL) = 69.25 m and the western approach 0.56 with queue length (QL) = 54.40 m. The average delay of the intersection is 27.31 sec/pcu and is included in the value of service level of service D.

Automatic detection of small-scale EUV brightenings observed by the Solar Orbiter/EUI

Context. Accurate detections of frequent small-scale extreme ultraviolet (EUV) brightenings are essential to the investigation of the physical processes heating the corona. Aims. We detected small-scale brightenings, termed campfires, using their morphological and intensity structures as observed in coronal EUV imaging observations for statistical analysis. Methods. We applied a method based on Zernike moments and a support vector machine (SVM) classifier to automatically identify and track campfires observed by Solar Orbiter/Extreme Ultraviolet Imager (EUI) and Solar Dynamics Observatory (SDO)/Atmospheric Imaging Assembly (AIA). Results. This method detected 8678 campfires (with length scales between 400 km and 4000 km) from a sequence of 50 High Resolution EUV telescope (HRIEUV) 174 Å images. From 21 near co-temporal AIA images covering the same field of view as EUI, we found 1131 campfires, 58% of which were also detected in HRIEUV images. In contrast, about 16% of campfires recognized in HRIEUV were detected by AIA. We obtain a campfire birthrate of 2 × 10−16 m−2 s−1. About 40% of campfires show a duration longer than 5 s, having been observed in at least two HRIEUV images. We find that 27% of campfires were found in coronal bright points and the remaining 73% have occurred out of coronal bright points. We detected 23 EUI campfires with a duration greater than 245 s. We found that about 80% of campfires are formed at supergranular boundaries, and the features with the highest total intensities are generated at network junctions and intense H I Lyman-α emission regions observed by EUI/HRILya. The probability distribution functions for the total intensity, peak intensity, and projected area of campfires follow a power law behavior with absolute indices between 2 and 3. This self-similar behavior is a possible signature of self-organization, or even self-organized criticality, in the campfire formation process.

Particle creation and annihilation in an exclusion process on networks

To mimic the complex transport-like collective phenomena in a man-made or natural system, we study an open network junction model of totally asymmetric simple exclusion process with bulk particle attachment and detachment. The stationary system properties such as particle density, phase transitions, and phase diagrams are derived theoretically utilising the mean field approach. The steady-state phases have been categorized into various sub-classes based upon the phase transitions occurring across the junction. It is found that the number of steady-state phases depends on the number of incoming and outgoing segments at the junction. Further, an increase in the particle non-conserving rates significantly affects the topology of the phase diagram, and the number of stationary phases changes in a non-monotonic way. For both the case of equal and unequal incoming and outgoing segments, the critical values of non-conserving rates at which the topology of the phase diagram changes are identified. The theoretical results are validated using extensive Monte Carlo simulations.

Effect of H-bonding on network junction and macroscopic elastomer properties in photocured polyacrylate films

Two series of polyacrylate films with different H-bonding capable monoacrylate copolymers were synthesized by UV-initiated photo-polymerization.

Clustering Urban Transport Network Junctions Using Convolutional Neural Networks and Fuzzy Logic Methods

The article develops methods to improve the accuracy of modeling and predicting the traffic capacity of intersections based on the fuzzy factors of intensity of pedestrian flow and flow discontinuity. Initial data was collected and analyzed using convolutional neural networks (YOLOv3). The article justifies the need for clustering signal-controlled junctions of the transport network to form a limited number of generic management algorithms for them. We analyzed the differences between clusters by the average values of independent factors. Regression modeling was completed for each cluster. Statistical analysis showed a significant improvement in the quality of the models within each cluster compared to the complete model of transport junctions, exceeding the maximum permissible quality thresholds. We built a model using fuzzy logic methods which reflect the distribution field of the influence of the most important factors to visually represent the influence of the fuzzy factors on the operation of a signal-controlled junction of the transport network.

A 1D:2D structured AgNW:MXene composite transparent electrode with high mechanical robustness for flexible photovoltaics

MXene nanosheets weld the wire–wire junctions of a AgNW network to improve the FTE performance, and flexible PSCs and OPVs based on AgNW:MXene FTE exhibit a champion PCE of 20.22% and 16.03%, respectively.

Calculation of electron transport in branched semiconductor nanostructures using quantum network model

Electron transport in branched semiconductor nanostructures provides many possibilities for creating fundamentally new devices. We solve the problem of its calculation using a quantum network model. The proposed scheme consists of three computational parts: S-matrix of the network junction, S-matrix of the network in terms of its junctions’ S-matrices, electric currents through the network based on its S-matrix. To calculate the S-matrix of the network junction, we propose scattering boundary conditions in a clear integro-differential form. As an alternative, we also consider the Dirichlet-to-Neumann and Neumann-to-Dirichlet map methods. To calculate the S-matrix of the network in terms of its junctions’ S-matrices, we obtain a network combining formula. We find electrical currents through the network in the framework of the Landauer–Büttiker formalism. Everywhere for calculations, we use extended scattering matrices, which allows taking into account correctly the contribution of tunnel effects between junctions. We demonstrate the proposed calculation scheme by modeling nanostructure based on two-dimensional electron gas. For this purpose we offer a model of a network formed by smooth junctions with one, two and three adjacent branches. We calculate the electrical properties of such a network (by the example of GaAs), formed by four junctions, depending on the temperature.

Ageing behaviour spanning months of NaMt, hectorite and Laponite gels: Surface forces and microstructure – A comprehensive analysis

Recent “artifact-free” microstructure information enabled the development of a more credible model for explaining the ageing time-dependent rheological behavior of NaMt, hectorite and Laponite gels. These gels displayed pronounced ageing behavior lasting months. The platelet morphology and the localised nature of the negative and positive charges produced the essential forces and interaction configurations to form the time-dependent structure. This structure is composed of nano-sized flexible platelets interacting both attractively to form the network junctions and repulsively to open up the structure. These junctions were formed by heterogeneous charge and van der Waals attractions between the jagged and curled edges, and the face of the interacting platelets. The force that is responsible for the time-dependent behaviour is the EDL repulsive force. This force governs the development of the 3-D network structure and drives it towards a minimum free energy state. This process takes a long time to complete. The resultant microstructure is completely interpenetrated with interconnected nanopores trapping as much as 99% of water in volume. At high ionic strength or 0.3 M KCl, the NaMt or bentonite gels became time independent as the van der Waals force formed the structure. The Leong model described the initial ageing behavior well. For the nanodiscotic Laponite gels, the 3-D structure is formed from sheets instead of primarily disks contradicting prevailing model. With the latest microstructure information, new mechanisms were proposed to account for the high yield stress at low solids, low permeability, intercalation behavior, layer stacking and enlarged dried platelets.

Pore-scale investigation of dynamic effects on the moisture retention curve during spontaneous imbibition

The moisture retention curve of porous materials is often assumed to be independent of the process dynamics, i.e., of the drying/wetting rate. Experimental outcomes and pore-scale simulations put this assumption into question though. It has been shown that dynamic effects can significantly affect the moisture retention curve, which presents different behaviours, depending on whether it is determined at transient or steady-state conditions. The cause of this phenomenon is addressed as “dynamic effects” in the literature. While dynamic effects of the drainage process have been widely studied, the data concerning spontaneous imbibition are still quite limited. We attempt at reducing this lack of knowledge by modelling spontaneous imbibition in an artificial material sample represented by a pore network model. In our model, the liquid flow is described via the Hagen-Poiseuille equation, while a percolation algorithm controls the dynamics of liquid-gas interfaces through the network junctions. A dynamic contact angle between liquid water and pore surface is considered, depending on the velocity of the meniscus. Dynamic states are determined by linking the local capillary pressure to the local moisture content in the artificial material sample subject to spontaneous imbibition. Our investigation demonstrates that dynamic effects due to contact angle variations may have a major impact on the imbibition process.

Lagrangian Method to Model Advection-Dispersion-Reaction Transport in Drinking Water Pipe Networks.

A Lagrangian method to simulate the advection, dispersion, and reaction of a single chemical, biological, or physical constituent within drinking water pipe networks is presented. This Lagrangian approach removes the need for fixed computational grids typically required in Eulerian and Eulerian-Lagrangian methods and allows for nonuniform computational segments. This makes the method fully compatible with the advection-reaction water quality engine currently used in EPANET. An operator splitting approach is used, in which the advection-reaction process is modeled before the dispersion process for each water quality step. The dispersion equation is discretized using a segment-centered finite-difference scheme, and flux continuity boundary conditions are applied at network junctions. A staged approach is implemented to solve the dispersion equation for interconnected pipe networks. First, a linear relationship between the boundary and internal concentrations is established for every pipe. Second, a symmetric and positive definite linear system of equations is constructed to calculate the concentrations at network junctions. Last, pipe internal concentrations are updated based on the junction concentrations. The solution generates exact results when the analytical solutions are available and leads to more accurate water quality simulations than advection-reaction-only water quality models, especially in the areas where dispersion dominates advection.

DNA Aptamer Functionalized Hydrogels for Interferometric Fiber-Optic Based Continuous Monitoring of Potassium Ions.

In the present paper, we describe a potassium sensor based on DNA-aptamer functionalized hydrogel, that is capable of continuous label-free potassium ion (K+) monitoring with potential for in situ application. A hydrogel attached to the end of an optical fiber is designed with di-oligonucleotides grafted to the polymer network that may serve as network junctions in addition to the covalent crosslinks. Specific affinity toward K+ is based on exploiting a particular aptamer that exhibits conformational transition from single-stranded DNA to G-quadruplex formed by the di-oligonucleotide in the presence of K+. Integration of this aptamer into the hydrogel transforms the K+ specific conformational transition to a K+ concentration dependent deswelling of the hydrogel. High-resolution interferometry monitors changes in extent of swelling at 1 Hz and 2 nm resolution for the hydrogel matrix of 50 µm. The developed hydrogel-based biosensor displayed high selectivity for K+ ions in the concentration range up to 10 mM, in the presence of physiological concentrations of Na+. Additionally, the concentration dependent and selective K+ detection demonstrated in the artificial blood buffer environment, both at room and physiological temperatures, suggests substantial potential for practical applications such as monitoring of potassium ion concentration in blood levels in intensive care medicine.

Molecularly Designed Additives for Chemically Deconstructable Thermosets without Compromised Thermomechanical Properties.

"Drop-in" additives that introduce chemically cleavable bonds into thermosets without compromising thermomechanical properties could enable triggered material deconstruction and enhanced sustainability. While the installation of cleavable bonds into the strands of the commercial thermoset polydicyclopentadiene (pDCPD) using comonomers facilitates chemical deconstruction, these additives can lower the material's glass transition temperature (Tg). By contrast, the installation of cleavable crosslinkers into pDCPD can maintain or potentially increase Tg but does not facilitate chemical deconstruction. Here, we introduce "strand-cleaving crosslinker" (SCC) additives that provide cleavable pDCPD network junctions. Notably, pDCPD samples featuring 10% v/v of SCCs can be deconstructed under mild conditions to yield soluble products and display a 48 °C higher Tg than analogous decontructable pDCPD made using cleavable comonomers and an equivalent Tg to virgin pDCPD. The SCC concept could offer a general strategy for the design of chemically deconstructable thermoset materials without compromise on thermomechanical performance.